Search

Physical Chemistry

Working Paper

Modeling the Photo-Absorption Properties of Noble Metal Nanoclusters: a Challenge for Density-Functional Theory

Priscila SEVEUR, Leïla BOUBEKEUR-LECAQUE, François MAUREL, Éric BRÉMOND

Version 2 posted 15 February 2023

325

Downloads

Theoretical and Computational Chemistry

Working Paper

DockSurf: A molecular modeling software for the prediction of protein/surface adhesion.

Florent Barbault, Eric Bremond, Julien Rey, Pierre Tuffery, François Maurel

Version 1 posted 07 April 2023

251

Downloads

Catalysis

Working Paper

Predicting Ruthenium Catalysed Hydrogenation of Esters using Machine Learning

Challenger Mishra, Niklas von Wolff, Abhinav Tripathi, Eric Brémond, Annika Preiss, Amit Kumar

Version 1 posted 11 January 2022

612

Downloads

Theoretical and Computational Chemistry

Working Paper

Predicting Redox Potentials by Graph-Based Machine Learning Methods

Linlin Jia, Éric Brémond, Larissa Zaida, Benoit Gaüzere, Vincent Tognetti, Laurent Joubert

Version 2 posted 19 March 2024

775

Downloads

Theoretical and Computational Chemistry

Working Paper

Improving the reliability of, and confidence in, DFT functional benchmarking through active learning

Javier E. Alfonso-Ramos, Carlo Adamo, Éric Brémond, Thijs Stuyver

Version 1 posted 12 December 2024

217

Downloads

Theoretical and Computational Chemistry

Working Paper

Boosting the Modeling of InfraRed and Raman Spectra of Bulk Phase Chromophores with Machine Learning

Abir KEBABSA, François MAUREL, Éric BRÉMOND

Version 2 posted 18 July 2024

283

Downloads

Theoretical and Computational Chemistry

Working Paper

Decoding the Signatures of Chromophore-Solvent Interactions in InfraRed Spectroscopy with Machine-Learning: Insights from a Hybrid Density-Functional Theory/Molecular Mechanics Dynamics Model

Abir KEBABSA, François MAUREL, Éric Brémond

Version 1 posted 28 May 2025

34

Downloads

Refine Search

7 results in Éric BRÉMOND in Authors: Éric BRÉMOND

Modeling the Photo-Absorption Properties of Noble Metal Nanoclusters: a Challenge for Density-Functional Theory

DockSurf: A molecular modeling software for the prediction of protein/surface adhesion.

Predicting Ruthenium Catalysed Hydrogenation of Esters using Machine Learning

Predicting Redox Potentials by Graph-Based Machine Learning Methods

Improving the reliability of, and confidence in, DFT functional benchmarking through active learning

Boosting the Modeling of InfraRed and Raman Spectra of Bulk Phase Chromophores with Machine Learning

Decoding the Signatures of Chromophore-Solvent Interactions in InfraRed Spectroscopy with Machine-Learning: Insights from a Hybrid Density-Functional Theory/Molecular Mechanics Dynamics Model

7 results in Authors: Éric BRÉMOND