Search

Transition-metal dichalcogenide (TMD) materials have promising properties that make them suitable for wearable bioelectronics and biosensors. Specifically, the Platinum based TMD materials, PtSe2 and PtTe2, can be fabricated at low temperatures, allowing for growth on flexible substrates, such as polyimide film. Exploration of piezoresistivity and piezoelectricity in PtSe2 and PtTe2 can enable more applications for the novel 2D material. This report focuses on the experimental setup and results for the verification of the piezoresistive and piezoelectric property in PtSe2 and PtTe2. The piezoresistivity experiment focuses on the change in resistance in the material due to strain induced by bending using a two-point bending fixture. In the piezoelectricity experiment, samples are put in a periodic strain at 2 Hz with the voltage response of the material being measured using a digital oscilloscope. An analysis of the experimental results is discussed along with a proposal for further applications for using piezoelectric materials as energy-harvesting elements of the next-generation bioelectronics.

Abstract: Polymers have various attractive properties (e.g., low volume mass density, low cost and excellent degradation resistance), and hence, they have become essential for a wide range of applications (e.g., aerospace, oil and gas and renewable energy industries). However, due to their limited mechanical, thermal and electrical properties in comparison with typical metallic materials (e.g., steel and aluminum alloys), polymers often need to be modified with different types of fillers to meet the requirements of specific applications. A multitude of filler materials (e.g., nano silver particles, carbon nano tubes, graphene) are available with a wide range of geometries, such as spherical, fiber and platelet shapes. Therefore, developing methods for efficiently characterizing and identifying mechanical and physical properties of filler modified polymers is an important engineering task. The objective of this thesis is to create and validate a numerical modeling framework for predicting mechanical, thermal and electrical properties of particulate polymer composites. In contrast to the high cost and time consuming nature of experiments, this framework is to provide a relatively time- and cost-effective means to guide material design and elucidate experimental observations and analysis results. The first phase of this research project was focused on developing a numerical multiphysics modeling framework to predict the mechanical and thermal properties (i.e., effective modulus of elasticity, Poisson’s ratio, coefficient of thermal expansion, and thermal conductivity), of a single-phase particulate polymer composite with randomly distributed spherical particles. The second phase focus was on expanding the modeling framework to enable property predictions, specifically thermal properties (i.e., effective thermal conductivity), of randomly distributed but aligned cylindrical particulate composites fillers. In the final phase of the research, the numerical framework was extended to predict electrical properties (i.e., effective electrical conductivity, percolation threshold and piezoresistivity), of spherical shape particulate composites. Predicted data were compared against experimental values and analytical models in the different contexts, which indicated overall good agreement between the predictions from the developed modeling framework and experimental works. The developed modeling framework is a valuable contribution facilitating the study of a broad range of material properties, thus improving the material design of filler modified polymers, by comprehensively capturing random aspects of particle and composite morphology.

