Selecting the best material to deliver optimum performance in real-world applications is one of the most significant challenges in engineering. Hundreds of thousands of computationally-predicted, but experimentally unexplored materials exist today in the public inorganic material databases as candidates for consideration. This thesis discusses three projects in the domain of...
Supervised learning model is one of the most fundamental machine learning models. It can provide powerful capability of prediction by learning complex patterns hidden in many, sometimes thousands, predictors. It can also be used as a building block of other machine learning tasks, like unsupervised learning and reinforcement learning. Such...
Metal–Organic Frameworks (MOFs) is a class of material comprising organic linkers and inorganic, metal-ion-containing nodes, with diverse functionalities and wide-range of applications. Because of their porous nature and functional nodes and linkers, they are competent candidates for gas storage, separation, catalysis, and so on. Most MOFs, however, are intrinsically insulating,...
Renewable energy technology, more so than ever before, is critical to the survival of humanity. For decades, concentrated efforts into designing and developing such novel devices resulted in the innovation of solar-driven photovoltaics that were competitive with nonrenewable alternatives. This thesis explores the dynamic behavior of alternative material candidates that...
Large scale adoption of sustainable technologies for energy productionand storage can be greatly facilitated by scientific advances impacting efficiency, cost and availability. The study of materials is instrumental in both upgrading the performance of existing technologies and enabling the development of new ones, and ab-initio methods and machine learning represent...
The relationship between the structure and function of proteins is a fundamental problem in biology with implications for the future of biotechnology and global health. For example, changes to the structure of a coronavirus spike protein led to a global pandemic where our best defenses were vaccines that could only...
Dental enamel is a complex bio-composite with compositional and structural features across a wide range of length scales. Defects in these features can compromise enamel’s ability to protect the tooth, resulting in adverse health outcomes. Acquired defects like tooth decay are familiar to most people and are the subject of...
The continuing increase in atmospheric CO2 to concentrations exceeding 400 ppm has attracted considerable attention from both scientists and policymakers. Industrial fossil fuel consumption generates a significant amount of CO2 emissions, and in particular, energy-intensive molecular separations that require thermal processes, such as distillation, drying, or evaporation, are responsible for...
Directional freeze-casting is a porous materials fabrication technique that is used to create materials with complex, three-dimensional pore structures. Particle suspensions are solidified under a thermal gradient, promoting anisotropic growth of dendrites and incorporation of particles within interdendritic space. A fully-solidified directional freeze-cast structure is composed of dendrites that are...
Herein, we present an overview of our studies of the morphology, dynamics, and formation of heterogeneous soft matter systems via the emerging technique of liquid phase transmission electron microscopy (LPTEM). This particular subset of materials, more commonly referred to as emulsions, is tremendously commercially and biologically relevant, encompassing applications in...