Structural phase transition and amorphization in hexagonal SiC subjected to dynamic loading

Feng, Lanxi; Li, Wanghui; Hahn, Eric N.; Branı́cio, Paulo S.; Zhang, Xiaoqing; Yao, Xiongliang

doi:10.1016/j.mechmat.2021.104139

Cited by 12 publications

(7 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[38][39][40][41][42][43][44][45] For instance, MD simulations on hexagonal SiC under ramp dynamic loading with strain rates ranging from 10 8 s −1 to 10 11 s −1 suggest that higher strain rates often lead to an increase in the strength, temperature and critical strain. [46] This effect is also observed in B 4 C, where the uniaxial compressive strength increases with increasing strain rate, [42,44] following Kimberley's model. [47,48] In particular, B 4 C, as an advanced ceramic, draws particular attention for its potential technological applications in shielding and nuclear technology [49,50] due to its unique properties such as a high Hugoniot elastic limit (HEL) and low density.…”

Section: Introductionmentioning

confidence: 57%

“…[59,60] The value of strain rate for these simulations is set to 5×10 9 s −1 , which is comparable to shock compression. [46] Furthermore, we employ the GB3 model to investigate the effects of strain rates, using a wide range of compressive strain rates ranging from 2×10 9 s −1 to 1×10 11 s −1 . Periodic boundary conditions are applied to elim-inate the possible surface effects and the integration timestep is set to 1.0 fs.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Quasi-plastic deformation mechanisms and inverse Hall–Petch relationship in nanocrystalline boron carbide under compression

Yue 岳,

Li 李,

Liu 刘

et al. 2024

Chinese Phys. B

View full text Add to dashboard Cite

Grain boundary (GB) plays a significant role in the deformation behaviors of nanocrystalline ceramics. Here, we investigate the compression behaviors of nanocrystalline boron carbide (n-B4C) with varying grain sizes, using molecular dynamics simulations with a machine-learning force field. The results reveal quasi-plastic deformation mechanisms in n-B4C: GB sliding, intergranular amorphization, and intragranular amorphization. GB sliding arises from the presence of the soft GBs, leading to intergranular amorphization. Intragranular amorphization arises from the interaction between grains with unfavorable orientations and the softened amorphous GBs, finally causing structural failure. Furthermore, the n-B4C models with varying grain sizes from 4.07 nm to 10.86 nm display an inverse Hall-Petch relationship due to the GB sliding mechanism. A higher strain rate in n-B4C often leads to higher yield strength, following a 2/3 power relationship. These deformation mechanisms are critical for the design of ceramics with superior mechanical properties.

show abstract

Section: Introductionmentioning

confidence: 57%

Section: Methodsmentioning

confidence: 99%

Quasi-plastic deformation mechanisms and inverse Hall–Petch relationship in nanocrystalline boron carbide under compression

Yue 岳,

Li 李,

Liu 刘

et al. 2024

Chinese Phys. B

View full text Add to dashboard Cite

show abstract

“…A ceramic of increasing importance is silicon carbide (SiC) which exhibits extreme polymorphism (over 250 polytypes) and demonstrates high-performance under extreme conditions such as ballistic impact, − high temperature, and under irradiation. , Moreover, high temperature and oxidation resistance has promoted its use in hypersonic, − and nuclear power − applications. Numerous computational studies − via classical atomistic simulations or ab initio methods have been performed on SiC to better understand its deformation behavior and phase transitions. A popular empirical potential for studying SiC behavior is the Vashishta potential, which has been used to investigate SiC shock response with system sizes exceeding six million atoms .…”

Section: Introductionmentioning

confidence: 99%

“…Numerous computational studies − via classical atomistic simulations or ab initio methods have been performed on SiC to better understand its deformation behavior and phase transitions. A popular empirical potential for studying SiC behavior is the Vashishta potential, which has been used to investigate SiC shock response with system sizes exceeding six million atoms . This potential predicts fitted properties such as cohesive energy, bulk modulus, and the C 11 elastic constant with a high degree of accuracy, but fails to accurately reproduce other properties, such as shear moduli and the C 33 elastic constant in the SiC–3C, SiC–2H, and SiC–6H polytypes (as will be discussed later in this work).…”

