DL_POLY Quantum 2.0: A modular general-purpose software for advanced path integral simulations.

DL_POLY Quantum 2.0, a vastly expanded software based on DL_POLY Classic 1.10, is a highly parallelized computational suite written in FORTRAN77 with a modular structure for incorporating nuclear quantum effects into large-scale/long-time molecular dynamics simulations.

Effects of Defects and Presence of Open-Metal Sites on the Structure and Dynamics of Water in Hydrophobic Zeolitic Imidazolate Frameworks.

Most of the chemistry in nanoporous materials with small pore sizes and windows takes place on the outer surface, which is in direct contact with the substrate/solvent, rather than within the pores and channels. Here, we report the results of our comprehensive atomistic molecular dynamics (MD) simulations to decipher the interaction of water with a realistic finite ∼5.1 nm nanoparticle (NP) model of ZIF-8, with edges containing undercoordinated Zn metal sites, vs a conventionally employed pristine crystalline bulk (CB) model.

Real-Time Dynamics and Detailed Balance in Ring Polymer Surface Hopping: The Impact of Frustrated Hops.

Ring polymer surface hopping (RPSH) has been recently introduced as a well-tailored method for incorporating nuclear quantum effects, such as zero-point energy and tunneling, into nonadiabatic molecular dynamics simulations. The practical widespread usage of RPSH demands a comprehensive benchmarking of different reaction regimes and conditions with equal emphasis on demonstrating both the cons and the pros of the method. Here, we investigate the fundamental questions related to the conservation of energy and detailed balance in the context of RPSH.

In Silico High-Throughput Design and Prediction of Structural and Electronic Properties of Low-Dimensional Metal-Organic Frameworks.

The advent of π-stacked layered metal-organic frameworks (MOFs), which offer electrical conductivity on top of permanent porosity and high surface area, opened up new horizons for designing compact MOF-based devices such as battery electrodes, supercapacitors, and spintronics. Permutation of structural building blocks, including metal nodes and organic linkers, in these electrically conductive (EC) materials, results in new systems with unprecedented and unexplored physical and chemical properties. With the ultimate goal of providing a platform for accelerated material design and discovery, here we lay the foundations for the creation of the first comprehensive database of EC-MOFs with an experimentally guided approach.

Healthcare workers' knowledge, attitude and practices during the COVID-19 pandemic response in a tertiary care hospital of Nepal.

Background: COVID-19 is an ongoing pandemic, for which appropriate infection prevention and control measures need to be adopted. Healthcare workers' adherence to prevention and control measures is affected by their knowledge, attitudes, and practices (KAP) towards COVID-19. In this study, we assessed the KAP among healthcare workers towards the COVID-19 during the ongoing pandemic.

Disorder by design: A data-driven approach to amorphous semiconductors without total-energy functionals.

X-ray diffraction, Amorphous silicon, Multi-objective optimization, Monte Carlo methods. This paper addresses a difficult inverse problem that involves the reconstruction of a three-dimensional model of tetrahedral amorphous semiconductors via inversion of diffraction data. By posing the material-structure determination as a multiobjective optimization program, it has been shown that the problem can be solved accurately using a few structural constraints, but no total-energy functionals/forces, which describe the local chemistry of amorphous networks.