Computational techniques for characterisation of electrically conductive MOFs: quantum calculations and machine learning approaches

Abstract

The customisability of metal–-organic frameworks (MOFs) has attracted exponentially growing interest in the realm of materials science. Because of their porous nature, MOF research has been primarily focused on gas...

Simulating excited states in metal organic frameworks: from light-absorption to photochemical CO2 reduction

“…Conductivity is therefore typically low, ranging from 10 À9 to 10 À3 S cm À1 . 19,87 The modularity of MOFs and their composite materials enables the band structure to be tuned, specifically the band gaps and band edges, which can lead to improved conductivity. Low conductivity is inconvenient for photocatalysis, which requires highly mobile photogenerated charge carriers.…”

“…Training a model with underestimated GGA band gaps makes the model susceptible to spurious property predictions, such as band conduction in an insulating MOF. 19 In studies seeking to identify purely metallic MOFs using quantum chemical methods, 87 caution is required. Of course, thermal conductivity may alternatively be studied using molecular dynamics.…”

Computational Characterization of Zr-Oxide MOFs for Adsorption Applications

“…Such interactions are normally described by assigning partial charges to framework atoms. Different methods have been developed to calculate MOF’s atomic charges, for which significant variations in adsorption predictions could arise. − Popular methods include semi-empirical approaches, such as charge equilibration methods and those based on bond connectivity that require no electronic structure calculation, or charge assignment approaches based on quantum mechanical calculations, such as CHarges from ELectrostatic Potentials using a Grid-based method (ChelpG), density derived electrostatic and chemical (DDEC), and repeating electrostatic potential extracted atomic (REPEAT), to generate electrostatic-potential-derived atomic charges. A number of studies have compared the sensitivity of gas adsorption predictions with respect to the method used to assign partial atomic charges.…”

Performance of GFN1-xTB for periodic optimization of metal organic frameworks

“…To search for a MOF with some specific property, synthesizing every single MOF is clearly impossible, therefore computational methods have been increasingly employed to guide experiments. [5][6][7][8][9][10] One standard procedure is a combinatorial enumeration followed by molecular simulation on every hypothetical structure. 11,12 Inevitably, the important aspect determining the success of this approach is in the accuracy and efficiency of the molecular simulation methods.…”