Section: Introductionmentioning

confidence: 99%

A Genetic Algorithm Trained Machine-Learned Interatomic Potential for the Silicon–Carbon System

MacIsaac,

Bavdekar,

Spearot

et al. 2024

J. Phys. Chem. C

View full text Add to dashboard Cite

A linear regression-based machine learned interatomic potential (MLIP) was developed for the silicon−carbon system. The MLIP was predominantly trained on structures discovered through a genetic algorithm, encompassing the entire silicon−carbon composition space, and uses as its foundation the Ultra-Fast Force Fields (UF 3 ) formulation. To improve MLIP performance, the learning algorithm was modified to include higher spline interpolation resolution in regions with large potential energy surface curvature. The developed MLIP demonstrates exceptional predictive performance, accurately estimating energies and forces for structures across the silicon−carbon composition and configuration space. The MLIP predicts structural, energetic, and elastic properties of silicon carbide (SiC) with high precision and captures fundamental volume-pressure and volumetemperature relationships. Uniquely, this silicon−carbon MLIP is adept at modeling complex high-temperature phenomena, including the peritectic decomposition of SiC and carbon dimer formation during SiC surface reconstruction, which cannot be captured with prior classical interatomic potentials for this material.

show abstract

“…Figure 15. The typical shock damage simulation model of SiC [94].Feng et al[94] studied the inelastic response to 6H-SiC and 4H-SiC under strong dynamic shock loading. Lee et al[95] studied the high-velocity shock compression of 3C-SiC.…”

mentioning

confidence: 99%

Molecular Dynamics Simulation Studies of Properties, Preparation, and Performance of Silicon Carbide Materials: A Review

Yan

Liu

et al. 2023

Energies

View full text Add to dashboard Cite

Silicon carbide (SiC) materials are widely applied in the field of nuclear materials and semiconductor materials due to their excellent radiation resistance, thermal conductivity, oxidation resistance, and mechanical strength. The molecular dynamics (MD) simulation is an important method to study the properties, preparation, and performance of SiC materials. It has significant advantages at the atomic scale. The common potential functions for MD simulations of silicon carbide materials were summarized firstly based on extensive literatures. The key parameters, complexity, and application scope were compared and analyzed. Then, the MD simulation of SiC properties, preparation, and performance was comprehensively overviewed. The current studies of MD simulation methods and applications of SiC materials were systematically summarized. It was found that the Tersoff potential was the most widely applied potential function for the MD simulation of SiC materials. The construction of more accurate potential functions for special application fields was an important development trend of potential functions. In the MD simulation of SiC properties, the thermal properties and mechanical properties, including thermal conductivity, hardness, elastic modulus, etc., were mainly studied. The correlation between MD simulations of microscopic processes and the properties of macroscopic materials, as well as the methods for obtaining different property parameters, were summarized. In the MD simulation of SiC preparation, ion implantation, polishing, sputtering, deposition, crystal growth, amorphization, etc., were mainly studied. The chemical vapor deposition (CVD) and sintering methods commonly applied in the preparation of SiC nuclear materials were reported rarely and needed to be further studied. In the MD simulation of SiC performance, most of the present studies were related to SiC applications in the nuclear energy research. The irradiation damage simulation in the field of nuclear materials was studied most widely. It can be found that SiC materials in the field of nuclear materials study were a very important topic. Finally, the future perspective of MD simulation studies of SiC materials were given, and development suggestions were summarized. This paper is helpful for understanding and mastering the general method of computation material science aimed at the multi-level analysis. It also has a good reference value in the field of SiC material study and MD method study.

show abstract

Structural phase transition and amorphization in hexagonal SiC subjected to dynamic loading

Cited by 12 publications

References 58 publications

Quasi-plastic deformation mechanisms and inverse Hall–Petch relationship in nanocrystalline boron carbide under compression

Quasi-plastic deformation mechanisms and inverse Hall–Petch relationship in nanocrystalline boron carbide under compression

A Genetic Algorithm Trained Machine-Learned Interatomic Potential for the Silicon–Carbon System

Molecular Dynamics Simulation Studies of Properties, Preparation, and Performance of Silicon Carbide Materials: A Review

Contact Info

Product

Resources

About