This thesis intends to cover the experimental investigation of the propagation of laser-generated optoacoustic waves in structural materials and how they can be utilized for damage detection. Firstly, a system for scanning a rectangular patch on the sample is designed. This is achieved with the help of xy stages which are connected to the laser head and allow it to move on a plane. Next, a parametric study was designed to determine the optimum testing parameters of the laser. The parameters so selected were then used in a series of tests which helped in discerning how the Ultrasound Waves behave when damage is induced in the sample (in the form of addition of masses). The first test was of increasing the mases in the sample. The second test was a scan of a rectangular area of the sample with and without damage to find the effect of the added masses. Finally, the data collected in such a manner is processed with the help of the Hilbert-Huang transform to determine the time of arrival. The major benefits from this study are the fact that this is a Non-Destructive imaging technique and thus can be used as a new method for detection of defects and is fairly cheap as well.

Non-Destructive Testing (NDT) is a branch of scientific methods and techniques

used to evaluate the defects and irregularities in engineering materials. These methods

conduct testing without destroying or altering material’s structure and functionality. Most

of these defects are subsurface making them difficult to detect and access.

SONIC INFRARED (IR) is a relatively new and emerging vibrothermography

method under the category of NDT methods. This is a fast NDT inspection method that

uses an ultrasonic generator to pass an ultrasonic pulse through the test specimen which

results in a temperature variation in the test specimen. The temperature increase around

the area of the defect is more because of frictional heating due to the vibration of the

specimen. This temperature variation can be observed using a thermal camera.

In this research study, the temperature variation in the composite laminate during

the SONIC IR experimentation using an infrared thermal camera. These recorded data are

used to determine the location, dimension and depth of defects through SONIC IR NDT

method using existing defect detection algorithms. Probability of detection analysis is

used to determine the probability of detection under specific experimental conditions for

two different types of composite laminates. Lastly, the effect of the process parameters

such as number of pulses, pulse duration and time delay between pulses of this technique

on the detectability and probability of detection is studied in detail.

More recently there have been a tremendous advancement in theoretical studies showing remarkable properties that could be exploited from transition metal dichalcogenide (TMDC) Janus crystals through various applications. These Janus crystals are having a proven intrinsic electrical field due to breaking of out-of-plane inversion symmetry in a conventional TMDC when one of the chalcogenides atomic layer is being completely replaced by a layer of different chalcogen element. However, due to lack of accurate processing control at nanometer scales, key for creating a highly crystalline Janus structure has not yet been familiarized. Thus, experimental characterization and implication of these Janus crystals are still in a state of stagnation. This work presents a new advanced methodology that could prove to be highly efficient and effective for selective replacement of top layer atomic sites at room temperature conditions.

This is specifically more focused on proving an easy repeatability for replacement of top atomic layer chalcogenide from a parent structure of already grown TMDC monolayer (via CVD) by a post plasma processing technique. Though this developed technique is not limited to only chalcogen atom replacement but can be extended to any type of surface functionalization requirements.

Basic characterization has been performed on the Janus crystal of SeMoS and SeWS where, creation and characterization of SeWS has been done for the very first time, evidencing a repeatable nature of the developed methodology.

Collective cell migration in the 3D fibrous extracellular matrix (ECM) is crucial to many physiological and pathological processes such as tissue regeneration, immune response and cancer progression. A migrating cell also generates active pulling forces, which are transmitted to the ECM fibers via focal adhesion complexes. Such active forces consistently remodel the local ECM (e.g., by re-orienting the collagen fibers, forming fiber bundles and increasing the local stiffness of ECM), leading to a dynamically evolving force network in the system that in turn regulates the collective migration of cells.

In this work, this novel mechanotaxis mechanism is investigated, i.e., the role of the ECM mediated active cellular force propagation in coordinating collective cell migration via computational modeling and simulations. The work mainly includes two components: (i) microstructure and micromechanics modeling of cellularized ECM (collagen) networks and (ii) modeling collective cell migration and self-organization in 3D ECM. For ECM modeling, a procedure for generating realizations of highly heterogeneous 3D collagen networks with prescribed microstructural statistics via stochastic optimization is devised. Analysis shows that oriented fibers can significantly enhance long-range force transmission in the network. For modeling collective migratory behaviors of the cells, a minimal active-particle-on-network (APN) model is developed, in which reveals a dynamic transition in the system as the particle number density ρ increases beyond a critical value ρc, from an absorbing state in which the particles segregate into small isolated stationary clusters, to a dynamic state in which the majority of the particles join in a single large cluster undergone constant dynamic reorganization. The results, which are consistent with independent experimental results, suggest a robust mechanism based on ECM-mediated mechanical coupling for collective cell behaviors in 3D ECM.

