Haikuan Dong
Materials Chemistry · 2018–2022
A researcher in the Science corpus: 3 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Materials Chemistry — 84 citations into it
Whom Haikuan Dong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Haikuan Dong's perspective
Ordered by how strongly the researchers Haikuan Dong trusts endorse each paper. Same corpus, a different order for every researcher.
- QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials (Journal of Physics: Condensed Matter)
- Fast parallel algorithms for short-range molecular dynamics
- On representing chemical environments
- Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials
- Natural Evolution Strategies
- DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics (Computer Physics Communications)
- Revisiting lattice thermal transport in PbTe: The crucial role of quartic anharmonicity (Applied Physics Letters)
- First-principles prediction of phononic thermal conductivity of silicene: A comparison with graphene
- Direct calculation of modal contributions to thermal conductivity via Green–Kubo modal analysis
- Statistical Mechanics: Theory and Molecular Simulation
Their papers
- GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations. (2022) — 395 citations
- Neuroevolution machine learning potentials: Combining high accuracy and low cost in atomistic simulations and application to heat transport (2021) — 306 citations
- Homogeneous nonequilibrium molecular dynamics method for heat transport and spectral decomposition with many-body potentials (2018) — 151 citations