<div>Sensing of mechanical state is critical in diverse fields including biomedical implants, intelligent robotics, consumer technology interfaces, and integrated structural health monitoring among many others. Recently, materials that are self-sensing via the piezoresistive effect (i.e. having deformation-dependent electrical conductivity) have received much attention due to their potential to enable intrinsic, material-level strain sensing with lesser dependence on external/ad hoc sensor arrays. In order to effectively use piezoresistive materials for strain-sensing, however, it is necessary to understand the deformation-resistivity change relationship. To that end, many studies have been conducted to model the piezoresistive effect, particularly in nanocomposites which have been modified with high aspect-ratio carbonaceous fillers such as carbon nanotubes or carbon nanofibers. However, prevailing piezoresistivity models have important limitations such as being limited to microscales and therefore being computationally prohibitive for macroscale analyses, considering only simple deformations, and having limited accuracy. These are important issues because small errors or delays due to these challenges can substantially mitigate the effectiveness of strain-sensing via piezoresistivity. Therefore, the first objective of this thesis is to develop a conceptual framework for a piezoresistive tensorial relation that is amenable to arbitrary deformation, macroscale analyses, and a wide range of piezoresistive material systems. This was achieved by postulating a general higher-order resistivity-strain relation and fitting the general model to experimental data for carbon nanofiber-modified epoxy (as a representative piezoresistive material with non-linear resistivity-strain relations) through the determination of piezoresistive constants. Lastly, the proposed relation was validated experimentally against discrete resistance changes collected over a complex shape and spatially distributed resistivity changes imaged via electrical impedance tomography (EIT) with very good correspondence. Because of the generality of the proposed higher-order tensorial relation, it can be applied to a wide variety of material systems (e.g. piezoresistive polymers, cementitious, and ceramic composites) thereby lending significant potential for broader impacts to this work. </div><div><br></div><div>Despite the expansive body of work on direct current (DC) transport, DC-based methods have important limitations which can be overcome via alternating current (AC)-based self-sensing. Unfortunately, comparatively little work has been done on AC transport-deformation modeling in self-sensing materials. Therefore, the second objective of this thesis is to establish a conceptual framework for the macroscale modeling of AC conductivity-strain coupling in piezoresistive materials. For this, the universal dielectric response (UDR) as described by Joncsher's power law for AC conductivity was fit to AC conductivity versus strain data for CNF/epoxy (again serving as a representative self-sensing material). It was found that this power law does indeed accurately describe deformation-dependent AC conductivity and power-law fitting constants are non-linear in both normal and shear strain. Curiously, a piezoresistive switching behavior was also observed during this testing. That is, positive piezoresistivity (i.e. decreasing AC conductivity with increasing tensile strain) was observed at low frequencies and negative piezoresistivity (i.e. increasing AC conductivity with increasing tensile strain) was observed at high frequencies. Consequently, there exists a point of zero piezoresistivity (i.e. frequency at which AC conductivity does not change with deformation) between these behaviors. Via microscale computational modeling, it was discovered that changing inter-filler tunneling resistance acting in parallel with inter-filler capacitance is the physical mechanism of this switching behavior.</div>

Feedback control of MEMS devices has the potential to significantly improve device performance and reliability. One of the main obstacles to its broader use is the small number of on-chip sensing options available to MEMS designers. A method of using integrated piezoresistive sensing is proposed and demonstrated as another option. Integrated piezoresistive sensing utilizes the inherent piezoresistive property of polycrystalline silicon from which many MEMS devices are fabricated. As compliant MEMS structures flex to perform their functions, their resistance changes. That resistance change can be used to transduce the structures' deflection into an electrical signal. This dissertation addresses three topics associated with integrated piezoresistive sensing: developing an empirical model describing the piezoresistive response of polycrystalline-silicon flexures, designing compliant MEMS with integrated piezoresistive sensing using the model, and implementing feedback control using integrated piezoresistive sensing. Integrated piezoresistive sensing is an effective way to produce small, reliable, accurate, and economical on-chip sensors to monitor compliant MEMS devices. A piezoresistive flexure model is presented that accurately models the piezoresistive response of long, thin flexures even under complex loading conditions. The model facilitates the design of compliant piezoresistive MEMS devices, which output an electrical signal that directly relates to the device's motion. The piezoresistive flexure model is used to design a self-sensing long displacement MEMS device. Motion is achieved through contact-aided compliant rolling elements that connect the output shaft to kinematic ground. Self-sensing is achieved though integrated piezoresistive sensing. An example device is tested that demonstrates 700 micrometers of displacement with a sensing resolution of 2 micrometers. The piezoresistive microdisplacement transducer (PMT) is a structure that uses integrated piezoresistive sensing to monitor the output displacement of a thermomechanical inplane microacutator (TIM). Using the PMT as a feedback sensor for closed-loop control of the TIM reduced the system's response time from 500~$mu$s to 190~$mu$s, while maintaining a positioning accuracy of $pm$29~nm. Feedback control of the TIM also increased its robustness and reliability by allowing the system to maintain its performance after it had been significantly damaged.

