7 papers
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…
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…
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…
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…
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…
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…