Sebastian Schmitt
I'm a postdoctoral researcher at Laboratory of Engineering Thermodynamics (LTD) of the University of Kaiserslautern (RPTU), Germany. My work focuses on hybrid thermodynamic models that combine physical knowledge with machine learning.
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Session
We present MLThermoProperties.jl, a Julia package that provides a variety of state-of-the-art thermodynamic models that combine modern machine learning methods with physical knowledge. These hybrid models obey hard physical constraints while being more accurate and applicable to a wider scope of substances than established models. MLThermoProperties.jl is built upon the Clapeyron.jl package, leveraging its rich thermodynamic solver ecosystem. The MLThermoProperties.jl models significantly improve molecular property prediction in various applications in science and engineering, e.g., chemical process engineering. Exemplary applications will be demonstrated in the talk by coupling MLThermoProperties.jl with Julia's rich ecosystem for scientific modelling and simulation.