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Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
American Chemical Society | 2019| -
Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
Free accessArXiv | 2018| -
Learning Properties of Ordered and Disordered Materials from Multi-fidelity Data
Free accessArXiv | 2020| -
Learning properties of ordered and disordered materials from multi-fidelity data
Springer Verlag | 2021| -
ELECTROCHEMICALLY-INDUCED AMORPHOUS TO ROCK SALT PHASE TRANSITIONS IN NIOBIUM OXIDE ELECTRODE FOR LITHIUM-ION BATTERIES
Free accessEuropean Patent Office | 2022| -
MACHINE LEARNING ENABLED TECHNIQUES FOR MATERIAL DESIGN AND ULTRA-INCOMPRESSIBLE TERNARY COMPOUNDS DERIVED THEREWITH
Free accessEuropean Patent Office | 2022| -
Conductive Binder for Si Anode with Boosted Charge Transfer Capability via n‑Type Doping
American Chemical Society | 2018| -
Inorganic Aromaticity of Mn6‑Ring Cluster in Layered Li(Ni0.5Mn0.5)O2
American Chemical Society | 2018| -
Complex Strengthening Mechanisms in the NbMoTaW Multi-Principal Element Alloy
Free accessArXiv | 2019| -
DEFECT-DRIVEN NIOBIUM OXIDE ELECTRODE FOR LITHIUM-ION BATTERIES
British Library Conference Proceedings | 2019| -
Few-Layer Fe3(PO4)2·8H2O: Novel H‑Bonded 2D Material and Its Abnormal Electronic Properties
American Chemical Society | 2016| -
A Performance and Cost Assessment of Machine Learning Interatomic Potentials
Free accessArXiv | 2019| -
Performance and Cost Assessment of Machine Learning Interatomic Potentials
American Chemical Society | 2020| -
Atomic-scale origin of the low grain-boundary resistance in perovskite solid electrolytes
Free accessArXiv | 2022|
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