5 papers
Correcting DFT formation energies towards experimental accuracy using foundational MLIPs and latent-feature delta-learning
Timo Reents, Marnik Bercx, Giovanni Pizzi
Crystal structure databases curated by high-throughput density functional theory calculations typically serve as the starting point for computational materials discovery efforts. T…
AIM2DAT: A Python-based Automated Ab Initio Material Modeling and Data Analysis Toolkit
Holger-Dietrich SaÃnick, Joshua Edzards, Timo Reents +1
The emergence of data-driven computational materials science offers unprecedented opportunities to explore complex material landscapes, complementing experimental research with the…
Score-based diffusion models for accurate crystal-structure inpainting and reconstruction of hydrogen positions
Timo Reents, Arianna Cantarella, Marnik Bercx +2
Generative AI models, such as score-based diffusion models, have recently advanced the field of computational materials science by enabling the generation of new materials with des…
MC3D: The Materials Cloud computational database of experimentally known stoichiometric inorganics
Sebastiaan P. Huber, Michail Minotakis, Marnik Bercx +7
DFT is a widely used method to compute properties of materials, which are often collected in databases and serve as valuable starting points for further studies. In this article, w…
Making atomistic materials calculations accessible with the AiiDAlab Quantum ESPRESSO app
Xing Wang, Edan Bainglass, Miki Bonacci +23
Despite the wide availability of density functional theory (DFT) codes, their adoption by the broader materials science community remains limited due to challenges such as software…