Browsing by Subject "Materials Science"

The majority of consumer electronic devices, electric vehicles, and aerospace electronics are powered by lithium ion batteries because of their high energy and power densities. Commercially available lithium ion batteries consist of electrodes, separators and current collectors fabricated in multilayer rolls that are packaged in cylindrical or rectangular cases. The size and shape of the package as well as the composition of the electrode has a significant impact on the battery life and design of the products they power. For example, the battery life and shape of portable electronics such as cell phones or laptops, is governed by the volume that is dedicated to the battery. In the case of electric vehicles, decreasing the size and weight of the battery while increasing capacity is an engineering challenge that affects vehicle range and cost. Therefore, the of my dissertation consists of the development of a novel 3D printable lithium ion battery nanocomposites and the integration of conductive metal nanomaterials into conventional lithium ion anodes. Here, we report the development of PLA-anode, cathode, and separator materials that enable 3D printing of complete lithium ion batteries with a low-cost FFF printer for the first time. The most common 3D printing polymer polylactic acid (PLA) is an insulator. However, our work demonstrates that 3D printed PLA can be infused with a mixture of ethyl methyl carbonate, propylene carbonate, and LiClO4 provides an ionic conductivity of 2.3 x 10−4 S cm−1 which is comparable to that of polymer and hybrid electrolytes (10−3 to 10−4 S cm−1). It was found that up to 12-30 volume % of solids, depending on the filler morphology, could be mixed into PLA without causing it to clog during 3D printing. It was also found that not only is electrical conductivity crucial to the performance of a 3D printed lithium ion battery, but efficient electrical contact to the active materials is as well. To that effect, we investigated the effect of aspect ratio of silver-copper core-shell nanowires on the performance enhancement of a commercially fabricated graphite lithium ion anodes. Currently, carbon is the most common conductive filler used in commercial lithium ion battery anodes. We hypothesize that a more conductive, high aspect ratio would improve the performance of a lithium ion battery. We examined the effect of exchanging carbon with CuAg nanowires as the conductive filler in graphite lithium ion batteries. We tested 4 different aspect ratios and found that not only does aspect ratio matter, diameter and length have profound effect on capacity and energy of the anode at the same volume percent as carbon conductive filler.

Effective computational materials search, categorization, and design necessitates a high-throughput (HT) approach. System by system analyses lack the scope and speed needed to uncover large portions of the materials landscape. By performing broad searches over structural or chemical classes of materials and guided by fundamental physical principles, materials with specific desired properties can be systematically found. Furthermore, the HT approach is an effective general tool for materials classification. Depending on the application, various properties can be computed leading to powerful classification schemes. To implement HT materials studies, however, a versatile and robust framework must first be developed. In this paper, the HT framework AFLOW that has been developed and used successfully over the last decade is presented. Specifically, attention is given to an origin-specific symmetry algorithm. The algorithm is designed to determine the relevant symmetry properties of an arbitrary crystal structure (e.g., point group, space group, etc.).

Metallosupramolecular polymers are increasingly of interest for functional and degradable polymeric materials. In these materials, the metal-ligand bonds often bear an external mechanical load, but little is yet understood about the nature of mechanically-triggered reactions of metal-ligand bonds and how that reactivity influences the mechanical limits of the material. This dissertation presents a poly(cyclooctene) polymer bearing 2,6-bis(1′-methyl-benzimidazolyl)pyridine (Mebip) ligands on sidechains, which provides easy incorporation into polymer backbones and sidechains, binding to a large variety of metal species, and facile synthesis with sites for future study substituent effects. This platform is employed in proof-of-concept studies comparing the crosslinking behavior of iron(II) trifluoromethanesulfonate and copper(II) trifluoromethanesulfonate. It was found through small molecule spectroscopic studies that both metal species bind in the desired 2:1 MeBip:metal stoichiometry for crosslinking. When these small molecule complexes are polymerized as crosslinkers in gel and solid networks, though the extent of crosslinking is found to be similar, the copper(II)-crosslinked networks exhibited a faster relaxation than the iron(II)-crosslinked networks. Further, under high strains, the copper(II)-crosslinked networks exhibited significantly higher extensibility. This work lays the foundation for further investigations of the effect of metal-ligand bonding on force-coupled properties of materials.

Tumor angiogenesis is critical to tumor growth and metastasis, yet much is unknown about the role vascular cells play in the tumor microenvironment. A major outstanding challenge associated with studying tumor angiogenesis is that existing preclinical models are limited in their recapitulation of in vivo cellular organization in 3D. This disparity highlights the need for better approaches to study the dynamic interplay of relevant cells and signaling molecules as they are organized in the tumor microenvironment. In this thesis, we combined 3D culture of lung adenocarcinoma cells with adjacent 3D microvascular cell culture in 2-layer cell-adhesive, proteolytically-degradable poly(ethylene glycol) (PEG)-based hydrogels to study tumor angiogenesis and the impacts of neovascularization on tumor cell behavior.

In initial studies, 344SQ cells, a highly metastatic, murine lung adenocarcinoma cell line, were characterized alone in 3D in PEG hydrogels. 344SQ cells formed spheroids in 3D culture and secreted proangiogenic growth factors into the conditioned media that significantly increased with exposure to transforming growth factor beta 1 (TGF-β1), a potent tumor progression-promoting factor. Vascular cells alone in hydrogels formed tubule networks with localized activated TGF-β1. To study cancer cell-vascular cell interactions, the engineered 2-layer tumor angiogenesis model with 344SQ and vascular cell layers was employed. Large, invasive 344SQ clusters developed at the interface between the layers, and were not evident further from the interface or in control hydrogels without vascular cells. A modified model with spatially restricted 344SQ and vascular cell layers confirmed that observed 344SQ cluster morphological changes required close proximity to vascular cells. Additionally, TGF-β1 inhibition blocked endothelial cell-driven 344SQ migration.

