Computational high-throughput screening using molecular simulations is a powerful tool for identifying topperforming metal−organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO 2 . Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal−Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. A strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

Titanium carbide (TiC) possesses fascinating properties like high electrical conductivity and high mechanical strength coupled with high corrosion resistance and stability in acidic and alkaline environments. The present study demonstrates the tunability of mechanistic aspects of oxygen reduction reaction (ORR) using TiC nanostructures. One dimensional TiC nanostructures (TiC-NW) have been synthesized using a simple, hydrothermal method and used as a catalyst for ORR. Shape dependent electroactivity is demonstrated by comparing the activity of TiC-NW with its bulk counterparts. Comparative studies reveal higher ORR activities in the case of 1D TiC-NW involving ~4 electrons showing efficient reduction of molecular oxygen. Excellent stability and high methanol tolerance with good selectivity for ORR is reported.

Entrapment of radioactive inert gases, Xe and Kr, generated from the spent nuclear fuel reprocessing or nuclear accidents is one of the challenging issues in successful implementation of nuclear energy as an alternative and sustainable energy. Metal–organic frameworks (MOFs) gained immense research interest for adsorption and separation of various important gases because of their fine tunable pore chemistry and topology. Here, we investigated a series of MOFs, MFM-300­(M) (M = Al, In, Ga, Sc, V, Cr, and Fe), for selective entrapment of Xe over Kr using both density functional theory (DFT) and grand canonical Monte Carlo (GCMC) simulation techniques. The calculated structural parameters of all of the considered MOFs are consistent with the reported experimental results. Different textural properties such as pore-limiting diameter, largest cavity diameter, surface area, void fraction, etc., are measured. From the binding energies calculated through DFT calculations at different loading capacities, adsorption of Xe is found to be stronger as compared to adsorption of Kr, and the binding energy is found to increase with loading. GCMC simulations indicate that the considered MOFs have significantly higher uptake capacities and are selective for Xe over Kr. Energy decomposition analysis indicates a strong adsorbate–adsorbate interaction at higher loading, which is more significant for Xe as compared to Kr. The strong adsorbate–adsorbate interactions are driven by the confinement effects of the one-dimensional cylindrical channels present in MFM-300­(M). Among the series of MOFs considered, MFM-300­(In) is shown to have the best selectivity for Xe over Kr. Our computational studies can provide valuable inputs for exploring MFM-300­(M) MOFs for selective separation and storage of noble gases.