School of Engineering Department of Chemical and Biological Engineering 72 Machine-Leaning Assisted Optimization of Pressure Swing Adsorption Processes Supervisor: GAO Hanyu / CBE Student: TAKARIANTO Abraham Aditya / CEEV Course: UROP1100, Spring Pressure swing adsorption is an alternative technology to propylene separation that could reduce the capital and operational cost. A good adsorption process has a good selectivity towards the adsorbed product. In this project a system of propylene and propane is selected, and Z10-4 (Zeochem) is selected as the adsorbent for the model system. An isotherm of the propylene and propane is plotted. A numerical model of system operating at 650C with the pressure swing between 1 – 30 bar is plotted. The result shows that the pressure equation needs to be modified to remove the pressure lag and a better adsorbent or higher linear driving force needs to be selected to increase the efficiency of the adsorption process. Active Learning for the Design of Polymerization Reactions Supervisor: GAO Hanyu / CBE Student: YANG Jianbo / CENG Course: UROP1100, Spring UROP2100, Summer Polymer is an essential material widely used in our daily lives. Their properties can vary significantly due to their complex microstructures including composition ratio of monomers, length of polymer chain, position of sub-chains, the sequence of monomers and so on. The complicity opens a large area for researchers to design multifunctional polymers, also bringing a challenge task on how to relate parameters of microstructure to properties along with novel products. Machine learning, a cutting-edge data processing method, fits this area well because it enables researchers to process large-scale data in a shorter time and make predictions based on current examples. In the project, we continue the progress in last semester and try to optimize the execution time problem.