(703i) Process-Based Screening of MOFs for Direct Air Capture (DAC)

DAC involves separation of CO2 from N2, O2 and H2O in high purities for sequestration. For DAC, a process needs to be developed such that the energy consumed is minimum and the productivity is at its maximum with a constraint on the purity of CO2 to be > 95%. In this work, we consider a temperature – vacuum swing adsorption (TVSA) process for DAC. We consider an amine-based sorbent (APDES – NFC) as a benchmark material. The experimental loadings were fitted to a Toth isotherm model. Detailed energy – productivity optimizations were performed after accounting for H2O sorption. On the other hand, the computational ready experimental MOF ( CoRE MOF) database was screened for potential candidates for DAC. CO2 and N2 isotherms were obtained for the CoRE MOFs using GCMC simulations and the isotherms were fit to SSL isotherm models. At 400 ppm, materials which exhibited CO2 pure component capacities greater than 0.3 mmol/g were only chosen for energy – productivity optimizations since capacities lesser than 0.3 mmol/g would not be suitable for DAC under CO2/N2 competitive conditions. For the initial cut, energy – productivity optimizations on CoRE MOFs were performed under dry conditions. The machine-assisted adsorption learner and emulator (MAPLE) framework, an artificial neural network (ANN) platform for rapid simulation of adsorption processes for deployed. The process optimization results and the comparison between different solid sorbents would be presented at the conference.