49 citations · 55 across the 8 of their papers we have counts for
9 papers
Mechanism-Dependent Descriptors Enable Predictive Design of Oxygen Capacity in Perovskite Oxides
Shuiping Gong, Yi Li, Jie Su +9
Perovskite oxides can reversibly accommodate substantial changes in oxygen stoichiometry, making them attractive for clean-energy technologies including chemical looping and oxygen…
Autonomous Optimization of Complex Oxides for Thermochemical Fuel Production
Shuiping Gong, Mingcheng Li, Han Hao +13
Two-step thermochemical fuel production, including H2O and CO2 splitting, offers a promising route to sustainable fuel manufacturing, with performance governed by redox-active oxid…
Predicting Interface Structure using the Minima Hopping Method with a Machine Learning Interatomic Potential
Chang-Ti Chou, Menghang Wang, Chao Yang +4
Predicting atomic-scale interfacial structures remains a central challenge in materials science due to their structural complexity and the difficulty of direct comparison between c…
Lattice-to-Total Thermal Conductivity Ratio: A Phonon-Glass Electron-Crystal Descriptor for Data-Driven Thermoelectric Design
Yifan Sun, Zhi Li, Tetsuya Imamura +3
Thermoelectrics (TEs) are promising candidates for energy harvesting with performance quantified by figure of merit, . To accelerate the discovery of high- materials, effor…
Origin of Glass-like Thermal Conductivity in Crystalline TlAgTe
Shantanu Semwal, Yi Xia, Chris Wolverton +1
Ordered crystalline compounds exhibiting ultralow and glass-like thermal conductivity are both fundamentally and technologically important, where phonon quasi-particles dominate th…
Interpretable Nanoporous Materials Design with Symmetry-Aware Networks
Zhenhao Zhou, Salman Bin Kashif, Jin-Hu Dou +4
Reticular frameworks hold promise for diverse sustainable applications, yet their immense chemical space limits efficient and systematic design. While machine learning provides a c…
High-throughput computational framework for lattice dynamics and thermal transport including high-order anharmonicity: an application to cubic and tetragonal inorganic compounds
Zhi Li, Huiju Lee, Chris Wolverton +1
Accurately predicting lattice thermal conductivity (kL) from first principles remains a challenge in identifying materials with extreme thermal behavior. While modern lattice dynam…
Accelerating High-Throughput Phonon Calculations via Machine Learning Universal Potentials
Huiju Lee, Vinay I. Hegde, Chris Wolverton +1
Phonons play a critical role in determining various material properties, but conventional methods for phonon calculations are computationally intensive, limiting their broad applic…
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
Matthew L. Evans, Johan Bergsma, Andrius Merkys +56
The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enh…