Machine learning interatomic potentials for heterogeneous catalysis
Atomistic modeling can provide valuable insights into the design of novel heterogeneous
catalysts as needed nowadays in the areas of, eg, chemistry, materials science, and biology …
catalysts as needed nowadays in the areas of, eg, chemistry, materials science, and biology …
Accelerating materials discovery for electrocatalytic water oxidation via center-environment deep learning in spinel oxides
Y Li, X Zhang, T Li, Y Chen, Y Liu… - Journal of Materials …, 2024 - pubs.rsc.org
Identifying efficient electrocatalysts for the oxygen evolution reaction (OER) is vital for
sustainable energy. This study focuses on efficient spinel OER electrocatalysts. We utilize a …
sustainable energy. This study focuses on efficient spinel OER electrocatalysts. We utilize a …
Efficient simulations of charge density waves in the transition metal Dichalcogenide TiSe2
Charge density waves (CDWs) in transition metal dichalcogenides are the subject of
growing scientific interest due to their rich interplay with exotic phases of matter and their …
growing scientific interest due to their rich interplay with exotic phases of matter and their …
Phonon transport governed by intrinsic scattering in short-period AlN/GaN superlattices
We employ density functional theory based phonon transport methods to provide a rigorous
understanding of the nature of thermal transport in coherent short-period AlN/GaN …
understanding of the nature of thermal transport in coherent short-period AlN/GaN …