**3. Triboemission and triboplasma**

#### **3.1. Triboemission**

Triboemission is defined as emission of electrons, charged particles, lattice components, photons, etc., under dry mechanical action, eg. surface damage caused by fracture processes or conditions of boundary friction. The fresh generated surface sites form a real bridge between physics and chemistry of the wear processes. Figure 4 depicts a simple idea of the exo-electron emission (EEE) process.

**Figure 4.** Exo-electron emission phenomenon.

There are many physical phenomena related to the wearing processes and mechanisms. These mechanisms are often connected with tribochemical reactions that are initiated by the surface enlargement effects. Figure 5 illustrates broadly the triboemission process.

**Figure 5.** Physical processes evolved by friction.

**Figure 3.** Initiation process of tribochemical reactions by the mechanical action.

Triboemission is defined as emission of electrons, charged particles, lattice components, photons, etc., under dry mechanical action, eg. surface damage caused by fracture processes or conditions of boundary friction. The fresh generated surface sites form a real bridge between physics and chemistry of the wear processes. Figure 4 depicts a simple idea of the

There are many physical phenomena related to the wearing processes and mechanisms. These mechanisms are often connected with tribochemical reactions that are initiated by the

surface enlargement effects. Figure 5 illustrates broadly the triboemission process.

**3. Triboemission and triboplasma**

exo-electron emission (EEE) process.

**Figure 4.** Exo-electron emission phenomenon.

**3.1. Triboemission**

Details are in reference [34], which distinguishes the following main types of triboemission phenomena: (a) emission of gas atoms and molecules, including emission of radicals and molecular clusters, (b) emission of electromagnetic radiation, (c) emission of electrons, (d) emission of ions, (e) emission of magnetic field, (f) emission of electric field including emission of electric charges and generation of tribocurrents, (g) emission of noise, vibration and acoustic emission, (h) heat evolvement.

Emission of gas atoms and molecules at friction results from the competition gas release and gas adsorption processes. When at certain sliding conditions, the rate of gas adsorption exceeds the rate of gas release, total emission rate becomes negative. Such emission of negative rate has been called *anti-emission.* The triboemission phenomena are classified into two classes by physical nature: emission of particles ('corpuscular'), and emission of energy, as shown in Figure 6 [29,34].

**Figure 6.** Classification of triboemission phenomena by physical nature.

The particle emission includes neutral particles (atoms, molecules, radicals and clusters) and charged particles (electrons, negative ions and positive ions). Three main types of energy emission encompass: electromagnetic energy, mechanical energy and heat. Mechanical energy includes mechanical oscillations of various frequency ranges, i.e. vibration, noise, ultrasonic emission, acoustic emission, etc. Electromagnetic emission can be classified into static and dynamic. Static emission includes static electric and magnetic fields, while dynamic emission includes electromagnetic waves of various wavelengths, i.e. radio waves; IR, visible, UV light; and X-rays [34]. Significant research in the field of triboemission was carried out by Nakayama et al. [35]. Kim et al. [36] investigated electron and photon evolvement (phE) from magnesia (MgO) under friction with diamond; they found that during indentation, prior to any fracture of MgO, only phE was observed. The relative intensities of these signals can therefore be used to follow the progress and extent of plastic deformation and fracture during wear on millisecond time scales [36].

General Approach to Mechanochemistry and Its Relation to Tribochemistry 217

Elastic deformation is the first stage of the mechanical energy interaction between solids and leads to a change of the bond distances in the affected solid. Actually, it concerns mechanical energy transmission to solids. By and large, there are few processes for the transmission of mechanical energy by impact treatment. Heinicke in the Tribochemistry book [8] states the following: *'Immediately at the commencement of a grain colliding at high velocity with a solid surface it comes to a quasi-adiabatic energy accumulation and to the formation of an "energy bubble" at the point of action in the sub-microscopic deformation zone'.* All these specific aspects are summarized in the phenomenological Magma-Plasma Model (MPM) [7,8]. As the MPM process is combined with the EEE process, it is of very significant importance for both

mechanochemistry and tribochemistry. Figure 7 depicts the Magma-Plasma Model.

