Impact Statement: The Lorentz-Equivariant Quantum Graph Neural Network (Lorentz-EQGNN) presented in this study offers a significant leap in quantum machine learning for high-energy physics (HEP) ...

Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi 214122, China ...

By combining granular activated carbon (GAC) saturated with PFAS and mineralizing agents like sodium or calcium salts, the researchers applied a high voltage to generate temperatures exceeding ...

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Researchers from the U.S. Army Research Laboratory (ARL) and Lehigh University have developed a nanostructured copper alloy that could redefine high-temperature materials for aerospace ...

NEST Lab, Department of Chemistry, College of Sciences, Shanghai University, Shanghai 200444, PR China Shenzhen Key Laboratory of Advanced Thin Films and Applications, College of Physics and ...

This paper proposes GSLTE, a graph structure learning method for MTAD ... GSLTE quantifies the direction and strength of the dependencies based on variable-lag transfer entropy which is achieved ...

SHRY (Suite for High-throughput generation of models with atomic substitutions implemented by python) is a tool for generating unique ordered structures corresponding to a given disordered structure.