Polymer bonded explosives (PBXs) are composites comprised of energetic crystals with a very high energy density surrounded by a polymer binder. The formation of hotspots within polymer bonded explosives can lead to the thermal decomposition and initiation of the energetic material. A frictional heating model is applied at the mesoscale to assess the potential for the formation of hotspots under low velocity impact loadings. Monitoring of the formation and growth of damage at the mesoscale is considered through the inclusion of a piezoresistive carbon nanotube network within the energetic binder providing embedded strain and damage sensing. A coupled multiphysics thermo-electro-mechanical peridynamics framework is developed to perform computational simulations on an energetic material microstructure subject to these low velocity impact loads. With increase in impact energy, the model predicts larger amounts of sensing and damage thereby supporting the use of carbon nanotubes to assess damage growth and subsequent formation of hotspots. The framework is also applied to assess the combined effects of thermal loading due to prescribed hotspots with inertial effects due to low velocity impact loading. It has been found that the present model is able to detect the presence of hotspot dominated regions within the energetic material through the piezoresistive sensing mechanism. The influence of prescribed hotspots on the thermo-electro-mechanical response of the energetic material under a combination of thermal and inertial loading was observed to dominate the lower velocity impact response via thermal shock damage. In contrast, the higher velocity impact energies demonstrated an inertially dominated damage response. Quantifying the piezoresistive effect derived from embedding carbon nanotubes in polymers remains a challenge since these nanocomposites exhibit significant variation in their electro-mechanical properties depending upon factors such as CNT volume fraction, CNT dispersion, CNT alignment and properties of the polymer. Of interest is electrical percolation where the electrical conductivity of the CNT/polymer nanocomposite increases through orders of magnitude with increase in CNT volume fraction. Estimates and distributions for the electrical conductivity and piezoresistive coefficients of the CNT/polymer nanocomposite are obtained and analyzed with increasing CNT volume fraction and varying barrier potential, which is a parameter that controls the extent of electron tunneling. The effect of CNT alignment is analyzed by comparing the electro-mechanical properties in the alignment direction versus the transverse direction for different orientation conditions. Estimates of piezoresistive coefficients are converted into gage factors and compared with experimental sources in literature. The methodology for this work uses automated scripts which are used in conjunction with high performance computing to generate several 5 μm ×5 μm realizations for different CNT volume fractions. These realizations are then analyzed using finite elements to obtain volume averaged effective values, which are then subsequently used to generate measures of central tendency (estimated mean) and variability (standard deviation, coefficient of variation, skewness and kurtosis) in a descriptive statistical analysis.

Abstract: In this research, a developed n-type piezoresistive three dimensional (3D) stress sensor with full temperature compensation is presented. The proposed sensing rosette benefits from the stress insensitivity of the full-circular n-type piezoresistor, oriented over (111) silicon plane, to detect only temperature changes for compensation. Moreover, the unique behavior of shear piezoresistive coefficient (π44) of n-Si is utilized to construct a piezoresistive stress sensing rosette over (111) silicon plane that is capable of extracting 3D stress components. Prototype stress sensing chip was microfabricated to test the capability of the developed sensing rosette to accurately extract stress applied on structures at different thermal environments. The fabricated sensing chip was subjected to different mechanical loads using a loading rig with a four-point bending fixture. The testing was carried out over a temperature range of -20 to 60 °С. The results showed that the proposed sensing chip has the capability of capturing the stress applied at different temperatures. Also, the developed sensing rosette showed less sensitivity to the uncertainty in piezoresistive coefficients’ values compared to the other developed 3D piezoresistive stress sensors. Further improvements of the proposed sensor were achieved by developing a hybrid smart temperature compensation system to reduce the temperature effect on both resistivity and sensitivity of the sensing rosette. The developed compensation system integrates a temperature sensor, placed in close proximity to the stress sensing rosettes, with the artificial neural networks (ANNs). The results showed an improvement in stress measurement accuracy compared to the other developed compensation systems for such 3D stress sensors. The proposed compensation system has merit since the employed temperature sensor shares the same thermal environment with the stress sensing rosette. Moreover, the developed system has the capability to compensate for both resistance and sensitivity, for 3D stress sensor, with no need for additional circuitry on the sensing device itself.

