+86-21-51987688
sales@chemsoon.com
Home > News > Investigating CO₂ Sorption in SIFSIX-3-M (M = Fe, Co, Ni, Cu, Zn) through Computational Studies
Investigating CO₂ Sorption in SIFSIX-3-M (M = Fe, Co, Ni, Cu, Zn) through Computational Studies
Summary: 
The authors from University of South Florida & partners developed the SIFSIX-3-M (M = Fe, Co, Ni, Cu, Zn) family of hybrid ultramicroporous materials (HUMs) with tunable pore sizes (3.54–3.84 Å), achieving CO₂ sorption capacities up to 2.68 mmol g⁻¹ at 0.1 bar and isosteric heats (Qst) spanning 42–54 kJ mol⁻¹ for selective CO₂ capture applications.
 
Background: 
1. To address high energy demands of amine scrubbing, prior work used MOFs/HUMs, yet lacked systematic tuning of sorption energetics across isostructural series. 
2. The authors herein combined GCMC/CMC simulations with periodic DFT to elucidate how metal substitution modulates CO₂ affinity.
 
Research Content: 
1. Synthesis: One-step solvothermal reaction of M²⁺SiF₆·xH₂O with pyrazine in methanol (85 °C, 3 days) followed by methanol exchange and activation at 75 °C under vacuum. 
2. Characterizations: 
   1) BET areas 223–368 m² g⁻¹; theoretical pore volumes 0.167–0.197 cm³ g⁻¹. 
   2) Single-crystal XRD gives pcu topology with 1D channels; pore size tuned by M²⁺ (Cu smallest, Fe/Zn largest). 
   3) Experimental isotherms at 278–328 K fitted to DSL; Qst via Clausius–Clapeyron. 
3. Application: Pure- and mixed-gas CO₂ capture tested; SIFSIX-3-Cu shows highest Qst (54 kJ mol⁻¹) and selectivity at low pressure. 
4. Mechanism: Smaller a/b lattice constants and pore size (Cu: 3.54 Å) strengthen F···C(CO₂) interactions; DFT ΔE correlates with Qst trend. Jahn–Teller distortion in Cu²⁺ contracts pore, enhancing electrostatics and induced dipoles.
 
Outlook: 
This study demonstrates precise control of CO₂ sorption energetics within an isostructural HUM platform, offering a blueprint for next-generation physisorbents in post-combustion and direct-air CO₂ capture.
 
Investigating CO₂ Sorption in SIFSIX-3-M (M = Fe, Co, Ni, Cu, Zn) through Computational Studies 
Authors: Katherine A. Forrest, Tony Pham, Sameh K. Elsaidi, Mona H. Mohamed, Praveen K. Thallapally, Michael J. Zaworotko, Brian Space 
DOI: 10.1021/acs.cgd.9b00086 
Link: https://pubs.acs.org/doi/10.1021/acs.cgd.9b00086 
 
The above review is for academic progress sharing. For any errors or copyright issues, please contact us for correction or removal.