**Abstract**

At the microscale, shape memory alloy (SMA) microelectromechanical system (MEMS) bimorph actuators offer great potential based on their inherently high work density. An optimization problem relating to the deflection and curvature based on shape memory MEMS bimorph was identified, formulated, and solved. Thicknesses of the SU-8 photoresist and nickel-titanium alloy (NiTi) was identified that yielded maximum deflections and curvature radius based on a relationship among individual layer thicknesses, elastic modulus, and cantilever length. This model should serve as a guideline for optimal NiTi and SU-8 thicknesses to drive large deflections and curvature radius that are most suitable for microrobotic actuation, micromirrors, micropumps, and microgrippers. This model would also be extensible to other phase-change-driven actuators where nonlinear and significant residual stress changes are used to drive actuation.

**Keywords:** shape memory alloy, thin film, microactuators, MEMS, optimization, radius of curvature, phase change

#### **1. Introduction**

In certain applications for MEMS microactuators, large deflections would be desired such as the case of micro-robotics [1–3], micromirrors [4–6], and microgrippers [3, 7]. Using a shape memory alloy (SMA), a material that undergoes large changes in stress during a temperature cycle due to a solid-solid phase change can be used to generate large, nonlinear deflections. We aim to find a relationship between deflections of a SMA MEMS actuator, and maximize the deflection of SMA MEMS bimorph. Shape memory alloy films based on sputtered NiTi have been exhaustively characterized in previous decades, leading to a wealth of information about the intricate interplay between Ni/Ti ratio, annealing temperatures and times, and thickness [8–31]. Bimorphic actuators can impart reversible deflection shape memory microactuators as previously demonstrated [32, 33].

To date, optimization of parameters for improving shape memory-induced actuation has not been explored. We chose for our candidate system an SU-8 patterned on top of NiTi SMA bimorph actuator. In this case, residual strains develop during the processing of MEMS actuators, and upon release from substrate, the device curls upward to relieve these strains. Thermal input converts the material into austenite, and shape memory effect drives the actuator into a more flat

position, a process that is reversible upon subsequent thermal cycles. Thermal effects can be delivered to the SMA MEMS using laser irradiation [34], and jouleheating [35], at frequencies up to at least 1 kHz. SU-8 is an ideal material due to its relative ease of use in MEMS, low modulus of elasticity enables more flexible devices with large deflection, and good chemical stability.

more interesting. The equation describing the recovery stress-induced deflection in

*Optimization of MEMS Actuator Driven by Shape Memory Alloy Thin Film Phase Change*

2 *NiTit* 2

where *σrec* ¼ recovery stress of the SMA MEMS actuator; *d* ¼ deflection of the SMA MEMS actuator; *l* ¼ total length of the SMA MEMS actuator; *ENiTi* ¼ elastic modulus of NiTi layer; *ESU*‐8 ¼ elastic modulus of SU-8 layer; *TNiTi* ¼ thickness

**Figure 1** shows stress vs. temperature curves for NiTi on Si wafer. These curves are experimentally generated, and indicate the recovery stress (difference between highest and lowest stress values), and the thermal hysteresis. Here, as an illustrative example, the NiTi thickness is 900 nm, and the temperature cycle is performed

Assumptions: we assume operating temperatures go between RT and 100°C to ensure full phase change. In all calculations, for simplicity we use Young's modulus of NiTi as a fixed value. In reality, the Young's modulus changes curing the phase change. Martensite (lower temperature phase usually has a lower elastic modulus

**Figure 2** shows the process used to build the SMA MEMS bimorph actuator comprised of the NiTi shape memory (SMA) layer underneath the SU-8 elastic layer. In step (a) deposition of SMA onto Si wafer and pattern using photolithography. In step (b) ion milling is performed to transfer the pattern into the SMA layer. In step (c) we spin on SU-8 and pattern it with mask plate and photolithography. In

difluoride (XeF2) gas. In step (e) we thermally actuate the two-way shape memory

*Stress vs. temperature curves for NiTi on Si wafer. These curves are experimentally generated, and indicate the*

*recovery stress (difference between highest and lowest stress values), and the thermal hysteresis.*

step (d) we release the MEMS bimorph by etching Si substrate with xenon

þ *E*2

2

3 *SU*‐8 *SU*‐8*t* 4 *SU*‐8 (1)

*SU*‐8 þ 4*tNiTit*

shape memory alloy (SMA) MEMS actuator is:

*NiTi* þ *ESU*‐8*ENiTi* 4*t*

*DOI: http://dx.doi.org/10.5772/intechopen.92393*

using a heating and cooling rate of 1°C/min.

