practical results match the COMSOL simulation results in Fig. 6.10b; The coupling between the primary surface coil and the single saddle coil decreases as the relative angle between their magnetic *B*1 elds increases. Furthermore, when the *B*1 elds were nearly orthogonal, the reection coecient curve showed no splitting in the resonance frequency, conrming that no inductive coupling occurred (Fig. 6.14b). In contrast, for the double saddle coil, the inductive coupling between the surface resonator and the micro-detector was maintained at a near-constant prole for the entire range of the relative axial orientations (Fig. 6.14a).

The magnetic *B*1 elds of the micro-saddle coils were mapped utilizing a low eld MRI scanner (Bruker ICON, *B*0 = 1T). As revealed in Fig. 6.15a, the double saddle coil generated a homo-

Figure 6.14: Measured reection coecient (S11) curves of a stationary primary resonator due to coupling with micro-saddle detector. The S11 curves demonstrate the resonance frequency splitting of a stationary resonator tuned at 63 MHz due to inductive coupling with **(a)** Micro-double saddle coil and **(b)** Micro-single saddle coil both tuned at 63 MHz.

geneously distributed magnetic eld surrounding the catheter tube, conrming the simulated magnetic eld distribution in Fig. 6.9. The MR images had a slice thickness of 1.25 mm, a eld of view (FoV) of 20mm×20mm, with an imaging matrix size set as 128×128 using echo time (TE) = 4.5 ms, repetition time (TR) = 278 ms, a ip angle of 40°, and using four averages.

Figure 6.15: Mapping the *B*1 elds of **(a)** A micro-double saddle coil and **(b)** A micro-single saddle coil in a 1 T MRI scanner.

# Part III.

# NMR Application - Automated High Throughput Nuclear Magnetic Resonance

# **7 State-of-the-art: high throughput NMR spectroscopy**

**N** MR spectroscopy is an information-rich analytical method utilized for characterizing materials by determining and quantifying molecular structure. NMR is an attractive screening tool as: i) it oers broad chemical coverage; ii) it is a non-destructive technique, permitting further upstream analytics; and iii) it does not require signicant sample preparation. The NMR technique measures the response of a sample's spins to a polarizing static magnetic eld (*B*0) and an excitation RF magnetic eld (*B*1), which generates a small electrical signal in an RF resonant detector. The polarizing *B*0 eld is provided by an external magnet, while the *B*1 excitation eld is commonly generated by the RF detector itself, as explained in detail in Chapter 2.

A standing challenge facing the present NMR technique is that it is generally limited to single sample measurements under low throughput conditions. Therefore, there is a disconnect between applications that require large parameter spaces screening and the opportunity to take advantage of this information-rich method. By addressing the NMR throughput challenge, it could lead to a signicant push to diverse elds, including drug discovery screening, clinical analysis, chemical process monitoring, bio-uid metabolomics, and food analysis.

Consider the eld of drug discovery as an example; NMR can resolve the binding of drugs to pathogens and can be used for screening compound libraries to investigate the molecular interactions with target proteins [15, 16]. Pharmaceutical companies have molecular libraries containing millions of compounds, which is ever-increasing as new molecules are being synthesized utilizing combinatorial methods. For example, Pzer, Inc. maintains 4 million compounds inside their molecular library that can be used for analyzing potential medicines, as reported in 2017 [17]. Hence, the development of high throughput NMR methods is a must to enhance the screening eciency of these massive and ever-increasing molecular libraries.

## **7.1 High throughput NMR approaches**

For the last decades, developing high throughput NMR techniques has been addressed extensively with the goal to involve this powerful technique in screening these large compound libraries. For a fully automated NMR measurement, several steps should be controlled [184]. The NMR spectroscopy process involves sample preparation, transferring the desired sample into the magnet, adjusting the NMR instrument (tuning, matching, shimming), performing the

This chapter's text was partially reproduced and adapted from the author's published work [ON5] (CC BY 4.0, 2021 Springer Nature)

measurement, transferring the sample outside the magnet, and processing the data. Several approaches have been developed, which can be divided into three main concepts: i) automated sample changers; ii) probe with multi RF coils; and iii) ow-based NMR systems.

### **7.1.1 Automatic sample changer**

The rst approach to be discussed is the automated sample changer systems. This approach was developed to analyze multiple samples with avoiding the manual samples changing as possible, i.e., overnight or weekends. The system possesses a sample preparation holder where each sample is physically separated to avoid cross-contamination. The sample holder is connected to the NMR magnet to transfer each sample individually using a pneumatic control system. Automated sample changers provides the user with easy and safe access to the NMR magnet without the need for ladders or steps. This automation approach allows users to access and automated operation overnight, which enhances the NMR spectroscopy throughput. Besides the automation process, manual control for the sample handling system is usually possible using a push button. Therefore, automated sample changer systems have been adequate for individual NMR glass sample tubes. However, this approach automates only the sample transfer into and outside the NMR magnet. The throughput is still limited by the NMR instrument re-adjusted (tuning, matching, shimming) after each sample exchange.

Since the automated sample changer was rst introduced, it has been enhanced and developed where commercial automated changers are now available and capable of queuing up to ∼ 500 samples for the NMR measurement [184,185]. For illustrating the capability of the automated sample changers, two examples of commercially available systems are discussed below. The rst example is for a sample changer system provided by Brucker [186], a photo of the system is shown in Fig. 7.1a. The sample holder possesses 24 or 60 sample positions compatible with various NMR sample tube lengths and diameters. The system can be connected to almost all Brucker's NMR magnets. The system has the distinction of being vibration-free and has no RF interference eect on NMR coils. Two versions of the systems are provided to control the samples set-point temperature, heated and cooled version. The heated version has a temperature range from room temperature up to 125 °C; thus, liquid polymers could be analyzed. On the other hand, the cooled version has a temperature range from 4 °C up to 40 °C, which is appropriate for analyzing various samples such as protein or biouid solutions.

The second example is the ASC24 system provided by JEOL [187], a photo of the system is shown in Fig. 7.1b. Several versions of the sample holder are available that possess 30, 64, or 100 sample positions. The sample changer is at the same height as the user, so no need for ladders or steps. Besides, there is a top-loading sample changer version installed on the top of the NMR magnet to save space. A manipulator controls the sample for insertion and ejection through an NMR magnet. The automatic sample changer comes with several advantages, However, the main drawback of these systems is that it requires NMR instrument readjustment after the

Figure 7.1: Examples of the commercially available automated NMR sample changer systems. *The pictures are reprinted from the companies' websites [186, 187]*.

insertion of each sample, such as tuning and matching of the RF coils and shimming of the main magnet.

### **7.1.2 Parallel detectors**

Developing NMR probes with multiple RF coils has been considered a practical approach for enhancing the NMR spectroscopy throughput. Instead of using a single RF detector to acquire an NMR spectrum from a single sample, a probe with multiple RF detectors could be designed to excite and acquire signals from various sample volumes simultaneously. Commonly, the reported multiple-coils probes have been designed in a way that each RF coil is warped around a capillary where the sample is located.

Sample excitation and NMR signal acquisition have been conducted following two main approaches using parallel coil NMR probes. The rst approach is attaching all coils to a single resonant circuit, and a gradient eld is applied during sample excitation to provide spatial frequency dependence. Thus, one receiver is used to acquire the NMR signal from the multiple coils, and each sample's signal is separated based on the frequency shift introduced by the gradient eld. This approach provides the advantage of simple hardware construction. Mac-Namara et al. [188] introduced a four coils NMR probe, shown in Fig. 7.2a. The four coils are connected in parallel and attached to a single resonance circuit with trimmer capacitors; the circuit is located beneath the sample region. To dierentiate the acquired signal based on the sample location, a static linear eld gradient has been applied in the direction of the *B*0 eld by changing the shim power supply.

The other approach is providing a separate resonant circuit for each coil to excite and detect signals separately with avoiding RF interference and coupling between the coils. Fabricating several RF receivers adds to the system hardware complexity and cost. Wang et al. [189] introduced an eight coils probe head developed with an interface to four receiver channels

spectrometer, shown in Fig. 7.2b. The eight coils have been divided into two groups (four coils each) where data from one group are acquired at a time. For designing an eight coils probe to t into the NMR magnet homogeneous region, the impedance matching circuits have been designed to be away from the coils. This design reduces the eciency of the RF coils, but a compromise for enhancing the lling factor was considered. Additionally, sucient grounding and proper shielding between the coils' circuits were required to avoid RF cross-coupling and interference as much as possible.

An application for the multiple coils principle is NMR detection for continuous-ow capillary electrophoresis (CE) [190]. Capillary electrophoresis is a powerful separation method for a mixture of various samples by exposing them to a transient electric eld. Although no physical separation, NMR measurement can be conducted based on the dierent electrophoretic mobility of the dierent samples [191]. Wolters et al. [190] introduced a two coils probe that has been used with performing CE NMR spectroscopy. Figure 7.2c shows a schematic illustration of the CE/NMR system with multiple coils. The system possesses a single separation capillary connected to multiple outlets, where each outlet has a coil with its detecting circuit. The coils' circuits are attached to an electromagnetic relay switch to determine which coil is

Figure 7.2: Examples of state-of-the-art multiple parallel coil NMR probes. **(a)** NMR probe head with four parallel ow-through coils [Right]. Spatial frequency encoding is considered for using single resonance circuit [Left], *reprinted from [188] with permission of Elsevier (Copyright © 1999 Elsevier Science B.V.)*. **(b)** NMR probe head with eight parallel RF coils. Each coil has its own resonant circuit, *reprinted from [189] with permission of Elsevier (Copyright © 2004 Elsevier Inc.)*. **(c)** Schematic illustration of the CE/NMR system with two micro-NMR RF coils [Right]. The results [Left] show that system with multiple coils and CE ow could separate the spectra, as shown in (A) and (B). On the other hand, without CE, the spectra are overlapped, as shown in (C), *reprinted with permission from [190], Copyright ©2002 American Chemical Society*.

connected to the transmit/receive channel, i.e., one coil is active at a time. Hence, continuous CE ow sequentially direct sample ow into the various outlets, and cycled stopped-ow detection process is conducted between the multiple NMR detectors.

In principle, the number of coils in multiple coil probes can be scaled up to increase the throughput, nevertheless, a limitation arise from the small volume of the homogeneous *B*0 eld inside the NMR magnet. The design of the coils and the minimum coils spacing should be considered to avoid RF cross-coupling and interference that could result in signals bleed between neighboring coils, i.e., exciting a specic coil can generate an RF signal in the adjacent detecting coil. These challenges could be addressed in several ways, such as; considering only one active coil and de-tuning the inactive neighboring coils or using dierent frequency adjustments for the various coils.

### **7.1.3 Flow-based NMR**

Flow-based NMR systems have also been considered to achieve high throughput NMR spectroscopy [192, 193]. Flow-based NMR spectroscopy is done by transferring a sample from outside the magnet through the NMR detector using uidic tubes. Several liquid handlers are available commercially (e.g., multiple probe 215 liquid handler provided by Gilson Inc [194]), or even standard syringe pumps can be used to inject the sample into the inlet of the owinjection probe. After analyzing the sample, it is transferred out of the magnet, and the following sample is injected without the need for hardware disassembling. Solvents can be used between every two successive samples for the rinsing purpose of the probe's tube to avoid cross-contamination. The main advantage of the ow-based approach is that the NMR instruments should be adjusted once (shimming, matching, and tuning) for the rst sample, and no need for re-adjustment.

Rehbein et al. [195] introduced a ow probe with a double resonance solenoidal detector having an active detection volume of 2 µL used for capillary HPLC-NMR spectroscopy coupling, a picture of the probe head and the whole system is shown in Fig. 7.3a. The NMR RF coil is warped directly around a horizontal capillary (OD/ID, 1.5/0.8 mm) attached at both ends to vertically oriented ow tubes. The NMR detector is immersed in a uorinated oil (FC-43) to match the susceptibility miss-match between air and copper. By using the introduced system, NMR spectroscopy can be done in a continuous-ow or stopped-ow measurement. The advantage of the stopped-ow method is that the NMR acquisition time could be increased leading to a greatly enhanced SNR. Also, with this method, it is possible to record 2D correlation NMR spectra.

Carret et al. [10] introduced a ow-based device that is compatible with any commercial NMR probe head, a picture of the device is shown in Fig. 7.3b. The device possesses a micro-coil with an inlet and outlet for the sample ow. The NMR signal is transferred from the micro-coil to the NMR system detector through induction coupling.

Macnaughtan et al. [196] introduced a system where a multiple coil probe is combined with ow-based NMR spectroscopy, a picture of the system is shown in Fig. 7.3c. The system injects four samples simultaneously into four coils installed on a probe head using a liquid handler possessing four controllable syringe pumps. The time consumption is improved by a factor of four compared to a single ow-through system. The four micro-solenoidal detectors were connected in parallel and attached to a single resonance circuit with two variable capacitors for tuning and matching. NMR analysis was performed based on the chemical shift imaging or selective excitation between the four NMR detectors [197].

The ow-based approach has proven to be a reliable alternative to enhance the NMR spectroscopy throughput, with additional enhancements by developing probes with multiple RF

Figure 7.3: Examples of state-of-the-art ow-through NMR probes. **(a)** A probe head possessing a microsolenoidal coil for ow-based NMR spectroscopy [Left]. Schematic illustration for a capillary HPLC-NMR spectroscopy coupling system, *reprinted from [195] with permission of John Wiley & Sons, Inc. (Copyright © 2007 WILEY-VCH Verlag GmbH & Co. KGaA)*. **(b)** Schematic illustration for a ow-based NMR device that is compatible with commercial NMR probe heads. *reprinted with permission from [10], Copyright ©2018 American Chemical Society*. **(c)** Schematic illustration for a system combining multiple coil probe with ow-based NMR spectroscopy, *reprinted with permission from [196], Copyright ©2003 American Chemical Society*.

