Discovery of Stacking Heterogeneity, Layer Buckling, and Residual Water in COF-999-NH 2 and Implications on CO 2 Capture
Year: 2025
Type: article
Abstract: Covalent organic frameworks (COFs), with their modular architectures and tunable functionalities, provide a versatile platform to design sorbents for direct capture of CO2 from air. Here, we combined density functional theory, molecular dynamics and grand canonical Monte Carlo simulations with experiment to understand structural factors for furthering COF-999-NH2’s performance as the precursor to COF-999 for direct air CO2 capture. Small energy differences among laterally shifted stackings reveal intrinsic stacking heterogeneity. The simulations show pronounced layer buckling coupled to extensive amine–nitrile hydrogen bonding and persistent pore water, which initiates undesired polymerization and undermines uptake. The predicted presence of water is confirmed by subsequent experiments. These insights point to a single, actionable design rule: exclude retained water by introducing hydrophobic pore environments to maximize CO2 capture efficiency.
DOI: 10.1021/jacs.5c18608
Authors: Hilal Daglar, Zihui Zhou, Ray Zhu, Pragya Parihar, J. Ilja Siepmann, Omar M. Yaghi, Laura Gagliardi
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: bronze
Awards: Discovery and Biological Signatures of Microbiome-Derived Xanthohumol (XN) Metabolites and their Role in Ameliorating Inflammatory Bowel Disease (IBD), NSF-DFG Confine: Diffusion of Water Confined in Patterned Hydrophilic-Hydrophobic Nanopores, DEVELOPMENT OF MACHINE LEARNING AND MOLECULAR SIMULATION APPROACHES TO ACCELERATE THE DISCOVERY OF POROUS MATERIALS FOR ENERGY-RELEVANT APPLICATIONS, G5531973609, G5914044554, G6691793984, G7043377807, DEVELOPMENT OF MACHINE LEARNING AND MOLECULAR SIMULATION APPROACHES TO ACCELERATE THE DISCOVERY OF POROUS MATERIALS FOR ENERGY-RELEVANT APPLICATIONS, G8513326252
OpenAlex ID: W4417536157