A5037026533- Machine Learning in Materials Science
- Electrocatalysts for Energy Conversion
- Advanced Photocatalysis Techniques
- Electronic and Structural Properties of Oxides
- Copper-based nanomaterials and applications
- X-ray Diffraction in Crystallography
- CO2 Reduction Techniques and Catalysts
- Catalytic Processes in Materials Science
- Catalysis and Oxidation Reactions
- Electrochemical Analysis and Applications
- Scientific Computing and Data Management
- Fuel Cells and Related Materials
- Computational Drug Discovery Methods
- Advanced battery technologies research
- Ionic liquids properties and applications
- Electron and X-Ray Spectroscopy Techniques
- Transition Metal Oxide Nanomaterials
- Chalcogenide Semiconductor Thin Films
- Semiconductor materials and devices
- Metal and Thin Film Mechanics
- Gas Sensing Nanomaterials and Sensors
- Spectroscopy and Chemometric Analyses
- Luminescence Properties of Advanced Materials
- Advanced X-ray and CT Imaging
- Geochemistry and Geologic Mapping
California Institute of Technology
2015-2024
nLIGHT (United States)
2021-2024
Joint Center for Artificial Photosynthesis
2013-2023
Pasadena City College
2014-2020
University of South Carolina
2016
Material Measurement Laboratory
2016
National Institute of Standards and Technology
2016
University of Maryland, College Park
2016
Lawrence Berkeley National Laboratory
2013-2015
Cornell University
2006-2013
Silicon can host a large amount of lithium, making it promising electrode for high-capacity lithium-ion batteries. Recent experiments indicate that silicon experiences plastic deformation upon Li absorption, which significantly decrease the stresses induced by lithiation and thus mitigate fracture failure electrodes. These issues become especially relevant in nanostructured electrodes with confined geometries. On basis first-principles calculations, we present study microscopic mechanism...
Advances in renewable and sustainable energy technologies critically depend on our ability to design realize materials with optimal properties. Materials discovery efforts ideally involve close coupling between prediction, synthesis characterization. The increased use of computational tools, the generation databases, advances experimental methods have substantially accelerated these activities. It is therefore an opportune time consider future prospects for by approaches. purpose this...
A study based on operando electrochemical scanning tunneling microscopy (EC-STM) has shown that a polycrystalline Cu electrode held at fixed negative potential, −0.9 V (vs SHE), in the vicinity of CO2 reduction reactions (CO2RR) 0.1 M KOH, undergoes stepwise surface reconstruction, first to Cu(111) within 30 min, and then Cu(100) after another min; no further transformations occurred establishment surface. The results may help explain Cu(100)-like behavior Cu(pc) terms CO2RR product...
The Materials Genome Initiative, a national effort to introduce new materials into the market faster and at lower cost, has made significant progress in computational simulation modeling of materials. To build on this progress, large amount experimental data for validating these models, informing more sophisticated ones, will be required. High-throughput experimentation generates volumes using combinatorial synthesis rapid measurement techniques, making it an ideal complement bring...
We present a first-principles-based formalism to provide quantitative measure of the thermodynamic instability and propensity for electrochemical stabilization, passivation, or corrosion metastable materials in aqueous media. demonstrate that this can assess relative Gibbs free energy candidate media as well their decomposition products, combining solid phases, function pH potential. On basis benchmarking against 20 stable reported literature also our experimental characterization...
Significance Combining high-throughput computation and experiment accelerates the discovery of photoelectrocatalysts for water oxidation explains origin their functionality, establishing ternary metal vanadates as a prolific class photoanode materials generation chemical fuels from sunlight.
Multimetallic nanoclusters (MMNCs) offer unique and tailorable surface chemistries that hold great potential for numerous catalytic applications. The efficient exploration of this vast chemical space necessitates an accelerated discovery pipeline supersedes traditional "trial-and-error" experimentation while guaranteeing uniform microstructures despite compositional complexity. Herein, we report the high-throughput synthesis extensive series ultrafine homogeneous alloy MMNCs, achieved by 1)...