NMR detectors. However, ow-based NMR spectroscopy faces mainly two challenges:

## **7.2 Adapted approach**

The sample exchange phase during an NMR experiment is not necessarily the only timeconsuming step. NMR spectroscopy is famous for its high resolution, with spectral line widths in ppb. This is because nuclear spins have relatively long relaxation periods, typically in the term of seconds for hydrogen nuclei in the liquid state. The relatively lengthy re-equilibration delay results in restricting the number of times an NMR experiment can be replicated. This recycling delay can be eliminated under the ow-based approach as freshly polarized samples are continuously transferred into the NMR-coil detection volume, avoiding the need for re-equilibration. This is particularly signicant when the target nuclei have relatively long relaxation time constants [10]. Combining the lengthy recycle times with the insensitivity of NMR spectroscopy results in the NMR being a low throughput technique. Hence, in situations where sample exchange and recycle delay become time-limiting processes, a ow-based approach will outperform the traditional sample handling technique and enhance throughput.

Therefore, a ow-based NMR spectroscopy is adapted here to enhance the NMR throughput. Instead of exchanging individual sample containers traditionally, a ow-through NMR system can be used to deliver a series of concentrated sample plugs separated by an immiscible uid from outside the magnet through the NMR detector. This two-phase ow eliminates the dead volume but requires continuous online measurement to track the sample plug's position and velocity to ensure that the target sample lls the NMR detection volume. In this contribution, a novel ow-based NMR system is introduced. The ow system features: i) integrated capacitive sensors for sample position and velocity measurements; and ii) a micro-saddle coil for

NMR spectroscopy. This ow system enables fully automated NMR spectroscopy while taking advantage of the improved experimental time per sample due to continuous sample ow. The system is discussed in detail in the next Chapter 8.

A ow-based NMR spectroscopy is extremely attractive when target sample quantities are small; instead of dealing with poor lling factors or diluting samples using standard NMR hardware, microuidic technologies and micro-NMR techniques can be used. The following subsections provide an overview of the state-of-the-art micro-NMR detectors and ow sensors.

## **7.3 Micro-NMR detectors**

The RF coil is the core element of the NMR system, allowing interaction of measurement device with the target sample magnetization. In this part of the thesis, 'coil' refers to any device capable of generating and detecting magnetic elds. The topology and design of the RF coil have a signicant impact on the NMR measurement. This section provides an overview of various NMR coils, which can be divided into two main categories: volume and planar.

### **7.3.1 Volume coils**

There are many shapes of the volume coils, such as solenoidal and Helmholtz coils. Volume coils have better eld homogeneity than planar coils. In the case of analyzing samples that can be cast into a cylindrical shape, such as liquids or powders, volume coils are the proper choice since the probe volume can be lled optimally, resulting in a high lling factor and sensitivity.

#### **Solenoidal coil**

Solenoidal coils have the classic topology represented by helically wrapped thin conductive wire around a cylinder used as a mechanical support for the coils. A schematic of the solenoidal coil is shown in Fig. 7.4a. In the case of NMR application, the supporting cylinder is a capillary that holds the sample during the measurement. Solenoidal coils are attractive for micro-NMR applications due to their several advantages including high lling factor, high sensitivity, ease of electric decoupling, highly uniform magnetic eld within the coil's core, and easily manufactured on the micro-scale [201].

However, integrating solenoidal coils into an NMR system faces some issues. The rst drawback is the sample handling, especially in ow-based spectroscopy, since the coil should be transversely located inside the NMR magnet. Another drawback is that the NMR magnet homogeneous *B*0 eld needs to penetrate through the coil's tracks before it polarizes the sample. This leads to the distortion of the *B*0 eld due to the susceptibility mismatch of dierent material interfaces, resulting in broader NMR signals. There are several approaches to overcome this challenge, for example, adding susceptibility materials for matching purposes [202].

Figure 7.4: Examples of state-of-the-art volume NMR coil. **(a)**, **(d)**, and **(f)** Schematic illustration for the solenoidal, Helmholtz, and saddle coils, respectively. The schematic illustrations show the *B*0 and *B*1 elds' expected orientations. **(b)** and **(c)** Examples for micro-solenoidal coils. **(b)** *Reprinted from [198] with permission of AIP Publishing (Copyright © 1997 AIP.)*, and **(c)** *reprinted from [199] with permission of Elsevier (Copyright © 2009 Elsevier B.V.)*. **(e)** Example for micro-Helmholtz coil, *reprinted from [200] with permission of IOP Publishing (Copyright © 2014 IOP Publishing Ltd)*. **(g)** and **(h)** Examples for micro-saddle coils. **(g)** *Reprinted from [143] with permission of IOP Publishing (Copyright © 2017 IOP Publishing Ltd)*, and **(h)** *reproduced from the author's published work [ON5] (CC BY 4.0, 2021 Springer Nature)*.

The coil eciency (*B*1/*I*) is the coils ability to produce a magnetic eld from a unit current which also expresses the detector ability to convert the NMR signal into a voltage signal [27]. Solenoidal coil eciency depends on the number of turns and the coil diameter [28],

$$\frac{B\_1}{I} = \frac{\mu\_0 N\_C}{d\_C \sqrt{1 + (h\_C/d\_C)}},\tag{7.1}$$

where *NC* is the number of turns, *dC* is the coil diameter, and *hC* is the coil height. The previous equation shows that decreasing the coil diameter, with maintaining a constant *hC*/*dC* ratio, increases the coil eciency. Hence, solenoidal coils on the micro-scale were developed using MEMS fabrication techniques [203].

#### **Helmholtz coil**

The basic shape of a Helmholtz coil is a pair of identical circular coil loops which are placed apart with a distance equivalent to the radius of the coil loop with a common axis. A schematic of the Helmholtz coil is shown in Fig. 7.4d. The two loops are electrically connected in series so that the same current passes through them in the same direction to generate a homogeneous *B*1 eld in the center.

The main advantage of Helmholtz coils over solenoidal coils is the homogeneity and direction of the *B*1 eld, which aligns the coil loops with the *BO* eld. Hence, the *B*0 eld does not penetrate several material interfaces as in the case of solenoidal coils, reducing *B*0 eld distortion. Moreover, the Helmholtz coil orientation inside the *B*0 eld results in more convenient sample handling, especially in ow-based NMR, where there is no need to remove the probe head to exchange the sample. Helmholtz coils can be fabricated using the MEMS technologies, where each of the two loops could be considered as a planar structure and then connected together [200,204]. But, the Helmholtz coils have lower sensitivity than the solenoidal coils [27].

#### **Saddle coil**

Saddle coil is a special type of a Helmholtz coil, where the coil loops take a cylindrical arrangement other than the planar arrangement in classical Helmholtz coils. A schematic of the saddle coil is shown in Fig. 7.4f. The cylindrical geometry maximizes the coil's lling factor, thus, saddle conguration for NMR is an appealing possibility for tube-based NMR experiments. For better magnetic eld homogeneity, it was shown that the angular width for each coil loop should be ≈ 120°, and the separation arc in between the loops should have angular width of ≈ 60° [205].

Saddle coils feature similar advantages as Helmholtz coils regarding *B*1 eld homogeneity and direction, as previously discussed. Moreover, they provide ample sample space, so an easier sample handling that is compatible with stationary and ow-based NMR.

The main challenge facing the saddle coil is the fabrication at the micro-scale due to the 3D conguration. In 2018 Wang et al. [143] introduced a robust micro-fabrication process for developing a micro-NMR saddle coil with an active sample volume of 82 nL. The developed process was to pattern 2D conductive layer onto a thin planar polyimide lm then rolling it around a glass capillary to achieve the 3D structure. The supporting glass tube was used as a microuidic sample chamber.

### **7.3.2 Surface coils**

Surface coils are the second group of coils beside the volume coils. Surface coils have simple structures that can be eciently designed and optimized compared to the volume coils. 2D planar coils could be easily fabricated at the micro-scale using standard lithography or fast prototyping techniques such as inkjet-printing [206]. The main advantage of the surface coils is

locating the sample on the top of the probe instead of inside of it, which means more straightforward sample handling and larger available sample space. Planar spiral and striplines are wide-used arrangements in MR applications.

#### **Planar spiral coils**

Planar spiral coils have been developed to oer small NMR detectors with high sensitivity and a straightforward sample handling. A schematic of the planar spiral coil is shown in Fig. 7.5a. The magnetic eld of the planar coils is not uniformly distributed in space; the magnetic *B*1 eld strength drops with distance from the coil surface. Hence, it is important to consider the sample location (volume of interest) with respect to the coil structure [209]. Moreover, a eld distortion is introduced by the electrical bridge between the outermost and innermost winding to create a closed-loop.

In the beginning, Stocker et al. [210] developed a rectangular planar micro-coil that was successfully employed to acquire NMR spectra of liquid samples. Later Dechow et al. [211] introduced micro-coils of gold tracks fabricated on gallium arsenide substrate with inner diameters ranging from 50 µm to 400 µm to serve samples with nL volumes. In 2015, Grisi et al. [212] introduced a single transceiver chip with dimensions of 1 mm2 , which features an integrated planar micro-coil. Montinaro et al. [213] used this chip to design 3D micro-channels to analyze sub nL samples using NMR spectroscopy. Commercial micro planar coils have been provided by Bruker BioSpin (Billerica, MA and Fällanden, Switzerland), which were used to interface

Figure 7.5: Examples of state-of-the-art surface NMR coil. **(a)**, **(b)**, and **(c)** Schematic illustration for the spiral planar, phased array, and striplines, respectively. **(d)** Example for micro-planar NMR coils, *reprinted from [206] with permission of Elsevier (Copyright © 2002 Elsevier Science B.V.)*. **(e)** Example for phased array coils, *reprinted from [207] with permission of IEEE (Copyright ©2011 IEEE)*. **(f)** Example for stripline, *reprinted from [208] with permission of AIP Publishing (Copyright © 2008 AIP)*.

digital microuidics with NMR micro-coils to manipulate droplets [214]. Lee et al. [215] introduced a phased array micro coils conguration to increase the eld of view (FOV), schematic for phased array coils is shown in Fig. 7.5b. A phased array is a conguration of multiple planar coils with a carefully designed dened overlap where the mutual inductance between the neighboring coils is canceled [207, 216]. This conguration is valid for samples with a large area or several parallel samples with minimal interference in between. Davoodi et al. [217] developed a broadband micro spiral coil that could acquire NMR spectra over a wide range of frequencies (125–500 MHz in an 11.74 T NMR magnet) without the need for a tuning interface circuit.

#### **Striplines**

Striplines or micro slot coils have a very simple structures; they are made od a single planar lines that can be easily fabricated using micro-fabrication technologies. A schematic of the stripline is shown in Fig. 7.5c. It operates as a wave-guide with geometrical dimensions that determine the resonance frequency, such as the conductive strip's geometries and the substrate's relative permittivity. Additionally, its magnetic eld *B*1 is proportional to the substrate (dielectric) thickness [218]. The matching circuit interface connected to the stripline signicantly aects its quality factor because of the thermal noise arise by the lumped components. This problem was raised while developing a lumped-element planar strip array (LPSA) to enhance parallel MRI imaging and decrease the scan time [219].

Several approaches have been developed to benet from the simple stripline structure and high sensitivity. The volume microstrip approach has been developed as a microstrips transmission line (MTL) to develop MR imaging of the human head [220]. In addition, this volume approach was also applied by using double microstrips for achieving a uniform magnetic eld within the volume of interest and better SNR. Moreover, they were able to analyze at samples such as cell layers [221]. Another approach to enhance the stripline magnetic eld homogeneity is adding two metal planes to force the eld line to be parallel to the planes, which enlarge the volume with a homogeneous magnetic eld [222]. Striplines have been utilized for analyzing living cells like cancer cells, where a microuidic device was developed to hold the sample then placed on the top of a micro slot detector to perform the NMR analysis [1].

## **7.4 Flow sensors**

Developing microuidic-compatible NMR devices has drawn signicant attention in recent years. Microuidic devices have been used in high-eld NMR spectroscopy (1H resonant frequency > 200 MHz), often integrating ow for biological sample monitoring [1–3], chemical reaction tracking [4–8], sensitivity enhancement techniques [9–12], and most recently, electrochemical functionality [13]. Except for the digital microuidic approach [8,223], the target sample in these examples has always been transferred from outside the magnet without considering the sample handling situation. For ow-based NMR spectroscopy, sample loading is done from outside the NMR magnet. Thus, eliminating dead volumes in lling transfer lines (often a few meters in length) before the sample reaches the NMR detector is the challenge. The feading dead volume can be converted into a multi-sample queue using two-phase ow, achieving high throughput by taking advantage of microuidic technologies. Hence, online tracking of the sample position and velocity must be addressed to ensure each NMR signal acquisition is synchronized to the target sample.

Fluids in microuidic applications are commonly detected by employing either optical or electrical sensing systems, examples of state-of-the-art ow sensor are shown in Fig. 7.6 . Electrical sensing is appealing for two-phase ow since samples are usually optically similar. Moreover, aqueous samples have a dielectric constant at least an order of magnitude dierent from standard immiscible oil. Hence, electrical sensing is an excellent candidate for two-phase plugs ow detection.

### **7.4.1 Optical sensors**

An optical sensing system consists mainly of an optical source, optical detector, and waveguides to guide the light beam. Several optical sources have been used, e.g., semiconductors laser sources, based on amplifying the stimulated emissions. Each laser has specic parameters

Figure 7.6: Examples of state-of-the-art ow sensor. **(a)** Liquid droplets detection using an optical system. [Top] Schematic illustration of the system, and [Bottom] microuidic device with the ow optical detecting system, *reprinted from [224] with permission of Elsevier (Copyright © 2005 Elsevier B.V.)*. **(b)** Multiplexed arrays (4 × 4) of capacitive and resistive sensors for sensing the ow of liquid plugs. The resistance of the resistive sensors (thin-lm serpentine resistors) varies according to the thermal conductivity of the liquid in contact. [Top] Schematic illustration of the multiplexed sensors, and [Bottom] microscopic image of the resistive sensors, *reprinted from [225] with permission of Elsevier (Copyright © 2008 Elsevier B.V.)*. **(c)** Microuidic device integrating capacitive sensors (coplanar electrodes) positioned beneath a ow channel with a thin insulation layer to prevent direct contact with the target uids. The capacitance of the sensor changes according to the permittivity of the owing uid. [Top] Schematic illustration of the microuidic device with an array of the capacitive sensors, and [bottom] microscopic image of the coplanar capacitive sensor, *reprinted from [226] with permission of Elsevier (Copyright © 2011 Elsevier B.V.)*.

such as the operating wavelength, single or multiple modes, and beam quality; the parameter of the laser is selected based on the application. Several optical detectors have been utilized, such as photo-diodes, photo-multiplier tubes (PMT), and charged coupled devices (CCD). The optical detector is used to receive the optical signal and detect the change in the signal intensity corresponding to a parameter of the sample. The detector converts the change in the light intensity to an electrical signal to be analyzed.