Two other lung adenocarcinoma cell lines were also explored in the tumor angiogenesis model: primary tumor-derived metastasis-incompetent, murine 393P cells and primary tumor-derived metastasis-capable human A549 cells. These lung cancer cells also formed spheroids in 3D culture and secreted proangiogenic growth factors into the conditioned media. Epithelial morphogenesis varied for the primary tumor-derived cell lines compared to 344SQ cells, with far less epithelial organization present in A549 spheroids. Additionally, 344SQ cells secreted the highest concentration of two of the three angiogenic growth factors assessed. This finding correlated to 344SQ exhibiting the most pronounced morphological response in the tumor angiogenesis model compared to the 393P and A549 cell lines.

Overall, this dissertation demonstrates the development of a novel 3D tumor angiogenesis model that was used to study vascular cell-cancer cell interactions in lung adenocarcinoma cell lines with varying metastatic capacities. Findings in this thesis have helped to elucidate the role of vascular cells in tumor progression and have identified differences in cancer cell behavior in vitro that correlate to metastatic capacity, thus highlighting the usefulness of this model platform for future discovery of novel tumor angiogenesis and tumor progression-promoting targets.

Utilizing the power of Monte Carlo simulations, a novel, semi-empirical method for investigating the performance of organic photovoltaics (OPVs) in resonant infrared, matrix-assisted pulsed laser evaporation (RIR-MAPLE) films is explored. Emulsion-based RIR-MAPLE offers a unique and powerful alternative to solution processing in depositing organic materials for use in solar cells: in particular, its usefulness in controlling the nanoscale morphology of organic thin films and the potential for creating novel hetero-structures make it a suitable experimental backdrop for investigating trends through simulation and gaining a better understanding of how different thin film characteristics impact OPV device performance.

The work presented in this dissertation explores the creation of a simulation tool that relies heavily on measureable properties of RIR-MAPLE films that impact efficiency and can be used to inform film deposition and dictate the paths for future improvements in OPV devices. The original nanoscale implementation of the Monte Carlo method for investigating OPV performance is transformed to enable direct comparison between simulation and experimental external quantum efficiency results. Next, a unique microscale formulation of the Dynamic Monte Carlo (DMC) model is developed based on the observable, fundamental differences between the morphologies of RIR-MAPLE and solution-processed bulk heterojunction (BHJ) films. This microscale model enables us to examine the sensitivity of device performance to various structural and electronic properties of the devices. Specifically, using confocal microscopy, we obtain an average microscale feature size for the RIR-MAPLE P3HT:PC61BM (1:1) BHJ system that represents a strategic starting point for utilizing the DMC as an empirical tool.

Building on this, the RIR-MAPLE P3HT:PC61BM OPV system is studied using input simulation parameters obtained from films with different material ratios and overall device structures based on characterization techniques such as grazing incidence-wide angle X-ray scattering (GI-WAXS) and X-ray photoelectron spectroscopy (XPS). The results from the microscale DMC simulation compare favorably to experimental data and allow us to articulate a well-informed critique on the strengths and limitations of the model as a predictive tool. The DMC is then used to analyze a different RIR-MAPLE BHJ system: PCPDTBT:PC71BM, where the deposition technique itself is investigated for differences in the primary solvents used during film deposition.

Finally, a multi-scale DMC model is introduced where morphology measurements taken at two different size scales, as well as structural and electrical characterization, provide a template that mimics the operation of OPVs. This final, semi-empirical tool presents a unique simulation opportunity for exploring the different properties of RIR-MAPLE deposited OPVs, their effects on OPV performance and potential design routes for improving device efficiencies.

Cancer comprises a collection of diseases, all of which begin with abnormal tissue growth from various stimuli, including (but not limited to): heredity, genetic mutation, exposure to harmful substances, radiation as well as poor dieting and lack of exercise. The early detection of cancer is vital to providing life-saving, therapeutic intervention. However, current methods for detection (e.g., tissue biopsy, endoscopy and medical imaging) often suffer from low patient compliance and an elevated risk of complications in elderly patients. As such, many are looking to “liquid biopsies” for clues into presence and status of cancer due to its minimal invasiveness and ability to provide rich information about the native tumor. In such liquid biopsies, peripheral blood is drawn from patients and is screened for key biomarkers, chiefly circulating tumor cells (CTCs). Capturing, enumerating and analyzing the genetic and metabolomic characteristics of these CTCs may hold the key for guiding doctors to better understand the source of cancer at an earlier stage for more efficacious disease management.

The isolation of CTCs from whole blood, however, remains a significant challenge due to their (i) low abundance, (ii) lack of a universal surface marker and (iii) epithelial-mesenchymal transition that down-regulates common surface markers (e.g., EpCAM), reducing their likelihood of detection via positive selection assays. These factors potentiate the need for an improved cell isolation strategy that can collect CTCs via both positive and negative selection modalities as to avoid the reliance on a single marker, or set of markers, for more accurate enumeration and diagnosis.

The technologies proposed herein offer a unique set of strategies to focus, sort and template cells in three independent microfluidic modules. The first module exploits ultrasonic standing waves and a class of elastomeric particles for the rapid and discriminate sequestration of cells. This type of cell handling holds promise not only in sorting, but also in the isolation of soluble markers from biofluids. The second module contains components to focus (i.e., arrange) cells via forces from acoustic standing waves and separate cells in a high throughput fashion via free-flow magnetophoresis. The third module uses a printed array of micromagnets to capture magnetically labeled cells into well-defined compartments, enabling on-chip staining and single cell analysis. These technologies can operate in standalone formats, or can be adapted to operate with established analytical technologies, such as flow cytometry. A key advantage of these innovations is their ability to process erythrocyte-lysed blood in a rapid (and thus high throughput) fashion. They can process fluids at a variety of concentrations and flow rates, target cells with various immunophenotypes and sort cells via positive (and potentially negative) selection. These technologies are chip-based, fabricated using standard clean room equipment, towards a disposable clinical tool. With further optimization in design and performance, these technologies might aid in the early detection, and potentially treatment, of cancer and various other physical ailments.

