Paper
25 April 2022 Solid-liquid coexistence simulation of silicon melting point and reverse fitting correction potential function
Pengtian Lou, Haoyang Pan, Yingkai Wu
Author Affiliations +
Proceedings Volume 12244, 2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022); 122441K (2022) https://doi.org/10.1117/12.2635082
Event: 2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022), 2022, Guilin, China
Abstract
In molecular dynamics simulation, the phase transition is a rather complex process, and the melting point of materials simulated often deviates greatly from the experimental reported ones. Therefore, this article simulates the phase transition temperature of silicon and tries to reduce the influence of the large error from the simulation results. We use the StillingerWeber (SW) potential to simulate the solid-liquid coexistence method and the direct heating method are used respectively to compare and simulate the melting process of silicon. The influence of atomic number on the solid-liquid coexistence simulation process of melting point is discussed, and the influence of time step and potential function directly on the melting process is further discussed. Finally, we tried to modify the SW potential function to get better results. The selected computer algorithm has been further discussed in the section "Inverse fitting Analysis".
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pengtian Lou, Haoyang Pan, and Yingkai Wu "Solid-liquid coexistence simulation of silicon melting point and reverse fitting correction potential function", Proc. SPIE 12244, 2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022), 122441K (25 April 2022); https://doi.org/10.1117/12.2635082
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KEYWORDS
Silicon

Chemical species

Monte Carlo methods

Computer simulations

Crystals

Genetic algorithms

Molecules

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