For the future plan, further substantiate the minimal cell migration model by incorporating more detailed cell-ECM interactions and relevant sub-cellular mechanisms is needed, as well as further investigation of the effects of fiber alignment, ECM mechanical properties and externally applied mechanical cues on collective migration dynamics.

The development of stab-resistant Kevlar armor has been an ongoing field of research
since the late 1990s, with the ultimate goal of improving the multi-threat capabilities of
traditional soft-body armor while significantly improving its protective efficiency - the amount
of layers of armor material required to defeat threats. To create a novel, superior materials
system to reinforce Kevlar armor for the Norica Capstone project, this thesis set out to
synthesize, recover, and characterize zinc oxide nanowire colloids.

The materials synthesized were successfully utilized in the wider Capstone effort to
dramatically enhance the protective abilities of Kevlar, while the data obtained on the 14
hydrothermal synthesis attempts and numerous challenges at recovery provided critical
information on the synthesis parameters involved in the reliable, scalable mass production of the
nanomaterial additive. Additionally, recovery was unconventionally facilitated in the absence of
a vacuum filtration apparatus with nanoscale filters by intentionally inducing electrostatic
agglomeration of the nanowires during standard gravity filtration. The subsequent application of
these nanowires constituted a pioneering use in the production of nanowire-reinforced
STF-based Kevlar coatings, and support the future development and, ultimately, the
commercialization of lighter and more-protective soft armor systems.

Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures or processing settings. While optimization techniques have mature applications to a large range of engineering systems, their application to material design meets unique challenges due to the high dimensionality of microstructures and the high costs in computing process-structure-property (PSP) mappings. The key to addressing these challenges is the learning of material representations and predictive PSP mappings while managing a small data acquisition budget. This dissertation thus focuses on developing learning mechanisms that leverage context-specific meta-data and physics-based theories. Two research tasks will be conducted: In the first, we develop a statistical generative model that learns to characterize high-dimensional microstructure samples using low-dimensional features. We improve the data efficiency of a variational autoencoder by introducing a morphology loss to the training. We demonstrate that the resultant microstructure generator is morphology-aware when trained on a small set of material samples, and can effectively constrain the microstructure space during material design. In the second task, we investigate an active learning mechanism where new samples are acquired based on their violation to a theory-driven constraint on the physics-based model. We demonstrate using a topology optimization case that while data acquisition through the physics-based model is often expensive (e.g., obtaining microstructures through simulation or optimization processes), the evaluation of the constraint can be far more affordable (e.g., checking whether a solution is optimal or equilibrium). We show that this theory-driven learning algorithm can lead to much improved learning efficiency and generalization performance when such constraints can be derived. The outcomes of this research is a better understanding of how physics knowledge about material systems can be integrated into machine learning frameworks, in order to achieve more cost-effective and reliable learning of material representations and predictive models, which are essential to accelerate computational material design.

Recently, two-dimensional (2D) materials have emerged as a new class of materials with highly attractive electronic, optical, magnetic, and thermal properties. However, there exists a sub-category of 2D layers wherein constituent metal atoms are arranged in a way that they form weakly coupled chains confined in the 2D landscape. These weakly coupled chains extend along particular lattice directions and host highly attractive properties including high thermal conduction pathways, high-mobility carriers, and polarized excitons. In a sense, these materials offer a bridge between traditional one-dimensional (1D) materials (nanowires and nanotubes) and 2D layered systems. Therefore, they are often referred as pseudo-1D materials, and are anticipated to impact photonics and optoelectronics fields.

This dissertation focuses on the novel growth routes and fundamental investigation of the physical properties of pseudo-1D materials. Example systems are based on transition metal chalcogenide such as rhenium disulfide (ReS2), titanium trisulfide (TiS3), tantalum trisulfide (TaS3), and titanium-niobium trisulfide (Nb(1-x)TixS3) ternary alloys. Advanced growth, spectroscopy, and microscopy techniques with density functional theory (DFT) calculations have offered the opportunity to understand the properties of these materials both experimentally and theoretically. The first controllable growth of ReS2 flakes with well-defined domain architectures has been established by a state-of-art chemical vapor deposition (CVD) method. High-resolution electron microscopy has offered the very first investigation into the structural pseudo-1D nature of these materials at an atomic level such as the chain-like features, grain boundaries, and local defects.

