IIT Publications Search

Publications
2024
Faran M., Ray D., Nag S., Raucci U., Parrinello M., Bisker G.
A Stochastic Landscape Approach for Protein Folding State Classification
Journal of Chemical Theory and Computation
DOI 10.1021/acs.jctc.4c00464 Article Journal
2024
Ruiz Munevar M.J., Rizzi V., Portioli C., Vidossich P., Cao E., Parrinello M., Cancedda L., De Vivo M.
Cation Chloride Cotransporter NKCC1 Operates through a Rocking-Bundle Mechanism
Journal of the American Chemical Society
DOI 10.1021/jacs.3c10258 Article Journal
2024
Kang P., Trizio E., Parrinello M.
Computing the committor with the committor to study the transition state ensemble
Nature Computational Science, vol. 4, (no. 6), pp. 451-460
DOI 10.1038/s43588-024-00645-0 Article Journal
2024
Ray D., Parrinello M.
Data-driven classification of ligand unbinding pathways
Proceedings of the National Academy of Sciences of the United States of America, vol. 121, (no. 10)
DOI 10.1073/pnas.2313542121 Article Journal
2024
Mullender L., Rizzi A., Parrinello M., Carloni P., Mandelli D.
Effective data-driven collective variables for free energy calculations from metadynamics of paths
PNAS Nexus, vol. 3, (no. 4)
DOI 10.1093/pnasnexus/pgae159 Article Journal
2024
Mambretti F., Raucci U., Yang M., Parrinello M.
How Does Structural Disorder Impact Heterogeneous Catalysts? The Case of Ammonia Decomposition on Non-stoichiometric Lithium Imide
ACS Catalysis, vol. 14, (no. 3), pp. 1252-1256
DOI 10.1021/acscatal.3c05376 Article Journal
2024
Perego S., Bonati L., Tripathi S., Parrinello M.
How Dynamics Changes Ammonia Cracking on Iron Surfaces
ACS Catalysis, pp. 14652-14664
DOI 10.1021/acscatal.4c01920 Article Journal
2024
Tripathi S., Bonati L., Perego S., Parrinello M.
How Poisoning Is Avoided in a Step of Relevance to the Haber-Bosch Catalysis
ACS Catalysis, vol. 14, (no. 7), pp. 4944-4950
DOI 10.1021/acscatal.3c06201 Article Journal
2024
Zhang P., Gardini A.T., Xu X., Parrinello M.
Intramolecular and Water Mediated Tautomerism of Solvated Glycine
Journal of Chemical Information and Modeling, vol. 64, (no. 9), pp. 3599-3604
DOI 10.1021/acs.jcim.4c00273 Article Journal
2024
Purcel M., Berendts S., Bonati L., Perego S., Muller A., Lerch M., Parrinello M., Muhler M.
Iron Nitride Formation and Decomposition during Ammonia Decomposition over a Wustite-Based Bulk Iron Catalyst
ACS Catalysis, vol. 14, (no. 18), pp. 13947-13957
DOI 10.1021/acscatal.4c04415 Article Journal
2024
Yang M., Trizio E., Parrinello M.
Structure and polymerization of liquid sulfur across the λ-transition
Chemical Science, vol. 15, (no. 9), pp. 3382-3392
DOI 10.1039/d3sc06282a Article Journal
2024
Abou El Kheir O., Bonati L., Parrinello M., Bernasconi M.
Unraveling the crystallization kinetics of the Ge2Sb2Te5 phase change compound with a machine-learned interatomic potential
npj Computational Materials, vol. 10, (no. 1)
DOI 10.1038/s41524-024-01217-6 Article Journal
2023
Bonati L., Trizio E., Rizzi A., Parrinello M.
A unified framework for machine learning collective variables for enhanced sampling simulations: mlcolvar
Journal of Chemical Physics, vol. 159, (no. 1)
DOI 10.1063/5.0156343 Article Journal
2023
Ray D., Trizio E., Parrinello M.
Deep learning collective variables from transition path ensemble
Journal of Chemical Physics, vol. 158, (no. 20)
DOI 10.1063/5.0148872 Article Journal
2023
Rizzi A., Carloni P., Parrinello M.
Free energies at QM accuracy from force fields via multimap targeted estimation
Proceedings of the National Academy of Sciences of the United States of America, vol. 120, (no. 46)
DOI 10.1073/pnas.2304308120 Article Journal