The strain and damage sensing abilities of randomly oriented multi-walled carbon nanotubes (MWCNTs) dispersed in the polymer binder of energetic composites were experimentally investigated. Ammonium perchlorate (AP) crystals served as the inert energetic and atomized aluminum as the metallic fuel, both of which were combined to create a representative fuel-oxidizer filler often used for aerospace propulsive applications. MWCNTs were dispersed within an elastomer binder of polydimethylsiloxane (PDMS), and hybrid energetics were fabricated from it, with matrix material comprised of the identified fillers. The nanocomposites were characterized based on their stress-strain response under monotonic uniaxial compression to failure, allowing for the assessment of effects of MWCNTs and aluminum powder on average compressive elastic modulus, peak stress, and strain to failure. The piezoresistive response was measured as the change in impedance with applied monotonic strain in both the mesoscopic and microscopic strain regimes of mechanical loading for each material system, as well as under ten cycles of applied compressive loading within those same strain regimes. Gauge factors were calculated to quantify the magnitude of strain and damage sensing in MWCNT-enhanced material systems. Electrical response of single-cycle thermal loading was explored with epoxy in place of the elastomer binder of the previously discussed studies. Piezoresistive response due to microscale damage from thermal expansion was observed exclusively in material systems enhanced by MWCNTs. The results discussed herein validate structural health monitoring (SHM) applications for embedded carbon nanotube sensing networks in polymer-based energetics under unprecedented cyclic loads.

This work explores the computational modeling of electromechanical problems using peridynamics and in particular, its application in studying the potential of carbon nanotube (CNT) reinforced nanocomposites for the purpose of sensing deformation and damage in materials. Peridynamics, a non-local continuum theory which was originally formulated for modeling problems in solid mechanics, has been extended in this research to electromechanical fields and applied to study the electromechanical properties of CNT nanocomposites at multiple length scales. Piezoresistivity is the coupling between the electrical properties of a material and applied mechanical loads, more specifically the change in resistance in response to deformation. This can include both, a geometric effect due to change in dimensions as well as the change in resistivity of the material itself. Nanocomposites referred to in this work are materials which consist of CNTs dispersed in a binding polymer matrix. The origins of the extraordinary piezoresistive properties of nanocomposites lie at the nanoscale where the non-local phenomenon of electron hopping plays a significant role in establishing the properties of the nanocomposite along with CNT network formation and inherent piezoresistivity of CNTs themselves. Electron hopping or tunneling allows for a current to flow between neighboring CNTs even when they are not in contact, provided the energy barrier for electrons to hop is small enough. This phenomenon is highly nonlinear with respect to the intertube distance and is also dependent on other factors such as the potential barrier of the polymer matrix. To investigate this in more detail, peridynamic simulations are first employed to study the piezoresistivity at the CNT bundle scale by considering a nanoscale representative volume element (RVE) of CNTs within polymer matrix, and by explicitly modeling electron hopping effects. This is done by introducing electron hopping bonds and it is shown that the conductivity and the non-local length scale parameter in peridynamics (the horizon) can be derived from a purely physics based model rather than assuming an ad-hoc value. Piezoresistivity can be characterized as a function of the deformation and damage within the material and thereby used as an in-situ indicator of the structural health of the material. As such, a material system for which real time in-situ monitoring may be useful is polymer bonded explosives. While these materials are designed for detonation under conditions of a strong shock, they can be damaged or even ignited under certain low magnitude impact scenarios such as during accidental drop or transportation. Since these materials are a heterogeneous system consisting of explosive grains within a polymer matrix binder, it is proposed that CNTs can be dispersed within the binder medium leading to an inherently piezoresistive hybrid nanocomposite bonded explosive material (NCBX) material which can then be monitored for a continuous assessment of deformation and damage within the material. To explore the potential use of CNT nanocomposites for this novel application, peridynamic simulations are carried out at the microscale level, first under quasistatic conditions and subsequently under dynamic conditions to allow the propagation of elastic waves. Peridynamics equations, which can be discretized to obtain a meshless method are particularly suited to this problem as the explicit modeling of crack initiation and propagation at the microscale is essential to understanding the properties of this material. Moreover, many other parameters such as electrical conductivity of the grain and the properties of the grain-binder interface are studied to understand their effect on the piezoresistive response of the material. For example, it is found that conductivity of the grain plays a major role in the piezoresistive response since it affects the preferential pathways of current density depending on the relative ease of flow through grain vs. binder. The results of this work are promising and are two fold. Peridynamics is found to be an effective method to model such materials, both at the nanoscale and the microscale. It alleviates some of difficulties faced by traditional finite element methods in the modeling of damage in materials and can be extended to coupled fields with relative ease. Secondly, simulations presented in this work show that there is much promise in this novel application of nanocomposites in the field of structural health monitoring of polymer bonded explosives.

