Empirical Interatomic Potential for Si-H Interactions

1993 ◽  
Vol 317 ◽  
Author(s):  
M.V. Ramana Murty ◽  
Harry A. Atwater ◽  
Thomas J. Watson
Keyword(s):  
Molecular Dynamics ◽  
Ab Initio ◽  
Interatomic Potential ◽  
Silicon Surfaces ◽  
Vibrational Modes ◽  
Silicon Hydride ◽  
Computationally Efficient ◽  
Bond Lengths

An empirical TersofF-type interatomic potential has been developed for describing Si-H interactions. The potential gives a reasonable fit to bond lengths, angles and energetics of silicon hydride molecules and hydrogen-terminated silicon surfaces. The frequencies of most vibrational modes are within 15% of the experimental and ab initio theory values. The potential is computationally efficient and suitable for molecular dynamics investigations of various processing treatments of hydrogen-terminated silicon surfaces.

Solvation effects on the vibrational modes in hydrated bicarbonate clusters

2018 ◽  
Vol 20 (6) ◽  
pp. 4571-4578 ◽  
Author(s):  
Xiangtao Kong ◽  
Shou-Tian Sun ◽  
Ling Jiang ◽  
Zhi-Feng Liu
Keyword(s):  
Molecular Dynamics ◽  
Ab Initio ◽  
Harmonic Analysis ◽  
Molecular Dynamics Simulations ◽  
Vibrational Modes ◽  
Solvation Effects ◽  
Dynamics Simulations

Harmonic analysis and ab initio molecular dynamics simulations reveal the solvation effects on the vibrational modes of HCO3−(H2O)n.

Multi-Scale Simulations of Silicon Etching by Halides: Effects of Surface Reaction Rates.

2001 ◽  
Vol 677 ◽  
Author(s):  
Matthias Kratzer ◽  
Werner Steinhögl ◽  
Alfred Kersch ◽  
Tanja Sachse ◽  
Volker Höink
Keyword(s):  
Molecular Dynamics ◽  
Amorphous Silicon ◽  
Surface Reaction ◽  
Interatomic Potential ◽  
Reaction Rates ◽  
Plasma Sheath ◽  
Silicon Surfaces ◽  
Kinetic Properties ◽  
Hybrid Plasma ◽  
Feature Evolution

ABSTRACTWe investigate the reactive ion etching of amorphous silicon by halides using a hierarchy of models on different time and length scales. The feature evolution is modeled using a two- dimensional cell based Monte-Carlo feature scale simulator. The fluxes, the energy distributions, and the angular distributions of the wafer-incident particles are provided by a hybrid plasma sheath simulator. The relevant surface reaction rates are calculated by a molecular dynamics simulator using a Stillinger-Weber representation of the interatomic potential. Our investigations show that the surface reaction rates are strongly determined by the particular surface morpho- logy, which, in turn, is strongly influenced by the kinetic properties of the impinging particles. Thus, we link the molecular dynamics simulator into the model as a whole.As results, we present calculations for the etching of amorphous silicon by fluorine, chlorine, and bromine. A Stillinger-Weber representation of the bromine and the silicon-bromine potential which was not yet available in literature is additionally developed. We discuss the different morphologies of halogenated silicon surfaces as a consequence of the energy distri- bution and the angular distribution of the impinging particles. Comparisons of the sputter yield functions of bare amorphous silicon surfaces and corresponding halogenated surfaces exhibit considerable differences, qualitative as well as quantitative.

