activity
19922026
most citedAFLOW: An automatic framework for high-throughput materials discovery

1.6k citations · 5k across the 41 of their papers we have counts for

collaborators

42 papers

cond-mat.mtrl-sci2026

The AFLOW Library of Crystallographic Prototypes: Part 5

Nicholas H. Anderson, Michael J. Mehl, Hagen Eckert +3

The AFLOW library of crystallographic prototypes has been updated to incorporate an additional 344 entries, which now reaches 2,127 prototypes. ICSD and CCDC numbers have been adde…

cond-mat.mtrl-sci2025★ 10 cited

AFLOW4: heading toward disorder

Simon Divilov, Hagen Eckert, Scott D. Thiel +10

AFLOW4 is the latest iteration of the AFLOW toolkit, specifically tailored to study high-entropy disordered materials. This upgrade includes innovative features like the Soliquidy…

cond-mat.mtrl-sci2024★ 20 cited

The AFLOW Library of Crystallographic Prototypes: Part 4

Hagen Eckert, Simon Divilov, Michael J. Mehl +5

The AFLOW Library of Crystallographic Prototypes has been updated to include an additional 683 entries, which now reaches 1,783 prototypes. We have also made some changes to the pr…

cond-mat.mtrl-sci2022★ 46 cited

aflow++: a C++ framework for autonomous materials design

C. Oses, M. Esters, D. Hicks +17

The realization of novel technological opportunities given by computational and autonomous materials design requires efficient and effective frameworks. For more than two decades,…

cond-mat.mtrl-sci2022★ 65 cited

aflow.org: A Web Ecosystem of Databases, Software and Tools

Marco Esters, Corey Oses, Simon Divilov +10

To enable materials databases supporting computational and experimental research, it is critical to develop platforms that both facilitate access to the data and provide the tools…

cond-mat.mtrl-sci2021★ 17 cited

Automated coordination corrected enthalpies with AFLOW-CCE

R. Friedrich, M. Esters, C. Oses +6

The computational design of materials with ionic bonds poses a critical challenge to thermodynamic modeling since density functional theory yields inaccurate predictions of their f…