Description du poste
Domaine
Matériaux, physique du solide
Contrat
Stage
Intitulé de l'offre
Stage BAC+5 Simulation multi-échelle H/F
Sujet de stage
Ab initio free-energy landscape of lithiated graphite
Durée du contrat (en mois)
6
Description de l'offre
Missions :
Graphite is the reference negative-electrode material in Li-ion batteries, but its lithiation involves complex phase transitions and staging. Quantitative phase-field models require the underlying free-energy density as an input. This internship aims to compute that free-energy landscape from first principles and transfer it to continuum electrode models, with the longer-term objective of improving the prediction of fast-charging behaviour. Your project will be to build or adapt a machine-learning interatomic potential for lithiated graphite using density-functional-theory (DFT) reference calculations; sample lithiation and phase transitions using Grand-Canonical Monte Carlo coupled to molecular dynamics, including biased sampling when needed; reconstruct quantitative free-energy profiles for one or several staging transitions; and connect the atomistic results to phase-field modelling and compare with electrochemical and advanced-characterisation data. CV and cover letter to be sent to: < e-mail verwijderd om veiligheidsredenen >
Profil du candidat
Diplôme préparé : Bac+5 - Diplôme Ecole d'ingénieurs
Compétences scientifiques : atomistic simulations, statistical physics, Density Functional Theory, Molecular Dynamics, Monte Carlo, machine learning, phase field simulations
Localisation du poste
Site
Grenoble
Localisation du poste
France, Auvergne-Rhône-Alpes, Isère (38)
Ville
Grenoble
Critères candidat
Diplôme préparé
Bac+5 - Diplôme École d'ingénieurs
Demandeur
Disponibilité du poste
01/02/2027
Domaine
Matériaux, physique du solide
Contrat
Stage
Intitulé de l'offre
Stage BAC+5 Simulation multi-échelle H/F
Sujet de stage
Ab initio free-energy landscape of lithiated graphite
Durée du contrat (en mois)
6
Description de l'offre
Missions :
Graphite is the reference negative-electrode material in Li-ion batteries, but its lithiation involves complex phase transitions and staging. Quantitative phase-field models require the underlying free-energy density as an input. This internship aims to compute that free-energy landscape from first principles and transfer it to continuum electrode models, with the longer-term objective of improving the prediction of fast-charging behaviour. Your project will be to build or adapt a machine-learning interatomic potential for lithiated graphite using density-functional-theory (DFT) reference calculations; sample lithiation and phase transitions using Grand-Canonical Monte Carlo coupled to molecular dynamics, including biased sampling when needed; reconstruct quantitative free-energy profiles for one or several staging transitions; and connect the atomistic results to phase-field modelling and compare with electrochemical and advanced-characterisation data. CV and cover letter to be sent to: < e-mail verwijderd om veiligheidsredenen >
Profil du candidat
Diplôme préparé : Bac+5 - Diplôme Ecole d'ingénieurs
Compétences scientifiques : atomistic simulations, statistical physics, Density Functional Theory, Molecular Dynamics, Monte Carlo, machine learning, phase field simulations
Localisation du poste
Site
Grenoble
Localisation du poste
France, Auvergne-Rhône-Alpes, Isère (38)
Ville
Grenoble
Critères candidat
Diplôme préparé
Bac+5 - Diplôme École d'ingénieurs
Demandeur
Disponibilité du poste
01/02/2027
