Marzari, Nicola

Advanced capabilities for materials modelling with Q uantum ESPRESSO

Giannozzi, P., Andreussi, O., Brumme, T., Bunau, O., Buongiorno Nardelli, M., Calandra, M., Car, R., Cavazzoni, C., Ceresoli, D., Cococcioni, M., et al. (2017) · Journal of Physics: Condensed Matter

Advanced Chemical Physics StudiesMachine Learning in Materials Science

Cited by 8,361

Maximally localized Wannier functions: Theory and applications

Marzari, N., Mostofi, A. A., Yates, J. R., Souza, I., & Vanderbilt, D. (2012) · Reviews of Modern Physics

Advanced Chemical Physics StudiesTopological Materials and Phenomena

Cited by 3,283

Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds

Mounet, N., Gibertini, M., Schwaller, P., Campi, D., Merkys, A., Marrazzo, A., Sohier, T., Castelli, I. E., Cepellotti, A., Pizzi, G., et al. (2018) · Nature Nanotechnology

Machine Learning in Materials Science2D Materials and Applications

Cited by 1,863

Reproducibility in density functional theory calculations of solids

Lejaeghere, K., Bihlmayer, G., Björkman, T., Blaha, P., Blügel, S., Blum, V., Caliste, D., Castelli, I. E., Clark, S. J., Dal Corso, A., et al. (2016) · Science

Advanced Chemical Physics StudiesMachine Learning in Materials Science

Cited by 1,649

Thermal Contraction and Disordering of the Al(110) Surface

Marzari, N., Vanderbilt, D., De Vita, A., & Payne, M. C. (1999) · Physical Review Letters

Thermodynamic and Structural Properties of Metals and AlloysSurface and Thin Film Phenomena

Cited by 1,255

Precision and efficiency in solid-state pseudopotential calculations

Prandini, G., Marrazzo, A., Castelli, I. E., Mounet, N., & Marzari, N. (2018) · npj Computational Materials

Machine Learning in Materials ScienceAdvanced Chemical Physics Studies

Cited by 917

Highly Active and Stable Iridium Pyrochlores for Oxygen Evolution Reaction

Lebedev, D., Povia, M., Waltar, K., Abdala, P. M., Castelli, I. E., Fabbri, E., Blanco, M. V., Fedorov, A., Copéret, C., Marzari, N., et al. (2017) · Chemistry of Materials

Electrocatalysts for Energy ConversionCatalytic Processes in Materials Science

Cited by 228

How to verify the precision of density-functional-theory implementations via reproducible and universal workflows

Bosoni, E., Beal, L., Bercx, M., Blaha, P., Blügel, S., Bröder, J., Callsen, M., Cottenier, S., Degomme, A., Dikan, V., et al. (2023) · Nature Reviews Physics

Advanced Chemical Physics StudiesMachine Learning in Materials Science

Cited by 89

Thermoelastic properties ofα-iron from first-principles

Dragoni, D., Ceresoli, D., & Marzari, N. (2015) · Physical Review B

Thermodynamic and Structural Properties of Metals and AlloysAdvanced Chemical Physics Studies

Cited by 48