Optical sensing systems are widely used for medical, cosmetic, and food industries. Nguyen et al. [224] developed an optical sensing system to control droplet size in a microuidic dropletbased system. The laser source was located above the micro-channel and a photo-diode detector on the other side of the channel. The laser light intensity varies as a droplet crosses the light beam due to diraction and absorption. As a result, the size and the shape of the droplets can be recorded. Camer et al. [227] developed an optical sensing system for counting formed droplets in a dripping system. The optical system was built around a transparent rectangularshaped ow channel with a width of 2.5 mm. A 760 nm laser source is located on one side of the channel, and a detector is located opposite it. The detector senses the interruption of the laser beam whenever a drop crosses it and transmits electrical data with a frequency of 200 kHz. Additionally, a CCD camera is used to monitor the drop breakup during dripping.

The optical methods have the advantage of being a non-invasive sensing technique, extending the exibility in sample handling. However, the main challenge is that the target samples are often optically similar. Other than the optical sensing system, the sensing element of the electric sensors can be easily fabricated using the standard lithography process within microuidic devices.

### **7.4.2 Electrical sensors**

Flow electrical sensors are mainly based on changing the impedance of the sensor corresponding to a change in the physical properties of the material in their vicinity. The commonly used ow electrical sensors could be categorized into resistive and capacitive sensors. Capacitive sensors provide an output signal based on the target sample dielectric constant, while resistive sensors sense the samples based on their thermal conductivity.

#### **Resistive sensors**

Resistive sensors are thermosensitive sensors, where the resistance changes with the change of the temperature. By applying a constant potential dierence across the resistive sensor, its temperature settles at constant temperature based on its temperature coecient of resistance (TCR) and the surroundings thermal conductivity. When samples with dierent thermal conductivity, or samples of the same liquid owing at dierent velocities, ow over the resistive sensor, the sensor's temperature varies correspondingly, changing the sensor's resistance and thus the output current.

Several studies have employed resistive sensors in droplet detection [225, 228]. However, The main limitation of the resistive sensor is that the target uid should come in direct contact with the sensor to change its resistance. This direct physical contact between the sensor and the sample could lead to sample's temperature uctuation and cross-contamination.

#### **Capacitive sensors**

The capacitive sensor is a suitable choice for most microuidic applications. In general, the capacitance of a capacitive sensor changes according to the change in the insulator dielectric constant or the capacitance dimensions. Capacitive sensors are suitable for various applications such as position, angle, pressure, and ll level measurements. The sensor conguration is optimized according to the application, e.g., in the case of ll-level capacitive sensors, the sensor conguration depends on whether the uid is conductive or non-conductive [229]. For conductive uid, the uid is considered as counter electrode, and an insulated electrode is immersed into the liquid with a single conductive electrode. On the other hand, for nonconductive uids, the uid is considered the dielectric insulator between the two inserted conductive electrodes. Soenksen et al. [230] developed a capacitive sensor to monitor and control a uid height without direct contact with the uid. Elbuken et al. [226] developed a planar interdigitated capacitive sensor for measuring droplets' size and speed. Ghafar-Zadeh and Sawan [231] developed a hybrid microuidic/CMOS capacitive sensor. The design of the sensing part is based on interdigitated electrodes (IDC), where the system output signal varies according to the dielectric constant of the material in contact.

Capacitive sensors feature several advantages including high sensitivity, no physical contact or interference with the sample, small temperature inuence, and good stability and reproducibility. In contrast, they feature some drawbacks such as the electrical connection inuences the output reading (i.e., interfacing electronic should be located near it), sensitivity to humidity and dust, and sometimes shielding is required to avoid susceptibility for interfering signals.

# **8 Automated high throughput NMR system**

**T** his chapter presents a thorough description of the design, characterization, and fabrication of a fully automated high throughput NMR system. Automating the NMR spectroscopy is achieved by combining microuidic technologies with thin-lm micro-NMR detectors. The system is based on the concept of ow-based NMR spectroscopy, where plugs of the target samples are loaded into a exible microuidic tube separated by an immiscible uid. The exible tube is fed through a glass capillary with a micro-NMR detector, and ow sensors are rolled around it and placed in the isocenter of an NMR magnet. The arrangement of successive plugs of samples and immiscible uid is kept under continuous ow. The ow sensors detect the aqueous-oil interfaces and synchronize the NMR spectroscopy acquisition via a microcontroller. The system possesses a pair of ow sensors that allows the system to operate regardless of the ow velocity and the plug volume.

This chapter is divided into four sections. Section 8.1 explains the technical details for the different components of the automated NMR system. Within this section, the control system's hardware connections and software algorithms are presented. Section 8.2 discusses the design, optimization, and characterization of the micro-NMR detector. Section 8.3 discusses the design, optimization, instrumentation, and validation of the ow sensing system. Section 8.4 introduces a robust thin-lm micro-fabrication process used for fabricating the micro-detector and ow sensors.

## **8.1 System description**

Figure 8.1a presents an overall schematic of the hardware components of the actively synchronized NMR system, with a detailed illustration of a custom-built NMR probe head in Fig. 8.1b. The primary part of the automated NMR system is a custom-built NMR probe head. The probe head is built from a 3D printed holder (see Appendix D for the holder's working drawing) supporting a PCB that possess three substantial modules:

1. **A micro-NMR detector** attached to pre-tuning and matching capacitors.

The pre-tuning and matching network is built from three non-magnetic capacitors (S111DUE, Johanson Technology) soldered directly on the PCB, having a balanced conguration of *CM*,*PCB* − (*L* k *CT*,*PCB*) −*CM*,*PCB*. The capacitor values can be modied to adjust the resonance frequency of the micro-NMR detector so the NMR spectroscopy could, in principle, be performed on any NMR-sensitive nucleus. This tuning and matching conguration is discussed previously in detail in Subsection 2.4.3, where

This chapter's text and gures were reproduced and adapted from the author's published work [ON5] (CC BY 4.0, 2021 Springer Nature)

Figure 8.1: Overall diagram of the fundamental elements of the novel high throughput NMR experimental setup. **(a)** A microuidic Teon tube (OD/ID, 1.6/1 mm) is utilized to transport a sequence of plugs of various samples separated by an immiscible uid through a custom-built NMR probe installed in an 11.7 T NMR magnet. A syringe pump is used to regulate the ow from outside the NMR magnet. A microcontroller is used to drive a pair of ow sensors integrated on the probe head to determine the samples' velocity and location and synchronize the NMR data acquisition. **(b)** Photograph of a customized probe head installed on the NMR probe. The probe head consists of a PCB supported by a 3D printed holder. The PCB possesses a micro-NMR coil with a pretuning and matching network, two ow sensors with their interface electronics, and a glass capillary (OD/ID, 2.15/1.72 mm) through which the exible sample ow tube is fed. Right: microscopic images for the micro-NMR detector, the IDC sensor, and the insertions of the Teon tube inside the glass capillary. Left: schematic diagram of the equivalent electronic circuit in the NMR probe.

*CT*,*PCB* is used to tune the NMR detector to 1H NMR frequency, and *CM*,*PCB* is used to match the circuit to 50 Ω to guarantee signal transfer and prevent signal reection.

2. **Two capacitive ow sensors**, before and after the micro-NMR detector, electrically connected to a capacitance-to-digital converter (CDC) microchip to convert the sensors' reading to digital data to be transferred outside of the magnet.

Two sensors were used to enable velocity calculation, where the total separation distance between them is set to 30 mm. The two sensors are anking the NMR detector with a separation of 10 mm w.r.t. the detector so that the NMR automated spectroscopy is independent of the ow direction. The capacitive sensors' readings were transferred to a microcontroller unit (MCU) located outside the NMR magnet via the CDC integrated circuit (IC). In addition, a digital pin of the MCU was connected to the triggering signal input-output unit (TTL I/O) of the NMR spectrometer console to synchronize NMR experiment acquisition.

3. **A glass capillary** with the micro-NMR and the ow sensors rolled around to contain the exible microuidic tube holding the ow.

The exible microuidic tube (OD/ID, 1.6/1 mm) holding the sequence of samples was

fed from outside of the NMR magnet through a customized NMR probe and the glass capillary (OD/ID, 2.15/1.72 mm). This arrangement of tting the ow tube inside the glass capillary provides several advantages:

The probe head's polylactic acid (PLA) material and the FR-4 of the PCB were eliminated next to the micro-NMR detector as they are a source of background signal and aect the homogeneity of the magnetic eld. The probe head was designed to be compatible with market available micro-imaging NMR probe and a triple-axis micro-gradient sleeve (Bruker). Hence, the system is compatible with pulsed-eld gradient (PFG) sequences for the magnetic resonance imaging (MRI) experiments.

The probe head is connected to the 1H channel of the custom-built NMR probe. The design of the NMR probe is adopted from commercial probes. The main addition in the developed probe is four built-in pipes inside the probe, allowing uidic and electrical access to the probe head. Like other commercial probes, the probe posses two trimmers (0.5 - 10 pF, TG 092 ROHS, EXXELIA) connected in series to the probe head for ne-tuning and matching. The trimmers can be mechanically adjusted using glass ber rods from outside the magnet. Figure 8.2 shows the conguration of the tuning and matching network in the probe and the probe head. The xed capacitor *CP* is added to the probe's circuit to set one of the trimmers in parallel with the probe head circuit to enable the tuning functionality; this electrical conguration is discussed in detail in Subsection 2.4.3. The probe was designed to locate the micro-NMR detector in the NMR magnet isocenter (the region with the magnet's highest homogeneity ). Locating the micro-detector in the isocenter enables the spectrometer shim system to correct the static *B*0 eld's minor deviations within the detection volume. A 3D CAD model of the probe is available in Appendix D.

Figure 8.2: Electrical RF tuning and matching network in the NMR probe. The saddle coil's three-terminals are connected in a way to keep the electrical current owing in the opposite direction in the two loops so that their magnetic eld constructively interfere in the coil center. The probe head has xed capacitors for pre-tuning and matching, and the probe has trimmers for ne-tuning and matching.

The train of samples was kept underow using a syringe pump positioned outside of the NMR magnet. Loading the microuidic tube with the samples was done manually and automatically, as discussed in Subsection 8.1.2.

### **8.1.1 Control system**

Figure 8.3 presents a schematic diagram of the hardware components of the automated NMR control system. As the train of aqueous plugs and oil plugs ow through the capillary tube with the ow sensors, a dierence in the sensors' capacitance is detected. The change in the capacitance results from the dierent eective dielectric interacting with the sensor's electric fringe eld. The changes in the capacitive sensor's values are then sensed by the MCU, which in turn synchronizes the NMR acquisition to collect the spectrum for each plug separately. The MCU sends the digital triggering signal (TTL) via a DIO pin (high = 5 V, Low = 0 V) to the TTL I/O unit of the NMR console. Hence, during the automatically synchronized NMR experiment, two software algorithms are executed in parallel. One algorithm on the MCU responsible for sending the TTL signal based on the ow interface. The other algorithm is the pulse sequence program on the NMR acquisition software (TopSpin 3.5pl2, Bruker BioSpin) to receive the TTL signal and increment the FIDs to save the spectrum from each plug on a dierent memory location.

Figure 8.4 presents a ow diagram for both algorithms, the source codes of the two algorithms are attached as supplementary material in Appendix D. On the NMR pulse program side, the acquisition software starts collecting the NMR scans of the rst FID following the system start. Following each collected scan, the NMR acquisition software checks the triggering input signal value sent from the MCU on the TTL signal pin in the NMR consol TTL I/O unit. If the TTL signal is low (0 volts), the spectrometer accumulates the collected scan to the current FID. In case the TTL signal is high (5 volts), the current FID is saved to the disk after adding the last NMR scan and then initiates the next FID measurement. Meanwhile, on the MCU side, the program monitors the capacitance values of the two sensors simultaneously. Once the measured capacitance value of either of the two sensors overrides a user-set threshold value,

Figure 8.3: Schematic diagram demonstrating the main hardware elements of the control system. The NMR data acquisition is synchronized by the microcontroller, which sends the TTL signal to the NMR spectrometer console's TTL I/O unit. The microcontroller generates the TTL pulse according to the values of the ow sensors.

the current time is recorded (*t*1). Additionally, a TTL signal is sent from the MCU'S DIO pin to the TTL pin in the TTL I/O unit of the NMR console after a delay (*d*). Subsequently, the MCU monitors the other sensor's capacitance value until it overrides the threshold value, and then

Figure 8.4: Flow chart illustrating the executed algorithms on both the MCU and the NMR acquisition software. During an automated NMR experiment, the two algorithms run in parallel. The algorithm on the MCU triggers the NMR pulse sequence to increment the FID based on the sample presence.

it records the time (*t*2). Afterward, the MCU monitors the rst sensor's value until it becomes lower than the threshold level, after which the MCU sends a TTL signal after a delay (*d*). Consequently, for each plug, the NMR TTL I/O unit receives two triggering pulses, the rst TTL pulse when a sample plug enters the NMR micro-detector (start new NMR FID acquisition) and the second TTL pulse when it leaves the micro-detector (save the current NMR FID). Afterward, the MCU monitors both sensors' capacitance value in a threshold detection loop, waiting for the next plug. This control algorithm results in saving the NMR scans collected for each sample in a dierent FID. At the beginning of each loop, the MCU monitors both sensors' capacitance values to maintain the exibility of running the NMR experiment in a bidirectional ow.

