CSD in Action: Computational Characterization of MOFs for Gas Adsorption
Understanding Gas Adsorption Properties of Zr-Oxide MOFs
Here we highlight work by Peyman Z. Moghadam and co-workers who used CSD data to derive structure–property relationships for CO2 adsorption in Zr-oxide MOFs through computational characterization.
The full article can be accessed here – ACS Appl. Mater. Interfaces 2022, 14, 51, 56938–56947.
MOFs and Features
Metal–organic frameworks (MOFs) are coordination networks constructed with metal cations (or metal clusters) and organic linkers, whose properties can be finely tuned.
Zr-oxide MOFs are particularly promising for gas adsorption and separation applications for their porosity, regenerability, and stability.
Gas Adsorption Properties
The key to predicting reliable gas adsorption properties in MOFs is to accurately describe the interactions between an adsorbate and the MOF atoms.
When quadrupolar adsorbates are involved, electrostatic interactions are described by assigning partial charges to the framework atoms.
The Computational Study
The team performed a systematic study and computational characterization of a subset of Zr-oxide MOFs extracted from the Cambridge Structural Database (CSD).
DFT calculations were performed to obtain the partial atomic charges of the frameworks, which were used for gas adsorption simulations and to derive structure–property relationships.
Using MOFs Data from the CSD
The study started with the identification of already-synthesized Zr-oxide MOFs in the CSD.
Using the software ConQuest, the team developed seven criteria to search for Zr-oxide MOFs in the CSD MOF subset, a collection of over 100,000 validated, experimentally obtained MOF structures.
A total of 102 Zr-oxide MOFs were identified and used to generate a curated subset of MOFs. The geometric properties of these MOFs were then characterized, which included the calculation of the largest cavity diameter (LCD), pore-limiting diameter (PLD), and void fraction. The team also assigned the topology of the MOFs, simulated their N2 adsorption isotherms at 77K, and calculated the surface areas.
CO2 Adsorption Studies
To investigate the performance of Zr-oxide MOFs for CO2 capture, the team had to consider the nature of the adsorbate.
As CO2 has a high quadrupole moment, its adsorption predictions are dependent on the electrostatic interactions with the framework. For polar and quadrupolar adsorbates, electrostatic interactions are usually described by assigning partial charges to the framework atoms.
DFT calculations were hence performed to predict partial atomic charges, before performing high-throughput grand canonical Monte Carlo (GCMC) simulations to identify promising candidates for CO2 adsorption.
Important structure–properties relationships were derived from this study, including that the CO2 adsorption is highly dependent on the chemistry of the Zr-oxide node.
It was also found that the maximum CO2 uptake is obtained for structures with a heat of adsorption >25kJ/mol and largest cavity diameters of ca. 6–7Å.
This study highlights the power of using big data.
In this work, we used the CCDC’s structural search tool, ConQuest, to develop search queries that extracted all the available experimentally created Zr-oxide MOFs from the CSD. The result enabled the generation of a subset of 102 Zr-oxide MOFs. We used this subset to perform high-throughput adsorption simulations and identified top candidates for post-combustion CO2 capture.
This study highlights the power of using big data in combination with molecular-level simulations to discover new uses for a wide range of promising, previously synthesized materials available in the CSD.
Peyman Z. Moghadam, Associate Professor in Data Driven Materials Engineering, University College London
Augmented Reality
As the final step, the team brought these MOFs to life using augmented reality (AR) visualization.
This emerging, three-dimensional visualization technology allowed the scientists to investigate in detail the MOF structures, understand the complexity of the MOF Zr-oxide nodes, and identify favourable adsorption sites for gas molecules.
Image on the left reprinted with permission from ACS Appl. Mater. Interfaces 2022, 14, 51, 56938–56947.