**Figure 7.** The Magma-Plasma Model (MPM) for the impact stress of flying grain.

The short life of the triboplasma causes no Maxwell-Boltzmann distribution, thus an equilibrium temperature cannot be given and the chemical process taking place in the excitation phase cannot be described by the laws of thermodynamics [8]. The highest stage of energy excitation changes dynamically into the next stage characterized by the relaxation of the plasma states and is termed as "edge-plasma" and "post-plasma". Work [45] describes the energy dissipation on solids activated by impact along with adequate

Mechanical forces make the atoms leave their equilibrium positions due to lattice vibration, alter bond lengths and angles of their atomic arrangements leading to electronically excited states (see Figures 3,5,7). The energy field incurred by the tribophysical effects, for example the EEE process, triboluminescence, triboplasma, crystal defects etc., initiates specific

Mechanochemistry in terms of processes being triggered in the solid state chemistry, due to the application of mechanical energy, is extremely complex. Tribochemistry as its branch is

**3.2. Triboplasma**

discussion.

tribochemical reactions.

The work of Molina et al. [37-38] characterized triboemission of electrons from diamondon-alumina, diamond-on-sapphire, alumina-on-alumina, and diamondon-aluminum. The three ceramic-materials consistently showed burst-type negatively charged triboemission during contact at constant load and speed, while the aluminum system produced no significant emission. Decaying emission after contact ceased also was detected from the three ceramic systems for durations exceeding the minute-range [39]. For the cases of diamond-on-alumina and diamond-on-sapphire, energy spectrometry showed that a large fraction of the triboemitted negative charges were of low-energy (eg. 1–5 eV). This finding was of significant importance because in the NIRAM approach, it was hypothesized that the energy level of triboelectrons to initiate tribochemical reaction should be 1–4 eV [40].

Interestingly, an early work [41] demonstrated that electrons of very low energy (EEE) can be produced from solids by mechanical deformation, X-ray irradiation and chemical reaction; if the excitation is not great enough to produce normal electron emission, steady EEE can be produced by steady excitation. Another early work [42] investigated EEE from aluminum abraded in different atmospheres and found that under high and ultra-high vacuum conditions, such electron emissions is associated with a shift of photo-electric threshold dependent upon the residual gas pressure to which the surface was exposed. It was evidenced that the initial growth stage of emission is due to the adsorption of water vapor, the subsequent decay being associated with oxidation [42]. EEE process is also combined with triboplasma. Extensive review paper [43] shows exo-emission as a sensitive method for the monitoring of the initial stages in the fragmentation of polymeric materials subjected to mechanical action, and demonstrates that the electrons emitted when solids (dielectric materials, metals, and polymers) are subjected to mechanical influences are capable of inducing the dissociative ionization of the water molecules adsorbed on the surfaces. The studies reviewed in [43] demonstrate unambiguously the interrelation between the mechanoemission phenomena and the mechanochemical processes. A correlation between the electron emission phenomenon and mechano-chemical processes in solids is also presented by Khrustalev [44].

#### **3.2. Triboplasma**

216 Tribology in Engineering

should be 1–4 eV [40].

solids is also presented by Khrustalev [44].

The particle emission includes neutral particles (atoms, molecules, radicals and clusters) and charged particles (electrons, negative ions and positive ions). Three main types of energy emission encompass: electromagnetic energy, mechanical energy and heat. Mechanical energy includes mechanical oscillations of various frequency ranges, i.e. vibration, noise, ultrasonic emission, acoustic emission, etc. Electromagnetic emission can be classified into static and dynamic. Static emission includes static electric and magnetic fields, while dynamic emission includes electromagnetic waves of various wavelengths, i.e. radio waves; IR, visible, UV light; and X-rays [34]. Significant research in the field of triboemission was carried out by Nakayama et al. [35]. Kim et al. [36] investigated electron and photon evolvement (phE) from magnesia (MgO) under friction with diamond; they found that during indentation, prior to any fracture of MgO, only phE was observed. The relative intensities of these signals can therefore be used to follow the progress and extent of plastic

The work of Molina et al. [37-38] characterized triboemission of electrons from diamondon-alumina, diamond-on-sapphire, alumina-on-alumina, and diamondon-aluminum. The three ceramic-materials consistently showed burst-type negatively charged triboemission during contact at constant load and speed, while the aluminum system produced no significant emission. Decaying emission after contact ceased also was detected from the three ceramic systems for durations exceeding the minute-range [39]. For the cases of diamond-on-alumina and diamond-on-sapphire, energy spectrometry showed that a large fraction of the triboemitted negative charges were of low-energy (eg. 1–5 eV). This finding was of significant importance because in the NIRAM approach, it was hypothesized that the energy level of triboelectrons to initiate tribochemical reaction

