Keke Song

Materials Chemistry · with Wang · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Keke Song trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. J. Behler

Papers from Keke Song's perspective

Ordered by how strongly the researchers Keke Song trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Fast parallel algorithms for short-range molecular dynamics
  2. On representing chemical environments
  3. Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials
  4. DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics (Computer Physics Communications)
  5. Natural Evolution Strategies
  6. QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials (Journal of Physics: Condensed Matter)
  7. Direct calculation of modal contributions to thermal conductivity via Green–Kubo modal analysis
  8. The Hiphive Package for the Extraction of High‐Order Force Constants by Machine Learning (Advanced Theory and Simulations)
  9. Machine learning for interatomic potential models. (Journal of Chemical Physics)
  10. Revisiting lattice thermal transport in PbTe: The crucial role of quartic anharmonicity (Applied Physics Letters)

Their papers