The triggering signal is always sent from the MCU to the NMR TTL I/O unit after a time delay (*d*) to ensure that the sample plug either reached or entirely left the NMR micro-detector. The delay (*d*) is calculated base on the times (*t*1 and *t*2) recorded during the ow using Equation 8.1, taking into consideration the separating distance between the ow sensor and the NMR detector of 10 mm, the total gap between the two ow sensors of 30 mm. The initial value of the time delay *d* is set to zero and updated after the MCU measures each plug's velocity. Hence, a dummy plug is usually added at the beginning to determine the time delay's rst value, which depends on the ow velocity.

$$d = \frac{t\_2 - t\_1}{3}.\tag{8.1}$$

On the one hand, to guarantee that the NMR spectrometer captures the triggering pulse, the pulse width (t*T T L*) needs to be longer than the summation of the NMR scan's acquisition time (*TAQ*) and relaxation delay (*D*1). On the other hand, the TTL pulse width must also be shorter than twice the summation of acquisition time and the relaxation delay; otherwise, it will be captured twice by the NMR spectrometer:

$$(T\_{AQ} + D1) < \mathbf{t}\_{TTL} < 2 \times (T\_{AQ} + D1). \tag{8.2}$$

### **8.1.2 Sample loading**

Filling the microuidic tube with the samples can be done manually or automatically. In both lling regimes, the same sequence was adopted as follow:

After each lling step, the tube's terminal was immersed in a pure deionized (DI) water reservoir for cleaning to avoid cross-contamination. Once all sample plugs are loaded in the tube, the ow was continuously switched on for the NMR acquisition.

In the manual lling regime, the motion of the tube's terminal between the dierent reservoirs and the synchronization of the syringe pump were both done by the user. On the other hand, in the automatic lling regime, a robotic arm was used to move the tube's terminal. A MCU was used to control the syringe pump and synchronize it with the robotic arm motion. An overview of the components of the automatic lling is illustrated in Fig. 8.5.

The automatic loading system consists of an MCU (Arduino Mega 2560 and customized Arduino shield), a robot arm (UR3e, UNIVERSAL ROBOTS), a syringe pump (Fusion 200-X Touch, KR Analytical), and a router. This shield contains a Wi-Fi module (ESP8266), a serial-RS232 converter, a switch for resetting the controller, and an LED to indicate the current controller activity. The MCU is connected to the syringe pump via a DB-9 serial connector, through which the pump receives the required commands to change pumping settings. The router is

Figure 8.5: Overview of the hardware components of the automated plugs loading system.

used as a message queuing telemetry transport (MQTT) host, through which the communication between the MCU and the UR3e robot arm is achieved wirelessly.

The user interface to control the automated loading system comprises three programs that all run on a computer and are connected to the MCU. The user interface allows the researcher to program the system's pumping sequence and know its progress. These programs include: i) an excel workbook that serves as the front-end where the user can set up the experiment sequence; ii) a python le that runs in the Windows shell, takes the input from the excel le and sends the control signal to the pump and the wi module; and iii) a program to monitor the MQTT client. A description of the user interface provided in Appendix D.

## **8.2 Micro NMR-detector**

### **8.2.1 Detector design and optimization**

The topology of an MR coil is typically dened based on the application and the target sample type. In general, volume coils are favored for NMR applications where the samples are chemical solutions or suspensions. In contrast, planar coils might be the choice for MRI applications where the samples have arbitrary shapes as tissues and animal organs. Key design considerations to maximize the performance (sensitivity and spectral resolution) for an MR detector are: i) the strength and homogeneity of the excitation magnetic *B*1 eld generated by the RF coil; and ii) the impact of the MR coil conductive tracks on the homogeneity of the primary static magnetic *B*0 eld. The performance of the *B*1 eld has a direct impact on the measurement sensitivity. The *B*0 eld homogeneity deviates within the RF region due to a magnetic susceptibility mismatch between material interfaces, directly impacting the MR signal spectral resolution. An MR coil with a slight deviation in the *B*1 eld homogeneity is acceptable in MRI applications even though this will aect the image contrast. On the other hand, for NMR spectroscopy, any deviation in the coil performance means wasted signals which can be a problem with low concentrate samples. Hence for NMR spectroscopy, the RF coil needs to be carefully optimized.

For the presented ow NMR application, a saddle coil geometry has been adapted for its advantages. Saddle coil is one of the most used geometries in NMR spectroscopy. A saddle coil is a special case of a Helmholtz coil; it is built out of two square loops facing each other and arranged in a cylindrical manner, as shown in Fig. 8.6.

The homogenous *B*1 eld generated by the saddle coil is in the center of the arrangement and is perpendicular to the coil structure, making it very suitable for the ow-based NMR applications. Finite element simulations were performed for the magnetic eld generated by the coil. The simulation results in Fig. 8.7 show the magnetic eld orthogonality with the coil loops. Since the *B*1 eld should be orthogonal to the *B*0 eld, the coil is oriented along the

Figure 8.6: Photograph (left) and schematics diagram of a micro-saddle coil. Design parameters of the saddle coil include the perimeter gap between the two square conductor loops, the length of the coil detection region (L2), and the length of the electric power leads (L1).

axis of the *B*0 eld. Therefore, the ow tube can be easily fed along the magnet's axis, making the sample handling comfortable. Moreover, in this arrangement, the *B*0 eld needs to cross fewer material interfaces near the RF detection region, making re-shimming of the coil more manageable. A solenoidal coil has a much higher lling factor than a saddle coil; nevertheless, its *B*1 eld is along its axis, which places it perpendicular to the *B*0 eld. Hence, for a solenoidal coil shimming and ow tube feeding can be a big challenge.

Finite element simulations using COMSOL Multiphysics software were performed to optimize the micro saddle coil geometrical dimensions of the saddle coil. The optimization aims to select the coil geometrical dimensions in a way to enhance the generated radio frequency eld *B*1 per unit current while maintaining the static *B*0 and RF *B*1 elds as homogeneous as possible. In the simulation model, a micro saddle coil geometry was constructed around two concentric tubes to model a glass capillary and a Teon tube lled with water. The saddle coil with the

Figure 8.7: Simulated saddle coil model (left) and the resulted magnetic eld (right). The simulated magnetic *B*1 elds of the saddle coil's two loops are pointing in the same direction, and thus they constructively interfere in the coil center (sample region).

glass and Teon tubes was located inside a cylinder-shaped domain to model the surrounding air. Two simulation scenarios were considered:

In both simulation scenarios, the coil had a track width of 100 µm with *L*1 and *L*2 of 2 mm and 4 mm, respectively (see Fig. 8.6 for description). Additionally, the gap between the saddle coil two rectangular loops (θ2) was swept to obtain the best performance (highest sensitivity with the most homogeneous *B*0 and *B*1 magnetic elds). The gap was swept in a way that the gap perimeter (θ2 ×*r*) changed from 100 µm to 1300 µm at steps of 100 µm. The simulation results are presented in Fig. 8.8, the coil sensitivity and the static *B*0 eld homogeneity are plotted versus the gap perimeter (arc distance between the rectangular loops). Furthermore, the *B*0 and *B*1 magnetic elds distribution are illustrated at dierent gaps.

The simulation results reveal that for a saddle coil, conductive tracks with a high degree of symmetry not only enhance the *B*0 and *B*1 magnetic elds homogeneity but also increase the sensitivity. According to the simulation study, a gap of 700 µm (equivalent to θ2 of 37.3°) was selected for the coil fabrication. The full geometrical dimensions of the implemented saddle coil are summarized in Table 8.1. The fabrication process can be found in micro-fabrication Section 8.4.

Table 8.1: Geometrical dimensions of the integrated saddle coil in the custom-built NMR probe head.

Figure 8.8: Finite element simulation (COMSOL Multiphysics) studies the eect of changing the perimeter gap between the saddle coil's loop on the coil sensitivity and the *B*0 magnetic elds' homogeneity. The graph is the simulated coil sensitivity and the simulated *B*0 homogeneity versus the gap between the saddle coil's loop. The *B*0 and *B*1 eld top view proles at a cross-section in the center of the saddle coil are plotted for dierent gap values (Top).

### **8.2.2 Detector characterization**

The fabricated micro-saddle coil was evaluated following the dierent evaluation approaches summarized in Table 2.1 in the MR characterization Subsection 2.4.4.

With a rolled-up micro-saddle coil connected to the custom-built probe, pre-matching and tuning was accomplished by adjusting the capacitors soldered on the probe head's PCB and validated using a network analyzer (Agilent, E5071B). The reection coecient *S*11 was used to check the resonance of the resonator. The coil was consecutively tuned to 500 MHz, the 1H proton resonance frequency (Larmor frequency) at 11.7 T, and matched to 50 Ω, as shown in Fig. 8.9. By knowing the bandwidth at −3 dB (∆*f*−3 dB) of the resonance frequency ( *f*0) and substituting in Equation 2.35, the loaded quality factor for a batch of fabricated coils was measured to be *QP* = 50±2.

The probe head was characterized using NMR spectroscopy measurements conducted using an AVANCE III 11.7 T NMR system (1H resonance frequency 500 MHz, Bruker BioSpin) under

Figure 8.9: Measured reection coecient S11 of a micro-saddle coil. The coil is connected to the custom-built NMR probe and lled with an aqueous sample, tuned at 500 MHz and matched to 50 Ω. The bandwidth at −3 dB was measured to be approximately 20 MHz, resulting in a loaded quality factor of ∼ 50.

stationary (non-owing) conditions. The coil was lled with a test sample (30 mM TSP dissolved in deionized (DI) water) using a Teon tube with an inner diameter of 1.0 mm, yielding an active sample volume of 3.14 µL. FWHM of the 1H NMR water resonance was used to evaluate the spectral resolution (Fig. 8.10, red spectrum), with the micro-coil yielding a line-width

Figure 8.10: Characterization of the NMR micro-saddle coil. Measurements were performed using a micro-saddle coil at 500 MHz NMR magnet. The graph shows the NMR spectrum of water (red, lower scale) and NMR Excitation pulse nutation spectrum (blue, upper scale). The time delay between successive nutation measurements was 10 s.

of 1.25 Hz. The excitation *B*1 magnetic eld performance was assessed by acquiring a nutation spectrum (a series of 1H NMR spectra at xed supplied power of *P* = 1W, varying the excitation pulse width from 1-105 µs, in increments of 5 µs (Fig. 8.10, blue spectra). The nutation spectrum envelop time period was measured to be *T*nut = 204µs (90° ip angle achieved at 51 µs), thus the nutation frequency was calculated to be *f* nut = 4.9 kHz.

The *B*1 eld strength was calculated using Equation 2.33 to be *B*1 ≈ 230µT ( 1H gyromagnetic ratio γ 1H = 42.756MHzT−1 , angle between the *B*1 and *B*0 elds θ = 90°). Thus, the micro-coil sensitivity (η*P*) was calculated using Equation 2.31 to be approximately 230µT/ √W, comparable to the simulation result in Fig. 8.8.

Additional electronic components (sensors, AD7746, and MCU) were added to the NMR system for realizing a synchronized NMR spectroscopy. These hardware components come with the cost of adding noise to the NMR signal, as illustrated in Fig. 8.11. A single scan 1H NMR spectroscopy was performed on a stationary (non-owing) sample (250 mM sucrose and 30 mM TSP in DI water) before and after powering up the periphery sensing components, leading to a reduction of the SNR by 55%, so that the *nLOD*ω increases from 1.19 nmol s1/2 to 2.18 nmol s1/2 . Nevertheless, the NMR probe head sensitivity was comparable to other micro-coils, even with the added noise [30]. The measured sensitivity of 1.19 nmol s1/2 is at a 500 MHz static magnetic eld. To facilitate comparison with other reported micro-coils, the sensitivity needs to be scaled to 600 MHz, which is then converted to 0.86 nmol s1/2 . For context, Finch *et al*. showed a sensitivity of nLODω(600 MHz) 1.57 nmol s1/2 using their optimized stripline micro-detector [232]. Even with the noise added with the active ow-sensing elements in operation (yielding nLODω(600 MHz) 1.58 nmol s1/2 ), the NMR detector performance is adequate.

Figure 8.11: Comparison of a single-scan 1H NMR spectra without (blue) and with (red) connecting the electrical power to the ow sensors' electronics interface. In this experiment, the sample was stationary (250 mM sucrose and 30 mM TSP dissolved in DI water). SNR was noted to decrease by ∼55 % after connecting the power for the electronics interface. The regions between 5.56 - 5.28 ppm, 3.68 - 3.36 ppm, and 0.15 - -0.15 ppm are re-plotted in red boxes for illustration. The water peak's intensity (5.2 - 4.3ppm) was set manually to zero.

A test sample was prepared with 300 mM glucose, 75 gL−1 coloring powder, and 30 mM TSP dissolved in DI water to characterize the SNR of the ow NMR system. The characterization results are presented in the next Section 9.2. The coloring powder is added to the sample to visually separate the sample plugs from the transparent immiscible oil plugs. A single scan 1H NMR spectroscopy of a stationary sample is shown in Fig. 8.12. The anomeric glucose hydrogen signal J-coupling could be resolved to ∼ 50 % from baseline. For comparison, Finch *et al*. demonstrated ∼ 85 % from baseline resolution of the same signal using the stripline micro-detector [232].

## **8.3 Capacitive Sensor**

### **8.3.1 Sensor design and optimization**

Interdigitated capacitive sensors (IDC) were used for detecting the ow, illustrated in Fig. 8.13. Interdigitated electrodes are sensitive to dierences in material permittivity, interfering with its fringe eld by modulating the sensor capacitance. Flow sensing dependent on capacitance calculation has several appealing characteristics: i) the non-invasive measurement avoids sample contamination; and ii) it requires low power minimizing temperature uctuations. Figure 8.13 presents a 2D layout of the interdigitated electrodes and the expected fringe eld lines within a rolled sensor detection region. The fringe eld is directed toward the ow by rolling the sensor around the ow capillary. Rolled IDC sensors have improved sensitivity to dierences in dielectric constants and are much more compact than conventional co-planar capacitive sensors.

