Progressive miniaturization in electronics demands advanced materials with excellent energy conversion and transport properties. Opportunities exist in novel material morphologies such as hierarchical structures, multi-functional composites and nanoscale architectures which may offer mechanical, thermal and electronic properties tailored to a wide range of applications (e.g., aerospace, robotics, biomedical etc.). However, the manufacturing capabilities have always posed a grand challenge in realizing the advanced material morphologies. Furthermore, the multi-scale modeling of complex material architectures has been extremely challenging owing to the limitations in computation methodologies and lack of understanding in nano-/micro-meter scale physics. To address these challenges, this work considers the morphology effect on carbon nanotube (CNT)-based composites, CNT fibers and thermoelectric (TE) materials. First, this work reports additively manufacturable TE morphologies and analyzes the thermo-electric transport behavior. This research introduces innovative honeycomb TE architectures that showed ~26% efficiency increase and ~25% density reduction compared to conventional rectangular TE architectures. Moreover, this work presents 3D printable compositionally segmented TE architecture which provides record-high efficiencies (up to 8.7%) over wide temperature ranges if the composition and aspect ratio of multiple TE materials are optimized within a single TE device. Next, this research proposes computationally efficient two-dimensional (2D) finite element model (FEM) to study the electrical and thermal properties in CNT based composites by simultaneously considering the stochastic CNT distributions, CNT fractions (upto 80%) and interfacial resistances. The FEM allows to estimate the theoretical maximum possible conductivities with corresponding interfacial resistances if the CNT morphologies are carefully controlled, along with appreciable insight into the energy transport physics. Then, this work proposes a data-driven surrogate model based on convolutional neural networks to rapidly approximate the composite conductivities in a second with accuracy > 98%, compared to FEM taking >100 minutes per simulation. Finally, this research presents a pseudo 2D FEM to approximate the electrical and thermal properties in CNT fibers at various CNT aspect ratios (up to 10,000) by simultaneously considering CNT-CNT interfacial effects along with the stochastic distribution of inter-bundle voids.

Polylactic Acid (PLA), a thermoplastic polymer is well-known for its biocompatibility, making it ideal for the manufacturing of biomedical devices. However, the current applications of PLA are commonly limited by its intrinsic polymer characteristics, such as low modulus, mechanical strength, and thermal conductivity. To enhance these physical properties, a biocompatible nanodiamond enhanced PLA filament has been studied. Thermogravimetric analysis was performed to unveil the composition of nanodiamond in the composite. Four printing parameters: nozzle temperature, layer height, infill pattern and printing speed were considered and the Taguchi L9 orthogonal array was implemented for the design of experiments. Fused deposition modeling (FDM) technique was utilized to 3D print the PLA/Nanodiamond samples by altering the four printing parameters considered and were tested according to the standards for tensile strength, flexural strength, and thermal conductivity. Using the Taguchi optimization approach and analysis of variance (ANOVA), the generated experimental data was used to find the optimum set of printing parameters. Finally, cell studies were performed to demonstrate the biocompatibility of PLA/Nanodiamond. All these results could aid in determining the working ranges for FDM fabrication of PLA/Nanodiamond for biomedical applications.

Achieving a viable process for advanced manufacturing of ceramics and metal-ceramic composites is a sought-after goal in a wide range of fields including electronics and sensors for harsh environments, microelectromechanical devices, energy storage materials, and structural materials, among others. In this dissertation, the processing, and manufacturing of ceramics and ceramic composites are addressed, specifically, a process for three-dimensional (3D) printing of polymer-derived ceramics (PDC), and a process for low-cost manufacturing as well as healing of metal-ceramic composites is demonstrated.Three-dimensional printing of ceramics is enabled by dispensing the preceramic polymer at the tip of a moving nozzle into a gel that can reversibly switch between fluid and solid states, and subsequently thermally cross-linking the entire printed part “at once” while still inside the same gel was demonstrated. The solid gel converts to fluid at the tip of the moving nozzle, allowing the polymer solution to be dispensed and quickly returns to a solid state to maintain the geometry of the printed polymer both during printing and the subsequent high-temperature (160 °C) cross-linking. After retrieving the cross-linked part from the gel, the green body is converted to ceramic by high-temperature pyrolysis. This scalable process opens new opportunities for low-cost and high-speed production of complex three-dimensional ceramic parts and will be widely used for high-temperature and corrosive environment applications, including electronics and sensors, microelectromechanical systems, energy, and structural applications. Metal-ceramic composites are technologically significant as structural and functional materials and are among the most expensive materials to manufacture and repair. Hence, technologies for self-healing metal-ceramic composites are important. Here, a concept to fabricate and heal co-continuous metal-ceramic composites at room temperature were demonstrated. The composites were fabricated by infiltration of metal (here Copper) into a porous alumina preform (fabricated by freeze-casting) through electroplating; a low-temperature and low-cost process for the fabrication of such composites. Additionally, the same electroplating process was demonstrated for healing damages such as grooves and cracks in the original composite, such that the healed composite recovered its strength by more than 80%. Such technology may be expanded toward fully autonomous self-healing structures.

A new uniaxial testing apparatus that has been proposed takes advantage of less costly methods such as 3D printing of tensile fixtures and image reference markers for accurate data acquisition. The purpose of this research is to find methods to improve the resolution, accuracy, and repeatability of this newly designed testing apparatus. The first phase of the research involved building a program that optimized the testing apparatus design depending on the sample being tested. It was found that the design program allowed for quick modifications on the apparatus in order to test a wide variety of samples. The second phase of research was conducted using Finite Elements to determine which sample geometry reduced the impact of misalignment error most. It found that a previously proposed design by Dr. Wonmo Kang when combined with the testing apparatus lead to a large reduction in misalignment errors.