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cond-mat.mtrl-sci2020

The Tin Pest Problem as a Test of Density Functionals Using High-Throughput Calculations

Michael J. Mehl, Mateo Ronquillo, David Hicks +7

At ambient pressure tin transforms from its ground-state semi-metal -Sn (diamond structure) phase to the compact metallic -Sn phase at 13C (286K). There may be a furt…

cond-mat.mtrl-sci2019

Predicting Superhard Materials via a Machine Learning Informed Evolutionary Structure Search

Patrick Avery, Xiaoyu Wang, Davide M. Proserpio +5

Good agreement was found between experimental Vickers hardnesses, , of a wide range of materials and those calculated by three macroscopic hardness models that employ t…

cond-mat.mtrl-sci2018

The AFLOW Library of Crystallographic Prototypes: Part 2

David Hicks, Michael J. Mehl, Eric Gossett +5

Materials discovery via high-throughput methods relies on the availability of structural prototypes, which are generally decorated with varying combinations of elements to produce…

cond-mat.mtrl-sci2018

AFLOW-CHULL: Cloud-oriented platform for autonomous phase stability analysis

Corey Oses, Eric Gossett, David Hicks +10

prediction of phase stability of materials is a challenging practice, requiring knowledge of all energetically-competing structures at formation conditions. Lar…

cond-mat.mtrl-sci2018

AFLOW-SYM: Platform for the complete, automatic and self-consistent symmetry analysis of crystals

David Hicks, Corey Oses, Eric Gossett +6

Determination of the symmetry profile of structures is a persistent challenge in materials science. Results often vary amongst standard packages, hindering autonomous materials dev…

cond-mat.mtrl-sci2017

The AFLOW Fleet for Materials Discovery

Cormac Toher, Corey Oses, David Hicks +48

The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the d…