Figure 8.12: Single-scan 1H NMR spectra of a stationary sample (300 mM glucose, 75 gL−1 coloring powder, and 30 mM TSP dissolved in DI water). In this experiment, the electrical power was not connected to the ow sensors' electronic interface. The regions between 5.5 - 5.1 ppm and 4.3 - 3.2 ppm are re-plotted in red boxes for illustration. The spectral region between 3.0 - 0.5 ppm (free region) was eliminated for clarity.

Figure 8.13: 2D schematic layout of the interdigitated capacitive sensors (IDC) and the expected fringe eld generated by the sensors after rolling around the glass capillary.

The strength and uniformity of the electric eld generated by the sensor dene its sensitivity and performance. Improving the sensor sensitivity can be achieved by optimizing the interdigitated sensor geometrical dimensions to enhance the sensor generated electric eld. To optimize the ow sensor performance, the sensor total width (*WS*), and the gap between the electrodes (*G*) were explored (Fig. 8.14). Optimization was done by simulating the capacitive sensor's generated electric eld using nite element simulation. In the simulation model, the interdigitated sensor was constructed around two concentric tubes to model a glass capillary and a Teon tube lled with air and placed in an air-like environment. The simulated sensor was excited with a sinusoidal signal of 5 V at 32 kHz (mimicking the existing system parameters), and the sensor generated electric eld was plotted. The simulated sensor had a

Figure 8.14: Finite element simulation (COMSOL Multiphysics) studies the impact of varying the gap between the IDC sensor's ngers (G) and the sensor total width (WS) on the produced electric eld inside the sensor. **(a)** Gap dependence: The electric eld at the sensor center is plotted versus the gap (bottom). Top view proles of the electric eld at a cross-section in the center of the sensor are plotted for dierent gap values of 20 µm, 60 µm, and 100 µm. The electric eld generated by the sensor decreases as the gap between the ngers increases. **(b)** Width dependence: The electric eld at the sensor center is plotted versus sensor width (bottom). Top view proles of the electric eld at a cross-section in the center of the sensor are plotted for sensors with widths of 2 mm, 3.5 mm, and 5 mm. The electric eld generated by the sensor increases as the sensor width increases.

total width *WS* = 3.725mm, a gap of *G* = 25µm, the number of sensing electrodes *N* = 30, each with a width of *W* = 100µm, and a length of *LS* = 6.6mm (slightly less than the outside circumference of the glass capillary 6.75 mm).

Figure 8.14a shows the eect of the gap width between the electrodes (*G*) on the generated electric eld. The gap width was swept from 10 µm to 100 µm at steps of 10 µm. Subsequently, the electric eld strength at the sensor center was plotted against the gap, as shown in Fig. 8.14a. Reducing the gap width increases the generated electric eld strength and hence increases the sensor's sensitivity as in the case of co-planar interdigitated capacitive sensors [233]. Figure 8.14b demonstrates the eect of the capacitive sensor overall width (WS) on the generated electric eld. The sensor width was swept from 2 mm to 5 mm with a step of 0.5 mm. Subsequently, the electric eld strength at the sensor center was plotted against the sensor width, as shown in Fig. 8.14b. On the one hand, expanding the sensor sensing region by increasing the sensor's width along the glass capillary increases the generated electric eld's strength and increases sensors sensitivity. On the other hand, the sensor width should be minimized to reduce the sensor's settling time. Increasing the number of sensing electrodes (*N*) within the sensor improves the generated electric eld homogeneity and hence the smoothness of the signal [226]. According to the simulation results and considering fabrication complexity to not select dimensions below 25 µm, several design iterations were tested. The selected dimensions of the interdigitated sensor implemented in the NMR probe head are summarized in Table 8.2.

The electric eld generated by the implemented sensor is simulated. The domain inside the Teon tube was modeled using, the relevant parameters, once for water (ε*r* = 80) and again for the separating oil FC-43 (ε*r* = 1.9). The electric eld within the detection volume is lower in water than in FC-43 due to the relatively high dielectric coecient of water compared to FC-43, as shown in Fig. 8.15. This variation in the sensor electric eld leads to the change in the interdigitated sensor capacitance, which is then sensed to detect the solutions' interface. The capacitance instrumentation technique is discussed in the following Subsection 8.3.2.

### **8.3.2 Sensor instrumentation and characterization**

The IDC sensor capacitance was read-out utilizing an o-the-shelf capacitance-to-digital converter (CDC) microchip (AD7746, Analog Devices). The AD7746 microchip is a high resolution sigma-delta (Σ−∆) CDC that posses two separate single-ended measurement channels, each of 24-bit resolution. The full-scale capacitance of each of the CDC's channels is ±4 pF from an internal set reference value (0-17 pF). The CDC measurement has an accuracy of 4 fF and a resolution down to 4 aF. The AD7746 chip provides two built-in excitation sources (up to 5 V at 16 or 32 kHz) and amplifying/ltering circuits. The sampling rate of the CDC can be set between 9.1 −90.9 Hz resulting in root-mean-square (RMS) noise levels of 4.2 −40 aF.

The AD7746 chip has a 16-lead TSSOP (Thin Shrink Small Outline Package) conguration

Table 8.2: Geometrical dimensions of the integrated ow IDC sensor in the custom-built NMR probe head.

(4.5 ×5 mm), enabling integration on the NMR probe head's PCB. Each of the two capacitive ow sensors was attached to a separate measurement channel of the CDC, via a positive capacitance input pin (CIN 1/2 (+)) and an excitation pin (EXC A/B) leveraging the single-end measurement. The excitation signal was set to 5 V at 32 kHz, and the CDC's sampling rate was set to 9.1 Hz. The PCB's conductive tracks connecting the capacitive sensors to the CDC chip were kept as far as possible from each other to limit cross-coupling between the two sensors. The CDC's digitized capacitance measurements were transmitted via I2C serial communication to a microcontroller outside the NMR magnet, as shown in Fig. 8.16. An Arduino board was used as an o-the-shelf MCU. Two Arduino shields have been developed compatible with Arduino Uno and Micro modules. The schematic designs and photographs of each of the two Arduino shields are provided in Appendix D. The Arduino shield was used to connect the I2C wires from the CDC to the Arduino board; it additionally featured LEDs for visual feedback and push-buttons for triggering the NMR experiment manually. The performance of the two microcontrollers (Arduino Uno and Micro) was observed to be equivalent.

The instrumentation system's functionality to detect permittivity dierences was validated by sensing the capacitance read-outs in the presence of various solvents, summarized in Fig. 8.17. The developed system was eciently able to dierentiate between toluene (εr = 2.38) and the uorinated oil FC-43(εr = 1.9) used for samples separation. Also, a dierence in capacitance

Figure 8.15: Finite element simulation (COMSOL Multiphysics) illustrating the electric eld prole inside the IDC sensor (water and FC-43 oil as examples). Left: an overview of the whole sensor, right: focusing on the target sensing region inside the Teon ow tube.

Figure 8.16: Electronic hardware components implemented for realizing the automatically triggered NMR experiment. Each of the two IDC sensors is connected to an input channel of a CDC microchip on the NMR probe head. The digitized sensors' readings are transferred to an MCU outside the NMR magnet over an I2C communication. An Arduino shield is developed comprising I2C interface, push-buttons for manual triggering, LEDs for visual feedback, and TTL signal interface.

measurement was observed between air and FC-43, opening the possibility of air-bubble detection. The measurement system's sensitivity was independent of the magnetic eld, with only a constant oset of +0.3 pF observed with the sensor located in the NMR magnetic eld. This capacitance oset could be compensated by re-calibrating the CDC IC, but since the o set does not aect the working principle of the system, this re-calibration was not performed. The measurement system's sensitivity to a dierence in relative permittivity was determined to be ∆ε*r* = 0.2.

Figure 8.17: IDC sensor measured capacitance when lled with dierent solutions. The error in the capacitance measurement arises from the CDC chip's noise (± 0.03 pF). The system is eciently capable of dierentiating toluene (ε*r* = 2.38) from FC-43 (ε*r* = 1.9) (inset).

The developed measurement system features two ow sensors to enable ow velocity measurement and bi-directional NMR ow synchronization. The system accuracy to measure the velocity was characterized by loading the line with plugs of colored aqueous samples separated with the uorinated oil FC-43 and recording the ow using a camera (60 fps). The plug velocities were extracted from the recorded video data using motion analysis software (Kinovea), which were then compared to the velocities measured by the developed system. The velocity measured by the system was within 4% of the camera results. The velocity characterization experiment was done outside of the NMR magnet to enable video recording.

Validating the sensors capability to synchronize NMR data acquisition was achieved by loading the ow tube with a line of three aqueous sample plugs separated by FC-43 oil. The three sample plugs are of dierent volumes and glucose concentrations, but all owing at 4 mm s−1 . Figure 8.18 demonstrates the sensors reading from the three aqueous sample plugs. The results reveal that a capacitance change above 100 fF is generated by the aqueous solutions separated by FC-43 plugs. Therefore, the capacitive sensor SNR is satisfactory even when the CDC microchip operates at the highest sampling rate of 90 Hz (RMS noise of 40 aF). As can be observed from the sensors measurements, the capacitance reading between the two ow sensors was not identical. The measured capacitance variation between the aqueous samples and the FC-43 oil for the 1st sensor was ∼ 190 fF (closer to the CDC IC) and ∼ 120 fF for the

Figure 8.18: Output readings of the ow sensors during a triggered NMR experiment. The experiment was performed on three plugs of dierent volumes (40 µL, 80 µL, and 120 µL) and dierent glucose concentrations (0 M, 1 M, and 2 M) separated by plugs of FC-43 (80 µL). In this experiment, the plugs were owing at a velocity of 4 mm s−1 . The MCU sends the TTL signals to the NMR console's TTL I/O unit after a calculated delay (*d*/3). This guarantees that a new NMR acquisition starts once the sample enters the NMR detection region. The time delay (*d*) is calculated using the sample's velocity measured by the capacitive sensors (top).

2 nd sensor. The dierence between the two capacitive sensors can be attributed to the fabrication tolerances and the variation in proximity between each sensor and the CDC microchip, where long tracks build up parasitic capacitance. Nevertheless, the system working principle is not aected by the variation in the ow sensors readings since an individual threshold value could be set for each sensor.

The sensors performance was comparable to other systems utilizing the same sensing principle, even with the parasitic capacitance eect [226,234]. A sensitivity advantage was achieved by rolling the ow sensors around the ow tube compared to planar IDC sensors [226] and capacitive sensors with less lling factor [234]. The signals acquired from the CDC microchip for the two ow sensors are suciently distinct that a robust triggering algorithm could be developed, as described previously in control system Subsection 8.1.1.

#### **8.4 Micro-fabrication**

The fabrication process used for realizing the micro-saddle NMR detector and the interdigitated capacitive ow sensors around a slender glass capillary with an outer diameter of 2.15 mm consist of two main steps, as shown in Fig. 8.19. The rst fabrication step was 2D patterning of a conductive layer in the form of the detector and the sensor on a exible polymer lm. The second fabrication step was rolling the 2D structured lm around the slender glass capillary, thereby realizing a 3D conductive structure around the glass capillary.

The conductive layer 2D patterning was achieved following a standard wet-etching photolithography process suitable for mass production at the wafer scale. A 25 µm Kapton lm covered from a single side with a 9 µm copper layer (AkaFlex KCL 2-9/25 HT, Krempel GmbH) was utilized as the base substrate for the photolithography process. Kapton was used due to its magnetic susceptibility, which is close to that of water [48]. A conductive copper layer of 9 µm provides the requisite conductor skin depth at 500 MHz, ensuring the minimal electrical resistive losses of the NMR detector. The wet-etching fabrication process is discussed in details in Section 3.1. After the 2D patterning process, the NMR saddle coil and ow sensors were cut from the Kapton lm (a photograph of the entire wafer with a batch of detectors and sensors is provided in Appendix D). After rolling the lm around the glass capillary (OD/ID, 2.15/1.72 mm, borosilicate glass, Hilgenberg GmbH), it was xed using epoxy glue (UHU-Plus). The glass capillary with the NMR detector and ow sensors was glued to the probe head PCB using the same epoxy.

The fabrication process's overall yield is very high (nearly 100%), owing to the standard processes used. After multiple uses, no failures in the glue holding the lm to the capillary were observed or in the glue holding the capillary to the PCB. If necessary, adhesion could be enhanced using a low temperature cure liquid polyimide such as LTC9300 provided by FUJI-FILM. The liquid polyimide can be applied and then hard-baked inside an oven at 200 °C for

180 min, then it will be converted into a lm, resulting in a solid xation of the structures.

Figure 8.19: Schematic illustration of micro-fabrication process of the micro-saddle coil and IDC sensor. **(a)** Five steps categorized in two processes. First process: a wet etching photolithography process: (1) Substrate preparation by laminating 25 µm Kapton lm covered with a 9 µm copper layer on a silicon wafer, (2) Patterning of a positive photoresist (AZ4533) layer using UV lithography, (3) Etching the exposed regions of the copper layer; and (4) Peeling o the Kapton lm from the silicon wafer. Second process: (5) Rolling the Kapton lm with the patterned conductive layer around the glass capillary. **(b)** Microscopic images of the 2D patterned conductive layer in the shape of (1) Saddle coil and (2) IDC sensor.

# **9 Automated ow NMR results**

**T** his chapter presents the results of the dierent experiments performed using the developed system for automating the NMR spectroscopy. This chapter is divided into four sections. Section 9.1 describes the material used for the NMR experiment as well as the sample preparation. Additionally, Within this section, NMR spectroscopy data processing is explained. Sections 9.2 and 9.3 present the experimental result for characterizing the automated ow-based NMR system where the system SNR was expressed as a function of the sample velocity, volume, and analyte concentration. Section 9.4 demonstrates the results of automating the NMR screening of various commercial beverages as a piece of evidence that the system can eciently automate NMR spectroscopy on dierent samples.

