Concept

Energy profile (chemistry)

Publications associées (32)

Weakly nonlinear versus semi-linear models of the nonlinear evolution of the centrifugal instability

We carry out a weakly nonlinear analysis of the centrifugal instability for a columnar vortex in a rotating fluid, and compare the results to those of the semi-linear model derived empirically by Yim et al. (J. Fluid Mech., vol. 897, 2020, A34). The asympt ...

CAMBRIDGE UNIV PRESS2023

Inferring free-energy barriers and kinetic rates from molecular dynamics via underdamped Langevin models

Sara Bonella, Fabio Pietrucci, David Daniel Girardier

Rare events include many of the most interesting transformation processes in condensed matter, from phase transitions to biomolecular conformational changes to chemical reactions. Access to the corresponding mechanisms, free-energy landscapes and kinetic r ...

Melville2023

Machine-learning the electronic density of states: electronic properties without quantum mechanics

Chiheb Ben Mahmoud

The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation ...

EPFL2023

How Robust Is the Reversible Steric Shielding Strategy for Photoswitchable Organocatalysts?

Simone Gallarati, Raimon Fabregat I De Aguilar-Amat, Veronika Juraskova, Théo Pierre Jaffrelot Inizan

A highly appealing strategy to modulate a catalyst's activity and/or selectivity in a dynamic and noninvasive way is to incorporate a photoresponsive unit into a catalytically competent molecule. However, the description of the photoinduced conformational ...

AMER CHEMICAL SOC2022

Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides

Michele Ceriotti, Alberto Fabrizio, Benjamin André René Meyer, Edgar Albert Engel, Raimon Fabregat I De Aguilar-Amat, Veronika Juraskova

The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of finite-temperature fluctuations. To reach this goal, a diverse set of methods has been pr ...

2022

Investigating Tetrel-Based Neutral Frustrated Lewis Pairs for Hydrogen Activation

Shubhajit Das

Tetrel Lewis acids are a prospective alternative to commonly employed neutral boranes in frustrated Lewis pair (FLP) chemistry. While cationic tetrylium Lewis acids, being isolobal and iso(valence)electronic, are a natural replacement to boranes, neutral t ...

AMER CHEMICAL SOC2021

The Role of Conserved Residues in the DEDDh Motif: the Proton-Transfer Mechanism of HIV-1 RNase H

RNase H is a prototypical example for two-metalion catalysis in enzymes. An RNase H activity cleaving the ribonucleic acid (RNA) backbone of a DNA/RNA hybrid is present not only in important drug targets, such as the HIV-1 reverse transcriptase, but also i ...

2021

Hamiltonian-Reservoir Replica Exchange and Machine Learning Potentials for Computational Organic Chemistry

Alberto Fabrizio, Benjamin André René Meyer, Raimon Fabregat I De Aguilar-Amat, Daniel Hollas

This work combines a machine learning potential energy function with a modular enhanced sampling scheme to obtain statistically converged thermodynamical properties of flexible medium-size organic molecules at high ab initio level. We offer a modular envir ...

AMER CHEMICAL SOC2020

Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems

Michele Ceriotti, Fabio Pietrucci

Machine learning encompasses tools and algorithms that are now becoming popular in almost all scientific and technological fields. This is true for molecular dynamics as well, where machine learning offers promises of extracting valuable information from t ...

AMER CHEMICAL SOC2020

Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems

Michele Ceriotti, Fabio Pietrucci

2020

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