Fast-Tracking Solar Cell Materials Discovery Using Automation, Physics Modeling, and Bayesian Machine Learning

Authors

Joseph Chakar (ORCID: https://orcid.org/0000-0001-5964-3383)
Yvan Bonnassieux (ORCID: https://orcid.org/0000-0003-4413-2067)
Jean‐Paul Kleider (ORCID: https://orcid.org/0000-0003-4388-6326)
Jean‐François Guillemoles (ORCID: https://orcid.org/0000-0003-0114-8624)
Philip Schulz (ORCID: https://orcid.org/0000-0002-8177-0108)
Stéfania Cacovich (ORCID: https://orcid.org/0000-0002-6402-4816)
J.P. Connolly (ORCID: https://orcid.org/0000-0003-0342-1719)
Jean-Baptiste Puel

Institutions

Institut de France (FR)
École Polytechnique (FR)
Institut Pprime (FR)
Laboratoire de Génie Électrique et Électronique de Paris (FR)
Laboratoire de Physique des Interfaces et des Couches Minces (FR)
Électricité de France (France) (FR)
Institut Polytechnique de Paris (FR)
Institut Photovoltaïque d’Île-de-France (FR)

Publication Details

Journal: SPIRE - Sciences Po Institutional REpository
Published: 2025-09-15
Primary Topic: Machine Learning in Materials Science
Type: article
Field-Weighted Citation Impact: 0.00

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article

Fast-Tracking Solar Cell Materials Discovery Using Automation, Physics Modeling, and Bayesian Machine Learning

Joseph Chakar, Yvan Bonnassieux, Jean‐Paul Kleider, Jean‐François Guillemoles et al.

Sep 15, 2025

SPIRE - Sciences Po Institutional REpository

Machine Learning in Materials Science

article

Fast-Tracking Solar Cell Materials Discovery Using Automation, Physics Modeling, and Bayesian Machine Learning

Joseph Chakar, Yvan Bonnassieux, Jean‐Paul Kleider, Jean‐François Guillemoles, Philip Schulz, Stéfania Cacovich, J.P. Connolly, Jean-Baptiste Puel

September 15, 2025article en

Abstract

No abstract available for this paper.

SPIRE - Sciences Po Institutional REpository

Institut de France (FR), École Polytechnique (FR), Institut Pprime (FR), Laboratoire de Génie Électrique et Électronique de Paris (FR), Laboratoire de Physique des Interfaces et des Couches Minces (FR), Électricité de France (France) (FR), Institut Polytechnique de Paris (FR), Institut Photovoltaïque d’Île-de-France (FR)

Openalex Percentile: Top 69%

Machine Learning in Materials Science

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