## **9.1 Sample preparation and NMR spectroscopy**

A 4.5 m microuidic tube was tted through the customized probe head and used for sample ow. The used tube is made out of polytetrauoroethylene (PTFE) (OD/ID, 1.6/1 mm, S1810-12, Bohlender GmbH), which provides the required exibility to be tted through the NMR system. The Fluorinert oil FC-43 ( > 99%, 3MTM Fluorinert Electronic Liquid) is used for separating the target sample plugs and was purchased from Ionic Liquids Technologies (IOLITEC) GmbH. FC-43 oil is commonly used in many electronic and chemical applications because of its technical properties [235]. It is a perfect candidate for separating the target sample plugs within a microuidic channel: i) it is chemically inert, thermally stable with low toxicity, making it compatible with the Teon tube and various target samples, ii) it is immiscible with many popular NMR solvents, iii) its viscosity is relatively low (4.7 mPa s) and therefore ows easily inside the microuidic channels, and iv) its electrical resistivity is relatively high (3.4×1015 Ωcm) preventing static charges.

The test sample used for characterizing the ow system SNR presented in Section 9.2 was prepared as 300 mM glucose, 75 gL−1 food coloring powder, and 30 mM TSP dissolved in deionized (DI) water. The glucose concentration series from 1 mM to 1 M presented in Section 9.3 was prepared using 50:50 DI water : D2O. D-glucose, 3-(trimethylsilyl)- propionic-2,2,3,3-d4 acid sodium salt (TSP), and deuterium oxide (D2O, 99.9% deuterium, Sigma Aldrich) which were purchased from Sigma-Aldrich. A market-available food coloring powder (Brauns Heitmann) was used. The beverages used in the automated NMR experiment represented in Section 9.4 were a selection of commercial beverages that were privately donated. Beverage samples were prepared by adding 1 mL of 5 mM TSP in D2O to 3 mL of the beverage ([TSP]*final* = 1.25 mM).

This chapter's text and gures were reproduced and adapted from the author's published work [ON5] (CC BY 4.0, 2021 Springer Nature)

NMR experiments were conducted on an 11.7 T wide-bore AVANCE III NMR spectrometer ( 1H resonance frequency 500 MHz). The customized ow-sensing probe head was installed on a custom micro-imaging NMR probe and is therefore fully compatible with magnetic resonance imaging (MRI). The NMR pulse sequence was a modied version of a conventional single-pulse experiment, including the trigger signal control. For a typical FID, the number of collected points was 5998 over a spectral width of 10 kHz, using a recycle delay of 0.1 s. For the beverage NMR experiments in Section 9.4, the number of collected points was raised to 12014. In all synchronized NMR experiments, FIDs were collected in a pseudo-2D NMR experiment, which was later separated and processed individually after the NMR experiment for all plugs was completed. Each FID was zero-lled by a factor of 2 prior to the Fourier transformation and multiplied by an exponential function equivalent to a line broadening of 0.3 Hz. After separating each spectrum, it was referenced to TSP (0 ppm), and the phase and baseline were corrected.

## **9.2 NMR characterization - varying sample volume and ow rate**

Characterizing the NMR performance was done by observing the acquired SNR using the automatic and manual acquisition of NMR data. Two series of experiments were done using the same test sample:

For manual triggering, a single sample plug was loaded into the ow tubing, bordered by FC-43. NMR acquisition was started and stopped manually when the sample entered and exited the probe. As a metric of NMR performance, the SNR of the TSP signal (0 ppm) was considered under each test condition. The normalized limit of detection (nLODω) was then calculated, as explained previously in Section 2.4.4, for the spectrum of each case based on the SNR of the TSP signal. The acquisition time for a single scan NMR experiment was set to be 0.299 s with the NMR detector sensitive volume of 3.14 µL.

The experimental results of the rst series of the NMR experiments, where the sample ow rate was varied, are presented in Fig 9.1a and b. The developed triggering system acquires and stores the time domain NMR signal (FID) separately, as shown in Fig. 9.1a. The ow rate was incremented after the NMR spectroscopy for an oil-sample plug pair was completed. The velocity values reported in the results are the values calculated by the MCU using the acquired capacitive sensor signals. The system performance proves that the developed system could robustly dierentiate the oil from aqueous signals. The TSP signal SNR was calculated in the frequency domain after applying the Fourier transformation to the FID.

The SNR at the dierent velocities for various volumes is plotted in Fig. 9.1b and d, and selected spectra are plotted in Fig. 9.3a. As the results reveal, the NMR spectrum's SNR decreases

Figure 9.1: Performance of the automated ow-based NMR experiments under varying sample volumes and ow velocities. **(a)** Measured FID of seven sample plugs (80 µL) separated by FC-43 oil plugs (80 µL) with varying the ow rate. **(b)** The relationship between TSP peak SNR (0 ppm) and the sample velocity measured by the dual IDC sensors. The sub-gure shows the nLODω at each sample volume (mean ± standard deviation over all tested ow velocities). **(c)** Measured FID of seven sample plugs separates by FC-43 oil plugs with varying the sample volume. The ow velocity was kept constant at 8 mm s−1 , and the oil plugs volume held constant at 80 µL. **(d)** The relationship between TSP peak SNR (0 ppm) and the sample volume measured by the dual IDC sensors. The sub-gure shows the nLODω at each sample velocity (mean ± standard deviation over all tested sample volumes). In (b) and (d), each data point represents the mean ± standard deviation of the NMR experiment performed in quadruplicate. The data were t using the damped least-squares method to a 2nd order polynomial.

as a function of the sample ow rate, as expected, since increasing the ow rate reduces the sample residence time in the NMR detector's detection region. The SNR was continuously enhanced using the developed automated synchronized system as compared to manual triggering. Consequently, approximately improvements by factors of 2.5, 3.0, and 4.0 in the spectra SNR was observed for sample plug volumes of 120 µL, 80 µL, and 40 µL, regardless of the sample ow velocity. The nLODω calculated from the SNR is plotted in the inset of Fig. 9.1b. The performance under the automated triggering system is four-time better than the previous micro-saddle coil results [143], with a value of 4-5 nmol s1/2 .

As the results reveal, the nLODω under manual triggering conditions increases as the sample volume decreases due to the increased contribution of the FC-43 oil signal (essentially noise) to the FID. The experimental results of the second series of the NMR experiments, where the sample plug volume was varied, are presented in Fig 9.1c and d. The FID signals of seven oil-sample FID pairs are shown in Fig. 9.1c, the volume of the sample plugs was incremented while the volume of the FC-43 oil plugs was held constant at 80 µL. The expected enhancement in the SNR of the TSP with increasing the sample volume is illustrated in Fig. 9.1d (selected spectra are plotted in Fig. 9.3a). The triggering system, once again, yielded a systematic SNR enhancement in comparison to the manual triggering condition, approximately by factors of 2.5, 3.0, and 4.0 for plugs velocities of 4 mm s−1 , 8 mm s−1 , and 12 mm s−1 regardless of sample plug volume. The enhancement in the NMR sensitivity when implementing the automated triggering system, as well as the micro-NMR detector performance, is further conrmed by the calculated nLODω for each ow rate (inset, Fig. 9.1d). The calculated nLODω and at each ow velocity are plotted in Fig. 9.2b.

Figure 9.2: NMR system's sensitivity under varying sample ow rates and volumes. **(a)** The change in the normalized limit of detection (nLODω ) with the sample velocity. Under automatic triggering conditions, The nLODω alters within a small range over the enter range of tested velocities for a given sample volume. Under manual triggering conditions, the nLODω increases as the volume of the sample decreased due to the increased signal contribution from the FC-43 oil signal (noise). **(b)** The change in the normalized limit of detection (nLODω ) with the sample volume. Under automatic triggering conditions, the nLODω is minimally enhanced by increasing the sample volume. Under manual triggering conditions, the nLODω is enhanced by increasing the volume of the sample as the contribution of the oil signal is reduced. The mean ± standard deviation of the data presented here are plotted in Fig. 9.1.

Figure 9.3: Selected 1H NMR spectra resulted from the ow NMR spectroscopy experiments on a test sample (300 mM glucose, 75 gL−1 coloring powder, and 30 mM TSP dissolved in DI water) with varying the sample volumes and ow rates (SNR of all extracted data are plotted in Fig. 9.1). **(a)** The SNR of TSP peak (0 ppm) for each spectrum is noted next to the signal. A focused view of the glucose anomeric proton (5.2 ppm) is located next to each spectrum in a gray box for spectral resolution comparison. The water signal (5.1-4.3 ppm) was eliminated for clarity. The baseline distortion in the spectra with a manual triggering system results from signal accumulation from the FC-43 oil phase (noise). **(b)** Representative full 1H NMR spectra of a 120 µL sample plug owing at velocity of 4 mm s−1 . The blue spectrum is obtained with the auto triggering system. In contrast, the red spectrum is obtained with manual triggering. The automatic triggering system eliminates the noise contribution from the oil phase.

A balance should be realized between the sample volume, ow rate, SNR, and spectral resolution to enhance the NMR throughput. Increasing the samples ow rate with keeping all other parameters constants result in the degradation of SNR and spectral resolution, as illustrated in Fig. 9.3. On the other hand, increasing the sample volume enhances SNR and spectral resolution. Increasing the ow rate reduces the NMR measurement time, leading to less noise

averaging over the accumulated signals. Simultaneously, increasing the ow rates allows a bigger fraction of the excited sample to leave the NMR detection region during NMR signal acquisition. Consequently, the FID is articially shortened and manifesting as a rise in the apparent relaxation time T2, results in broadening the spectral line as shown in Fig. 9.3. At extremely high ow rates, the whole excited part of the sample leaves the detection volume before NMR signal acquisition is completed, therefore adding more noise into the collected signal.

## **9.3 NMR characterization - concentration limit of detection**

The dependence of the developed automated NMR spectroscopy system on the sample concentration was estimated by loading the ow tube with a series of nine aqueous samples spanning a glucose concentration range from 1 mM to 1 M. The aqueous sample plugs with dierent glucose concentrations had a volume of 120 µL and were separated by FC-43 oil plugs with a volume of 80 µL. The automated ow NMR experiment was done at two dierent ow velocities 6 mm s−1 and 10 mm s−1 .

The results of the concentration experiment are summarized in Fig. 9.4. The automated NMR triggering system, as with previous experiments, could eciently separate signals from aqueous plugs and oil plugs, as shown in the FID signals in Fig. 9.4a. The relation between the SNR of the glucose anomeric hydrogen signal (5.1-5.3 ppm) and the glucose concentration is plotted in Fig. 9.4b for the two ow rates tested. Selected NMR spectra for these auto synchronized experiments are plotted in Fig. 9.4c. The NMR signal SNR has a linear relation with the sample concentration (R2 > 0.99). The SNR is greater at a lower ow velocity of 6 mm s−1 versus the higher ow velocity of 10 mm s−1 , considering the samples at lower velocity have a longer residence time in the NMR coil detection region, allowing greater signal accumulation. The total experimental time required by the automated ow-based NMR system to acquire the NMR signal of all oil and aqueous plugs (18 measurement in total) was 6.1 min and 3.6 min, or eectively 25.5 s and 15.3 s per aqueous sample at ow velocities of 6 mm s−1 and 10 mm s−1 .

Obtaining the relation between SNR and sample concentration is suitable for examining the sample plugs' cross-contamination. After loading the line with the nine aqueous samples, the measurements were performed in four consecutive runs after reversing the ow direction (i.e., all plugs signal were acquired in one ow direction followed by reversing the sample ow direction and repeating the measurements). Hence, the linear plot between the SNR and concentration after repeating the measurement four-time conrms that there was no crosscontamination of the Teon tube or between the dierent sample plugs.

Employing a plug ow approach will always raise the issue of cross-contamination. In the

case reported here of aqueous samples and FC-43 plugs owing in a Teon tube, cross contamination was not recognized at the NMR detection limit. However, in situations where cross contamination may be problematic, one could introduce additional solvent plugs to clean the ow line.

Figure 9.4: Performance of the automated ow-based NMR experiments under varying sample concentrations. **(a)** Automatically measured FID signals of nine aqueous sample plugs (120 µL) separated by FC-43 oil plugs (80 µL). owing at 10 mm s−1 . The aqueous samples contained glucose concentrations ranging from 0.001 M to 1 M. **(b)** The SNR (calculated using the glucose anomeric hydrogen signal (5.3-5.1 ppm)) versus glucose concentration under two ow velocities. Each data point is the mean ± standard deviation of the NMR experiment performed in quadruplicate. The Linear data t (dashed lines) had R2 > 0.99 in both cases. **(c)** Selected 1H NMR spectra from the automated ow NMR spectroscopy experiments with varying the glucose concentrations dissolved in DI water. The water signal (5-4 ppm) was eliminated for clarity. The glucose anomeric proton's SNR for each spectrum is noted next to the signal with a focused view of the peak (5.18-5.14 ppm) in a gray box for spectral resolution comparison.

## **9.4 Automated sample throughput - beverage application**

The developed system functionality was validated on a set of samples beyond simple test solutions. The ow tube was loaded with seven samples of dierent beverages and separated by FC-43 oil plugs. Each beverage sample plug had a volume of 120 µL, and the FC-43 oil plugs had a volume of 80 µL, and the NMR spectroscopy was done at a ow rate of 4 mm s−1 .

The total experimental time of the NMR signal acquisition under these conditions was 7 min with eectively 38.3 s acquisition time per beverage sample. Figures 9.5a and b demonstrate the resulting FID and spectra of all samples. TSP was added to the samples with a target concentration of 1.25 mM to facilitate referencing the resulted spectrum. However, it was observed from the results that the solubility of the TSP within the beverages was sampledependent, and therefore the TSP signal could not be utilized for quantication (only for chemical shift referencing).

