938 citations · 2.1k across the 25 of their papers we have counts for
26 papers
Pseudo-hybrid density functional ACBN0 for Hubbard correction in a numeric atom-centered orbital basis
Svetlana A. Artiukova, Ilia M. Odud, Sergey V. Levchenko
We present a formulation and implementation of the Agapito-Curtarolo-Buongiorno Nardelli (ACBN0) pseudo-hybrid density functional in a numeric atom-centered orbital basis. The meth…
Combining genetic algorithm and compressed sensing for features and operators selection in symbolic regression
Aliaksei Mazheika, Sergey V. Levchenko, Luca M. Ghiringhelli
Symbolic-inference methods have recently found a broad application in materials science. In particular, the Sure-Independence Screening and Sparsifying Operator (SISSO) performs sy…
Material Hardness Descriptor Derived by Symbolic Regression
Christian Tantardini, Hayk A. Zakaryan, Zhong-Kang Han +4
Hardness is a materials' property with implications in several industrial fields, including oil and gas, manufacturing, and others. However, the relationship between this macroscal…
A benchmark of first-principles methods for accurate prediction of semiconductor band gaps
Saeid Abedi, Mehdi Tarighi Ahmadpour, Samira Baninajarian +4
The band gap is an important parameter of semiconductor materials that influences several functional properties, in particular optical properties. However, a fast and reliable firs…
Shared Metadata for Data-Centric Materials Science
Luca M. Ghiringhelli, Carsten Baldauf, Tristan Bereau +32
The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps r…
Hierarchical symbolic regression for identifying key physical parameters correlated with bulk properties of perovskites
Lucas Foppa, Thomas A. R. Purcell, Sergey V. Levchenko +2
Symbolic regression identifies key physical parameters describing materials properties by uncovering correlations as nonlinear analytical expressions. However, the pool of expressi…