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Machine learned interatomic potential for dispersion strengthened plasma facing components

Authors :
E. L. Sikorski
M. A. Cusentino
M. J. McCarthy
J. Tranchida
M. A. Wood
A. P. Thompson
Source :
The Journal of Chemical Physics. 158:114101
Publication Year :
2023
Publisher :
AIP Publishing, 2023.

Abstract

Tungsten (W) is a material of choice for the divertor material due to its high melting temperature, thermal conductivity, and sputtering threshold. However, W has a very high brittle-to-ductile transition temperature, and at fusion reactor temperatures (≥1000 K), it may undergo recrystallization and grain growth. Dispersion-strengthening W with zirconium carbide (ZrC) can improve ductility and limit grain growth, but much of the effects of the dispersoids on microstructural evolution and thermomechanical properties at high temperatures are still unknown. We present a machine learned Spectral Neighbor Analysis Potential for W–ZrC that can now be used to study these materials. In order to construct a potential suitable for large-scale atomistic simulations at fusion reactor temperatures, it is necessary to train on ab initio data generated for a diverse set of structures, chemical environments, and temperatures. Further accuracy and stability tests of the potential were achieved using objective functions for both material properties and high temperature stability. Validation of lattice parameters, surface energies, bulk moduli, and thermal expansion is confirmed on the optimized potential. Tensile tests of W/ZrC bicrystals show that although the W(110)–ZrC(111) C-terminated bicrystal has the highest ultimate tensile strength (UTS) at room temperature, observed strength decreases with increasing temperature. At 2500 K, the terminating C layer diffuses into the W, resulting in a weaker W–Zr interface. Meanwhile, the W(110)–ZrC(111) Zr-terminated bicrystal has the highest UTS at 2500 K.

Details

ISSN :
10897690 and 00219606
Volume :
158
Database :
OpenAIRE
Journal :
The Journal of Chemical Physics
Accession number :
edsair.doi.dedup.....f87c4eee06c9ad7c4b2ab6e08037ccee
Full Text :
https://doi.org/10.1063/5.0135269