MEMS device between curled and flat states.

compared to the higher temperature austenite phase).

*E*2 *NiTit* 4

**Figure 1.**

**27**

*d* ¼ 3*ENiTiσrectNiTitSU*‐8ð Þ *tNiTi* þ *tSU*‐8 *l*

3

modulus of NiTi layer; *TSU*‐8 ¼ thickness modulus of SU-8 layer.

*NiTitSU*‐8 þ 6*t*

Much literature exists for thin film development and characterization of nickeltitanium shape memory alloy [1–4]. Although many demonstrations of SMA MEMS actuators have been shown [9, 34–43], none of these citations perform design optimization studies to maximize deflection or curvature radius due to residual stress changes due to phase change. When the nitinol is thermally cycled between martensite and austenite phases, there is a corresponding change in residual stress, which is used to drive the nonlinear deflections. This nonlinear and large change in stress is defined as the recovery stress, and is a principal factor influencing the deflection and curvature radius. Our novel contributions take a realistic SMA MEMS bimorph design based on SU-8 on NiTi, and determine optimal thickness combinations to yield maximized deflections, which would be desirable in certain applications were large strokes are desired. We feed into the model the Young's modulus values for NiTi thin films that have been determined previously using nanoindentation techniques [44, 45].

#### **2. Building and characterizing the SMA MEMS actuators**

The nickel-titanium alloy (NiTi) would be co-sputtered onto a 4″ silicon wafer based on the methods reported in previous works [8, 34–36]. The substrate is rotated and heated during deposition to ensure crystallization of the film. The wafer stress vs. temperature measurements are performed, using Stoney's equation to determine recovery stress, hysteresis, and residual stress in the NiTi film. After verification of good shape memory alloy properties in the film at wafer level, a photomask is used to pattern bimorph actuator. Ion milling is used to remove portions of the NiTi film on the wafer. The SU-8 2000.5 is spin coated (where the RPM is used to control SU-8 thickness) and another mask plate is used to pattern SU-8 on top of the NiTi cantilever. Finally, the device is released by etching the Si substrate away in xenon difluoride (XeF2) gas. In practice, SU-8 thickness would be controlled by varying spin speed, and NiTi thickness based on sputtering time.

#### **2.1 Problem identification**

The design problem is to maximize the deflection of a MEMS bimorph cantilever beam based on the nonlinear shape memory alloy (SMA) as the actuating mechanism. The deflection is dependent in large part on the parameter called recovery stress. The larger the recovery stress, the larger the deflection. We may also wish to decrease the overall mass or volume of the actuator, of minimize the curvature radius. The objectives are competing in that reduction in the shape memory alloy thickness, generally leads to reduction of the recovery stress. The bimorph actuator could consist of SU-8 on top of NiTi thin film, but this optimization model would be easily extensible to other cases of interest.

We should consider that the equation describing the recovery stress-induced deflection in shape memory alloy MEMS actuator is (Eq. 1).

Initially, the contour plots of SU-8 and NiTi thickness showed that the optimization problem was not interesting for the simplest case of constant recovery stress over the range of NiTi thickness. To our advantage, the NiTi recovery stress is a parameter that depends on NiTi thickness, which makes the optimization problem

more interesting. The equation describing the recovery stress-induced deflection in shape memory alloy (SMA) MEMS actuator is:

$$d = \frac{3E\_{\text{NTiT}} \sigma\_{\text{re}} t\_{\text{NTiT}} t\_{\text{SU-8}} (t\_{\text{NTiT}} + t\_{\text{SU-8}}) l^2}{E\_{\text{NTiT}}^2 t\_{\text{NTiT}}^4 + E\_{\text{SU-8}} E\_{\text{NTiT}} \left( 4t\_{\text{NTiT}}^3 t\_{\text{SU-8}} + 6t\_{\text{NTiT}}^2 t\_{\text{SU-8}}^2 + 4t\_{\text{NTiT}} t\_{\text{SU-8}}^3 \right) + E\_{\text{SU-8}}^2 t\_{\text{SU-8}}^4} \tag{1}$$

where *σrec* ¼ recovery stress of the SMA MEMS actuator; *d* ¼ deflection of the SMA MEMS actuator; *l* ¼ total length of the SMA MEMS actuator; *ENiTi* ¼ elastic modulus of NiTi layer; *ESU*‐8 ¼ elastic modulus of SU-8 layer; *TNiTi* ¼ thickness modulus of NiTi layer; *TSU*‐8 ¼ thickness modulus of SU-8 layer.