Biofouling, the accumulation of biomolecules, cells, organisms and their deposits on submerged and implanted surfaces, is a ubiquitous problem across various human endeavors including maritime operations, medicine, food industries and biotechnology. Since several decades, there have been substantial research efforts towards developing various types of antifouling and fouling release approaches to control bioaccumulation on man-made surfaces. In this work we hypothesized, investigated and developed dynamic change of the surface area and topology of elastomers as a general approach for biofouling management. Further, we combined dynamic surface deformation of elastomers with other existing antifouling and fouling-release approaches to develop multifunctional, pro-active biofouling control strategies.

This research work was focused on developing fundamental, new and environment-friendly approaches for biofouling management with emphasis on marine model systems and applications, but which also provided fundamental insights into the control of infectious biofilms on biomedical devices. We used different methods (mechanical stretching, electrical-actuation and pneumatic-actuation) to generate dynamic deformation of elastomer surfaces. Our initial studies showed that dynamic surface deformation methods are effective in detaching laboratory grown bacterial biofilms and barnacles. Further systematic studies revealed that a threshold critical surface strain is required to debond a biofilm from the surface, and this critical strain is dependent on the biofilm mechanical properties including adhesion energy, thickness and modulus. To test the dynamic surface deformation approach in natural environment, we conducted field studies (at Beaufort, NC) in natural seawater using pneumatic-actuation of silicone elastomer. The field studies also confirmed that a critical substrate strain is needed to detach natural biofilm accumulated in seawater. Additionally, the results from the field studies suggested that substrate modulus also affect the critical strain needed to debond biofilms. To sum up, both the laboratory and the field studies proved that dynamic surface deformation approach can effectively detach various biofilms and barnacles, and therefore offers a non-toxic and environmental friendly approach for biofouling management.

Deformable elastomer systems used in our studies are easy to fabricate and can be used as complementary approach for existing commercial strategies for biofouling control. To this end, we aimed towards developed proactive multifunctional surfaces and proposed two different approaches: (i) modification of elastomers with antifouling polymers to produce multifunctional, and (ii) incorporation of silicone-oil additives into the elastomer to enhance fouling-release performance.

In approach (i), we modified poly(vinylmethylsiloxane) elastomer surfaces with zwitterionic polymers using thiol-ene click chemistry and controlled free radical polymerization. These surfaces exhibited both fouling resistance and triggered fouling-release functionalities. The zwitterionic polymers exhibited fouling resistance over short-term (∼hours) exposure to bacteria and barnacle cyprids. The biofilms that eventually accumulated over prolonged-exposure (∼days) were easily detached by applying mechanical strain to the elastomer substrate. In approach (ii), we incorporated silicone-oil additives in deformable elastomer and studied synergistic effect of silicone-oils and surface strain on barnacle detachment. We hypothesized that incorporation of silicone-oil additive reduces the amount of surface strain needed to detach barnacles. Our experimental results supported the above hypothesis and suggested that surface-action of silicone-oils plays a major role in decreasing the strain needed to detach barnacles. Further, we also examined the effect of change in substrate modulus and showed that stiffer substrates require lower amount of strain to detach barnacles.

In summary, this study shows that (1) dynamic surface deformation can be used as an effective, environmental friendly approach for biofouling control (2) stretchable elastomer surfaces modified with anti-fouling polymers provides a pro-active, dual-mode approach for biofouling control, and (3) incorporation of silicone-oils additives into stretchable elastomers improves the fouling-release performance of dynamic surface deformation technology. Dynamic surface deformation by itself and as a supplementary approach can be utilized biofouling management in biomedical, industrial and marine applications.

A variety of intriguing surface patterns have been observed on developing natural systems, ranging from corrugated surface of white blood cells at nanometer scales to wrinkled dog skins at millimeter scales. To mimetically harness functionalities of natural morphologies, artificial transformative skin systems by using soft active materials have been rationally designed to generate versatile patterns for a variety of engineering applications. The study of the mechanics and design of these dynamic surface patterns on soft active materials are both physically interesting and technologically important.

This dissertation starts with studying abundant surface patterns in Nature by constructing a unified phase diagram of surface instabilities on soft materials with minimum numbers of physical parameters. Guided by this integrated phase diagram, an electroactive system is designed to investigate a variety of electrically-induced surface instabilities of elastomers, including electro-creasing, electro-cratering, electro-wrinkling and electro-cavitation. Combing experimental, theoretical and computational methods, the initiation, evolution and transition of these instabilities are analyzed. To apply these dynamic surface instabilities to serving engineering and biology, new techniques of Dynamic Electrostatic Lithography and electroactive anti-biofouling are demonstrated.

Perovskite photovoltaics has attracted tremendous attention recently due to the advance in the device performance. However, it is still challenging to effectively commercialize the perovskite technology due to several issues including current-voltage hysteresis, stability, complicated device architectures, etc. In this dissertation, we use the additive to tailor the properties of the functional layers in perovskite photovoltaic devices, aiming to engineer the interface, film morphology, carrier dynamics and film crystallization process. By using the additive engineering approaches, our goal is to achieve high-performance perovskite photovoltaics with reduced hysteresis, improved stability, versatile processing methods and simplified device architectures.

Perovskite solar cells usually employ p-i-n device architectures and TiO2 is a typical n-type semiconductor widely used in perovskite solar cells. However, perovskite/TiO2 interface is not preferable for the photo-excited carrier collection due to the energy band misalignment, conductivity mismatch, etc. In chapter 2, additive was used to tailor the properties of TiO2 and enable improved interface for perovskite solar cells. With Nb5+ as additive in TiO2, the conductivity of TiO2 and interface band alignment were simultaneously improved. Consequently, high-performance perovskite solar cells were successfully obtained with reduced hysteresis by using the Nb-TiO2.

