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,...
Recent developments have enabled L12-strengthened Co-based superalloys, which have thepotential to surpass Ni-based superalloys as the material of choice for the hottest sections of turbine
blades due to cobalt’s 40 ºC higher melting point. The most-studied branch of Co-based
superalloys are based on the L12 phase Co3(Al,W); however, there is...
Nanomaterials present an exciting landscape of innovation at length scales below 100 nm, wherein controllable synthesis and materials metrology have led to tunable structure-property relationships and next-generation products. The disruptive field of nanotechnology is poised to capitalize upon the exotic chemistry and physics of these nanomaterials to enable more efficient...
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...
In the face of a changing climate caused by anthropomorphic release of carbon dioxide and other greenhouse gases, major governments have committed to the reduction of CO2 and other emissions over time, requiring increased reliance on forms of carbon-free renewable energy. The inherent intermittency of renewable electricity sources creates a...
The past decade has seen the rapid progress of deep learning, which becomes a game-changing technique in different data-intensive domains, with the availability of large scale data, cost-effective computing hardware and more advanced learning theory and algorithms. Despite of the rapid progress of deep learning methods in daily-life applications, such...
Thermoelectric devices utilize semiconducting n-type and p-type thermoelectric materials to convert heat into electricity. Despite their promise for deep space power generation or waste heat recovery, most high-performing thermoelectric materials reported in literature are absent in practical applications - partially due to inconsistent synthesis and poor mechanical performance. This work...
This dissertation explores ways to utilize physical parameters at the nanoscale interface to control the properties of mixed-dimensional heterojunctions (MDHJs). MDHJs combine the desirable properties of different classes of low-dimensional nanomaterials (materials that are quantum confined in at least one dimension). While MDHJs have achieved superlative performance for a variety...
Metallic conductivity and broken inversion symmetry were long thought to be contraindicated properties, under the assumption that long-range Coulombic interactions (screened by free charge carriers) were necessary for coordinated polar displacements. Within the past decade, the discovery of polar metals has prompted a rethinking of the relationship between metallicity and...
Ordered arrays of metallic nanoparticles (NPs) are a promising platform for technological applications and fundamental investigations due to their ability to excite surface lattice resonances (SLRs). SLRs can support extremely high local electric fields that have been used to realize exotic physical phenomena. The open cavity architecture lends itself to...