At present, structural health monitoring efforts focus primarily on the sensors and sensing systems for detecting instances and locations of damage through techniques such as X-ray, micro CT, acoustic emission, infrared thermography, lamb wave etc., which only detect cracks at relatively large length scales and rely heavily on sensors and sensing systems which are external to the material system. As an alternative to conventional commercially available SHM techniques, the current work explores processing-structure-property relationships starting from carbon nanotube (CNT) based nanocomposites to particulate composites with nanocomposite binder/matrix materials, i.e. hybrid particulate composites to investigate deformation and damage sensing capabilities of inherently sensing materials and structures through their piezoresistive (coupled electro-mechanical) response. Initial efforts focused on controlling the dispersion of CNTs and orientation of CNT filaments within nanocomposites under dielectrophoresis to guide design and fabrication process of nanocomposites by tuning CNT concentration, applied AC electric field intensity, frequency and exposure time. It is observed that a combination of exposure time to AC electric field and the AC field frequency are the key drivers of filament width and spacing and that the network for filament formation is much more efficient for pristine CNTs than for acid treated functionalized CNTs. With the knowledge obtained from controlling the morphological features, AC field-induced long range alignment of CNTs within bulk nanocomposites was scaled up to form structural test coupons. The morphology, electrical and mechanical properties of the coupons were investigated. The anisotropic piezoresistive response both for parallel and transverse to CNT alignment direction within bulk composite coupons under various loading conditions was obtained. It is observed that control of the CNT network allows for the establishment of percolation paths and piezoresistive response well below the nominal percolation threshold observed for random, so called well-dispersed CNT network distributions. The potential for use of such bulk nanocomposites in SHM applications to detect strain and microdamage accumulation is further demonstrated, underscoring the importance of microscale CNT distribution/orientation and network formation/disruption in governing the piezoresistive sensitivities. Finally, what may be the first experimental study in the literature is conducted for real-time embedded microscale strain and damage sensing in energetic materials by distributing the CNT sensing network throughout the binder phase of inert and mock energetic composites through piezoresistive response for SHM in energetic materials. The incorporation of CNTs into inert and mock energetic composites revealed promising self-diagnostic functionalities for in situ real-time SHM applications under quasi-static and low velocity impact loading for solid rocket propellants, detonators and munitions to reduce the stochastic nature of safety characterization and help in designing insult tolerant energetic materials.

The study of self-sensing cementitious materials is a constantly expanding topic of study in the materials and civil engineering fields and refers to the creation and utilization of cement-based materials (including cement paste, cement mortar, and concrete) that are capable of sensing (i.e. measuring) stress and strain states without the use of embedded or attached sensors. With the inclusion of electrically conductive fillers, cementitious materials can become truly self-sensing. Previous researchers have provided only qualitative studies of self-sensing material stress-electrical response. The overall goal of this research was to modify and apply previously developed predictive models on cylinder compression test data in order to provide a means to quantify stress-strain behavior from electrical response. The Vipulanandan and Mohammed (2015) stress-resistivity model was selected and modified to predict the stress state, up to yield, of cement cylinders enhanced with nanoscale iron(III) oxide (nanoFe2O3) particles based on three mix design parameters: nanoFe2O3 content, water-cement ratio, and curing time. With the addition of a nonlinear model, parameter values were obtained and compiled for each combination of nanoFe2O3 content and water-cement ratio for the 28-day cured cylinders. This research provides a procedure and lays the framework for future expansion of the predictive model.

