高分子科学中机器学习和人工智能的进展综述

Q3 Materials Science
Sheetal Mavi, Sarita Kadian, Pradeepta Kumar Sarangi, Ashok Kumar Sahoo, Shruti Singh, M. Z. A. Yahya, Nor Mas Mira Abd Rahman
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引用次数: 0

摘要

技术、医疗保健和运输只是历史上依赖聚合物基材料的一些行业。在过去的几个世纪里,创新聚合物材料的创造一直依赖于大量的实验和错误程序,这需要大量的资源和时间。为了探索机器学习(ML)和人工智能(AI)在材料发现、设计和优化方面的变革潜力,本文探讨了机器学习和人工智能在聚合物基材料研究中的集成。研究人员能够利用复杂的算法和计算模型来加速新型聚合物基材料的开发,这些材料具有更好的性能和功能。研究了机器学习和人工智能在聚合物研究中的应用,重点是这些技术如何刺激创新和扩大材料科学研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancements in Machine Learning and Artificial Intelligence in Polymer Science: A Comprehensive Review

Technology, health care, and transport are merely some of the industries that historically rely on polymer-based materials. In past centuries, the creation of innovative polymer materials has been dependent upon extensive experiments and error procedures that require an extensive number of resources as well as time. With the objective to explore the transformative potential of machine learning (ML) and artificial intelligence (AI) in material discovery, design, and optimization, this paper explores the integration of ML and AI in polymer-based materials research. Researchers are able to speed the development of new polymer-based materials with improved properties and functionalities by utilizing sophisticated algorithms and computational models. The use of ML and AI in polymer research is examined, with a focus on how these technologies may stimulate innovation and expand material science research.

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来源期刊
Macromolecular Symposia
Macromolecular Symposia Materials Science-Polymers and Plastics
CiteScore
1.50
自引率
0.00%
发文量
226
期刊介绍: Macromolecular Symposia presents state-of-the-art research articles in the field of macromolecular chemistry and physics. All submitted contributions are peer-reviewed to ensure a high quality of published manuscripts. Accepted articles will be typeset and published as a hardcover edition together with online publication at Wiley InterScience, thereby guaranteeing an immediate international dissemination.
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