A transferable interatomic potential for MgO from ab initio molecular dynamics

2002 ◽  
Vol 356 (5-6) ◽  
pp. 437-444 ◽  
Author(s):  
Andrés Aguado ◽  
Leonardo Bernasconi ◽  
Paul A. Madden
Keyword(s):  
Molecular Dynamics ◽  
Ab Initio ◽  
Interatomic Potential ◽  
Ab Initio Molecular Dynamics

Combustion Driven by Fragment-based Ab Initio Molecular Dynamics Simulation

2019 ◽  
Author(s):  
Liqun Cao ◽  
Jinzhe Zeng ◽  
Mingyuan Xu ◽  
Chih-Hao Chin ◽  
Tong Zhu ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Ab Initio ◽  
Large Scale ◽  
Methane Combustion ◽  
Combustion Method ◽  
Dynamics Simulation ◽  
Ab Initio Molecular Dynamics ◽  
Computational Time ◽  
Combustion Mechanism ◽  
Daily Lives

Combustion is a kind of important reaction that affects people's daily lives and the development of aerospace. Exploring the reaction mechanism contributes to the understanding of combustion and the more efficient use of fuels. Ab initio quantum mechanical (QM) calculation is precise but limited by its computational time for large-scale systems. In order to carry out reactive molecular dynamics (MD) simulation for combustion accurately and quickly, we develop the MFCC-combustion method in this study, which calculates the interaction between atoms using QM method at the level of MN15/6-31G(d). Each molecule in systems is treated as a fragment, and when the distance between any two atoms in different molecules is greater than 3.5 Å, a new fragment involved two molecules is produced in order to consider the two-body interaction. The deviations of MFCC-combustion from full system calculations are within a few kcal/mol, and the result clearly shows that the calculated energies of the different systems using MFCC-combustion are close to converging after the distance thresholds are larger than 3.5 Å for the two-body QM interactions. The methane combustion was studied with the MFCC-combustion method to explore the combustion mechanism of the methane-oxygen system.

Active Learning Accelerates Ab Initio Molecular Dynamics on Pericyclic Reactive Energy Surfaces

2020 ◽  
Author(s):  
Shi Jun Ang ◽  
Wujie Wang ◽  
Daniel Schwalbe-Koda ◽  
Simon Axelrod ◽  
Rafael Gomez-Bombarelli
Keyword(s):  
Molecular Dynamics ◽  
Potential Energy ◽  
Transition State ◽  
Potential Energy Surface ◽  
Ab Initio ◽  
Energy Surface ◽  
Computational Cost ◽  
Reactive Trajectories ◽  
Dynamics Simulations ◽  
Energy Surfaces

<div>Modeling dynamical effects in chemical reactions, such as post-transition state bifurcation, requires <i>ab initio</i> molecular dynamics simulations due to the breakdown of simpler static models like transition state theory. However, these simulations tend to be restricted to lower-accuracy electronic structure methods and scarce sampling because of their high computational cost. Here, we report the use of statistical learning to accelerate reactive molecular dynamics simulations by combining high-throughput ab initio calculations, graph-convolution interatomic potentials and active learning. This pipeline was demonstrated on an ambimodal trispericyclic reaction involving 8,8-dicyanoheptafulvene and 6,6-dimethylfulvene. With a dataset size of approximately</div><div>31,000 M062X/def2-SVP quantum mechanical calculations, the computational cost of exploring the reactive potential energy surface was reduced by an order of magnitude. Thousands of virtually costless picosecond-long reactive trajectories suggest that post-transition state bifurcation plays a minor role for the reaction in vacuum. Furthermore, a transfer-learning strategy effectively upgraded the potential energy surface to higher</div><div>levels of theory ((SMD-)M06-2X/def2-TZVPD in vacuum and three other solvents, as well as the more accurate DLPNO-DSD-PBEP86 D3BJ/def2-TZVPD) using about 10% additional calculations for each surface. Since the larger basis set and the dynamic correlation capture intramolecular non-covalent interactions more accurately, they uncover longer lifetimes for the charge-separated intermediate on the more accurate potential energy surfaces. The character of the intermediate switches from entropic to thermodynamic upon including implicit solvation effects, with lifetimes increasing with solvent polarity. Analysis of 2,000 reactive trajectories on the chloroform PES shows a qualitative agreement with the experimentally-reported periselectivity for this reaction. This overall approach is broadly applicable and opens a door to the study of dynamical effects in larger, previously-intractable reactive systems.</div>

Sign in / Sign up

Export Citation Format

Share Document