Abstract
We performed nanosecond timescale computer simulations of clusterization and agglomeration processes of boron nitride (BN) nanostructures in hot, high pressure gas, starting from eleven different atomic and molecular precursor systems containing boron, nitrogen and hydrogen at various temperatures from 1500 to 6000 K. The synthesized BN nanostructures self-assemble in the form of cages, flakes, and tubes as well as amorphous structures. The simulations facilitate the analysis of chemical dynamics and we are able to predict the optimal conditions concerning temperature and chemical precursor composition for controlling the synthesis process in a high temperature gas volume, at high pressure. We identify the optimal precursor/temperature choices that lead to the nanostructures of highest quality with the highest rate of synthesis, using a novel parameter of the quality of the synthesis (PQS). Two distinct mechanisms of BN nanotube growth were found, neither of them based on the root-growth process. The simulations were performed using quantum-classical molecular dynamics (QCMD) based on the density-functional tight-binding (DFTB) quantum mechanics in conjunction with a divide-and-conquer (DC) linear scaling algorithm, as implemented in the DC-DFTB-K code, enabling the study of systems as large as 1300 atoms in canonical NVT ensembles for 1 ns time.
Original language | English |
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Pages (from-to) | 3803-3819 |
Number of pages | 17 |
Journal | Chemical Science |
Volume | 9 |
Issue number | 15 |
DOIs | |
State | Published - 2018 |
Funding
This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Material Sciences and Engineering Division Grant No. DE-AC02-09CH11466 (PSK and LH). SI was supported by the Laboratory Directed Research and Development (LDRD) Program of Oak Ridge National Laboratory. ORNL is managed by UT-Battelle, LLC, 651 for DOE under Contract DE-AC05-00OR22725. The presented results were computed using the HAWK computer cluster at Nagoya University. We acknowledge Yoshifumi Nishimura (Waseda University) and Hayashi Taku (Nagoya University) for their help in setting up the runtime environment and initial testing of DC-DFTB-K on HAWK computing facility. We are grateful to Igor Kaganovich and Yevgeny Raitses of PPPL for inspiring discussions.
Funders | Funder number |
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U.S. Department of Energy | DE-AC05-00OR22725 |
Office of Science | |
Basic Energy Sciences | DE-AC02-09CH11466 |
Oak Ridge National Laboratory | |
Laboratory Directed Research and Development | |
Japan Society for the Promotion of Science | 26248009 |