7 citations · 7 across the 2 of their papers we have counts for
5 papers
Training collective variables for enhanced sampling via neural networks based discriminant analysis
Luigi Bonati
A popular way to accelerate the sampling of rare events in molecular dynamics simulations is to introduce a potential that increases the fluctuations of selected collective variabl…
Using metadynamics to build neural network potentials for reactive events: the case of urea decomposition in water
Manyi Yang, Luigi Bonati, Daniela Polino +1
The study of chemical reactions in aqueous media is very important for its implications in several fields of science, from biology to industrial processes. Modelling these reaction…
The role of water in host-guest interaction
Valerio Rizzi, Luigi Bonati, Narjes Ansari +1
One of the main applications of atomistic computer simulations is the calculation of ligand binding energies. The accuracy of these calculations depends on the force field quality…
Data-Driven Collective Variables for Enhanced Sampling
Luigi Bonati, Valerio Rizzi, Michele Parrinello
Designing an appropriate set of collective variables is crucial to the success of several enhanced sampling methods. Here we focus on how to obtain such variables from information…
Neural networks-based variationally enhanced sampling
Luigi Bonati, Yue-Yu Zhang, Michele Parrinello
Sampling complex free energy surfaces is one of the main challenges of modern atomistic simulation methods. The presence of kinetic bottlenecks in such surfaces often renders a dir…