Παρακολούθηση
Luigi Bonati
Luigi Bonati
Resarcher, Italian Institute of Technology, Genoa, IT
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα iit.it - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
Έτος
Ab initio phase diagram and nucleation of gallium
H Niu, L Bonati, PM Piaggi, M Parrinello
Nature communications 11 (1), 2654, 2020
1802020
Deep learning the slow modes for rare events sampling
L Bonati, GM Piccini, M Parrinello
Proceedings of the National Academy of Sciences 118 (44), e2113533118, 2021
1772021
Data-driven collective variables for enhanced sampling
L Bonati, V Rizzi, M Parrinello
The journal of physical chemistry letters 11 (8), 2998-3004, 2020
1642020
Silicon Liquid Structure and Crystal Nucleation from Ab Initio Deep Metadynamics
L Bonati, M Parrinello
Physical review letters 121 (26), 265701, 2018
1602018
Neural networks-based variationally enhanced sampling
L Bonati, YY Zhang, M Parrinello
Proceedings of the National Academy of Sciences 116 (36), 17641-17647, 2019
1362019
Using metadynamics to build neural network potentials for reactive events: the case of urea decomposition in water
M Yang, L Bonati, D Polino, M Parrinello
Catalysis Today 387, 143-149, 2022
1302022
The role of water in host-guest interaction
V Rizzi, L Bonati, N Ansari, M Parrinello
Nature Communications 12 (1), 1-7, 2021
632021
A unified framework for machine learning collective variables for enhanced sampling simulations: mlcolvar
L Bonati, E Trizio, A Rizzi, M Parrinello
The Journal of Chemical Physics 159 (1), 2023
472023
The role of dynamics in heterogeneous catalysis: Surface diffusivity and N2 decomposition on Fe(111)
L Bonati, D Polino, C Pizzolitto, P Biasi, R Eckert, S Reitmeier, R Schlögl, ...
Proceedings of the National Academy of Sciences 120 (50), e2313023120, 2023
412023
Characterizing metastable states with the help of machine learning
P Novelli, L Bonati, M Pontil, M Parrinello
Journal of Chemical Theory and Computation 18 (9), 5195-5202, 2022
232022
Unraveling the crystallization kinetics of the Ge2Sb2Te5 phase change compound with a machine-learned interatomic potential
O Abou El Kheir, L Bonati, M Parrinello, M Bernasconi
npj Computational Materials 10 (1), 33, 2024
212024
How Poisoning Is Avoided in a Step of Relevance to the Haber–Bosch Catalysis
S Tripathi, L Bonati, S Perego, M Parrinello
ACS Catalysis 14 (7), 4944-4950, 2024
152024
Deep learning path-like collective variable for enhanced sampling molecular dynamics
T Fröhlking, L Bonati, V Rizzi, FL Gervasio
The Journal of Chemical Physics 160 (17), 2024
92024
How dynamics changes ammonia cracking on iron surfaces
S Perego, L Bonati, S Tripathi, M Parrinello
ACS Catalysis 14 (19), 14652-14664, 2024
82024
Combining transition path sampling with data-driven collective variables through a reactivity-biased shooting algorithm
J Zhang, O Zhang, L Bonati, TJ Hou
Journal of Chemical Theory and Computation, 2024
72024
Transfer learning for atomistic simulations using GNNs and kernel mean embeddings
J Falk, L Bonati, P Novelli, M Parrinello, M Pontil
Advances in Neural Information Processing Systems 36, 2024
62024
Descriptor-Free Collective Variables from Geometric Graph Neural Networks
J Zhang, L Bonati, E Trizio, O Zhang, Y Kang, TJ Hou, M Parrinello
Journal of Chemical Theory and Computation 20 (24), 10787-10797, 2024
52024
Advanced simulations with PLUMED: OPES and machine learning collective variables
E Trizio, A Rizzi, PM Piaggi, M Invernizzi, L Bonati
arXiv preprint arXiv:2410.18019, 2024
42024
Iron nitride formation and decomposition during ammonia decomposition over a wustite-based bulk iron catalyst
M Purcel, S Berendts, L Bonati, S Perego, A Muller, M Lerch, M Parrinello, ...
ACS Catalysis 14 (18), 13947-13957, 2024
32024
Data-efficient modeling of catalytic reactions via enhanced sampling and on-the-fly learning of machine learning potentials
S Perego, L Bonati
32024
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Άρθρα 1–20