**Figure 1** shows stress vs. temperature curves for NiTi on Si wafer. These curves are experimentally generated, and indicate the recovery stress (difference between highest and lowest stress values), and the thermal hysteresis. Here, as an illustrative example, the NiTi thickness is 900 nm, and the temperature cycle is performed using a heating and cooling rate of 1°C/min.

Assumptions: we assume operating temperatures go between RT and 100°C to ensure full phase change. In all calculations, for simplicity we use Young's modulus of NiTi as a fixed value. In reality, the Young's modulus changes curing the phase change. Martensite (lower temperature phase usually has a lower elastic modulus compared to the higher temperature austenite phase).

**Figure 2** shows the process used to build the SMA MEMS bimorph actuator comprised of the NiTi shape memory (SMA) layer underneath the SU-8 elastic layer. In step (a) deposition of SMA onto Si wafer and pattern using photolithography. In step (b) ion milling is performed to transfer the pattern into the SMA layer. In step (c) we spin on SU-8 and pattern it with mask plate and photolithography. In step (d) we release the MEMS bimorph by etching Si substrate with xenon difluoride (XeF2) gas. In step (e) we thermally actuate the two-way shape memory MEMS device between curled and flat states.

#### **Figure 1.**

*Stress vs. temperature curves for NiTi on Si wafer. These curves are experimentally generated, and indicate the recovery stress (difference between highest and lowest stress values), and the thermal hysteresis.*

position, a process that is reversible upon subsequent thermal cycles. Thermal effects can be delivered to the SMA MEMS using laser irradiation [34], and jouleheating [35], at frequencies up to at least 1 kHz. SU-8 is an ideal material due to its relative ease of use in MEMS, low modulus of elasticity enables more flexible

Much literature exists for thin film development and characterization of nickeltitanium shape memory alloy [1–4]. Although many demonstrations of SMA MEMS actuators have been shown [9, 34–43], none of these citations perform design optimization studies to maximize deflection or curvature radius due to residual stress changes due to phase change. When the nitinol is thermally cycled between martensite and austenite phases, there is a corresponding change in residual stress, which is used to drive the nonlinear deflections. This nonlinear and large change in stress is defined as the recovery stress, and is a principal factor influencing the deflection and curvature radius. Our novel contributions take a realistic SMA MEMS bimorph design based on SU-8 on NiTi, and determine optimal thickness combinations to yield maximized deflections, which would be desirable in certain applications were large strokes are desired. We feed into the model the Young's modulus values for NiTi thin films that have been determined previously using

The nickel-titanium alloy (NiTi) would be co-sputtered onto a 4″ silicon wafer based on the methods reported in previous works [8, 34–36]. The substrate is rotated and heated during deposition to ensure crystallization of the film. The wafer stress vs. temperature measurements are performed, using Stoney's equation to determine recovery stress, hysteresis, and residual stress in the NiTi film. After verification of good shape memory alloy properties in the film at wafer level, a photomask is used to pattern bimorph actuator. Ion milling is used to remove portions of the NiTi film on the wafer. The SU-8 2000.5 is spin coated (where the RPM is used to control SU-8 thickness) and another mask plate is used to pattern SU-8 on top of the NiTi cantilever. Finally, the device is released by etching the Si substrate away in xenon difluoride (XeF2) gas. In practice, SU-8 thickness would be controlled by varying spin speed, and NiTi thickness based on sputtering time.

The design problem is to maximize the deflection of a MEMS bimorph cantilever beam based on the nonlinear shape memory alloy (SMA) as the actuating mechanism. The deflection is dependent in large part on the parameter called recovery stress. The larger the recovery stress, the larger the deflection. We may also wish to decrease the overall mass or volume of the actuator, of minimize the curvature radius. The objectives are competing in that reduction in the shape memory alloy thickness, generally leads to reduction of the recovery stress. The bimorph actuator could consist of SU-8 on top of NiTi thin film, but this optimization model would be

We should consider that the equation describing the recovery stress-induced

Initially, the contour plots of SU-8 and NiTi thickness showed that the optimization problem was not interesting for the simplest case of constant recovery stress over the range of NiTi thickness. To our advantage, the NiTi recovery stress is a parameter that depends on NiTi thickness, which makes the optimization problem

devices with large deflection, and good chemical stability.

**2. Building and characterizing the SMA MEMS actuators**

nanoindentation techniques [44, 45].