In addition to the interface, we explored the impact of morphology and carrier dynamics of perovskite films on solar cell performance. In chapter 3, NH4SCN and PbI2 were used as additives to tune the morphology and charge carrier dynamics of perovskite films. Using NH4SCN additive could significantly enlarge the grain size of the polymorph perovskite films while using PbI2 additive could increase charge carrier lifetime of perovskite films. It was found that the open-circuit voltage and fill factor of perovskite photovoltaics were correlative with charge carrier lifetime while short-circuit current density of perovskite photovoltaics were correlative with grain sizes. Using both PbI2 and NH4SCN simultaneously could synergistically improve the quality of perovskite films and performance of perovskite solar cells.

Based on the understanding from chapter 3, a room-temperature process was developed to deposit high-quality perovskite films by using PbI2 and methylammonium thiocyanate (MASCN) as additives in chapter 4. Due to the synergistic effects of the additives, room-temperature-processed perovskite films with micron-size grains and microsecond-range carrier lifetime were successfully obtained for high-performance devices. More importantly, we established the correlation between the crystal grain size in resultant perovskite films and the precursor aggregate size in precursor solutions. The correlation suggested that the perovskite grain sizes from solution process depended on the precursor aggregate sizes.

Following the understanding built in chapter 3, we used the additive engineering method to impact the performance of ETL-free perovskite solar cells. In chapter 5, we found out that the photo-excited carrier injection at the interface was significantly inhibited without the assistance of an ETL, which would compromise the collection of the photo-excited carriers. By using PbI2 as additive to tune the carrier lifetimes in perovskite films, it was found out that increased carrier lifetimes in perovskite films could effectively counterbalance the inferior interface without ETLs and enabled high performance for ETL-free perovskite solar cells. By using perovskite with microsecond carrier lifetime, ETL-free perovskite solar cells were successfully realized with performance comparable to that of ETL-containing perovskite devices. Such results offer the opportunity for the perovskite devices with simplified device architecture.

Bone is a dynamic tissue which continuously undergoes remodeling primarily through osteoblast-mediated bone formation and osteoclast-mediated bone resorption. This balance is vital in maintaining both bone homeostasis and bone regeneration. With the increase in the global elderly population, the two most prominent bone disorders of fracture and osteoporosis pose a tremendous burden to the healthcare system. While these bone disorders are increasing in prevalence, treatment options remain stagnant, demonstrating the unmet need for new clinical solutions. Strategies that induce innate repair yet eliminate the need for expensive cellular or recombinant protein-based therapies are appealing. Adenosine, a naturally occurring nucleoside, has emerged as a part of key metabolic pathway that regulates bone tissue formation, function, and homeostasis. In this dissertation, I investigate the therapeutic potential of adenosine delivery to mitigate bone disorders. Despite the regenerative capacity of bone, age-associated changes result in injuries that suffer delayed healing. Therapeutic interventions that circumvent the age-associated impairments in bone tissue and promote healing are attractive options for geriatric fracture repair. Herein, I examined the changes in extracellular adenosine signaling with aging and the potential of local delivery of adenosine to promote fracture healing in aged mice. My results showed a concomitant reduction of CD73 expression in the bone and marrow of aged mice. Local delivery of adenosine using injectable microgel building blocks and drug carriers yielded a pro-regenerative environment and promoted fracture healing in aged mice. This study provides new understandings of age-related physiological changes in adenosine levels and demonstrates the therapeutic potential of local delivery of adenosine at the fracture site to circumvent the impaired healing capacity of aged fractures. Given the multi-functionality of adenosine signaling, it is possible that extracellular adenosine delivery influences various phases of bone healing. Towards this, I examined the potential immunomodulatory effect of adenosine delivery on both the local and systemic immune system for fracture repair. My results indicated that the immune cell populations of neutrophils and macrophages did not change with adenosine treatment in the fractured callus at either 3-, 7-, or 14-days post fracture. Additionally in the peripheral blood, CD8+ and CD4+ T cell populations did not change at any of the timepoints following adenosine treatment. This study provides potential insight into the role of exogenous adenosine in the inflammatory stage of fracture healing in young animals. Aging not only poses a risk for delayed fracture healing, but also for the development of osteoporosis. Osteoporosis results in bone fragility and subsequently a higher risk for fracture incidence. This disease is characterized by an imbalance in the coupled bone remodeling process with enhanced osteoclastic activity can lead to excessive bone resorption, resulting in bone thinning. Once activated, osteoclasts bind to the bone surface and acidify the local niche. This acidic environment could serve as a potential trigger for the delivery of therapeutic agents into the osteoporotic bone tissue. To this end, I developed a pH-responsive nanocarrier-based drug delivery system that binds to the bone tissue and delivers the osteoanabolic molecule, adenosine. Adenosine is incorporated into a hyaluronic acid (HA)-based nanocarrier through a pH-sensitive ketal group. The HA-nanocarrier was further functionalized with alendronate moieties to improve binding to the bone tissues. Systemic administration of the nanocarrier containing adenosine attenuated bone loss in an ovariectomized mice model of osteoporosis and showed comparable bone qualities to that of healthy mice. Delivery of osteoanabolic small molecules, such as adenosine, that can contribute to bone formation and inhibit excessive osteoclast activity by leveraging the tissue-specific milieu could serve as viable therapeutics for osteoporosis. Overall, this dissertation offers novel findings regarding adenosine as a therapeutic to treat both fractures and osteoporosis. These findings, along with the biomaterial delivery systems developed, further advance the potential of using adenosine as a therapeutic molecule to treat bone disorders.

