AI-PRE: AI for Explainable Roundtrip Multiscale Emulsion Polymerization Processes
Sabine Beuermann (TU Clausthal), Jelena Fiosina (TU Clausthal)
Kernel Methods for Confidence Regions in Optimal Experimental Design and Parameter Estimation
Erik Esche (TU Berlin), Michael Bortz (FHI f. Techno- und Wirtschaftsmathematik (ITWM))
Generalizing Automated Neural Flowsheet Synthesis to Novel Chemical Systems
Jakob Burger (TUM), Dominik Grimm (Weihenstephan-Triesdorf HSWT)
Translating Thermodynamic Knowledge to Computers
Hans Hasse (RPTU), Sophie Fellenz (RPTU), Heike Leitte (RPTU)
Sample-efficient physics-informed reinforcement learning for liquid-liquid separation process control
Manuel Dahmen (FZ Juelich), Andreas Jupke (RWTH Aachen)
Machine learning for design of chemical engineering unit operations
Pascal Friederich (KIT), Alexander Stroh (KIT), Roland Dittmeyer (KIT)
Generative graph machine learning for integrated molecule and process design
Martin Grohe (RWTH Aachen), Alexander Mitsos (RWTH Aachen)
Machine Learning and Optimal Experimental Design for Thermodynamic Property Modeling
Roland Herzog (Universitaet Heidelberg), Markus Richter (TU Chemnitz)
Safe Reinforcement Learning under Uncertainty for Hybrid Separation Processes with Recycles in Chemical Engineering
Jens-Uwe Repke (TU Berlin), Sergio Lucia Gil (TU Dortmund)
Improving Simulations of Large-Scale Dense Particle-Laden Flows with Machine Learning: A Genetic Programming Approach
Sanaz Mostaghim (Otto von Guericke University Magdeburg), Berend van Wachem (Otto von Guericke University Magdeburg)
Machine Learning for the Design and Control ofPower2X Processes with Application to MethanolSynthesis (mlP2X)
Achim Kienle (Otto von Guericke University Magdeburg), Sebastian Sager (Otto von Guericke University Magdeburg), Ronny Zimmermann (Max Planck Institute for Dynamics of Complex Techncial Systems Magdeburg)
Autoregressive Deep Learning for Accelerated Multiscale Simulation of Electrochemical Flow Reactors
Fridolin Röder (Universität Bayreuth), Johannes Margraf (Universität Bayreuth)
Learning Groups for Group Contribution Methods (LEGO)
Fabian Jirasek (RPTU), Sophie Fellenz (RPTU), Marius Kloft (RPTU)
Collaborating projects:
Artificial intelligence on linked chemical engineering data
Artur Schweidtmann (TU Delft)
Molecular Descriptors in Matrix Completion Methods
Fabian Jirasek (RPTU), Hans Hasse (RPTU), Heike Leitte (RPTU)
