José G. B. A. Lima, Anderson S. L. Gomes, Adiel T. de Almeida-Filho
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引用次数: 0
摘要
人工智能在材料科学领域的应用减少了开发新材料的工作量和成本。尽管人工智能仍是一个新兴的研究领域,但一些有前景的成果和技术已成功应用于智能材料的发现。本文对人工智能(AI)方法在材料科学领域的应用进行了系统的文献综述,介绍了通过人工智能实现智能材料的文献和趋势。此次文献综述从 1995 年至 2022 年期间的 Web of Science 和 Scopus 数据库中检索了 527 篇文章和评论。结果显示,人工智能在材料科学领域的应用数量以及引用人工智能应用的出版物数量都在增长。在这些结果中,确定了在材料科学中使用的最流行和最相关的算法,这些算法具有广泛的应用可能性和未来发展方向。
Intelligent Materials Improvement Through Artificial Intelligence Approaches: A Systematic Literature Review
Artificial intelligence applications to enhance materials science have reduced the efforts and costs of developing new materials. Although it is still a recent research field, some promising results, and techniques have successfully been deployed for intelligent material discovery. This paper presents a systematic literature review considering applications of Artificial Intelligence (AI) approaches within the Materials Science context, presenting the literature and trends on intelligent materials through Artificial Intelligence. For this literature review, 527 articles and reviews were retrieved from Web of Science and Scopus databases from 1995 to 2022. The results showed that the number of AI applications in Materials Science has grown as well as the number of publications citing AI applications. Among the results, the most popular and relevant algorithms used in materials science are identified with a wide diversity of application possibilities with future directions.
期刊介绍:
Archives of Computational Methods in Engineering
Aim and Scope:
Archives of Computational Methods in Engineering serves as an active forum for disseminating research and advanced practices in computational engineering, particularly focusing on mechanics and related fields. The journal emphasizes extended state-of-the-art reviews in selected areas, a unique feature of its publication.
Review Format:
Reviews published in the journal offer:
A survey of current literature
Critical exposition of topics in their full complexity
By organizing the information in this manner, readers can quickly grasp the focus, coverage, and unique features of the Archives of Computational Methods in Engineering.