Virtually every consumer product available on the market today contains some form of fossil fuel-based polymer. However, these materials pose environmental, human health, and economic concerns due to their enduring presence in the global ecosystem and their degradation products. Addressing this crisis necessitates scalable production of biodegradable alternatives, such as polyhydroxyalkanoates (PHAs). PHAs are presented as promising substitutes due to their biodegradability, biocompatibility, and the potential for complete renewable utilization post-degradation, but a current challenge to widespread use of these materials lies in understanding the quantitative relationship between the structural characteristics of PHAs, their environmental interactions, and their degradation rates to enhance their industrial production and distribution. To bridge this knowledge gap, the dissertation outlines a comprehensive approach involving the development of a specialized dataset, the application of machine learning (ML) models to predict degradation rates based on structural and environmental factors, and the experimental validation of these predictions. The first part of this research focuses on assembling a manually curated dataset from the extensive, available open-access literature, aimed at understanding the effects of structural and environmental features on PHA degradation. The second part leverages this dataset through ML modeling, employing techniques like random forest regression to predict degradation profiles with over 80% accuracy. This methodology enables a deeper understanding of the complex interplay between chemical structures and degradation properties, surpassing traditional trial-and-error approaches. The final part of this research aims to complete an iterative workflow for dataset development by validating ML model predictions through physical experiments, enriching the original dataset with comprehensive experimental data on PHA degradation in hydrolytic environments with contact angle, molecular weight, and thermal property characterizations. The incorporation of experimental findings into the ML dataset, particularly through expanded ML techniques that emphasize pairwise feature importance such as explainable boosting machines (EBM), helps in pinpointing critical factors influencing PHA degradation, such as environmental temperature and material properties. The model performances indicate a strong performance of manually assembled literature-based datasets when predicting degradation rate for PHAs. In conclusion, a data science-based framework has been developed for exploring PHA biopolyester degradation and explores the combination of features of the material and its environment that integrates the structure, properties, and experimentally verified degradation profiles of the material. This workflow will be a useful and generalizable pipeline for PHAs and other polymers to expand the biopolymer design space with degradation in mind.

Computer simulations based on electronic structure theory, particularly Kohn-Sham density-functional theory (KS-DFT), are facilitating scientific discoveries across a broad range of disciplines such as chemistry, physics, and materials science. The tractable size of KS-DFT is often limited by an algebraic eigenproblem, the computational cost of which scales cubically with respect to the problem size. There have been continuous efforts to improve the performance of eigensolvers, and develop alternative algorithms that bypass the explicit solution of the eigenproblem. As the number of algorithms grows, it becomes increasingly difficult to comparatively assess their relative computational cost and implement them efficiently in electronic structure codes.

The research in this dissertation explores the feasibility of integrating different electronic structure algorithms into a single framework, combining their strengths, assessing their accuracy and computational cost relative to each other, and understanding their scope of applicability and optimal use regime. The research has led to an open-source software infrastructure, ELSI, providing the electronic structure community with access to a variety of high-performance solver libraries through a unified software interface. ELSI supports and enhances conventional cubic scaling eigensolvers, linear scaling density-matrix-based algorithms, and other reduced scaling methods in between, with reasonable default parameters for each of them. Flexible matrix formats and parallelization strategies adopted in ELSI fit the need of most, if not all, electronic structure codes. ELSI has been connected to four electronic structure code projects, allowing us to rigorously benchmark the performance of the solvers on an equal footing. Based on the results of a comprehensive set of benchmarks, we identify factors that strongly affect the efficiency of the solvers and regimes where conventional cubic scaling eigensolvers are outperformed by lower scaling algorithms. We propose an automatic decision layer that assists with the algorithm selection process.

The ELSI infrastructure is stimulating the optimization of existing algorithms and the development of new ones. Following the worldwide trend of employing graphical processing units (GPUs) in high-performance computing, we have developed and optimized GPU acceleration in the two-stage tridiagonalization eigensolver ELPA2, targeting distributed-memory, hybrid CPU-GPU architectures. A significant performance boost over the CPU-only version of ELPA2 is achieved, as demonstrated in routine KS-DFT simulations comprising thousands of atoms, for which a couple of GPU-equipped supercomputer nodes reach the throughput of some tens of conventional CPU supercomputer nodes. The GPU-accelerated ELPA2 solver can be used through the ELSI interface, smoothly and transparently bringing GPU support to all the electronic structure codes connected with ELSI. To reduce the computational cost of systems containing heavy elements, we propose a frozen core approximation with proper orthonormalization of the wavefunctions. This method is tolerant of errors due to the finite precision of numerical integrations in electronic structure codes. A considerable saving in the computational cost can be achieved, with the electron density, energies, and forces all matching the accuracy of all electron calculations.

This research shows that by integrating a broad range of electronic structure algorithms into one infrastructure, new algorithmic developments and optimizations can take place at a faster pace. The outcome is open and beneficial to the entire electronic structure community, instead of being restricted to one particular code project. The ELSI infrastructure has already been utilized to accelerate large-scale electronic structure simulations, some of which were not feasible before.

Phase separation of macromolecules is a critical phenomenon for the human condition. This phenomenon has also been exploited for biotechnological development to improve human morbidity and mortality. However, there is still much more to learn regarding how this behavior is encoded within a protein sequence. Thus, this thesis seeks to 1) further explore the sequence space to understand how phase separation is encoded, with an emphasis on polypeptides with upper critical solution temperature (UCST) transitions and 2) use this phase separation to control availability of macromolecules at various length scales.

Using traditional molecular biology techniques, we will recombinantly express and purify a large number of polypeptides with variable sequence composition and sequence architecture. Then, using traditional polymer science and material science techniques combined with microscopic techniques that span the macro-scale and nano-scale, we will characterize their phase separation behavior and the interaction of these materials with biological systems.

We developed a practical mutation strategy that allows for complete control of the UCST binodal line in physiologic conditions that is useful for de novo design of artificial IDPs with UCST phase behavior. We evaluated the interaction of these polypeptides and their phase separation in the presence of bacterial, eukaryotic cells and in mice demonstrating how this binodal line fused to biological active partners can control biologic functions.