*Advanced Functional Materials*

**2.1 Problem identification**

**26**

easily extensible to other cases of interest.

deflection in shape memory alloy MEMS actuator is (Eq. 1).

shown to drop off completely, so we impose constraints for NiTi thickness to vary

*Optimization of MEMS Actuator Driven by Shape Memory Alloy Thin Film Phase Change*

Based on the curve fitting equation (*third-order polynomial*), the single-objective

2

100 *μm* ≤*l*≤ 300 *μm* (3) 150 *nm* ≤*tNiTi* ≤1000 *nm* (4) 200 *nm* ≤*tSU*‐8 ≤2000 *nm* (5)

3 *SU*‐8

*σrec* ≥ 0 (6)

2 þ 2*:*45*E*15*tNiTi* � 2*:*58*E*08 SI units ð Þ (7)

2

3 *SU*‐8

*SU*‐8 þ 4*tNiTit*

*g*1 : 100 � 10�6 � *l* ≤0; (9) *g*2 : *l* � 300 � 10�6 ≤0; (10) *g*3 : 150 � 10�9 � *tNiTi* ≤0; (11) *g*4 : *tNiTi* � 1300 � 10�9 ≤0; (12)

*g*5 : 200 � 10�9 � *tSU*‐8 ≤0; (13) *g*6 : *tSU*‐8 � 2000 � 10�9 ≤0; (14)

*g*7 : �*σrec* ≤0 (15)

2 � 2*:*45 � 1015*tNiTi* þ 2*:*58 � 108 ¼ 0

*SU*‐8*t* 4 *SU*‐8

*SU*‐8*t* 4 *SU*‐8 (2)

(8)

(16)

*SU*‐8 þ 4*tNiTit*

*maximize* :

2 *NiTit* 2

þ *E*2

between 150 and 1300 nm.

*E*2 *NiTit* 4

*E*2 *NiTit* 4

*subjected to*::

*h*1: *σrec* � 5*:*36 � 1026*tNiTi*

**3.2 MATLAB optimization toolbox (fmincon)**

*K* ¼ �*E*0

*tNiTi* ¼ 359 *nm*, *tSU*‐8 ¼ 824 *nm*, *l* ¼ 300 *μm*.

**3.3 Multi-objective optimization**

**29**

*subjected to*::

*σrec* ¼ 5*:*36*E*26*tNiTi*

optimization problem can be written as following:

*NiTi* þ *ESU*‐8*ENiTi* 4*t*

*DOI: http://dx.doi.org/10.5772/intechopen.92393*

Covert to standard form in SI units:

*NiTi* þ *ESU*‐8*ENiTi* 4*t*

*d* ¼ 3*ENiTiσrectNiTitSU*‐8ð Þ *tNiTi* þ *tSU*‐8 *l*

3

3 � 2*:*15*E*21*tNiTi*

*f* ¼ �3*ENiTiσrectNiTitSU*‐8ð Þ *tNiTi* þ *tSU*‐8 *l*

3

*NiTitSU*‐8 þ 6*t*

*minimize* :

2 *NiTit* 2

þ *E*2

*NiTitSU*‐8 þ 6*t*

3 þ 2*:*15 � 1021*tNiTi*

The curvature of a bilayer elastic material [46] is given as

*SU*‐8*tSU*‐8*E*0

*G E*0

According to the toolbox (and as shown in **Figure 4**), optimal solution is:

*SU*‐8*tSU*‐8 þ *E*0

*NiTitNiTi*ð Þ *tNiTi* þ *tSU*‐8

*NiTitNiTi Δε* (17)

**Figure 2.** *SMA MEMS fabrication process for SU-8 on NiTi bimorph.*


**Preface to "Novel Strategies in the Development of New Therapies, Drug Substances and Drug Carriers"**

At present, there is a strong need for new therapies that are effective and safe for widespread diseases. In developing new treatments, areas of current interest include drug-development-related strategies, new therapeutic molecules, and new drug delivery systems. This book is conceived to promote synergy between research and industrial activities in the design and development of new drugs and, therefore, was not limited to any specific aspect of development. It covers the entire process from the identification of a molecular target, studies of drug–protein interactions, the modeling and optimization of the functional activity, design and chemical synthesis, biological evaluation, and the development of new pharmaceutical carriers.

The original articles and reviews are focused on the design and development of new anticancer treatments, new anticancer low-molecular-weight agents as potential drug substances, and the elucidation of their mechanisms of action. The book also includes studies on novel modulators of the serotonergic system used to treat central nervous system disorders, novel agents against infectious diseases, and the development of anti-plasmodial and anti-inflammatory agents. The successful identification of new compounds for development as drug substances comes from a rich source of medicinal plants and medicinal chemistry approaches. The molecular mechanism of potential drug substances is important to their development as drugs.