Pressure-dependent Raman spectroscopy and DFT calculations have investigated the origin of the Raman vibrational modes in TiS3 and TaS3, and discovered the unusual pressure response and its effect on Raman anisotropy. Interestingly, the structural and vibrational anisotropy can be retained in the Nb(1-x)TixS3 alloy system with the presence of phase transition at a nominal Ti alloying limit. Results have offered valuable experimental and theoretical insights into the growth routes as well as the structural, optical, and vibrational properties of typical pseudo-1D layered systems. The overall findings hope to shield lights to the understanding of this entire class of materials and benefit the design of 2D electronics and optoelectronics.

Layer structured two dimensional (2D) semiconductors have gained much interest due to their intriguing optical and electronic properties induced by the unique van der Waals bonding between layers. The extraordinary success for graphene and transition metal dichalcogenides (TMDCs) has triggered a constant search for novel 2D semiconductors beyond them. Gallium chalcogenides, belonging to the group III-VI compounds, are a new class of 2D semiconductors that carry a variety of interesting properties including wide spectrum coverage of their bandgaps and thus are promising candidates for next generation electronic and optoelectronic devices. Pushing these materials toward applications requires more controllable synthesis methods and facile routes for engineering their properties on demand.

In this dissertation, vapor phase transport is used to synthesize layer structured gallium chalcogenide nanomaterials with highly controlled structure, morphology and properties, with particular emphasis on GaSe, GaTe and GaSeTe alloys. Multiple routes are used to manipulate the physical properties of these materials including strain engineering, defect engineering and phase engineering. First, 2D GaSe with controlled morphologies is synthesized on Si(111) substrates and the bandgap is significantly reduced from 2 eV to 1.7 eV due to lateral tensile strain. By applying vertical compressive strain using a diamond anvil cell, the band gap can be further reduced to 1.4 eV. Next, pseudo-1D GaTe nanomaterials with a monoclinic structure are synthesized on various substrates. The product exhibits highly anisotropic atomic structure and properties characterized by high-resolution transmission electron microscopy and angle resolved Raman and photoluminescence (PL) spectroscopy. Multiple sharp PL emissions below the bandgap are found due to defects localized at the edges and grain boundaries. Finally, layer structured GaSe1-xTex alloys across the full composition range are synthesized on GaAs(111) substrates. Results show that GaAs(111) substrate plays an essential role in stabilizing the metastable single-phase alloys within the miscibility gaps. A hexagonal to monoclinic phase crossover is observed as the Te content increases. The phase crossover features coexistence of both phases and isotropic to anisotropic structural transition.

Overall, this work provides insights into the controlled synthesis of gallium chalcogenides and opens up new opportunities towards optoelectronic applications that require tunable material properties.

Alloying in semiconductors has enabled many civilian technologies in optoelectronic, photonic fields and more. While the phenomenon of alloying is well established in traditional bulk semiconductors, owing to vastly available ternary phase diagrams, the ability to alloy in 2D systems are less clear. Recently anisotropic materials such as ReS2 and TiS3 have been extensively studied due to their direct-gap semiconductor and high mobility behaviors. This work is a report on alloys of ReS2 & ReSe2 and TiS3 &TiSe3.

Alloying selenium into ReS2 in the creation of ReS2xSe2-x, tunes the band gap and changes its vibrational spectrum. Depositing this alloy using bottom up approach has resulted in the loss of crystallinity. This loss of crystallinity was evidenced by grain boundaries and point defect shown by TEM images.

Also, in the creation of TiS3xSe3-x, by alloying Se into TiS3, a fixed ratio of 8% selenium deposit into TiS3 host matrix is observed. This is despite the vastly differing precursor amounts and growth temperatures, as evinced by detailed TEM, EDAX, TEM diffraction, and Raman spectroscopy measurements. This unusual behavior contrasts with other well-known layered material systems such as MoSSe, WMoS2 where continuous alloying can be attained. Cluster expansion theory calculations suggest that only limited composition (x) can be achieved. Considering the fact that TiSe3 vdW crystals have not been synthesized in the past, these alloying rejections can be attributed to energetic instability in the ternary phase diagrams estimated by calculations performed. Overall findings highlight potential means and challenges in achieving stable alloying in promising direct gap and high carrier mobility TiS3 materials.