In bacteria, we made artificial phase separated puncta, akin to naturally occurring phase separated droplets, that have non-canonical function, demonstrating how primary features of the polypeptide chain affect enzymatic function. We created block co-polypeptides comprised of UCST and LCST protein sequences that exhibit remarkably tunable and robust nanoscale self-assembly into spherical micelles, worm-like micelles and vesicular structures capable of displaying large targeting domains on their surface. In the presence of eukaryotic cells, these nanomaterials can dramatically increase polypeptide uptake, increasing the avidity of the targeting molecule by over 1000-fold.

Finally, we demonstrated that phase separated polypeptides can sequester an active peptide GLP-1 from systemic circulation, controlling the peptide’s bioactivity through control of the phase diagram. Taken together, we demonstrate the universal power of the phase diagram, across many length scales, where the transducing agent for controlling biological activity is an engineered, repetitive polypeptide sequence.

The structure-property relationship is the foundation for materials modeling, predicting the behavior of compounds based on structural characteristics. With the advancement of ab initio methods and high performance computing, atomic configurations are being explored at an unprecedented rate. To effectively navigate the vast search space, procedures are presented for analyzing and prototyping crystalline compounds for high-throughput simulation. Integrated into the Automatic Flow (AFLOW) framework for computational materials discovery, these tools are the underlying workhorse for symmetry classification and materials generation. In particular, algorithms are detailed for determining the set of isometries for crystals, featuring a comprehensive collection of symmetry descriptions along with routines to handle ill-conditioned structural data. A library of crystallographic structures is also introduced — showcasing nearly 600 prototypes with representatives from each space group — and is complemented with functionality for rapidly creating materials via prototype decoration. Lastly, a module for comparing crystalline compounds is described to identify duplicate entries within large data sets and detect novel structure-types, independent of representation. Mechanisms are featured for converting geometries into a standard prototype convention, providing a direct pathway for incorporation into the crystallographic library. With these autonomous computational approaches, compounds are automatically classified and generated, enabling the design of new and structurally distinct materials.

Burn injuries in the United States account for over one million hospital admissions per year, with treatment estimated at four billion dollars. Of severe burn patients, 30-90% will develop hypertrophic scars (HSc). Current burn therapies rely upon the use of bioengineered skin equivalents (BSEs), which assist in wound healing but do not prevent HSc. HSc contraction occurs of 6-18 months and results in the formation of a fixed, inelastic skin deformity, with 60% of cases occurring across a joint. HSc contraction is characterized by abnormally high presence of contractile myofibroblasts which normally apoptose at the completion of the proliferative phase of wound healing. Additionally, clinical observation suggests that the likelihood of HSc is increased in injuries with a prolonged immune response. Given the pathogenesis of HSc, we hypothesize that BSEs should be designed with two key anti-scarring characterizes: (1) 3D architecture and surface chemistry to mitigate the inflammatory microenvironment and decrease myofibroblast transition; and (2) using materials which persist in the wound bed throughout the remodeling phase of repair. We employed electrospinning and 3D printing to generate scaffolds with well-controlled degradation rate, surface coatings, and 3D architecture to explore our hypothesis through four aims.

In the first aim, we evaluate the impact of elastomeric, randomly-oriented biostable polyurethane (PU) scaffold on HSc-related outcomes. In unwounded skin, native collagen is arranged randomly, elastin fibers are abundant, and myofibroblasts are absent. Conversely, in scar contractures, collagen is arranged in linear arrays and elastin fibers are few, while myofibroblast density is high. Randomly oriented collagen fibers native to the uninjured dermis encourage random cell alignment through contact guidance and do not transmit as much force as aligned collagen fibers. However, the linear ECM serves as a system for mechanotransduction between cells in a feed-forward mechanism, which perpetuates ECM remodeling and myofibroblast contraction. The electrospinning process allowed us to create scaffolds with randomly-oriented fibers that promote random collagen deposition and decrease myofibroblast formation. Compared to an in vitro HSc contraction model, fibroblast-seeded PU scaffolds significantly decreased matrix and myofibroblast formation. In a murine HSc model, collagen coated PU (ccPU) scaffolds significantly reduced HSc contraction as compared to untreated control wounds and wounds treated with the clinical standard of care. The data from this study suggest that electrospun ccPU scaffolds meet the requirements to mitigate HSc contraction including: reduction of in vitro HSc related outcomes, diminished scar stiffness, and reduced scar contraction. While clinical dogma suggests treating severe burn patients with rapidly biodegrading skin equivalents, these data suggest that a more long-term scaffold may possess merit in reducing HSc.

In the second aim, we further investigate the impact of scaffold longevity on HSc contraction by studying a degradable, elastomeric, randomly oriented, electrospun micro-fibrous scaffold fabricated from the copolymer poly(l-lactide-co-ε-caprolactone) (PLCL). PLCL scaffolds displayed appropriate elastomeric and tensile characteristics for implantation beneath a human skin graft. In vitro analysis using normal human dermal fibroblasts (NHDF) demonstrated that PLCL scaffolds decreased myofibroblast formation as compared to an in vitro HSc contraction model. Using our murine HSc contraction model, we found that HSc contraction was significantly greater in animals treated with standard of care, Integra, as compared to those treated with collagen coated-PLCL (ccPLCL) scaffolds at d 56 following implantation. Finally, wounds treated with ccPLCL were significantly less stiff than control wounds at d 56 in vivo. Together, these data further solidify our hypothesis that scaffolds which persist throughout the remodeling phase of repair represent a clinically translatable method to prevent HSc contraction.

