TY - JOUR
T1 - MPInterfaces
T2 - A Materials Project based Python tool for high-throughput computational screening of interfacial systems
AU - Mathew, Kiran
AU - Singh, Arunima K.
AU - Gabriel, Joshua J.
AU - Choudhary, Kamal
AU - Sinnott, Susan B.
AU - Davydov, Albert V.
AU - Tavazza, Francesca
AU - Hennig, Richard G.
N1 - Funding Information:
K. Mathew and R.G. Hennig are funded by the National Science Foundation under the CAREER award No. DMR-1056587 and the award No. ACI-1440547 , and by the National Institute of Standards and Technology (NIST) under award 00095176 . A. Singh is funded by the Professional Research Experience Postdoctoral Fellowship under award No. 70NANB11H012 . J.J. Gabriel, F. Tavazza and A. Davydov are funded by the Material Genome Initiative funding allocated to NIST . This research used computational resources provided by the University of Florida Research Computing ( http://researchcomputing.ufl.edu ) and the Texas Advanced Computing Center under Contracts TG-DMR050028N, TG-DMR140143, and TG-DMR150006. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant No. ACI-1053575.
Publisher Copyright:
© 2016 Elsevier B.V.
PY - 2016/9/1
Y1 - 2016/9/1
N2 - A Materials Project based open-source Python tool, MPInterfaces, has been developed to automate the high-throughput computational screening and study of interfacial systems. The framework encompasses creation and manipulation of interface structures for solid/solid hetero-structures, solid/implicit solvents systems, nanoparticle/ligands systems; and the creation of simple system-agnostic workflows for in depth computational analysis using density-functional theory or empirical energy models. The package leverages existing open-source high-throughput tools and extends their capabilities towards the understanding of interfacial systems. We describe the various algorithms and methods implemented in the package. Using several test cases, we demonstrate how the package enables high-throughput computational screening of advanced materials, directly contributing to the Materials Genome Initiative (MGI), which aims to accelerate the discovery, development, and deployment of new materials.
AB - A Materials Project based open-source Python tool, MPInterfaces, has been developed to automate the high-throughput computational screening and study of interfacial systems. The framework encompasses creation and manipulation of interface structures for solid/solid hetero-structures, solid/implicit solvents systems, nanoparticle/ligands systems; and the creation of simple system-agnostic workflows for in depth computational analysis using density-functional theory or empirical energy models. The package leverages existing open-source high-throughput tools and extends their capabilities towards the understanding of interfacial systems. We describe the various algorithms and methods implemented in the package. Using several test cases, we demonstrate how the package enables high-throughput computational screening of advanced materials, directly contributing to the Materials Genome Initiative (MGI), which aims to accelerate the discovery, development, and deployment of new materials.
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U2 - 10.1016/j.commatsci.2016.05.020
DO - 10.1016/j.commatsci.2016.05.020
M3 - Article
AN - SCOPUS:84973091533
VL - 122
SP - 183
EP - 190
JO - Computational Materials Science
JF - Computational Materials Science
SN - 0927-0256
ER -