As technology advances and engineering capabilities improve, more research has focused on microscopic possibilities. Microelectromechanical systems (MEMS) is one area that has received much attention recently. Within MEMS much research has focused on sensing and actuation. This thesis presents work on a particular actuator of interest, the thermomechanical in-plane microactuator (TIM). Recent work has shown the possibility of a novel approach of sensing mechanical outputs of the TIM without ancillary sensors. This sensing approach exploits the piezoresistive property of silicon. However, to implement this approach a full model of the TIM would need to be obtained to describe the physics of the TIM, as well as development of a calibration approach to account for variations between devices. This thesis develops a multi-physics model of the TIM to realize this sensing approach. This model determines the mechanical state of the TIM using the same electrical signal that actuates the TIM. In this way the TIM is able to operate as a self-sensing actuator. To allow this multi-physics model to be tractable, work was done to simplify the thermal modeling of the TIM. A preliminary calibration approach was developed to adequately compensate for variations between devices. Thermal modeling and calibration were coupled with mechanical modeling and a developed sensing approach to form the full multi-physics model of the TIM. Validation testing of the model was performed with a modified calibration approach which showed good correlation with experimental data.

Yes / In this paper, two types of nano carbon materials including 0D nano carbon black and 2D graphene are assembled through electrostatic adsorption to develop smart cement-based composites. Owing to their excellent mechanical, electrical properties and synergistic effect, self-assembled 0D/2D nano carbon materials can form toughening and conductive networks in cement-based materials at low content level and without changing the preparation process of conventional cement-based materials, thus endowing cement-based materials with smart and multifunctional properties including high toughness, self-sensing property to stress/strain and damage, shielding/absorbing property to electromagnetic wave. The developed smart cement-based composites with self-assembled 0D/2D nano carbon materials have promising application in the fields of oil well cementing, structural health monitoring, and electromagnetic protection and anti-electromagnetic pollution. It can therefore conclude that electrostatic self-assembled 0D/2D nano carbon materials provide a simple preparation method and excellent composite effect for developing nano cement-based materials, which can be applied in large-scale infrastructures. / The National Science Foundation of China (51908103) and the China Postdoctoral Science Foundation (2019M651116).

Yes / In view of high-performance, multifunctional and low-carbon development of infrastructures, there is a growing demand for smart engineering materials, making infrastructures intelligent. This paper reports a new-generation self-sensing cementitious composite (SSCC) incorporated with a hierarchically structured carbon fiber-carbon nanotube composite filler (CF-CNT), which is in-situ synthesized by directly growing CNT on CF. Various important factors including catalyst, temperature, and gas composition are considered to investigate their kinetic and thermodynamic influence on CF-CNT synthesis. The reciprocal architecture of CF-CNT not only alleviates the CNT aggregation, but also significantly improves the interfacial bonding between CF-CNTs and matrix. Due to the synergic and spatially morphological effects of CF-CNT, i.e., the formation of widely distributed multiscale reinforcement networks, SSCCs with CF-CNTs exhibit high mechanical properties and electrical conductivity as well as excellent self-sensing performances, particularly enhanced sensing repeatability. Moreover, the SSCCs with CF-CNTs are integrated into a full-scale maglev girder to devise a smart system for crack development monitoring. The system demonstrates high sensitivity and fidelity to capture the initiation of cracks/damage, as well as progressive and sudden damage events until complete failure of the maglev girder, indicating its considerable potential for structural health monitoring of infrastructures. / The work described in this paper is supported by grants from the National Science Foundation of China (51978127 and 51578110) and grants from the China Postdoctoral Science Foundation (2022M710973 and 2022M720648).

