Project Overview

Adsorption processes for post combustion carbon capture are a promising alternative for solvent based energy intensive processes. Literature lacks a comprehensive understanding on modeling, optimization and control of such processes. This work aims to apply hybrid machine learning strategies to develop digital twins for pressure swing adsorption. The digital twins will be used for addressing the grand challenge of process+materials optimization and also for development of advanced process control strategies.