Research Explorer

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Project

Interacting Particle Networks: a new deep learning approach to molecular simulation of condensed phases.

Outputs & Impact

Publications & research data ( 15 )

Explicit electrons in machine learning potentials

Maarten Cools-CeuppensJoni DambreToon Verstraelen

Nuclear quantum effects in proton transfer reactions

Aran LamaireMassimo BocusRuben GoeminneSander VandenhauteMaarten Cools-CeuppensToon VerstraelenVeronique Van Speybroeck

Physical constraints on polarization and charge transport in machine-learning potentials

Maarten Cools-CeuppensJoni DambreToon Verstraelen

Machine learning potentials for metal-organic frameworks using an incremental learning approach

Sander VandenhauteMaarten Cools-CeuppensSimon DeKeyserToon VerstraelenVeronique Van Speybroeck

A1 Journal Article in NPJ COMPUTATIONAL MATERIALS

Quantum free energy profiles for molecular proton transfers

Aran LamaireMaarten Cools-CeuppensMassimo BocusToon VerstraelenVeronique Van Speybroeck

A1 Journal Article in JOURNAL OF CHEMICAL THEORY AND COMPUTATION

The influence of nuclear quantum effects on proton hopping kinetics in the H-SSZ-13 zeolite through ab initio derived machine learning potentials

Massimo BocusRuben GoeminneAran LamaireMaarten Cools-CeuppensToon VerstraelenVeronique Van Speybroeck

Machine learning potentials for metal-organic frameworks with thermodynamic transferability

Sander VandenhauteVeronique Van SpeybroeckToon VerstraelenMaarten Cools-Ceuppens

A physically sound basis for polarization in machine-learning force fields

Maarten Cools-CeuppensJoni DambreToon Verstraelen

Physically sound long-range interactions in machine-learning potentials

Maarten Cools-CeuppensJoni DambreToon Verstraelen

Incorporating long-range interactions and polarization in machine learning potentials with explicit electrons

Maarten Cools-CeuppensToon VerstraelenJoni Dambre

Modeling electronic response properties with an explicit-electron machine learning potential

Maarten Cools-CeuppensJoni DambreToon Verstraelen

A1 Journal Article in JOURNAL OF CHEMICAL THEORY AND COMPUTATION

The eMLP : a novel machine learning potential to model electronic properties with explicit-electrons

Maarten Cools-CeuppensJoni DambreToon Verstraelen

IOData: A python library for reading, writing, and converting computational chemistry file formats and generating input files

Toon VerstraelenWilliam AdamsLeila PujalAlireza TehraniBraden D. KellyLuis MacayaFanwang MengMichael RicherRaymundo Hernandez-EsparzaXiaotian Derrick Yang et al.

A1 Journal Article in JOURNAL OF COMPUTATIONAL CHEMISTRY

Machine learning and materials science : ab initio screening to microstructure analysis

Michiel LarmuseauMaarten Cools-CeuppensMichael SluydtsToon VerstraelenStefaan Cottenier

Evaluating a linear machine learning force field for aluminium

Maarten Cools-CeuppensToon Verstraelen

Activities ( 0 )

Results

Impact narratives ( 0 )

Patents ( 0 )