156 citations · 336 across the 15 of their papers we have counts for
7 papers · 1 filter
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…
Massive Atomic Diversity: a compact universal dataset for atomistic machine learning
Arslan Mazitov, Sofiia Chorna, Guillaume Fraux +4
The development of machine-learning models for atomic-scale simulations has benefited tremendously from the large databases of materials and molecular properties computed in the pa…
A Python workflow definition for computational materials design
Jan Janssen, Janine George, Julian Geiger +8
Numerous Workflow Management Systems (WfMS) have been developed in the field of computational materials science with different workflow formats, hindering interoperability and repr…
Accurate and efficient protocols for high-throughput first-principles materials simulations
Gabriel de Miranda Nascimento, Flaviano José dos Santos, Marnik Bercx +3
Advancements in theoretical and algorithmic approaches, workflow engines, and an ever-increasing computational power have enabled a novel paradigm for materials discovery through f…
First-principles Hubbard parameters with automated and reproducible workflows
Lorenzo Bastonero, Cristiano Malica, Eric Macke +4
We introduce an automated, flexible framework (aiida-hubbard) to self-consistently calculate Hubbard and parameters from first-principles. By leveraging density-functional…
Charting the landscape of Bardeen-Cooper-Schrieffer superconductors in experimentally known compounds
Marnik Bercx, Samuel Poncé, Yiming Zhang +8
We perform a high-throughput computational search for novel phonon-mediated superconductors, starting from the Materials Cloud 3-dimensional structure database of experimentally kn…