Xiangning Zhang, Li Zhou, Guodong Feng, Kai Xi, Hassan Algadi, Mengyao Dong
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The incorporation of machine learning algorithms in laser manufacturing processes further optimizes parameters, enhances real-time error correction, and improves quality control. This review uniquely emphasizes the synergistic effects of combining laser technologies with artificial intelligence, presenting a comprehensive comparison of different laser machining techniques and their practical applications. By addressing current limitations and exploring new research avenues, this review highlights the significant advancements and future potential in laser-based manufacturing technologies.</p><h3>Graphic Abstract</h3>\n<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":7220,"journal":{"name":"Advanced Composites and Hybrid Materials","volume":"8 1","pages":""},"PeriodicalIF":23.2000,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Laser technologies in manufacturing functional materials and applications of machine learning-assisted design and fabrication\",\"authors\":\"Xiangning Zhang, Li Zhou, Guodong Feng, Kai Xi, Hassan Algadi, Mengyao Dong\",\"doi\":\"10.1007/s42114-024-01154-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The integration of laser technologies and machine learning has marked a transformative era in functional materials manufacturing. 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This review uniquely emphasizes the synergistic effects of combining laser technologies with artificial intelligence, presenting a comprehensive comparison of different laser machining techniques and their practical applications. 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Laser technologies in manufacturing functional materials and applications of machine learning-assisted design and fabrication
The integration of laser technologies and machine learning has marked a transformative era in functional materials manufacturing. This review highlights how AI-driven methods optimize laser-assisted processes, enabling real-time error correction and parameter adjustment. By comparing different laser machining techniques and emphasizing their synergy with machine learning, this paper provides insights into the future of smart manufacturing and new research avenues for improving material performance. Laser-assisted processes, such as laser cutting and laser-induced oxidation, improve precision, reduce thermal damage, and enable the fabrication of complex geometries. Additionally, laser cladding and coating technologies enhance interfacial properties. The incorporation of machine learning algorithms in laser manufacturing processes further optimizes parameters, enhances real-time error correction, and improves quality control. This review uniquely emphasizes the synergistic effects of combining laser technologies with artificial intelligence, presenting a comprehensive comparison of different laser machining techniques and their practical applications. By addressing current limitations and exploring new research avenues, this review highlights the significant advancements and future potential in laser-based manufacturing technologies.
期刊介绍:
Advanced Composites and Hybrid Materials is a leading international journal that promotes interdisciplinary collaboration among materials scientists, engineers, chemists, biologists, and physicists working on composites, including nanocomposites. Our aim is to facilitate rapid scientific communication in this field.
The journal publishes high-quality research on various aspects of composite materials, including materials design, surface and interface science/engineering, manufacturing, structure control, property design, device fabrication, and other applications. We also welcome simulation and modeling studies that are relevant to composites. Additionally, papers focusing on the relationship between fillers and the matrix are of particular interest.
Our scope includes polymer, metal, and ceramic matrices, with a special emphasis on reviews and meta-analyses related to materials selection. We cover a wide range of topics, including transport properties, strategies for controlling interfaces and composition distribution, bottom-up assembly of nanocomposites, highly porous and high-density composites, electronic structure design, materials synergisms, and thermoelectric materials.
Advanced Composites and Hybrid Materials follows a rigorous single-blind peer-review process to ensure the quality and integrity of the published work.