The oxygen evolution reaction (OER) is a critical component of industrial processes such as electrowinning metals and the chlor-alkali process. It also plays central role in development renewable energy field for generation solar fuels by providing both protons electrons needed to generate H2 or reduced hydrocarbons from CO2. To improve these processes, it necessary expand fundamental understanding catalytically active species at low overpotential, which will further electrocatalysts with...
Abstract The photocatalytic conversion of the greenhouse gas CO 2 to chemical fuels such as hydrocarbons and alcohols continues be a promising technology for renewable generation energy. Major advancements have been made in improving efficiencies product selectiveness currently known reduction electrocatalysts, nonetheless, materials discovery is needed enable economically viable, industrial-scale reduction. We report here largest photocathode search date, starting with 68860 candidate...
Abstract Renewable fuel generation is essential for a low carbon footprint economy. Thus, over the last five decades, significant effort has been dedicated towards increasing performance of solar fuels generating devices. Specifically, to hydrogen efficiency photoelectrochemical cells progressed steadily its fundamental limit, and faradaic valuable products in CO 2 reduction systems increased dramatically. However, there are still numerous scientific engineering challenges that must be...
The hydrodynamics of electrochemical CO2 reduction (CO2R) systems is an insufficiently investigated area research that has broad implications on catalyst activity and selectivity. While most previous reports are limited to laminar CO2-sparged systems, herein we address a wide range via electrolyte recirculation systems. We find increased at the electrode surface results directly in changes ethylene methane Tafel slopes, demonstrating mass transport equal footing with active sites determining...
We report a new Ce-rich family of active oxygen evolution reaction (OER) catalysts composed earth abundant elements, discovered using high-throughput methods.
High-throughput experimentation provides efficient mapping of composition-property relationships, and its implementation for the discovery optical materials enables advancements in solar energy other technologies. In a high throughput pipeline, automated data processing algorithms are often required to match experimental throughput, we present an Tauc analysis algorithm estimating band gap energies from spectroscopy data. The mimics judgment expert scientist, which is demonstrated through...
High throughput electrochemical techniques are widely applied in material discovery and optimization. For many applications, the most desirable characterization requires a three-electrode cell under potentiostat control. In high screening, library is explored by either employing an array of such cells, or rastering single over library. To attain this latter capability with unprecedented throughput, we have developed highly integrated, compact scanning droplet that optimized for rapid...
Electrocatalysis of the oxygen evolution reaction is central to several energy technologies including electrolyzers, solar fuel generators, and air-breathing batteries. Strong acid electrolytes are desirable for many implementations these technologies, although deployment such device designs often hampered by lack non-precious-metal electrocatalysts, with Ir-based oxides comprising only known catalysts that exhibit stable activity at low overpotential. During our exploration Mn–Sb–O system...
Benchmarking metrics for materials discovery <italic>via</italic> sequential learning are presented, to assess the efficacy of existing algorithms and be scientific in our assessment accelerated science.
With their ability to rapidly elucidate composition-structure-property relationships, high-throughput experimental studies have revolutionized how materials are discovered, optimized, and commercialized. It is now possible synthesize characterize libraries that systematically address thousands of individual cuts fabrication parameter space. An unresolved issue remains transforming structural characterization data into phase mappings. This difficulty related the complex information present in...
Assembling the world's largest materials image and spectroscopy dataset enables training of machine learning models that learn hidden relationships in data, providing a key example data requirements to capitalize on recent advancements computer science.
Ce‐rich mixed metal oxides comprise a recently discovered class of electrocatalysts for the oxygen evolution reaction (OER). In particular, at current densities below 10 mA cm −2 , Ni 0.3 Fe 0.07 Co 0.2 Ce 0.43 O x exhibits superior activity compared to corresponding transition oxides, despite relative inactivity ceria. To elucidate enhanced and underlying catalytic mechanism, detailed structural characterization this quinary oxide electrocatalyst is reported. Transmission electron...