Interestingly, an early work [41] demonstrated that electrons of very low energy (EEE) can be produced from solids by mechanical deformation, X-ray irradiation and chemical reaction; if the excitation is not great enough to produce normal electron emission, steady EEE can be produced by steady excitation. Another early work [42] investigated EEE from aluminum abraded in different atmospheres and found that under high and ultra-high vacuum conditions, such electron emissions is associated with a shift of photo-electric threshold dependent upon the residual gas pressure to which the surface was exposed. It was evidenced that the initial growth stage of emission is due to the adsorption of water vapor, the subsequent decay being associated with oxidation [42]. EEE process is also combined with triboplasma. Extensive review paper [43] shows exo-emission as a sensitive method for the monitoring of the initial stages in the fragmentation of polymeric materials subjected to mechanical action, and demonstrates that the electrons emitted when solids (dielectric materials, metals, and polymers) are subjected to mechanical influences are capable of inducing the dissociative ionization of the water molecules adsorbed on the surfaces. The studies reviewed in [43] demonstrate unambiguously the interrelation between the mechanoemission phenomena and the mechanochemical processes. A correlation between the electron emission phenomenon and mechano-chemical processes in

deformation and fracture during wear on millisecond time scales [36].

Elastic deformation is the first stage of the mechanical energy interaction between solids and leads to a change of the bond distances in the affected solid. Actually, it concerns mechanical energy transmission to solids. By and large, there are few processes for the transmission of mechanical energy by impact treatment. Heinicke in the Tribochemistry book [8] states the following: *'Immediately at the commencement of a grain colliding at high velocity with a solid surface it comes to a quasi-adiabatic energy accumulation and to the formation of an "energy bubble" at the point of action in the sub-microscopic deformation zone'.* All these specific aspects are summarized in the phenomenological Magma-Plasma Model (MPM) [7,8]. As the MPM process is combined with the EEE process, it is of very significant importance for both mechanochemistry and tribochemistry. Figure 7 depicts the Magma-Plasma Model.

**Figure 7.** The Magma-Plasma Model (MPM) for the impact stress of flying grain.

The short life of the triboplasma causes no Maxwell-Boltzmann distribution, thus an equilibrium temperature cannot be given and the chemical process taking place in the excitation phase cannot be described by the laws of thermodynamics [8]. The highest stage of energy excitation changes dynamically into the next stage characterized by the relaxation of the plasma states and is termed as "edge-plasma" and "post-plasma". Work [45] describes the energy dissipation on solids activated by impact along with adequate discussion.

Mechanical forces make the atoms leave their equilibrium positions due to lattice vibration, alter bond lengths and angles of their atomic arrangements leading to electronically excited states (see Figures 3,5,7). The energy field incurred by the tribophysical effects, for example the EEE process, triboluminescence, triboplasma, crystal defects etc., initiates specific tribochemical reactions.

Mechanochemistry in terms of processes being triggered in the solid state chemistry, due to the application of mechanical energy, is extremely complex. Tribochemistry as its branch is

even more entangled. Our present knowledge shows that mechanochemistry is also well combined with nanoscience [46].

General Approach to Mechanochemistry and Its Relation to Tribochemistry 219

**4.2. Examples of NIRAM applications**

*4.2.1. Traditional approach to mechanisms of AW and EP lubricant additives*

mating solid elements and thereby reducing wear and seizure.

**Figure 9.** Tribochemical 'TREE' according to reference [47].

*4.2.2. Examples of NIRAM controlled tribochemical reactions*

selected organic compounds.

Tribochemistry of lubricating oils is overviewed in Pawlak's book [47]. Important and interesting approach to oil formulations and complex lubrication processes is assigned to inverse micelle. Figure 9 illustrates the inverse micelles involvement to interactions of base oils with major engine oil additives. The nature of the tribochemical film is the key to better understand the mechano-chemical processes that give rise to chemical films separating

The chemistry and tribology of EP additives have been recently well reviewed from the viewpoint of the presently accepted action mechanism [48]. On the other hand, chapters in the same book consider also the NIRAM approach [49-50]. Chapter on *'Tribochemistry'* [51] details the NIRAM approach, presents specific reactive intermediates and mechanisms of

Work [52] investigated tribochemical reactions of carboxylic acids under boundary lubrication conditions and it was found that, apart from regular salt (monodentate


**3. All-optical neural networks**

As was discussed above, neural networks have been successfully used to solve rather complex problems in nanophotonics in particular. There are two fundamentally different alternatives for the implementation of neural networks: a software simulation in conventional computers or a particular hardware solution capable of dramatically decreasing execution time. Software simulation can be useful to develop and debug new algorithms, as well as to benchmark them using small networks. However, if large networks are to be used, software simulation is not enough. The problem is the time required for the learning process, which can increase exponentially with the size of the network.