In the third aim, we attempt to optimize cell-scaffold interactions by employing an anti-inflammatory coating on electrospun PLCL scaffolds. The anti-inflammatory sub-epidermal glycosaminoglycan, hyaluronic acid (HA) was used as a coating material for PLCL scaffolds to encourage a regenerative healing phenotype. To minimize local inflammation, an anti-TNFα monoclonal antibody (mAB) was conjugated to the HA backbone prior to PLCL coating. ELISA analysis confirmed mAB activity following conjugation to HA (HA+mAB), and following adsorption of HA+mAB to the PLCL backbone [(HA+mAB)PLCL]. Alican blue staining demonstrated thorough HA coating of PLCL scaffolds using pressure-driven adsorption. In vitro studies demonstrated that treatment with (HA+mAB)PLCL prevented downstream inflammatory events in mouse macrophages treated with soluble TNFα. In vivo studies using our murine HSc contraction model suggested positive impact of HA coating, which was partiall impeded by the inclusion of the TNFα mAB. Further characterization of the inflammatory microenvironment of our murine model is required prior to conclusions regarding the potential for anti-TNFα therapeutics for HSc. Together, our data demonstrate the development of a complex anti-inflammatory coating for PLCL scaffolds, and the potential impact of altering the ECM coating material on HSc contraction.

In the fourth aim, we investigate how scaffold design, specifically pore dimensions, can influence myofibroblast interactions and subsequent formation of OB-cadherin positive adherens junctions in vitro. We collaborated with Wake Forest University to produce 3D printed (3DP) scaffolds with well-controlled pore sizes we hypothesized that decreasing pore size would mitigate intra-cellular communication via OB-cadherin-positive adherens junctions. PU was 3D printed via pressure extrusion in basket-weave design with feature diameter of ~70 µm and pore sizes of 50, 100, or 150 µm. Tensile elastic moduli of 3DP scaffolds were similar to Integra; however, flexural moduli of 3DP were significantly greater than Integra. 3DP scaffolds demonstrated ~50% porosity. 24 h and 5 d western blot data demonstrated significant increases in OB-cadherin expression in 100 µm pores relative to 50 µm pores, suggesting that pore size may play a role in regulating cell-cell communication. To analyze the impact of pore size in these scaffolds on scarring in vivo, scaffolds were implanted beneath skin graft in a murine HSc model. While flexural stiffness resulted in graft necrosis by d 14, cellular and blood vessel integration into scaffolds was evident, suggesting potential for this design if employed in a less stiff material. In this study, we demonstrate for the first time that pore size alone impacts OB-cadherin protein expression in vitro, suggesting that pore size may play a role on adherens junction formation affiliated with the fibroblast-to-myofibroblast transition. Overall, this work introduces a new bioengineered scaffold design to both study the mechanism behind HSc and prevent the clinical burden of this contractile disease.

Together, these studies inform the field of critical design parameters in scaffold design for the prevention of HSc contraction. We propose that scaffold 3D architectural design, surface chemistry, and longevity can be employed as key design parameters during the development of next generation, low-cost scaffolds to mitigate post-burn hypertrophic scar contraction. The lessening of post-burn scarring and scar contraction would improve clinical practice by reducing medical expenditures, increasing patient survival, and dramatically improving quality of life for millions of patients worldwide.

Just as heat, light and electricity do, mechanical forces can also stimulate reactions. Conventionally, these processes - known as mechanochemistry - were viewed as comprising only destructive events, such as bond scission and material failure. Recently, Moore and coworkers demonstrated that the incorporation of mechanophores, i.e., mechanochemically active moieties, can bring new types of chemistry. This demonstration has inspired a series of fruitful works, at both the molecular and material levels, in both theoretical and experimental aspects, for both fundamental research and applications. This dissertation evaluates mechanochemical behavior in all of these contexts.

At the level of fundamental reactivity, forbidden reactions, such as those that violate orbital symmetry effects as captured in the Woodward-Hoffman rules, remain an ongoing challenge for experimental characterization, because when the competing allowed pathway is available, the reactions are intrinsically difficult to trigger. Recent developments in covalent mechanochemistry have opened the door to activating otherwise inaccessible reactions. This dissertation describes the first real-time observation and quantified measurement of four mechanically activated forbidden reactions. The results provide the experimental benchmarks for mechanically induced forbidden reactions, including those that violate the Woodward-Hoffmann and Woodward-Hoffmann-DePuy rules, and in some cases suggest revisions to prior computational predictions. The single-molecule measurement also captured competing reactions between isomerization and bimolecular reaction, which to the best of our knowledge, is the first time that competing reactions are probed by force spectroscopy.

Most characterization for mechanochemistry has been focused on the reactivity of mechanophores, and investigations of the force coupling efficiency are much less reported. We discovered that the stereochemistry of a non-reactive alkene pendant to a reacting mechanophore has a dramatic effect on the magnitude of the force required to trigger reactivity on a given timescale (here, a 400 pN difference for reactivity on the timescale of 100 ms). The stereochemical perturbation has essentially no measurable effect on the force-free reactivity, providing an almost perfectly orthogonal handle for tuning mechanochemical reactivity independently of intrinsic reactivity.

Mechanochemical coupling is also applied here to the study of reaction dynamics. The dynamics of reactions at or in the immediate vicinity of transition states are critical to reaction rates and product distributions, but direct experimental probes of those dynamics are rare. The s-trans, s-trans 1,3-diradicaloid transition states are trapped by tension along the backbone of purely cis-substituted gem-difluorocyclopropanated polybutadiene using the extensional forces generated by pulsed sonication of dilute polymer solutions. Once released, the branching ratio between symmetry-allowed disrotatory ring closing (of which the trapped diradicaloid structure is the transition state) and symmetry-forbidden conrotatory ring closing (whose transition state is nearby) can be inferred. Net conrotatory ring closing occurred in 5.0 ± 0.5% of the released transition states, as compared to 19 out of 400 such events in molecular dynamics simulations.