Yes / Ultra-high performance concrete (UHPC) is an innovative cementitious composite, that has been widely applied in numerous structural projects because of its superior mechanical properties and durability. However, ensuring the safety of UHPC structures necessitates an urgent need for technology to continuously monitor and evaluate their condition during their extended periods of service. Self-sensing ultra-high performance concrete (SSUHPC) extends the functionality of UHPC system by integrating conductive fillers into the UHPC matrix, allowing it to address above demands with great potential and superiority. By measuring and analyzing the relationship between fraction change in resistivity (FCR) and external stimulates (force, stress, strain), SSUHPC can effectively monitor the crack initiation and propagation as well as damage events in UHPC structures, thus offering a promising pathway for structural health monitoring (SHM). Research on SSUHPC has attracted substantial interests from both academic and engineering practitioners in recent years, this paper aims to provide a comprehensive review on the state of the art of SSUHPC. It offers a detailed overview of material composition, mechanical properties and self-sensing capabilities, and the underlying mechanisms involved of SSUHPC with various functional fillers. Furthermore, based on the recent advancements in SSUHPC technology, the paper concludes that SSUHPC has superior self-sensing performance under tensile load but poor self-sensing performance under compressive load. The mechanical and self-sensing properties of UHPC are substantially dependent on the type and dosage of functional fillers. In addition, the practical engineering SHM application of SSUHPC, particularly in the context of large-scale structure, is met with certain challenges, such as environment effects on the response of SSUHPC. Therefore, it still requires further extensive investigation and empirical validation to bridge the gap between laboratory research and real engineering application of SSUHPC. / The full-text of this article will be released for public view at the end of the publisher embargo on 28 Dec 2024.

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Yes / Super-fine stainless wire (SSW) can not only form widely distributed enhancing, toughening and conductive network in reactive powder concrete (RPC) at low dosage level, but also improve weak interface area and refine cracks due to its micron scale diameter and large specific surface. In addition, the crack resistance zone generated by SSWs and RPC matrix together has potential to further enhance the fracture properties of composites. Therefore, fracture and self-sensing characteristics of SSW reinforced RPC composites were investigated in this paper. Experimental results indicated that adding 1.5 vol. % of SSW leads to 183.1% increase in the initial cracking load of RPC specimens under three-point bending load. Based on two parameter fracture model calculations, an increase of 203.4% in fracture toughness as well as an increase of 113.3% in crack tip opening displacement of the composites reinforced with 1.5% SSWs are achieved. According to double-K fracture model calculations, the initiation fracture toughness and unstable fracture toughness of the composites are enhanced by 185.2% and 179.2%, respectively. The increment for fracture energy of the composites reaches up to 1017.1% because of the emergence of blunt and tortuous cracks. The mixed mode Ⅰ-Ⅱ fracture toughness of the composites is increased by 177.1% under four-point shearing load. The initial angle of mixed mode Ⅰ-Ⅱ cracks of the composites decreases with the increase of SSW content. The initiation and propagation of cracks in the composites can be monitored by their change in electrical resistivity. The excellent fracture toughness of the composites is of great significance for the improvement of structure safety in serviceability limit states, and the self-sensing ability of the composites can also provide early warning for the degradation of structure safety. / National Key Research and Development Program of China (2018YFC0705601), the National Science Foundation of China (51578110), China Postdoctoral Science Fundation (2019M651116) and the Fundamental Research Funds for the Central Universities in China (DUT18GJ203).