The current state of the art in structural health monitoring is primarily reliant on sensing deformation of structures at discrete locations using sensors and detecting damage using techniques such as X-ray, microCT, acoustic emission, impedance methods etc., primarily employed at specified intervals of service life. There is a need to develop materials and structures with self-sensing capabilities such that deformation and damage state can be identified in-situ real time. In the current work, the inherent deformation and damage sensing capabilities of carbon nanotube (CNT) based nanocomposites are explored starting from the nanoscale electron hopping mechanism to effective macroscale piezoresistive response through finite elements based computational micromechanics techniques. The evolution of nanoscale conductive electron hopping pathways which leads to nanocomposite piezoresistivity is studied in detail along with its evolution under applied deformations. The nanoscale piezoresistive response is used to evaluate macroscale nanocomposite response by using analytical micromechanics methods. The effective piezoresistive response, obtained in terms of macroscale effective gauge factors, is shown to predict the experimentally obtained gauge factors published in the literature within reasonable tolerance. In addition, the effect of imperfect interface between the CNTs and the polymer matrix on the mechanical and piezoresistive properties is studied using coupled electromechanical cohesive zone modeling. It is observed that the interfacial separation and damage at the nanoscale leads to a larger nanocomposite irreversible piezoresistive response under monotonic and cyclic loading because of interfacial damage accumulation. As a sample application, the CNT-polymer nanocomposites are used as a binding medium for polycrystalline energetic materials where the nanocomposite binder piezoresistivity is exploited to provide inherent deformation and damage sensing. The nanocomposite binder medium is modeled using electromechanical cohesive zones with properties obtained through the Mori-Tanaka method allowing for different local CNT volume fractions and orientations. Finally, the traditional implementation of Material Point Method (MPM) is extended for composite problems with large deformation (e.g. large strain nanocomposite sensors with elastomer matrix) allowing for interfacial discontinuities appropriately. Overall, the current work evaluates nanocomposite piezoresistivity using a multiscale modeling framework and emphasizes through a sample application that nanocomposite piezoresistivity can be exploited for inherent sensing in materials.

Nanocomposites have incredible potential when integrated as matrices in fiber-reinforced composites for transformative conductivity-based structural health monitoring (SHM). Key to this potential is the dependence of nanocomposite conductivity on well-connected nanofiller networks. Damage that severs the network or strain that affects the connectivity will manifest as a conductivity change. These damage or strain-induced conductivity changes can then be detected and spatially located by electrical impedance tomography (EIT). The nanofiller network therefore acts as an integrated sensor network giving unprecedented insight into the mechanical state of the structure. Despite the potential of combining nanocomposite matrices with EIT, important limitations exist. EIT, for example, requires large electrode arrays that are too unwieldy to be practically implemented on in-service structures. EIT also tends to be insensitive to small, highly localized conductivity losses as is expected from common modes fiber-reinforced composite damage such as matrix cracking and delamination. Furthermore, there are gaps in the fundamental understanding of nanocomposite conductivity. This thesis advances the state of the art by addressing the aforementioned limitations of EIT for conductivity-based SHM. This is done by insightfully leveraging the unique properties of nanocomposite conductivity to circumvent EIT's limitations. First, nanocomposite conductive properties are studied. This results in fundamental contributions to the understanding of nanocomposite piezoresistivity, the influence of nanofiller alignment on transverse percolation and conductivity, and conductivity evolution due to electrical loading. Next, the potential of EIT for conductivity-based health monitoring is studied and demonstrated for damage detection in carbon nanofiber (CNF)/epoxy and glass fiber/epoxy laminates manufactured with carbon black (CB) filler and for strain detection in CNF/polyurethane (PU). Lastly, the previously developed insights into nanocomposite conductive properties and damage detection via EIT are combined to greatly enhance EIT for SHM. This is done by first exploring how the sensitivity of EIT to delamination can be enhanced through nanofiller alignment and tailoring. A method of coupling the EIT image reconstruction process with known conductivity changes such as those induced by straining piezoresistive nanocomposites is developed and presented. This approach will tremendously bolster the image quality of EIT or, synonymously, significantly abate the number of electrodes required by EIT.

