Study of Grain Boundary: From Crystallization Engineering to Machine Learning
Abstract
:1. Introduction
2. Crystallization Engineering in Grain Boundaries
3. Machine Learning in Grain Boundaries
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Author | Semiconductor | Result Summary | Mobility | References |
---|---|---|---|---|
He et al. | TIPS pentacene | Semicrystalline polymer PEO modulated semiconductor diffusivity, crystallization, and grain boundary | 0.025 cm2/Vs | [200] |
He et al. | TIPS pentacene | Poly(butyl acrylate) polymer promoted semiconductor nucleation, alignment, and grain width | 0.11 cm2/Vs | [201] |
Wo et al. | TIPS pentacene | Different speeds of hollow capillary writing process impacted domain orientation and grain boundary | 0.8 cm2/Vs | [202] |
Hou et al. | TIPS pentacene | Vapor annealing using different solvents impacted the topography, grain boundary density, and further gas sensing properties | 0.15 cm2/Vs | [187] |
Chen et al. | TIPS pentacene | Solution casting system enabled good control of grain dimension and boundary in needle-shaped and isotropic-shaped domains | 0.91 ± 0.08 cm2/Vs | [203] |
Park et al. | TIPS pentacene | Ar gas injection resulted in crystal and grain boundary alignment in parallel with the current flow direction | 0.53 ± 0.02 cm2/Vs | [158] |
Shao et al. | TIPS pentacene | Solvent choice impacted grain boundary density and gas sensing performance | 30 ± 6 × 10−3 cm2/Vs | [204] |
Lee et al. | TIPS pentacene | Different substrate temperatures modulated grain boundary and charge transport | 0.44 ± 0.09 cm2/Vs | [205] |
Author | Material | Result Summary | Reference |
---|---|---|---|
Priedeman et al. | Nickle | Grain boundary crystallography is correlated with the atomic structural unit content | [230] |
Rosenbrock et al. | Nickle | Grain boundary mobility is impacted by the local atomic environments and grain boundary dislocations | [227] |
Rosenbrock et al. | Nickle | Grain boundary energies, mobility, and shear coupling are assessed | [228] |
Orme et al. | Mg alloy | Grain dimension and bulk dislocation density impact twin nucleation, while grain boundary and misorientation impact twin propagation | [231] |
Gomberg et al. | Aluminum | Atomistic grain boundary simulations are studied using a “process–structure–property” (PSP) paradigm | [223] |
Lawrence et al. | Aluminum oxide | Abnormal enlargement of minority grain growth is impacted by processing variables | [232] |
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He, Z.; Bi, S.; Asare-Yeboah, K. Study of Grain Boundary: From Crystallization Engineering to Machine Learning. Coatings 2025, 15, 164. https://doi.org/10.3390/coatings15020164
He Z, Bi S, Asare-Yeboah K. Study of Grain Boundary: From Crystallization Engineering to Machine Learning. Coatings. 2025; 15(2):164. https://doi.org/10.3390/coatings15020164
Chicago/Turabian StyleHe, Zhengran, Sheng Bi, and Kyeiwaa Asare-Yeboah. 2025. "Study of Grain Boundary: From Crystallization Engineering to Machine Learning" Coatings 15, no. 2: 164. https://doi.org/10.3390/coatings15020164
APA StyleHe, Z., Bi, S., & Asare-Yeboah, K. (2025). Study of Grain Boundary: From Crystallization Engineering to Machine Learning. Coatings, 15(2), 164. https://doi.org/10.3390/coatings15020164