On the materials level, the inevitable stress in materials during usage causes bond breakage, materials aging and failure. A strategy for solving this problem is to learn from biological materials, which are capable to remodel and become stronger in response to the otherwise destructive forces. Benzocyclobutene has been demonstrated to mechanically active to ortho-quinodimethide, an intermediate capable for [4+4] dimerization and [4+2] cycloaddition. These features make it an excellent candidate for and synthesis of mechanochemical remodeling. A polymer containing hundreds of benzocyclobutene on the backbone was synthesized. When the polymer was exposed to otherwise destructive shear forces generated by pulsed ultrasound, its molecular weight increased as oppose to other mechanophore-containing polymers. When a solution of the polymer with bismaleimide was subjected to pulsed ultrasonication, crosslink occurred and the modulus increased by two orders of magnitude.

Cadmium sulfide (CdS) is one of the most commonly used II/VI semiconductor materials because of its electron energy band edge positions. CdS nanoparticles (NPs) are widely used in applications such as photodegradation of organic molecules, photocatalysis of water splitting, and as building blocks of photovoltaic devices. Bacterial precipitation of CdS NPs provides an innovative, environmentally friendly route for the synthesis of NPs with controllable electronic properties. Our previous research shows that CdS NPs can be extracellularly precipitated with tunable CdS crystallite sizes ranging from 5 nm to over 15 nm in diameter. In this thesis, I investigated the potential application of these bacterially precipitated CdS NPs for photodegradation of organic molecules, photocurrent generation, and for photoelectrochemical (PEC) hydrogen evolution. The results show that the bacterially precipitated CdS NPs and their devices performed competitively when compared with their counterparts that were synthesized via chemical bath deposition (CBD). In photodegradation experiments, the bacterially precipitated CdS NPs showed a slower rate of degradation than CBD CdS. In transient photocurrent response experiments, the devices incorporating bacterially precipitated CdS NPs showed a higher current response to visible light. Furthermore, in electrochemical hydrogen generation experiments, the bacterially precipitated CdS NP device showed a lower onset potential to trigger the reaction when irradiated with light. Collectively, the preliminary results show that biosynthesized CdS NPs have potentially promising applications for the photodegradation of organic molecules and for the photoelectrochemical hydrogen generation.

Additive manufacturing (AM, or 3D printing) has revolutionized fabrication of three dimensional (3D) parts with increased control over design at macro/meso-scale (part scale geometry, porous topology) and micro/nanoscale (topography). AM has enabled fabrication of metallic, polymeric, and ceramic scaffolds with complex porous architectures which were not previously achievable with traditional manufacturing methods. In particular, selective laser melting (SLM) has emerged as a leading technology for fabrication of porous metallic scaffolds for biomedical and other applications. Titanium alloy (Ti6Al4V) scaffolds are of interest due to the material’s high strength, corrosion resistance, and biocompatibility. Architecting porous scaffolds with tunable properties is highly relevant for load-bearing medical implants, including treatment of bone defects. Although established relationships exist for metallic foams, the complex topologies enabled by AM necessitate further characterization. In particular, investigation of processing-structure-property relationships for novel sheet-based architectures produced via SLM where topology strongly influences performance. Thus, the overall objective of this work is to develop fundamental topology driven processing-structure-property relationships considering tradeoffs between strength, fatigue resistance, and osseointegrative behavior of SLM titanium scaffolds.

Nanoparticles are being used or implemented in a wide array of applications including health care, cosmetics, automotive, food, beverage, coatings, consumer electronics, and coatings. Despite this widespread use, we are unable to predict how nanoparticles will interact with biological systems. This is important for both nanotoxicity resulting from human exposure to nanomaterials and the development of new nano-based biotechnologies. The first step in the interaction of nanoparticles with biological systems is often with blood, for biomedical applications, or lung fluid, when nanoparticles are inhaled. In both cases, the nanoparticles are exposed to proteins that form a "corona" by adsorbing on the nanoparticle surface. The subsequent cellular response is determined by this protein corona rather than the bare nanoparticle.Our goal is to develop a predictive capability for protein-nanoparticle interactions. This requires lab automation, large datasets, machine learning, and mechanistic studies. We first developed and validated a semi-automated approach to generate, purify, and characterize protein coronas using a liquid handling robot and low-cost proteomics. Using this semi-automated approach, we characterized the formation of protein coronas with increasing incubation time and serum concentration. Incubation time was found to be an important parameter for corona composition and concentration at high incubation concentrations but yielded only a small effect at low serum incubation concentrations. To better understand how the protein corona affects biological responses, we investigated the response of macrophage cells to titanium dioxide nanoparticles as a function of the protein corona. As in our previous work with serum proteins, we measured the concentration and composition of murine lung fluid proteins adsorbed on the surface of titanium dioxide nanoparticles. We found that a low concentration of lung fluid corona, relative to fetal bovine serum and bovine serum albumin coronas, led to an increased expression of cytokines (interleukin 6 (IL-6), tumor necrosis factor-alpha (TNF-α), and macrophage inflammatory protein 2 (MIP-2)), indicating an inflammation response. This underscores the importance of understanding how the composition and concentration of the protein corona governs organism responses to nanoparticle exposures. Our validated high-throughput lab automation work allowed us to synthesize a library of magnetic nanoparticles and characterize their resulting protein coronas. The resulting nanoparticle dataset has 12 unique NP surfaces, seven surface charges, two core sizes, and two core materials. We used this dataset to generate and characterize, via proteomics, a variety of protein coronas varying incubation concentration and purification methods. We used the resulting proteomic dataset in conjunction with a database of protein physicochemical properties to build a machine learning model that identifies the most important nanoparticle and protein properties for protein corona formation. The model was tested using external datasets and found that it can predict human serum and lung fluid coronas on varying nanoparticle surfaces. Overall, this combination of lab automation, machine learning, and mechanistic analysis suggests that a generalizable understanding of the protein corona formation and its effects is forthcoming.