> **Andrzej Kutner, Geoffrey Brown, and Enik ¨o Kallay** *Editors*


2.4.2. Cation Transport Experiments

The fast filter method was used for data collection. 100 μL of stock vesicle solution was suspended in 1.85 mL of the corresponding bu ffer (10 mM PBS pH 6.4 containing 100 mM of the analyzed cation) and placed into a quartz fluorimetric cell. The emission of HPTS at 510 nm was monitored at two excitation wavelengths (403 and 460 nm) simultaneously. 0.464 mM lipid was used in each experiment. The final concentration of the compound is 0.06 mM for 12.9 mol% of compound/lipid ratio. This concentration is high enough for crown ethers to assemble as channels in lipid bilayers, assuming the insertion is complete. At 20 s, 29 μL of aqueous NaOH (0.5 M) was added, and macrocyclic compound added at 50 s, detergent was added after 340 s, and the measurement lasted another 50 s. For experiments involving FCCP, the compound was added at 40 s, and the tested macrocyclic compound was added at 60 s. The lysis started at 350 s for 50 s to finish the measurements this time. Experiments without FCCP (from 50 s to 340 s) are compared to experiments with FCCP (from 60 s to 350 s). The extent of transport was monitored using the ratio of the emission intensities of HPTS at 460 and 403 nm (I460 and I403). We calculated the first-order initial rate constant from the slopes of the plot of ln ([H+]in − [H+]out) versus time, where [H+]in and [H+]out are the intravesicular and the extravesicular proton concentrations, respectively. The [H+]out was assumed to remain constant during the experiment (pH 7.4), while [H+]in values were calculated for each point from HPTS emission intensity using the equation pH = 1.1684 × log(I460/I403) + 6.9807. The initial and final pH are pH at *t* = 0 s and at the end of the experiment, respectively. In the picture, I refer to the intensity at 460 nm, and I0 refers to intensity at 403 nm. To calculate EC50 and Hill coe fficient *n*, we used the fractional activity Y. Y was calculated for each curve using the normalized value of I460/I403 (just before lysis of the vesicles). We expressed Y as a function of time, and we performed fittings using a 2-parameter equation, which is, Hill equation: Y = Yblank + (Ymax − Yblank)/(1 + (EC50/[C])n), from which Yblank is the fractional activity from the experiment of blank and Ymax is the largest fractional activity from the same series of experiments.


**10. General principles in the treatment of shock**

In order to provide a patient with the benefit of rational and effective treatment, it is critical to identify the specific cause of shock in each case. Although treatment should be aimed at the underlying etiology of shock, the most critical aspect of treatment is the prompt restoration of normal hemodynamics.

From a hemodynamic perspective, there are three main categories in the management of shock:

In hypovolemic shock, the primary derangement is low central venous pressure (CVP) so therefore IV fluids are the cornerstone of therapy. If the patient is profoundly hypotensive, vasopressors are sometimes used temporarily but only while definitive access is obtained, and fluids are pushed as quickly as possible. If a patient in hypovolemic shock is requiring vasopressors to maintain enough perfusion pressure to stay conscious, they are in critical need for more fluid. Since these patients are already extremely hyper dynamic, there are no benefits of inotropes which will only risk worsening tachycardia to the point that diastolic filling time is too short for the left ventricle to fill.

In distributive shock, the primary derangement is low SVR. Vasopressors are therefore almost always necessary. Since most of these patients are also hypovolemic, or at the very least, have fluid maldistributed to the extravascular space rather than central circulation, IV fluids are also used in every case. Because of sepsis induced cardiomyopathy, some patients with sepsis may also benefit from inotropes but identifying those patients can be a challenge.

In cardiogenic shock, the primary problem is low cardiac output, thus inotropes are the mainstay therapy. Both fluids and vasopressors are not only unnecessary but contraindicated. In fact, reduction in preload by using diuretics, and reducing the afterload helps in augmenting the cardiac output in patients with cardiogenic shock.

Finally, in obstructive shock, it is impossible to generalize about the appropriateness of fluids, vasopressors and inotropes and if there is a response to any of those, it is likely only temporary. Definitive relief of the obstruction is still critical. For pneumothorax (PTX), this is either chest tube or needle thoracostomy which consists of a needle placed into the pleural space via the second intercostal space in the midclavicular line. For cardiac tamponade, pericardiocentesis can be performed, a procedure in which a needle is placed in the pericardial space most commonly via a subxiphoid approach. In case of massive pulmonary embolism, depending on the circumstances, this may require systemic thrombolysis or embolectomy.

General treatment principles are summarized in **Table 6**.

**Table 6.**

*General approach to therapy with regards to type of shock.*