Engineering Frustrated Lewis Pair Active Sites in Porous Organic Scaffolds for Catalytic CO2 Hydrogenation

31 January 2024, Version 2
This content is a preprint and has not undergone peer review at the time of posting.


Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad homogeneous catalytic processes. Immobilizing the active Lewis sites to a solid support, especially to porous scaffolds, has shown great potential to ameliorate FLP catalysis by circumventing some of its inherent drawbacks, such as product separation and catalyst recyclability. Nevertheless, designing immobilized Lewis pair active sites (LPASs) is challenging due to the requirement of placing the donor and acceptor centers in appropriate geometric arrangements while maintaining the necessary chemical environment to perform catalysis, and clear design rules have not yet been established. In this work, we formulate simple guidelines to build highly active LPASs for direct catalytic hydrogenation of CO2 through a large-scale screening of a diverse library of 25,000 immobilized FLPs. The library is built by introducing boron-containing acidic sites in the vicinity of the existing basic nitrogen sites of the organic linkers of metal-organic frameworks collected in a ``top-down" fashion from an experimental database. The chemical and geometrical appropriateness of these LPASs for CO2 hydrogenation is determined by evaluating a series of simple descriptors representing the intrinsic strength (acidity and basicity) of the components and their spatial arrangement in the active sites. Analysis of the leading candidates enables the formulation of pragmatic and experimentally-relevant design principles and the leading candidates constitute the starting point for further exploration of FLP-based catalysts for the reduction of CO2.


frustrated Lewis pairs
co2 hydrogenation
volcano plots
metal-organic frameworks
high-throughput virtual screening

Supplementary materials

Supporting Information
dataset generation and curation; computational details; construction of the plots for mapping chemical composition to activity; conformational analysis of the selected linkers; distribution of the geometric descriptors for all LPASs; distribution of the chemical descriptors for LPASs with appropriate geometry; free energy profile of a selected LPAS for hydrogenation;machine-learning model for porosity prediction


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