Nanoseminar in Chemistry and Materials

IN PERSON EVENT - ENTER HERE to attend.

By Dr. L. Ricardez-Sandoval—Department of Chemical Engineering at the University of Waterloo, Ontario, Canada.

Abstract: This talk will present the recent efforts made by our group to innovate the fields of catalyst design for CO₂ conversion and chemical process flowsheet design using advanced active learning methods. In the first part of the talk, potential catalysts for CO₂ conversion using CeO₂-based materials for Reverse Water Gas Shift (RWGS) reaction will be presented. Our study combines experimental tests, density functional theory (DFT) calculations and active learning methods to discover new insights and avenues for catalysis development. The second part of the talk will present a novel reinforcement learning framework to perform chemical process flowsheet design that does not require the a priori specification of a superstructure/flowsheet thus promoting exploration and potential discovery of new chemical flowsheets. A case study that links our framework with Aspen Plus will be presented to demonstrate the potential of our RL strategy as a promising tool to find new chemical process flowsheets.

Short Bio: 

Dr. L. Ricardez-Sandoval is a Professor in the Department of Chemical Engineering at the University of Waterloo (UW). Dr. Ricardez-Sandoval holds a Canada Research Chair (Tier II) in Multiscale Modelling and Process Systems and leads the development of methods for optimal design and operations management under uncertainty, the development of novel CO2 capture and conversion technologies aimed at reducing the carbon footprint, and computer-aided design of novel catalyst materials. Dr. Ricardez-Sandoval has published more than 235 journal articles, 80 full-length peer-reviewed conference papers, 5 book chapters and 1 book. Dr. Ricardez-Sandoval (h-index: 51) has 15 publications that each have been cited more than 100 times and has published numerous publications on optimal process integration, modelling and optimization of conventional and emerging CO2 capture technologies, atomistic and molecular design of novel catalyst materials for CO2 conversion, chemical looping combustion (CLC) technologies, and the implementation of machine learning (ML) methods for the optimal design and manufacture of nano-scale and macro-scale systems and materials. Dr. Ricardez-Sandoval‘s novel contributions in optimal process integration, multiscale modelling, process systems and CO2 capture and conversion technologies have been widely recognized by delivering multiple plenary and keynote talks at international conferences, leading the organization of top-tier conferences (e.g. International Program Chair: 2022 DYCOPS-CAB IFAC Symposium) and receiving multiple research-related awards, e.g., the 2024 D.G. Fisher Award sponsored by the Chemical Institute of Canada (CIC), the NSERC Discovery Accelerator Supplement (2017), and Ontario’s Early Researchers Award (2015). Dr. Ricardez-Sandoval serves as editor for Computers & Chemical Engineering, Digital Chemical Engineering and the Canadian Journal of Chemical Engineering. More information about Dr. Ricardez-Sandoval’s research activities can be found at the following links:

https://www.linkedin.com/in/luis-ricardez-sandoval-182b72298/

https://uwaterloo.ca/chemical-process-optimization-multiscale-modelling-process-systems/ 

Introductory Talk by Francisco A. Molina, Junior Machine Learning Engineer at AI Platform@ICN2—Automating image analysis to accelerate research

Hosted by Andrés Henao—Artificial Intelligence Platform, Machine Learning Engineer at ICN2