At the same time, there are ongoing attempts to implement this architecture in a hardware form, which should allow for substantial gains for scaling and distributed approaches. Digital circuits are usually implemented by using robust CMOS technology, where the neuron state summation is realised via common multipliers and adders. The activation function is more complicated to implement, which require a highly nonlinear response. One of the technical difficulties is related to the implementation of communication channels. In general, the connection scales as a square of the number of inputs. One of the solutions to this problem can be provided by optical networks, where the communication channels do not need to be hard-wired [22, 23]. Also, in free space, light waves can cross each other without affecting the carrying information. Other benefits include low energy to transmit the signal and high switching time up to 40 GHz. Thus, analogue optical technology allows to implement artificial neural networks directly in hardware, with data encoded in pulses of light and neurons made from optical elements, such as lenses, prisms, beam splitters, waveguides and spatial light modulators (SLMs), see **Figure 6a**. In particular, SLMs are used for algebraic operations, including matrix multiplication with a specific phase mask design [24].

#### **Figure 6.**

*(a) Schematic of a generic two-layer artificial optical neural network with linear operation realised via programmable SLM and nonlinear activation by employing nonlinear media. (b) Optical micrograph and highlighted region of the implemented optical neural network of 22-mode on-chip interference unit. The system acts as an optical FPGA. Matrix multiplication and amplification are realised fully optically via Mach-Zehnder interferometer (MZI) phase-shifters.*

**75**

*Deep Learning Enabled Nanophotonics DOI: http://dx.doi.org/10.5772/intechopen.93289*

example, in the boson sampling approach.

resonator at the neuron's output.

and high information density.

**4. Conclusion and outlook**

Recently, another approach to realise optical neural networks was based on Mach-Zehnder interferometers (MZIs) to calculate matrix products [25, 26], see **Figure 6b**. By carefully manipulating a specific phase shift between a coherent pair of incoming light pulses allow to multiply a two-element vector, encoded in the amplitude of the pulses, by a two-by-two matrix [27, 28]. An array of the interferometers can then perform arbitrary matrix operations, which is widely used, for

One of the main challenges for the successful realisation of the optical neural networks is to find a suitable implementation of the activation function. Due to its inherent nonlinear response, light pulses are required to interact with a nonlinear media. Various nonlinear effects have been proposed for such functionality. To avoid optical signal loss, mostly dielectric materials have been considered. It includes photorefractive crystals, liquid crystals, and various semiconductors [29]. Most promising nonlinear effects are based on harmonics generation, phase conjugation, optical limiter, and bistable response. Recently, researchers from The Hong Kong University of Science and Technology proposed a new approach based on cold atoms exhibiting electromagnetic induced transparency effect to implement the nonlinear activation function [24]. Importantly, it requires very weak laser power and is based on nonlinear quantum interference. It is also possible to produce different activation

The group from the University of Münster has suggested an alternative approach by exploiting the wavelength-division multiplexing (WDM) to transport and sum multiple pulses at different wavelengths using single waveguides [30]. Importantly, they suggest a phase-change material (PCM) for both linear summing and nonlinear firing. In this approach, each neuron is implemented as a ring-shaped resonator of varying diameters to tap light signals with corresponding resonant wavelengths from a common waveguide. When the total power of all those signals exceeds a certain threshold, they then switch another piece of PCM, this time embedded in a

Despite recent progress in all-optical implementation of neural networks, various groups investigated hybrid optoelectronic systems in which neurons convert signals from light into electricity and then back to light. The group from Princeton suggested using electro-absorption modulation for the optimal integrated photonics implementation of the neural networks [31]. One of the essential aspects is the integration density. The electro-optical induced nonlinearity is realised by using photodiode couplers. Moreover, it also allows for spiking signal processing, which enables the direct implementation of neuromorphic computing. It led to the development of a new and quite promising platform of neuromorphic photonics combining the advantages of optics and electronics to build systems with high efficiency, high interconnectivity

Although deep learning was proposed and found great success in the context of computer vision and speech/image recognition, it has become a powerful approach to solve complex problems in biology, physics and chemistry. As a branch of physics, nanophotonics has witnessed huge progress based on deep learning. Deep learning allows us to inversely design nanophotonic devices with even less computation source and time compared to conventional computational approaches, such as topology optimisation and genetic algorithm. Currently, the research interests and efforts are still fast-growing and expanding in deep learning-enabled nanophoton-

ics. More research opportunities may be brought in this area.

functions by varying the positions of counterpropagating beams.

