纳米制造
人工智能
转化式学习
计算机科学
机器学习
数字化制造
大数据
深度学习
纳米技术
制造工程
工程类
材料科学
数据挖掘
心理学
教育学
作者
Mutha Nandipati,Olukayode Fatoki,Salil Desai
出处
期刊:Materials
[MDPI AG]
日期:2024-04-02
卷期号:17 (7): 1621-1621
被引量:51
摘要
Nanomanufacturing and digital manufacturing (DM) are defining the forefront of the fourth industrial revolution—Industry 4.0—as enabling technologies for the processing of materials spanning several length scales. This review delineates the evolution of nanomaterials and nanomanufacturing in the digital age for applications in medicine, robotics, sensory technology, semiconductors, and consumer electronics. The incorporation of artificial intelligence (AI) tools to explore nanomaterial synthesis, optimize nanomanufacturing processes, and aid high-fidelity nanoscale characterization is discussed. This paper elaborates on different machine-learning and deep-learning algorithms for analyzing nanoscale images, designing nanomaterials, and nano quality assurance. The challenges associated with the application of machine- and deep-learning models to achieve robust and accurate predictions are outlined. The prospects of incorporating sophisticated AI algorithms such as reinforced learning, explainable artificial intelligence (XAI), big data analytics for material synthesis, manufacturing process innovation, and nanosystem integration are discussed.
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