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20162023
most citedGPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations

463 citations · 864 across the 15 of their papers we have counts for

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Showing 2019 · cond-mat.mtrl-sciShow all

5 papers · 2 filters

cond-mat.mtrl-sci2019

Defects from phonons: Atomic transport by concerted motion in simple crystalline metals

Erik Fransson, Paul Erhart

Point defects play a crucial role in crystalline materials as they do not only impact the thermodynamic properties but are also central to kinetic processes. While they are necessa…

cond-mat.mtrl-sci2019

Effect of local chemistry and structure on thermal transport in doped GaAs

Ashis Kundu, Fabian Otte, Jesús Carrete +4

Using a first-principles approach, we analyze the impact of \textit{DX} centers formed by S, Se, and Te dopant atoms on the thermal conductivity of GaAs. Our results are in good ag…

cond-mat.mtrl-sci2019

Structurally driven asymmetric miscibility in the phase diagram of W-Ti

Mattias Ångqvist, J. Magnus Rahm, Leili Gharaee +1

Phase diagrams for multi-component systems represent crucial information for understanding and designing materials but are very time consuming to assess experimentally. Computation…

cond-mat.mtrl-sci2019

Efficient construction of linear models in materials modeling and applications to force constant expansions

Erik Fransson, Fredrik Eriksson, Paul Erhart

Linear models, such as force constant (FC) and cluster expansions, play a key role in physics and materials science. While they can in principle be parametrized using regression an…

cond-mat.mtrl-sci2019

icet - A Python library for constructing and sampling alloy cluster expansions

Mattias Ångqvist, William A. Muñoz, J. Magnus Rahm +5

Alloy cluster expansions (CEs) provide an accurate and computationally efficient mapping of the potential energy surface of multi-component systems that enables comprehensive sampl…