Stepwise crystallographic visualization of dynamic guest binding in a nanoporous framework.

Binding sites are at the heart of all host-guest systems, whether biological or chemical. When considering binding sites that form covalent bonds with the guest, we generally envision a single, highly specific binding motif. Through single-crystal X-ray crystallography, the dynamic binding of a guest that displays a variety of covalent binding motifs in a single site of adsorption is directly observed for the first time.

Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture.

In this work, we have developed quantitative structure-property relationship (QSPR) models using advanced machine learning algorithms that can rapidly and accurately recognize high-performing metal organic framework (MOF) materials for CO2 capture. More specifically, QSPR classifiers have been developed that can, in a fraction of a section, identify candidate MOFs with enhanced CO2 adsorption capacity (>1 mmol/g at 0.15 bar and >4 mmol/g at 1 bar).

Phosphonate monoesters as carboxylate-like linkers for metal organic frameworks.

Bidentate phosphonate monoesters are analogues of popular dicarboxylate linkers in MOFs, but with an alkoxy tether close to the coordinating site. Herein, we report 3-D MOF materials based upon phosphonate monoester linkers. Cu(1,4-benzenediphosphonate bis(monoalkyl ester), CuBDPR, with an ethyl tether is nonporous; however, the methyl tether generates an isomorphous framework that is porous and captures CO(2) with a high isosteric heat of adsorption of 45 kJ mol(-1).