#### *Deep Learning Enabled Nanophotonics DOI: http://dx.doi.org/10.5772/intechopen.93289*

*Advances and Applications in Deep Learning*

**3. All-optical neural networks**

tolerance of fabrication and measurements.

increase exponentially with the size of the network.

with a specific phase mask design [24].

*Zehnder interferometer (MZI) phase-shifters.*

wavelength in the visible wavelength range. **Figure 5g** shows the chirality spectra of measurement and prediction from BoNet. The discrepancy can be attributed to the

As was discussed above, neural networks have been successfully used to solve rather complex problems in nanophotonics in particular. There are two fundamentally different alternatives for the implementation of neural networks: a software simulation in conventional computers or a particular hardware solution capable of dramatically decreasing execution time. Software simulation can be useful to develop and debug new algorithms, as well as to benchmark them using small networks. However, if large networks are to be used, software simulation is not enough. The problem is the time required for the learning process, which can

At the same time, there are ongoing attempts to implement this architecture in a hardware form, which should allow for substantial gains for scaling and distributed approaches. Digital circuits are usually implemented by using robust CMOS technology, where the neuron state summation is realised via common multipliers and adders. The activation function is more complicated to implement, which require a highly nonlinear response. One of the technical difficulties is related to the implementation of communication channels. In general, the connection scales as a square of the number of inputs. One of the solutions to this problem can be provided by optical networks, where the communication channels do not need to be hard-wired [22, 23]. Also, in free space, light waves can cross each other without affecting the carrying information. Other benefits include low energy to transmit the signal and high switching time up to 40 GHz. Thus, analogue optical technology allows to implement artificial neural networks directly in hardware, with data encoded in pulses of light and neurons made from optical elements, such as lenses, prisms, beam splitters, waveguides and spatial light modulators (SLMs), see **Figure 6a**. In particular, SLMs are used for algebraic operations, including matrix multiplication

*(a) Schematic of a generic two-layer artificial optical neural network with linear operation realised via programmable SLM and nonlinear activation by employing nonlinear media. (b) Optical micrograph and highlighted region of the implemented optical neural network of 22-mode on-chip interference unit. The system acts as an optical FPGA. Matrix multiplication and amplification are realised fully optically via Mach-*

**74**

**Figure 6.**

Recently, another approach to realise optical neural networks was based on Mach-Zehnder interferometers (MZIs) to calculate matrix products [25, 26], see **Figure 6b**. By carefully manipulating a specific phase shift between a coherent pair of incoming light pulses allow to multiply a two-element vector, encoded in the amplitude of the pulses, by a two-by-two matrix [27, 28]. An array of the interferometers can then perform arbitrary matrix operations, which is widely used, for example, in the boson sampling approach.

One of the main challenges for the successful realisation of the optical neural networks is to find a suitable implementation of the activation function. Due to its inherent nonlinear response, light pulses are required to interact with a nonlinear media. Various nonlinear effects have been proposed for such functionality. To avoid optical signal loss, mostly dielectric materials have been considered. It includes photorefractive crystals, liquid crystals, and various semiconductors [29]. Most promising nonlinear effects are based on harmonics generation, phase conjugation, optical limiter, and bistable response. Recently, researchers from The Hong Kong University of Science and Technology proposed a new approach based on cold atoms exhibiting electromagnetic induced transparency effect to implement the nonlinear activation function [24]. Importantly, it requires very weak laser power and is based on nonlinear quantum interference. It is also possible to produce different activation functions by varying the positions of counterpropagating beams.

The group from the University of Münster has suggested an alternative approach by exploiting the wavelength-division multiplexing (WDM) to transport and sum multiple pulses at different wavelengths using single waveguides [30]. Importantly, they suggest a phase-change material (PCM) for both linear summing and nonlinear firing. In this approach, each neuron is implemented as a ring-shaped resonator of varying diameters to tap light signals with corresponding resonant wavelengths from a common waveguide. When the total power of all those signals exceeds a certain threshold, they then switch another piece of PCM, this time embedded in a resonator at the neuron's output.

Despite recent progress in all-optical implementation of neural networks, various groups investigated hybrid optoelectronic systems in which neurons convert signals from light into electricity and then back to light. The group from Princeton suggested using electro-absorption modulation for the optimal integrated photonics implementation of the neural networks [31]. One of the essential aspects is the integration density. The electro-optical induced nonlinearity is realised by using photodiode couplers. Moreover, it also allows for spiking signal processing, which enables the direct implementation of neuromorphic computing. It led to the development of a new and quite promising platform of neuromorphic photonics combining the advantages of optics and electronics to build systems with high efficiency, high interconnectivity and high information density.