The mammalian cochlea has been the inspiration to develope contemporary cochlear implants and active dynamic sensors that operate in the sensor's resonance region and possess favorable nonlinear characteristics. In the present work, multi-channel and self-sensing active artificial hair cells (AHCs) made of piezoelectric cantilevers and controlled by a cubic damping feedback controller are developed numerically and experimentally. These novel AHCs function near a Hopf bifurcation and amplify or compress the output by a one-third power-law relationship with the input, analogous to the mammalian cochlear amplifier. The multi-channel AHCs have extended frequency bandwidth to sense over multiple resonant frequencies, unlike conventional single-channel AHCs. Therefore, the adoption of these AHCs reduces the number of required sensors to cover the desired bandwidth of interest in an array format. Furthermore, a novel self-sensing active AHC is created in this study using quadmorph beams for future cochlear implants or sensor design applications. The self-sensing scheme allows miniaturization of the system, embedding AHCs in a limited space, and fabrication of AHC arrays by omitting external sensors from the system for practical implementation. Preliminary research on the extension of this research to MEMS AHCs and arrays of AHCs is also presented. The active AHCs can lead to transformative improvements in the dynamic range, sharpness of the response, and threshold of sound detection in cochlear implants to aid individuals with sensorineural hearing loss. Additionally, they can enhance the dynamic properties of sensors such as fluid flow sensors, microphones, and vibration sensors for various applications. / Doctor of Philosophy / In the mammalian auditory system, the acoustic wave that enters the ear canal is transmitted to the cochlea of the inner ear where it is decomposed into its frequency components. The cochlea then amplifies faint sounds and compresses high-level signals and as these processes stop due to damage, severe hearing loss occurs. Therefore, the present work is focused on developing artificial hair cells (AHCs) that can accurately replicate cochlea's behavior and aid the creation of prostheses for hearing restoration. In this work, the AHC is a beam with piezoelectric layers that is integrated with a control system designed to apply the cochlea-like amplification/compression on the beam. Experimental and simulation results show that the AHC is able to amplify or compress the output based on its input level similar to the mammalian cochlea. In contrast to previous designs of AHCs where each AHC could sense a single frequency, the system developed in this work possesses multiple sensing channels to increase the frequency range of the AHC. Furthermore, the development of a novel self-sensing scheme allows the omission of the external sensor that was required for the AHC operation in previous devices. This advancement in the self-sensing AHC design paves the way for creating fully implantable AHCs to replace the damaged parts of the cochlea. These multi-channel self-sensing AHCs have the potential to be used in the creation of cochlear implants, or sensors such as accelerometers, microphones, and hydrophones with improved dynamic properties. AHCs with different lengths, i.e. different sensing frequencies, can be mounted in an array format to cover the speech frequency range for speech recognition in individuals with hearing loss.

The ability to reduce flexural vibrations of lightweight structures has been a goal for many researchers. A type of transducer-controller system that accomplishes this is a piezoelectric patch connected to an electrical impedance, or shunt. The piezoelectric patch converts the vibrational strain energy of the structure to which it is bonded into electrical energy. This converted electrical energy is then modified by the shunt to influence to mechanical response. There are many types of shunt circuits which have demonstrated effective control of flexural systems. Of interest in this work is the negative capacitance shunt, which has been shown to produce significant reduction in vibration over a broad frequency range. A negative capacitance circuit produces a current that is 180̊ out of phase from a traditional, passive capacitor. In other words, the voltage of the capacitor decreases as charge is added. The negative capacitance shunt consists of a resistor and an active negative capacitance element. By adding a resistor and negative capacitor to the electrical domain, the shunt acts as a damper and negative spring in the mechanical domain. The performance of the negative capacitance shunt can be increased through proper selection of the shunt's electrical components. Three aspects of component selection are investigated: shunt efficiency, maximum suppression, and stability. First, through electrical modeling of the shunt-patch system, the components can be chosen to increase the efficiency of the shunt for a given impedance. Second, a method is developed that could be utilized to adaptively tune the magnitude of resistance and negative capacitance for maximum control at a given frequency. Third, with regard to stability, as the control gain of the circuit is increased, by adjusting the circuit parameters, there is a point when the shunt will become unstable. A method to predict the stability of the shunt is developed to aid in suppression prediction. The negative capacitance shunt is also combined with a periodic piezoelectric patch array to modify the propagating wave behavior of a vibrating structure. A finite element method is utilized to create models to predict both the propagation constant, which characterizes the reduction in propagating waves, and the velocity frequency response of a full system. Analytical predictions are verified with experimental results for both a 1- and 2-D periodic array. Results show significant attenuation can be achieved with a negative capacitance shunt applied to a piezoelectric patch array. Three electromechanical aspects are developed: design for maximum suppression, more accurate stability prediction, and increased power-output efficiency. First, a method is developed that may be used to adaptively tune the magnitude of resistance and negative capacitance for maximum suppression. Second, with regard to stability, a method is developed to predict the circuit components at which the circuit will obtain a stable output. Third, through electrical modeling of the shunt-patch system, the components are chosen to increase the power output efficiency of the shunt circuit for a given impedance. The negative capacitance shunt is also combined with a periodic piezoelectric patch array to modify the propagating wave behavior of a vibrating structure. Analytical predictions are verified with experimental results for both a 1- and 2-D periodic array. Results show significant attenuation can be achieved with a negative capacitance shunt applied to a piezoelectric patch array.