2025 AIChE Annual Meeting
(444d) A Combined Experimental-Computational Methodology to Accelerate Screening and Discovery of Solid Sorbents for Moisture-Swing Carbon Capture
Authors
Here, we integrate computational modeling, synthesis, characterization, and MSA breakthrough analysis to design a series of ordered, mesoporous sorbents containing different cationic functional groups. A high-throughput molecular modeling workflow was used to identify target cation-anion pairs by: (i) calculating free energies for OH- formation as a function of active site hydration, and (ii) predicting MSA reactivity based on a shift in the CO2 capture step from exergonic to endergonic as a function of humidity. Computationally predicted model sorbents were prepared by functionalizing SBA-15 mesoporous silica with quaternary ammonium cations containing organic substituents of varying chain length (e.g., R1, R2) charge-balanced by carbonate anions. The sorbents were evaluated for moisture-responsive CO2 capture over multiple cycles in a fixed bed adsorber at 298 K with 400 ppmv CO2 and between 0.64-2.4 kPa H2O. Our findings reveal that cation-anion interactions can be influenced by changing the organic substituents, leading to an ~5× increase in CO2 uptake (normalized per mole of N+) during a 20-min adsorption step without adversely affecting sorption kinetics (Figure 1). This approach demonstrates that molecular modeling in conjunction with empirical relationships between material properties and performance can enable pre-screening of potential MSA sorbents and guide the discovery of new materials for CO2 capture.
References:
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