Epitaxy of III-nitrides on two-dimensional materials and its applications

Xu, Yu; Wang, Jianfeng; Cao, Bing; Xu, Ke

doi:10.1088/1674-1056/ac921f

Cited by 4 publications

(2 citation statements)

References 113 publications

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“…Optoelectronic material processes typically involve tuning multiple parameters and variables with complex interrelationships. [132,133] ML can process high-dimensional data and find complex correlations between parameters to optimize the process.…”

Section: Process Optimizationmentioning

confidence: 99%

Applications and potentials of machine learning in optoelectronic materials research: An overview and perspectives

Zhang 张,

Fu 付

2023

Chinese Phys. B

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Optoelectronic materials are essential for today's scientific and technological development, and machine learning provides new ideas and tools for their research. In this paper, we first summarize the development history of optoelectronic materials and how materials informatics drives the innovation and progress of optoelectronic materials and devices. Then, we introduce the development of machine learning and its general process in optoelectronic materials and describe the specific implementation methods. We focus on the cases of machine learning in several application scenarios of optoelectronic materials and devices, including the methods related to crystal structure, properties (defects, electronic structure) research, materials and devices optimization, material characterization, and process optimization. In summarizing the algorithms and feature representations used in different studies, it is noted that prior knowledge can improve optoelectronic materials design, research, and decision-making processes. Finally, the prospect of machine learning applications in optoelectronic materials is discussed, along with current challenges and future directions. This paper comprehensively describes the application value of machine learning in optoelectronic materials research and aims to provide reference and guidance for the continuous development of this field.

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Section: Process Optimizationmentioning

confidence: 99%

Applications and potentials of machine learning in optoelectronic materials research: An overview and perspectives

Zhang 张,

Fu 付

2023

Chinese Phys. B

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“…[11] Xu et al overview several methods of preparing various 2D materials, including recent progress and applications of III-nitrides for optoelectronic devices. [12] In energy materials and devices, we have collected five articles covering DFT-based energy materials design, as well as batteries and solar cells. We start with a perspective article by Kang and co-authors.…”

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confidence: 99%