#### **9.5 Conclusions**

As the results reveal in all previous experiments: i) the developed automatic triggering system was able to separate the sample and oil signals robustly; ii) the resulted NMR signals for the dierent tested sample were of excellent spectral quality (both in terms of resolution and SNR); and iii) there were no additional signals recognized in the oil NMR spectra, ruling out possible diusion into the oil plugs from the aqueous samples (at the NMR detection limit). Assuming a 1.0 mm I.D. PTFE tube, 100 µL sample plugs, and 100 µL oil plugs, then in a 100 m long PTFE tube, approximately 400 individual samples can be loaded. The number of the NMR visible plugs could be doubled by loading the immiscible phase with measurable molecules. Loading a 100 m PTFE tube is a time-limiting process, although this was also automated, as

Figure 9.5: Automated NMR acquisition of beverage sample plugs. **(a)** Automatically measured FID signals of seven beverage and FC-43 oil plugs. The sample volume was 120 µL, and the FC-43 oil volume was 80 µL, the experiment ran at a ow velocity of 4 mm s−1 . **(b)** The resulted NMR spectra of the beverage samples.

discussed in the loading Section 8.1.2. Using the developed automated measuring system with selecting a reasonable ow rate of 4 mm s−1 (minimum tested ow rate), considering an acquisition time of 40 s per sample (as was done in the beverage example in Section 9.4), and both plug phases contain NMR measurable content, then these 800 samples would require ∼ 9 h of measurement time. If the immiscible oil phase serves only to separate samples, then 400 samples would be screened in ∼ 9 h. This could be enhanced by incorporating the ow pump into the control loop and adjusting the ow rate so that the oil plugs ow through the detection volume more quickly. In contrast, 300 samples require a measurement time of 120 h when done manually following the conventional procedure (500 µL per sample, 5 mm sample tubes, 7 min acquisition time per sample neglecting instrument adjustment time after each sample exchange, without implementing automatic sample exchanger) [236].

Conclusions and Outlook

# **10 Conclusion and outlook**

Through the introduction chapter of this work, three main objectives were raised. The rst objective was enhancing the thin-lm micro-fabrication technology to address micro-MR applications. The second objective was utilizing the developed micro-fabrication technologies to solve MR-catheter issues regarding visual reliability and heating hazard. The third objective was employing the improved micro-fabrication technologies in tackling the NMR spectroscopy drawback of being a low throughput technique. This chapter concludes the key achievements in each objective and provides potential possibilities for future work.

## **10.1 Micro-fabrication of exible electronics**

An extensive study has been presented for the dierent depositing approaches for conductive seed-layers onto a exible polymer substrate. The study covers various photolithography methods as well as fast prototyping techniques. It focuses on the seed-layer adhesion onto the exible substrate as it is a challenging topic. Moreover, a benecial comparison between the dierent approaches has been given, covering each depositing technique's advantages, disadvantages, resolution, and reproducibility.

Two novel composite insulating inks have been developed for fully inkjet-printed high quality MIM capacitors with high capacitance density. Benzocyclobutene (BCB) was used as the base polymer for the developed inks due to its low dissipation factor. In addition, BaTiO3 and TiO2 were dispersed in the BCB polymer to increase its dielectric constant, reducing the capacitor size to be compatible with microelectronic applications. Dierent weight ratios of the ceramic powder to BCB polymer have been analyzed. The dielectric constant, roughness and thickness of the deposited lm, and quality factor have been characterized for each ink. The TiO2/BCB inks provide surface roughness of 970-1220 nm, a loss tangent of 0.037-0.04, a dielectric constant of 7-20, and capacitance density 32-64 pFmm−2 . The BaTiO3/BCB inks have surface roughnesses of 830-1000 nm, loss tangents of 0.045-0.052, dielectric constants of 10-37, and capacitance densities of 19-67 pFmm−2 . A comparison between the produced capacitors and state of art has been given. The developed printing process shows no blending between the conductive layer and the insulating layers. Moreover, the process is compatible with the fabrication of multi-layer components.

An organic Cu-PTAA-Ag Schottky diode has been developed by using inkjet-printing and the electroplating process. The low working function electrode (copper) of the diode was formed by printing silver electrode and then electroplating with copper. PTAA p-type semiconductors have been used due to their stability in the ambient atmosphere. The developed diode was successfully used to build a half-wave rectier, which provided a DC output voltage up to 3 V at 1 MHz.

A versatile and programmable current source based on MHCS was developed for the pulsed electroplating process. The current source have precise and stable output power even when operating under relatively high current densities (≈ 6A dm−2 ) and various frequencies (DC up to few kHz). The developed system oers extensive freedom to set the pulsed electroplating parameters, opening further exploration of complex pulsed electroplating waveforms. The developed plating setup has been used in controlling the deposited layer's micro-structure and has been employed in several crucial applications: i) solving the delamination issue when electroplating inkjet-printed conductive traces on unstructured exible substrates, ii) electroplating of a laser carbonized polyaramid-based lm, iii) electroplating of carbon micro-lattice architecture achieved by 3D stereo-lithography printing. The current source is compatible with the parallelization concept, where the output current channel can be duplicated. A developed system with eight channels was successfully utilized for plating eight 4 inch wafer in parallel, which saved materials, time, and eort. The setup is cost-eective and straightforward to be copied and used laboratory which maintains moderate electronic skills.

## **10.2 Interventional MRI using MR-catheters**

A novel wireless decoupling approach has been introduced to address the MR-catheter heating hazard. Moreover, an innovative double-saddle coil is developed to maintain catheter visibility in MR images through the entire range of axial orientations during interventions. The system tracks a micro-resonator placed on the catheter tip wirelessly through induction coupling. The catheter micro-resonator is connected to a variable capacitor controlled via a DC signal provided by a half-wave rectier. The input power to the half-wave rectier is wirelessly transmitted through induction coupling between two coils tuned at a frequency far from the Larmor frequency. The MR-resonator on the catheter tip along with the decoupling system has been fabricated using inkjet-printing on a 25 µm Kapton lm. The developed system was successfully used for wirelessly controlling the resonance frequency of the catheter microresonator within a range of 15 MHz.

The proposed double saddle detector oers wireless tracking of MR-catheters with orientation independence during interventional MRI operations. A comparison between the performance of the proposed double saddle detector and that of a traditional single saddle detector was done using numerical simulations and veried by experiments. The generated magnetic elds *B*1 by the micro detectors were numerically simulated using COMSOL multiphysics and were experimentally mapped in a low eld 1 T MRI scanner. The double saddle detector generated a homogeneously distributed magnetic eld surrounding the catheter tube. The induction coupling eciency between a surface resonator and the micro detectors was numerically simulated using COMSOL multiphysics and experimentally characterized using a home-built setup. The double saddle detector maintains near-constant coupling through the entire range of axial orientations. On the other hand, the coupling between the surface coil and the conventional

single detector decreases as the angle between their *B*1 elds increases, and no coupling was observed at orthogonal orientation of their elds. A novel multi-layer fabrication processes for rolled MEMS were developed for fabricating the double saddle detector. One method was based on standard lithography micro-fabrication, and the other employed inkjet-printing. Both processes were successful in fabricating double saddle detectors, which were then rolled around a 5 fr catheter tube.

Within this work, the developed coupling system is fabricated with inkjet-printing except for the varicap. As a future plan, the varicap could also be fabricated via inkjet-printing of p-type and n-type semiconductors. Hence, a wireless tunable MR-resonator could be fully printed to be compatible with roll to roll inkjet-printing fabrication technique, enabling mass production and disposable electronics. The main focus of this work was developing and characterizing the hardware. However, the introduced wireless tuning methodology oers a large room for further enhancements and applications in micro MRI and NMR applications where the MRdetector has limited access. Therefore, the developed MR-catheter with a wireless decoupling system is ready for the next step to be tested in vivo.

## **10.3 Automated high throughput NMR spectroscopy**

A novel plug ow-based approach has been introduced to address the NMR spectroscopy drawback of low sample throughput. The proposed technology enhances NMR throughput by a factor of 40 (when operating at the minimum eciency) and reduces the NMR sample volume at the same time to under a hundred micro-liters. The introduced system consists of a custom-built NMR probe head that takes advantage of thin-lm micro-NMR detectors combined with microuidic technologies. The key concept integrates thin-lm ow capacitive sensors interfaced to a microcontroller unit. Together with the NMR sensor, they enable realtime detection of sample plugs in a ow-based sample handling system with high sensitivity to dierences in relative permittivity. The NMR signal acquisition system gains a degree of automation by implementing an independent measuring mode for ow positing and velocity, further improving throughput. A detailed description of the system design, fabrication, and characterization has been given in Chapter 8. The micro-NMR detector enables highresolution NMR spectroscopy with a sensitivity of 2.18 nmol s1/2 with the ow sensors in operation. The spectral resolution under stationary conditions, quantied by resonance line width, was found to be 1.25 Hz for the water signal. The ow sensors had a high sensitivity to a relative permittivity detection dierence of 0.2, allowing them to distinguish between most typical solvents. The modeling, simulation, and characterization of the NMR-detector and ow sensor are included. The probe head is plug-and-play ready with market-available NMR systems. After installing the developed probe head into the NMR system, a microuidic tube is fed through the probe head loaded with a sample series, comprising of an unlimited number of dierent sample plugs, separated by an immiscible uid. The system was successfully used to automate ow-based NMR measurement in a 500 MHz NMR system. A complete characterization of the automated ow-based NMR system has been given in Chapter 9. It was demonstrated that fully automated NMR spectroscopy of nine dierent 120 µL samples could be done in 3.6 min or eectively 15.3 s per sample.

The NMR ow-sensing approach, described in this thesis, has opened up a new concept toward automated high throughput NMR spectroscopy by splitting a large sample into small droplets. The NMR spectrum is individually acquired for each droplet with high SNR. Furthermore, the developed NMR probe head is an additional step towards increasing the NMR system functionality, allowing for greater experimental exibility and complexity or improved SNR compared to standard equipment. The platform is compatible with the parallelization concept described in Chapter 7 and, as recently reported for low-eld NMR spectroscopy [237], potentially further increasing NMR sample throughput scaled by the number of parallel NMR channels. Additionally, the application space could be extended by reducing the system dimensions to enable particle sensing within a carrying medium towards, for example, NMR measurement of cells.

### **Bibliography**

thrombectomy eligible patients indicates signicant potential for growth of endovascular stroke therapy in the usa," *Journal of neurointerventional surgery*, vol. 9, no. 8, pp. 722–726, 2017.

# **A Appendix to chapter 3**

**Inkjet-printed BCB insulating ink**

Figure A.1: Inkjet-printed droplets and straight lines of the BCB insulating ink. The measured droplets diameter was ≈ 105µm, therefore, the drop spacing was set to 50 µm.

#### **Inkjet-printed composite insulating ink**

Table A.1: Surface morphology of the inkjet-printed insulating lm using composite inks.

#### **Spin-coated PTAA semiconductor of MS diode**

Figure A.2: Spin-coated PTAA semiconductor of MS diode with dierent weight concentrations. PTAA powder was dissolved in toluene solvent with concentrations of **(a)** 5wt.% and **(b)** 2wt.%. Both solutions were spin-coated at 1000 rpm for 1 min. High PTAA concentrations lead to a cracked semiconductor layer which results in a short circuit.

# **B Appendix to chapter 4**

## **2.1 Modied Howland Current Source (MHCS) modeling**

**Transfer function**

Figure B.1: Equivelant schematic circuit of the Modied Howland Current Source (MHCS).

The output current (*IOUT* ) of the *MHCS* can be expressed in terms of the input control signal (*VControl*) by applying Kirchho's Current Law (*KCL*) (nodal analysis) at the nodes from 1-4,

$$\text{(@ node 1: } \quad \frac{V^- - V\_{Control}}{R\_1} + \frac{V^- - V\_O}{R\_2} + \frac{V^- - V^+}{Z\_{in}} = 0,\tag{B.1a}$$

$$\text{Q0 node 2:} \quad \frac{V^{+}}{R\_{3}} + \frac{V^{+} - V\_{OUT}}{R\_{4}} + \frac{V^{+} - V^{-}}{Z\_{\text{in}}} = 0,\tag{\text{B.1b}}$$

$$\text{@ node 3:} \quad \frac{V\_O - V\_{OUT}}{r} + \frac{V\_O - V^-}{R\_2} + \frac{V\_O - (V^+ - V^-) \cdot A}{Z\_O} = 0,\tag{\text{B.1c}}$$

$$\text{Q} \text{ node 4:} \quad I\_{OUT} = \frac{V^{+} - V\_{OUT}}{R\_4} + \frac{V\_O - V\_{OUT}}{r}. \tag{8.1d}$$

An ideal operational amplier (*OPAMP*) is assumed to have innite open-loop gain, innite input impedance (*Zin*), and zero output impedance (*ZO*). Hence, no electric current ow between the input terminals of the opamp leading to *V* + =*V* −. Solving the three equations B.1a - B.1c together, *V* +, *V* − and *VO* can be expressed in terms of *VControl* and *VOUT* ,

$$V^{+} = V\_{OUT} \frac{R\_3}{R\_3 + R\_4},\tag{B.2a}$$

$$V\_O = V\_{OUT} \frac{R\_3(R\_2 + R\_1)}{R\_1(R\_3 + R\_4)} - V\_{Courlol} \frac{R\_2}{R\_1} \,. \tag{B.2b}$$

Substituting by B.2a and B.2b in B.1d, the output current (*IOUT* ) can be driven as follow,

$$I\_{\rm OUT} = -V\_{\rm control} \frac{R\_2}{R\_1 r} + V\_{\rm OUT} \frac{R\_1 (R\_4 + r) - R\_2 R\_3}{R\_1 r (R\_3 + R\_4)} \,. \tag{B.3}$$

#### **Virtual capacitance**

Following the technical report provided by Texas Instrument [136], the virtual output capacitance of the *MHCS* (*COUT* ) can be derived by calculating the *OPAMP*'s output current (*IO*) in the presence of a time-varying signal at the output node of the circuit (*dVT* /*dt*) and a very small error input signal (*Verror*) across the *OPAMP*'s inputs. The applied voltage at the output node of the *MHCS* is assumed to be a ramp signal moving from a negative voltage in the positive direction. The system is solved at the moment when the signal passes zero volts, (*VT* = 0+*dVT* /*dt*). The calculated current, in that case *IO*, is known as the capacitive current since it's related only to *dVT* /*dt*.

