Equipartitioning of Molecular Degrees of Freedom in MD Simulations of Gaseous Systems via an Advanced Thermostatization Strategy.

This work introduces a dedicated thermostatization strategy for molecular dynamics simulations of gaseous systems. The proposed thermostat is based on the stochastic canonical velocity rescaling approach by Bussi and co-workers and is capable of ensuring an equal distribution of the kinetic energy among the translational, rotational, and vibrational degrees of freedom. The outlined framework ensures the correct treatment of the kinetic energy in gaseous systems, which is typically not the case in standard approaches due to the limited number of collisions between particles associated with a large free mean path.

Modelling bulk and surface characteristics of cubic CeO, GdO, and gadolinium-doped ceria using a partial charge framework.

The development and characterization of materials for solid oxide fuel cells (SOFC) is an important step towards sustainable energy technologies. This present study models cubic CeO, GdO, and gadolinium-doped ceria (GDC) using newly constructed interaction potentials based on a partial atom charge framework. The interaction model was validated by comparing the structural properties with experimental reference data, which were found to be in good agreement.

Storage and Diffusion of Carbon Dioxide in the Metal Organic Framework MOF-5─A Semi-empirical Molecular Dynamics Study.

Metal-organic frameworks (MOFs) have attracted increasing attention due to their high porosity for exceptional gas storage applications. MOF-5 belongs to the family of isoreticular MOFs (IRMOFs) and consists of ZnO clusters linked by 1,4-benzenedicarboxylate. Due to the large number of atoms in the unit cell, molecular dynamics simulation based on density functional theory has proved to be too demanding, while force field models are often inadequate to model complex host-guest interactions.

Accessing Position Space Wave Functions in Band Structure Calculations of Periodic Systems─A Generalized, Adapted Numerov Implementation for One-, Two-, and Three-Dimensional Quantum Problems.

In this work, a generalized, adapted Numerov implementation capable of determining band structures of periodic quantum systems is outlined. Based on the input potential, the presented approach numerically solves the Schrödinger equation in position space at each momentum space point. Thus, in addition to the band structure, the method inherently provides information about the state functions and probability densities in position space at each momentum space point considered.

Terminal methylene phosphonium ions: precursors for transient monosubstituted phosphinocarbenes.

Isolable singlet carbenes are among the most important tools in chemistry, but generally require the interaction of two substituents with the electron deficient carbon atom. We herein report a synthetic approach to monosubstituted phosphinocarbenes deprotonation of hitherto unknown diprotic terminal methylene phosphonium ions. Two methylene phosphonium salts bearing bulky -heterocyclic imine substituents at the phosphorus atom were isolated and fully characterized.

Beyond the Status Quo: Density Functional Tight Binding and Neural Network Potentials as a Versatile Simulation Strategy to Characterize Host-Guest Interactions in Metal- and Covalent Organic Frameworks.

In recent years, research focused on synthesis, characterization, and application of metal-organic frameworks (MOFs) has attracted increased interest, from both an experimental as well as a theoretical perspective. Self-consistent charge density functional tight binding (SCC DFTB) in conjunction with a suitable constrained molecular dynamics (MD) simulation protocol provides a versatile and flexible platform for the study of pristine MOFs as well as guest@MOF systems. Although being a semi-empirical quantum mechanical method, SCC DFTB inherently accounts for polarization and many-body contributions, which may become a limiting factor in purely force field-based simulation studies.

From vibrational spectroscopy and quantum tunnelling to periodic band structures - a self-supervised, all-purpose neural network approach to general quantum problems.

In this work, a feed-forward artificial neural network (FF-ANN) design capable of locating eigensolutions to Schrödinger's equation self-supervised learning is outlined. Based on the input potential determining the nature of the quantum problem, the presented FF-ANN strategy identifies valid solutions solely by minimizing Schrödinger's equation encoded in a suitably designed global loss function. In addition to benchmark calculations of prototype systems with known analytical solutions, the outlined methodology was also applied to experimentally accessible quantum systems, such as the vibrational states of molecular hydrogen H and its isotopologues HD and D as well as the torsional tunnel splitting in the phenol molecule.