Simulations of the synthesis of boron-nitride nanostructures in a hot, high pressure gas volume

Abstract

Quantum-classical molecular dynamics reveals optimal molecular precursors and temperatures for synthesis of boron-nitride nanostructures.

Adsorption of NO2, HCN, HCHO and CO on pristine and amine functionalized boron nitride nanotubes by self-consistent charge density functional tight-binding method

“…The SCC-DFTB can also include reliable description of dispersions and weak interactions (Van der Waals and H-bonding) that are important roles for investigation of gas adsorption on a sensing material which is consistent with experimental observations [40,45,47,48]. Moreover, the SCC-DFTB was proved to be effective in the simulation studies of boron nitride nanostructures systems [49][50][51].…”

Modification of boron nitride nanocages by titanium doping results unexpectedly in exohedral complexes

“…12. At typical temperature range (1500-2500 K) for producing BN nanocages 32,33 , isomer Ti & 4 with a heptagonal ring is the most abundant product, followed by Ti & 3. Despite being the lowest energy isomer at 0 K, Ti & 2 is only the third major product at synthesis temperatures up to~2400 K. Beyond that temperature, other relatively higher energy isomers (especially Ti & 7) become more competitive.…”

“…As strongly contrasted with carbon fullerenes, it is highly exergonic for a BN cage to attach a Ti atom from outside, whereas encaging it is totally hindered from a thermodynamic point of view. This suggests that exohedral Ti(BN) n complexes can most likely be produced by high-temperature synthesis 32,33 like arcmelting, where global minimum structures on the free energy surface are usually formed. Furthermore, changes in cage structure take place upon doping with a single Ti atom, even more drastic than the case of carbon fullerenes.…”

Dcdftbmd: Divide‐and‐Conquer Density Functional Tight‐Binding Program for Huge‐System Quantum Mechanical Molecular Dynamics Simulations

“…The benchmark calculations showed that simulation of one MD step for water system consisting of a few millions of atoms is completed within minutes using more than one hundred thousands of cores . The developed program has acquired robustness to the reactive system by means of grid box type fragments and enabled QM‐based MD simulations for systems consisting of from hundreds to thousands of atoms routinely when using laboratory workstation and/or moderate computer resources …”

“…[52] The developed program has acquired robustness to the reactive system by means of grid box type fragments and enabled QM-based MD simulations for systems consisting of from hundreds to thousands of atoms routinely when using laboratory workstation and/or moderate computer resources. [53][54][55][56][57][58][59][60][61] Although the parallelized DC-DFTB calculation has bridged the gap of system size existing between QM-based and classical MD simulations, further integrating advanced extensions into the program is necessary to allow the user to facilitate his or her theoretical analysis beyond the straightforward MD simulation under the plain DC-DFTB potential energy surfaces (PES). For example, timescale of DC-DFTB-based MD simulation is typically limited within nanoseconds, which makes it difficult to study chemical reactions with high energy barrier and to sample slow motion events including protein folding and arrangement of molecular aggregates.…”