252 citations · 819 across the 18 of their papers we have counts for
6 papers · 1 filter
Roadmap on Electronic Structure Codes in the Exascale Era
Vikram Gavini, Stefano Baroni, Volker Blum +38
Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state…
The NOMAD Artificial-Intelligence Toolkit: Turning materials-science data into knowledge and understanding
Luigi Sbailò, Ádám Fekete, Luca M. Ghiringhelli +1
We present the Novel-Materials-Discovery (NOMAD) Artificial-Intelligence (AI) Toolkit, a web-browser-based infrastructure for the interactive AI-based analysis of materials-science…
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…
FAIR data enabling new horizons for materials research
Matthias Scheffler, Martin Aeschlimann, Martin Albrecht +11
The prosperity and lifestyle of our society are very much governed by achievements in condensed matter physics, chemistry and materials science, because new products for sectors su…
Accelerating Materials-Space Exploration for Thermal Insulators by Mapping Materials Properties via Artificial Intelligence
Thomas A. R. Purcell, Matthias Scheffler, Luca M. Ghiringhelli +1
Reliable artificial-intelligence models have the potential to accelerate the discovery of materials with optimal properties for various applications, including superconductivity, c…
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…