摘要
由一位新闻记者兼机器人与机器学习的新闻编辑每日新闻-关于人工智能的最新研究结果已经发表。根据NewsRx记者来自中华民国四川的新闻，研究表明："主要由多酚类化合物组成的多酚B基材料因其独特的化学结构和生物活性而引起了广泛的关注。"本研究的资金支持包括四川省科技支持项目。我们的新闻记者从西南交大的研究中得到一句话：“然而，多酚类化合物的衍生物很多，导致多酚类材料的复杂性和多样性，传统的方法难以适应多酚类材料的快速发展。Machine Learning以其在预测性能、优化合成工艺和设计新材料方面的能力而闻名，”摘要:综述了近年来国内外多酚基材料和机器学习的研究进展,讨论了多酚基材料与机器学习的交叉,以及它们在生物医学、环境和能源领域的应用。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial in telligence have been published. According to news originating from Sichuan, Peop le’s Republic of China, by NewsRx correspondents, research stated, “Polyphenol-b ased materials, primarily composed of polyphenolic compounds, have attracted con siderable attention due to their unique chemical structures and biological activ ities.” Financial supporters for this research include Sichuan Province Science And Tech nology Support Program. Our news correspondents obtained a quote from the research from Southwest Jiaoto ng University: “However, there are many derivatives of polyphenols, resulting in the complexity and diversity of polyphenolbased materials. Traditional methods are difficult to meet the rapid development of polyphenol-based materials. Mach ine learning, known for its proficiency in predicting performance, optimizing sy nthesis processes, and designing novel materials, offers significant potential i n the intelligent design and applications of polyphenol-based materials. In this review, we summarize the recent advancements in the research and development of polyphenol-based materials and machine learning. The intersection of polyphenol -based materials and machine learning is also discussed, including their applica tions in biomedical, environmental, and energy fields.”
NETL
NSTL