Automated Synthesis of Steady-State Continuous Processes using Reinforcement Learning. - Quirin Göttl; Dominik G. Grimm; Jakob Burger (CoRR, 2021)

Policy-Based Self-Competition for Planning Problems. - Jonathan Pirnay; Quirin Göttl; Jakob Burger; Dominik Gerhard Grimm (ICLR, 2023)

Deep reinforcement learning uncovers processes for separating azeotropic mixtures without prior knowledge. - Quirin Göttl; Jonathan Pirnay; Jakob Burger; Dominik G. Grimm (CoRR, 2023)

Convex Envelope Method for determining liquid multi-phase equilibria in systems with arbitrary number of components. - Quirin Göttl; Jonathan Pirnay; Dominik G. Grimm; Jakob Burger (Comput. Chem. Eng., 2023)

Automated Design in Hybrid Action Spaces by Reinforcement Learning and Differential Evolution. - Quirin Göttl; Haris Asif; Alexander Mattick; Robert Marzilger; Axel Plinge (KI, 2024)

Deep reinforcement learning enables conceptual design of processes for separating azeotropic mixtures without prior knowledge. - Quirin Göttl; Jonathan Pirnay; Jakob Burger; Dominik G. Grimm (Comput. Chem. Eng., 2025)