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at EM2C lab, which consists in introducing virtual species and reactions whose thermodynamic and chemical properties are optimized by machine learning algorithms to retrieve properties of reference flames
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. This last aspect is particularly developed using machine learning methods, in which the team has recognized experience. These methods are deployed on a wide variety of study sites and projects, including
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.2021.118920 [3] Trends in Chemistry, 6, (2024), doi.org/10.1016/j.trechm.2023.12.001 [4] Machine Learning for Advanced Functional Materials, Springer, (2023); doi.org/10.1007/978-981-99-0393-1_8 Funding
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