IIT Publications Search

Publications
2026
Tripathi S., Bonati L., Perego S., Parrinello M.
Nitrogen adsorption and dissociation on flat and stepped Fe(110) surfaces
Journal of Catalysis, vol. 454
DOI 10.1016/j.jcat.2025.116576
Article Journal
2025
Das S., Raucci U., Trizio E., Kang P., Neves R.P., Ramos M.J., Parrinello M.
A Machine Learning-Driven, Probability-Based Approach to Enzyme Catalysis
ACS Catalysis, vol. 15, (no. 11), pp. 9785-9792
DOI 10.1021/acscatal.5c02431
Article Journal
2025
Raucci U.
Capturing Excited State Proton Transfer Dynamics with Reactive Machine Learning Potentials
Journal of Physical Chemistry Letters, pp. 4900-4906
DOI 10.1021/acs.jpclett.5c00688
2025
Visigalli A., Trizio E., Bonati L., Vidossich P., Parrinello M., De Vivo M.
Coordinated Residue Motions at the Enzyme-Substrate Interface Promote DNA Translocation in Polymerases
Journal of the American Chemical Society
DOI 10.1021/jacs.5c05888
Article Journal
2025
Parrinello M., Greed S.
Discussions with a dignitary of molecular dynamics
Nature Reviews Chemistry, vol. 9, (no. 9)
DOI 10.1038/s41570-025-00754-y
Note Journal
2025
Tian X., Tosello Gardini A., Raucci U., Xiao H., Zhuo Y., Parrinello M.
Electrochemical potential-driven water dynamics control CO2 electroreduction at the Ag/H2O interface
Nature Communications, vol. 16, (no. 1)
DOI 10.1038/s41467-025-65630-1
2025
Zhu K., Trizio E., Zhang J., Hu R., Jiang L., Hou T., Bonati L.
Enhanced Sampling in the Age of Machine Learning: Algorithms and Applications
Chemical Reviews
DOI 10.1021/acs.chemrev.5c00700
2025
Trizio E., Kang P., Parrinello M.
Everything everywhere all at once: a probability-based enhanced sampling approach to rare events
Nature Computational Science
DOI 10.1038/s43588-025-00799-5
2025
Novelli P., Meanti G., Buigues P.J., Rosasco L., Parrinello M., Pontil M., Bonati L.
Fast and Fourier features for transfer learning of interatomic potentials
npj Computational Materials, vol. 11, (no. 1)
DOI 10.1038/s41524-025-01779-z
2025
Novelli P., Meanti G., Buigues P., Rosasco L., Parrinello M., Pontil M., Bonati L.
Fast and Fourier Features for Transfer Learning of Interatomic Potentials
arXiv
DOI 10.48550/arXiv.2505.05652
2025
Tokita A.M., Devergne T., Saitta A.M., Behler J.
Free energy profiles for chemical reactions in solution from high-dimensional neural network potentials: The case of the Strecker synthesis
Journal of Chemical Physics, vol. 162, (no. 17)
DOI 10.1063/5.0268948
Article Journal
2025
Bonati L., Novelli P., Rossi A.
From trial-and-error to intelligent workflows: machine learning and simulations for scalable 2D material synthesis
2D Materials
DOI 10.1088/2053-1583/ae2692
Article Journal
2025
Tosello Gardini A., Raucci U., Parrinello M.
Machine learning-driven molecular dynamics unveils a bulk phase transformation driving ammonia synthesis on barium hydride
Nature Communications, vol. 16, (no. 1)
DOI 10.1038/s41467-025-57688-8
Article Journal
2025
Yang H., Raucci U., Iyer S., Hasan G., Golin Almeida T., Barua S., Savolainen A., Kangasluoma J., Rissanen M., Vehkamaki H., Kurten T.
Molecular dynamics-guided reaction discovery reveals endoperoxide-to-alkoxy radical isomerization as key branching point in α-pinene ozonolysis
Nature Communications, vol. 16, (no. 1)
DOI 10.1038/s41467-025-55985-w
2025
Perego S., Purcel M., Baum Y., Chen S., Muller A.S., Parrinello M., Behrens M., Muhler M., Bonati L.
No Time for Nitrides: How Cobalt Alloying Promotes Iron Catalysts for Ammonia Decomposition
ACS Catalysis, vol. 15, pp. 16690-16702
DOI 10.1021/acscatal.5c04795
Article Journal
2025
Tribello G.A., Bonomi M., Bussi G., Camilloni C., Armstrong B.I., Arsiccio A., Aureli S., Ballabio F., Bernetti M., Bonati L., Brookes S.G.H., Brotzakis Z.F., Capelli R., Ceriotti M., Chan K.-T., Cossio P., Dasetty S., Donadio D., Ensing B., Ferguson A.L., Fraux G., Gale J.D., Gervasio F.L., Giorgino T., Herringer N.S.M., Hocky G.M., Hoff S.E., Invernizzi M., Languin-Cattoen O., Leone V., Limongelli V., Lopez-Acevedo O., Marinelli F., Febrer Martinez P., Masetti M., Mehdi S., Michaelides A., Murtada M.H., Parrinello M., Piaggi P.M., Pietropaolo A., Pietrucci F., Pipolo S., Pritchard C., Raiteri P., Raniolo S., Rapetti D., Rizzi V., Rydzewski J., Salvalaglio M., Schran C., Seal A., Shayesteh Zadeh A., Silva T.F.D., Spiwok V., Stirnemann G., Sucerquia D., Tiwary P., Valsson O., Vendruscolo M., Voth G.A., White A.D., Wu J.
PLUMED Tutorials: A collaborative, community-driven learning ecosystem
Journal of Chemical Physics, vol. 162, (no. 9)
DOI 10.1063/5.0251501
2025
Cigrang L.L.E., Curchod B.F.E., Ingle R.A., Kelly A., Mannouch J.R., Accomasso D., Alijah A., Barbatti M., Chebbi W., Doslic N., Eklund E.C., Fernandez-Alberti S., Freibert A., Gonzalez L., Granucci G., Hernandez F.J., Hernandez-Rodriguez J., Jain A., Janos J., Kassal I., Kirrander A., Lan Z., Larsson H.R., Lauvergnat D., Le De B., Lee Y., Maitra N.T., Min S.K., Pelaez D., Picconi D., Qiu Z., Raucci U., Robertson P., Sangiogo Gil E., Sapunar M., Schurger P., Sinnott P., Tretiak S., Tikku A., Vindel-Zandbergen P., Worth G.A., Agostini F., Gomez S., Ibele L.M., Prlj A.
Roadmap for Molecular Benchmarks in Nonadiabatic Dynamics
Journal of Physical Chemistry A, vol. 129, (no. 31), pp. 7023-7050
DOI 10.1021/acs.jpca.5c02171
Review Journal
2025
Turri G., Bonati L., Zhu K., Pontil M., Novelli P.
Self-Supervised Evolution Operator Learning for High-Dimensional Dynamical Systems
arXiv
DOI 10.48550/arXiv.2505.18671
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