Séminaire Simon PONTON 31.03.2026

Simon Ponton

Chargé de recherche CNRS – Section 12

UGA, Grenoble-INP, SIMaP

Development of the combinatorial approach for the CVD thin film deposition process: Multiphysics coupling and machine learning

Abstract

The combinatorial approach applied to chemical vapor deposition processes integrating high-throughput experiments, computational simulations, and machine learning seems to emerge as a transformative paradigm to accelerate the discovery of novel materials. Through systematic gradient explorations, large-scale datasets can be generated to deepen our understanding of process-structure-property relationships. Machine learning models, trained on experimental and simulated data enable rapid prediction and identification of high-potential solutions, thereby guiding future experiments and simulations. The synergy not only reduces the time or cost associated with material discovery but also unlocks access to previously unexplored regions of the materials space.

Short Bio/CVMy academic journey began in Grenoble, where I studied chemistry before developing a keen interest in materials sciences, particularly nanostructures and their processing. Driven by a desire to unravel the underlying mechanisms, I started my PhD in Toulouse, between the CIRIMAT and LGC. There, I expanded my expertise in chemical engineering and Multiphysics simulation. After nearly two years of postdoctoral research, I sought to broaden my research perspective and joined Polytechnique Montréal in the chemical engineering section for two postdoctoral positions that led to an associate professor role. However, my longing for French cheese proved irresistible, I successfully secured a position at CNRS and joined SIMaP in February 2026.