Marnik Bercx

Paul Scherrer Institute — Switzerland

Materials Science · Physical Sciences

11h-index645citations48works1.92yr avg
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Research Topics

Machine Learning in Materials Science(12), X-ray Diffraction in Crystallography(10), Crystallization and Solubility Studies(9), Chalcogenide Semiconductor Thin Films(7), Experimental Learning in Engineering(7)

Publications48 total

Reply to: An explanation for the Rule of Four in Inorganic Materials
npj Computational Materials·2026Open Access
MC3D: the materials cloud computational database of experimentally known stoichiometric inorganics
Digital Discovery·2026Open Access
Massive Atomic Diversity: a compact universal dataset for atomistic machine learning
Scientific Data·2025· 2 citedOpen Access
Author response for "A Python workflow definition for computational materials design"
2025
Charting the Landscape of Bardeen-Cooper-Schrieffer Superconductors in Experimentally Known Compounds
PRX Energy·2025· 2 citedOpen Access
Massive Atomic Diversity: a compact universal dataset for atomistic machine learning
ArXiv.org·2025· 1 citedOpen Access
First-principles Hubbard parameters with automated and reproducible workflows
npj Computational Materials·2025· 6 citedOpen Access
A Python workflow definition for computational materials design
arXiv (Cornell University)·2025Open Access
Accurate and efficient protocols for high-throughput first-principles materials simulations
ArXiv.org·2025· 1 citedOpen Access
A python workflow definition for computational materials design
Digital Discovery·2025Open Access
Author Correction: The rule of four: anomalous distributions in the stoichiometries of inorganic compounds
npj Computational Materials·2024· 1 citedOpen Access
The rule of four: anomalous distributions in the stoichiometries of inorganic compounds
npj Computational Materials·2024· 10 citedOpen Access
How to verify the precision of density-functional-theory implementations via reproducible and universal workflows
Nature Reviews Physics·2023· 64 citedOpen Access
Plasmonic effects in the neutralization of slow ions at a metallic surface
Contributions to Plasma Physics·2023Open Access
The rule of four: anomalous stoichiometries of inorganic compounds
2023· 2 citedOpen Access
The rule of four: anomalous stoichiometries of inorganic compounds
arXiv (Cornell University)·2023Open Access
How to verify the precision of density-functional-theory implementations via reproducible and universal workflows
arXiv (Cornell University)·2023· 5 citedOpen Access
Virtual Computational Chemistry Teaching Laboratories—Hands-On at a Distance
Journal of Chemical Education·2021· 25 citedOpen Access
Common workflows for computing material properties using different quantum engines
npj Computational Materials·2021· 3 citedOpen Access
Virtual computational chemistry teaching laboratories – hands-on at a distance
2021· 4 citedOpen Access
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Frequent Co-authors

D. Lamoen(19), Nicola Marzari(18), Giovanni Pizzi(18), Sebastiaan P. Huber(12), Samuel Poncé(11), Carl S. Adorf(11), B. Partoens(10), Iurii Timrov(8), Christopher J. Sewell(8), Rika Kobayashi(7), N. Ole Carstensen(7), Thomas M. Soini(7), Edward Linscott(7), Francisco Ramirez(7), Leopold Talirz(7), Carolien Callaert(7), J. Hadermann(6), Patrick Shea(5), Joel B. Varley(5), Vitalie Stavila(5)