It has been observed that carbon nanotube (CNT)-polymer nanocomposite material has observable piezoresistive effect, that is to say that changes in applied strain may induce measurable changes in resistance. The first focus of the work is on modeling the piezoresistive response of the CNT-polymer nanocomposites by using computational micromechanics techniques based on finite element analysis. The in-plane, axial, the three dimensional piezoresistive responses of the CNT-polymer nanocomposites are studied by using 2D, axisymmetric, and 3D electromechanically coupled and multiscale finite element models. The microscale mechanisms that may have a substantial influence on the overall piezoresistivity of the nanocomposites, i.e. the electrical tunneling effect and the inherent piezoresistivity of the CNT, are included in microscale RVEs in order to understand their influence on macroscale piezoresistive response in terms of both the normalized change in effective resistivity and the corresponding effective gauge factor under applied strain. The computational results are used to better understand the driving mechanisms for the observed piezoresistive response of the material. The second focus of the work is on modeling the piezoresistive response of fuzzy fiber reinforced polymer composites by applying a 3D multiscale micromechanics model based on finite element analysis. Through explicitly accounting for the local piezoresistive response of the anisotropic interphase region, the piezoresistive responses of the overall fuzzy fiber reinforced polymer composites are obtained. The modeling results not only provide a possible explanation for the small gauge factors as observed in experiments, but also give guidance for the manufacture of fuzzy fiber reinforced polymer composites in order to achieve large, consistent, and predictable gauge factors. The third focus of the work is on modeling the coupled effect between continuum damage and piezoresistivity in the CNT-polymer nanocomposites by using computational micromechanics techniques based on a concurrent multiscale finite element analysis. The results show that there is a good correlation between continuum damage and piezoresistive response of the nanocomposites, which gives theoretical and modeling support for the use of CNT-polymer nanocomposites in structural health monitoring (SHM) applications for damage detections.

Abstract: This work involves the design, microfabrication, calibration, and testing of a new silicon-based piezoresistive rosette capable of extracting the three-dimensional (3D) stresses in the silicon upon deformation. A new 10-element piezoresistive rosette was devised to extract all stress components with temperature compensation compared to the 8-element rosette developed by previous researchers, which delivers partially temperature-compensated stress output. The proposed rosette is made up of either dual- or single-polarity sensing elements through utilizing the unique behavior of the shear piezoresistive coefficient (pi44) in n-Si with impurity concentration. An analytical study was conducted to investigate the feasibility of the new approach. The analysis is based on solving the determinants of the coefficients of the matrices describing the resistance change versus stress and temperature for the sensing elements. The calculated determinants over a range of impurity concentrations showed non-zero regions, thus indicating the feasibility of the approach. A full experimental study including the microfabrication, calibration and testing of the 10-element single-polarity rosette was conducted to demonstrate the actual behavior of the rosette in extraction of the 3D stresses. An early prototype, named POC chip, using diffusion doping was used to calibrate the piezoresistive coefficients and temperature coefficient of resistance and calculate the determinants to support the analytical study. The calibration process involved applying uni-axial and thermal loads on the sensing elements. The resulting determinants from the calibration process indicated non-zero values, thus verified the experimental feasibility of the approach. On the other hand, the second prototype, named test chip, using ion implantation doping was used for testing of the rosette after conducting a full calibration process involving uni-axial, thermal, and hydrostatic loads. The testing of the test chip was conducted by applying a four-point bending of a chip-on-beam specimen at room temperature. Three chip orientations and three rosette-sites were used to induce five stress components in a controlled manner, while the out-of-plane normal stress was not tested independently due to its low sensitivity in the current microfabrication run. A finite element model (FEM) of the chip-on-beam loading was developed to compare to the stress output from the experimental testing. The five stress components were extracted from the three rosette-sites and showed good correlation with the FEM.