4 papers
From Feasible to Practical: Pareto-Optimal Synthesis Planning
Friedrich Hastedt, Dongda Zhang, Antonio del Rio Chanona
Current computer-aided synthesis planning (CASP) methods often treat retrosynthesis as solved once a single feasible route is identified, focusing primarily on convergence or short…
Reinforcement learning for robust dynamic metabolic control
Sebastián Espinel-RÃos, River Walser, Dongda Zhang
Dynamic metabolic control allows key metabolic fluxes to be modulated in real time, enhancing bioprocess flexibility and expanding available optimization degrees of freedom. This i…
Constraint-Guided Symbolic Regression for Data-Efficient Kinetic Model Discovery
Miguel Ãngel de Carvalho Servia, Ilya Orson Sandoval, King Kuok +4
The industrialization of catalytic processes hinges on the availability of reliable kinetic models for design, optimization, and control. Traditional mechanistic models demand exte…
Simplest Mechanism Builder Algorithm (SiMBA): An Automated Microkinetic Model Discovery Tool
Miguel Ãngel de Carvalho Servia, King Kuok, Hii +3
Microkinetic models are key for evaluating industrial processes' efficiency and chemicals' environmental impact. Manual construction of these models is difficult and time-consuming…