The rate of change of an *OPAMP*'s output voltage is function in the input signal across it's inputs and the Gain Bandwidth Product (*GBMP*):

$$\frac{d\text{V}\_O}{dt} = V\_{error} \, 2\pi GBWP,\tag{B.4a}$$

$$
\ldots \, V\_{error} = \frac{dVo}{dt} \, \frac{1}{2\pi G BWP}.\tag{B.4b}
$$

When applying a time-changing signal at the output node of the *MHCS* (*dVT* /*dt*), the rate of change of the voltage at the positive terminal of the *OPAMP* can be derived using potential divider rule:

$$\frac{dV^{+}}{dt} = \frac{R\_{3}}{R\_{3} + R\_{4}} \frac{dV\_{T}}{dt},\tag{B.5a}$$

Taking into consideration the applied error signal (*Verror* and assuming an ideal *OPAMP*, the the rate of change of the voltage at the negative terminal of the *OPAMP* can be derived:

$$\frac{dV^{-}}{dt} = \frac{R\_3}{R\_3 + R\_4} \frac{dV\_T}{dt} + V\_{error},\tag{B.5b}$$

hence, the rate of change of the voltage at the *OPAMP*'s output is the same as the change at

the negative input magnied by *R*1 +*R*2/*R*1,

$$\frac{d\,\delta O}{dt} = \frac{R\_3}{R\_3 + R\_4} \,\frac{R\_1 + R\_2}{R\_1} \,\frac{d\,V\_T}{dt} - V\_{error} \,\frac{R\_1 + R\_2}{R\_1} \,. \tag{B.5c}$$

By solving Equations B.4b and B.5c together:

$$V\_{error} = \frac{dV\_T}{dt} \frac{1}{2\pi GBWP} \frac{R\_3}{R\_3 + R\_4} \frac{R\_1 + R\_2}{R\_1} - V\_{error} \frac{1}{2\pi GBWP} \frac{R\_1 + R\_2}{R\_1} \tag{B.6}$$

The momentary when *VT* = 0+*dVT* /*dt*, the value of the *OPAMP*'s output voltage at is:

$$V\_O = \frac{R\_1 + R\_2}{R\_1} \ V\_{error},\tag{B.7a}$$

$$\text{Let } V\_O = \frac{dV\_T}{dt} \frac{1}{2\pi G B W P} \frac{R\_3}{R\_3 + R\_4} \left[\frac{R\_1 + R\_2}{R\_1}\right]^2 - V\_{error} \frac{1}{2\pi G B W P} \left[\frac{R\_1 + R\_2}{R\_1}\right]^2. \tag{B.7b}$$

The momentary when*VT* = 0+*dVT* /*dt*, no electric current is going through *R*4 and the current going through *r* is,

$$I\_O = I\_r = V\_O/r,\tag{B.8a}$$

$$\text{i.: } lo = \frac{dV\_T}{dt} \, \frac{1}{2\pi rGBWP} \, \frac{R\_3}{R\_3 + R\_4} \, [\frac{R\_1 + R\_2}{R\_1}]^2 - V\_{error} \, \frac{1}{2\pi rGBWP} \, [\frac{R\_1 + R\_2}{R\_1}]^2. \tag{B.8b}$$

This capacitive current is equivalent to *IO* = *CO dVT* /*dt*,

$$\left| C\_O = \frac{\mathcal{R}\_3 (\mathcal{R}\_1 + \mathcal{R}\_2)^2}{2\pi r \mathcal{R}\_1^2 (\mathcal{R}\_3 + \mathcal{R}\_4) G B W P}. \right| \tag{8.9}$$

## **2.2 Electronic schematics of the electroplating current source**

Figure B.2: Schematic of the module used for generating the voltage control signal.

Figure B.3: Schematic of the MHCS.

Figure B.4: Schematic of the power supply module.

Figure B.5: Schematic of the feedback module module.

Figure B.6: Schematic of the real-time clock (RTC) module.

Figure B.7: Full schematic without the power supply module.

Figure B.8: Schematic of the fan control module.

## **2.3 Source codes**

After connecting the developed current source circuit to the BeagleBone Black (BBB) wireless board, the following steps need to be followed for the BBB software setup:

#### **BeagleBone board conguration code**

The conguration code (in Shell Script) needs to run once after booting the BeagleBone board to congure the SPI and I2C pins :

```
1 #!/bin/bash
2 config-pin P9_17 spi_cs
3 config-pin P9-18 spi
4 config-pin P9-21 spi
5 config-pin P9-22 spi_sclk
6 config-pin P9-28 spi_cs
7 config-pin P9-29 spi
8 config-pin P9-30 spi
9 config-pin P9-31 spi_sclk
10 config-pin -q P9_17
11 config-pin -q P9_18
```
 config-pin -q P9\_21 config-pin -q P9\_22 config-pin -q P9\_28 config-pin -q P9\_29 config-pin -q P9\_30 config-pin -q P9\_31 config-pin P9\_19 i2c config-pin P9\_20 i2c config-pin -q P9\_19 config-pin -q p9\_20

#### **Electroplating power source code**

The following python code generate uni-polar waveform:

```
1 import Adafruit_BBIO.GPIO as GPIO #library controlling GPIOs
2 from Adafruit_BBIO.SPI import SPI #library controlling SPIs
3 import time #BBB time library
4
5 #function for calulating SPI 16bit word for a given current
6 def word(I):
7 Rone = 10000 #Resistors values of the MHCS
8 Rtwo = 6800
9 Rfive= 10
10 Vin = ((I)*Rtwo*Rfive/(Rone+Rfive))/1000 #MHCS transfer function
11 volt_b = int((abs(Vin)*32768/2.5)+32768)
12 if I > 0:
13 volt_b = volt_b ^ 0xffff
14 a = (volt_b >> 8) & 0xff
15 b = volt_b & 0xff
16 return a, b
17
18 #Setup GPIOs
19 GPIO.setup("P8_27",GPIO.OUT) #led
20 GPIO.setup("P8_29",GPIO.OUT) #led
21 GPIO.setup("P8_8",GPIO.OUT) #power supply
22 GPIO.setup("P8_7",GPIO.OUT) #fan
23 GPIO.setup("P9_25",GPIO.OUT) #LDAC
24 GPIO.setup("P9_27",GPIO.OUT) #CS
25
26 #Control GPIOs
27 GPIO.output("P8_27",GPIO.LOW) #led off
```

```
28 GPIO.output("P8_29",GPIO.LOW) #led off
29 GPIO.output("P8_8",GPIO.LOW) #power supply off
30 GPIO.output("P8_7",GPIO.LOW) #fan off
31 GPIO.output("P9_25",GPIO.LOW) #LDAC is tied low
32 GPIO.output("P9_27",GPIO.HIGH)
33
34 time.sleep(0.05)
35
36 # Send the SPI word from the BBB to the ADC
37 spi = SPI(2,1)
38 a, b = word(0+2.7)
39 GPIO.output("P9_27",GPIO.LOW)
40 print spi.xfer2([a,b])
41 GPIO.output("P9_27",GPIO.HIGH)
42 GPIO.output("P8_8",GPIO.HIGH)
43
44 #A loop for generating a uni-polar waveform with Ip=20mA, TON=200ms, and
      TOFF=100ms.
45 while 1:
46 a, b = word(20)
47 GPIO.output("P9_27",GPIO.LOW)
48 print spi.xfer2([a,b])
49 GPIO.output("P9_27",GPIO.HIGH)
50 time.sleep(0.2)
51 a, b = word(0+2.9)
52 GPIO.output("P9_27",GPIO.LOW)
53 print spi.xfer2([a,b])
54 GPIO.output("P9_27",GPIO.HIGH)
55 time.sleep(0.1)
```
The previous Python code is used for generating any other waveform by replacing the part of the code inside the while loop (from line number 46) with the required waveform. Below is a python code template for explaining how to generate any waveform:

```
1 #This following block with five lines is used to generate a single pulse
    :
2
3 #The following code line is used to take the required current's value (I
    ) and convert it to a 16-bit word using the previously defined
    function.
4 #The value of I is in mA and can be positive, negative, or zero.
```

```
5 a, b = word(I)
6
7 #The following three code lines are used to transfer the 16-bit word
    from the BBB to the ADC.
8 GPIO.output("P9_27",GPIO.LOW)
9 print spi.xfer2([a,b])
10 GPIO.output("P9_27",GPIO.HIGH)
11
12 #The final line of the code is used to set the pulse-width by inserting
    T in ms.
13 time.sleep(T)
14
15 #The previous code block is repeated each time the current level change
    within a single waveform cycle.
```
Below are the python codes for the plating waveforms used through the thesis:

Bipolar waveform: *I*C = 20mA, *I*A = −20mA, *T* C = 200ms, and *T*A = 50ms.

```
1 # Positive pulse
2 a, b = word(20)
3 GPIO.output("P9_27",GPIO.LOW)
4 print spi.xfer2([a,b])
5 GPIO.output("P9_27",GPIO.HIGH)
6 time.sleep(0.2)
7 # Negative pulse
8 a, b = word(-20)
9 GPIO.output("P9_27",GPIO.LOW)
10 print spi.xfer2([a,b])
11 GPIO.output("P9_27",GPIO.HIGH)
```

```
12 time.sleep(0.05)
```
Bipolar with o time: *I*C = 20mA, *I*A = −20mA, *T* C = 200ms, *T*A = 50ms, *T* O = 10ms, and *T* 'O = 20ms.

```
1 #Positive pulse
2 a, b = word(20)
3 GPIO.output("P9_27",GPIO.LOW)
4 print spi.xfer2([a,b])
5 GPIO.output("P9_27",GPIO.HIGH)
6 time.sleep(0.2)
7 #Off
8 a, b = word(0)
```
GPIO.output("P9\_27",GPIO.LOW)

```
10 print spi.xfer2([a,b])
```

```
13 #Negative pulse
```

```
14 a, b = word(-20)
```

```
15 GPIO.output("P9_27",GPIO.LOW)
```

```
16 print spi.xfer2([a,b])
```

```
17 GPIO.output("P9_27",GPIO.HIGH)
```

```
18 time.sleep(0.05)
```

```
19 #Off'
```

```
20 a, b = word(0)
```

```
21 GPIO.output("P9_27",GPIO.LOW)
```

```
22 print spi.xfer2([a,b])
```

```
23 GPIO.output("P9_27",GPIO.HIGH)
```

```
24 time.sleep(0.02)
```
# **C Appendix to chapter 6**

**Frequency splitting modeling**

Figure C.1: Equivalent schematic of inductively coupled resonators. **(a)** Magnetic ux linkage between two indicators. **(b)** Equivalent schematic circuit of a pair of inductively coupled resonators.

As a pair of inductors approach each other, the electric current (I) variation in one of the inductors developed a magnetic eld around the inductor that induces an electromotive force (emf) in the other inductor, as shown Fig. C.1a. The magnetic coupling linking inductors is described by Faraday's law of induction, where the emf is the variation of the magnetic ux with time. The magnetic ux, in turn, is dened by the magnetic ux density (B) and the enclosed area (A),

$$\text{emf} = \frac{d\phi\_B}{dt}, \quad \phi\_B = \int\_{\Sigma} B \, dA. \tag{C.1}$$

The electric currents owing in both inductors (*I*1 and *I*2) contribute to the ux leakage of each inductor (λ1 and λ2),

$$
\mathcal{A}\_{\parallel} = L\_{\parallel}I\_{\parallel} + M\_{\parallel 2}I\_{\perp}, \tag{C.2a}
$$

$$
\lambda \mathfrak{z} = L \mathfrak{z} I \mathfrak{z} + M \mathfrak{z} I \mathfrak{z}, \tag{\text{C.2b}}
$$

where *L*1 and *L*2 are the self-inductance of each inductor, and *M* is the mutual induction connecting the two inductors. The magnitude of the magnetic coupling can be expressed by calculating the ratio between the ux linkage of the two inductors at two special cases: 1) in the one case, the rst inductor is left open (*I*1 = 0); and 2) in the other case, the second inductor is left open (*I*2 = 0). The previous calculation result in a ratio between the mutual inductance and the mean of the self-inductance, which is known as coupling coecient (K),

$$\boxed{K = \frac{M\_{12}}{\sqrt{L\_1 L\_2}}}\,\,\,\,\tag{C.3}$$

An electrical resonator is an inductor connected in parallel to a capacitor, as shown in Fig. C.1b. Practically, the conductive wire forming the inductor has a resistance, thus the total impedance (*Z*) of a resonator (*RLC*) is,

$$Z = j(a\alpha L - \frac{1}{a\alpha C}) + R(a\alpha). \tag{C.4}$$

The resonance frequency (ω0) of a resonator is the frequency at which the electrical inductance and capacitance compensate each other. At the resonance frequency, the energy on the resonator oscillates between its two forms; electrical and magnetic. From Equation C.4, the resonator's resonance frequency can be derived:

$$
\rho\_0 = \frac{1}{\sqrt{LC}}.\tag{C.5}
$$

Equation C.2 reveals that mutual inductance, as for self-inductance, relates magnetic ux and electric current. Hence, mutual inductance contributes to the resonator's impedance and consequently inuences its resonance frequency. According to Kirchho's law, the loop equations of a pair of coupled resonators equivalent to zero [238]:

$$Z\_1 I\_1 + j \alpha M\_{12} I\_2 = 0,\tag{C.6a}$$

$$Z\_2 I\_2 + j\alpha M\_{12} I\_1 = 0.\tag{C.6b}$$

Solving these two loop equations together results in two resonance frequencies (ω1 and ω2). This means that magnetic coupling between a pair of resonator introduces an additional degree-of-freedom (current path), as shown:

$$a\_{1,2}^2 = (a\_{01}^2 + a\_{02}^2) \frac{-1 \pm \sqrt{1 - \frac{4(1 - K^2)}{\left(\alpha\_{01}/\alpha\_{02}\right)^2 + \left(\alpha\_{02}/\alpha\_{01}\right)^2 + 2}}}{2(1 - K^2)}.\tag{C.7}$$