有机合成中的机器学习进步:人工智能在化学中应用的重点探索

Rizvi Syed Aal E Ali , Jiaolong Meng , Muhammad Ehtisham Ibraheem Khan , Xuefeng Jiang
{"title":"有机合成中的机器学习进步:人工智能在化学中应用的重点探索","authors":"Rizvi Syed Aal E Ali ,&nbsp;Jiaolong Meng ,&nbsp;Muhammad Ehtisham Ibraheem Khan ,&nbsp;Xuefeng Jiang","doi":"10.1016/j.aichem.2024.100049","DOIUrl":null,"url":null,"abstract":"<div><p>Artificial intelligence (AI) is driving a revolution in chemistry, reshaping the landscape of molecular design. This review explores AI’s pivotal roles in the field of organic synthesis applications. AI accurately predicts reaction outcomes, controls chemical selectivity, simplifies synthesis planning, accelerates catalyst discovery, and fuels material innovation and so on. It seamlessly integrates data-driven algorithms with chemical intuition to redefine molecular design. As AI chemistry advances, it promises accelerated research, sustainability, and innovative solutions to chemistry’s pressing challenges. The fusion of AI and chemistry is poised to shape the field’s future profoundly, offering new horizons in precision and efficiency. This review encapsulates the transformation of AI in chemistry, marking a pivotal moment where algorithms and data converge to revolutionize the world of molecules.</p></div>","PeriodicalId":72302,"journal":{"name":"Artificial intelligence chemistry","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949747724000071/pdfft?md5=ca6a79f1c6ae5ed3980ec0ff3589b022&pid=1-s2.0-S2949747724000071-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Machine learning advancements in organic synthesis: A focused exploration of artificial intelligence applications in chemistry\",\"authors\":\"Rizvi Syed Aal E Ali ,&nbsp;Jiaolong Meng ,&nbsp;Muhammad Ehtisham Ibraheem Khan ,&nbsp;Xuefeng Jiang\",\"doi\":\"10.1016/j.aichem.2024.100049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Artificial intelligence (AI) is driving a revolution in chemistry, reshaping the landscape of molecular design. This review explores AI’s pivotal roles in the field of organic synthesis applications. AI accurately predicts reaction outcomes, controls chemical selectivity, simplifies synthesis planning, accelerates catalyst discovery, and fuels material innovation and so on. It seamlessly integrates data-driven algorithms with chemical intuition to redefine molecular design. As AI chemistry advances, it promises accelerated research, sustainability, and innovative solutions to chemistry’s pressing challenges. The fusion of AI and chemistry is poised to shape the field’s future profoundly, offering new horizons in precision and efficiency. This review encapsulates the transformation of AI in chemistry, marking a pivotal moment where algorithms and data converge to revolutionize the world of molecules.</p></div>\",\"PeriodicalId\":72302,\"journal\":{\"name\":\"Artificial intelligence chemistry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2949747724000071/pdfft?md5=ca6a79f1c6ae5ed3980ec0ff3589b022&pid=1-s2.0-S2949747724000071-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Artificial intelligence chemistry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949747724000071\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial intelligence chemistry","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949747724000071","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

人工智能(AI)正在推动化学领域的一场革命,重塑分子设计的格局。本综述探讨了人工智能在有机合成应用领域的关键作用。人工智能可以准确预测反应结果、控制化学选择性、简化合成规划、加速催化剂发现以及推动材料创新等。它将数据驱动算法与化学直觉无缝结合,重新定义了分子设计。随着人工智能化学的发展,它有望加速研究、实现可持续发展,并为化学面临的紧迫挑战提供创新解决方案。人工智能与化学的融合将深刻塑造该领域的未来,为精确性和效率开辟新天地。这篇综述概括了人工智能在化学领域的变革,标志着算法与数据融合以彻底改变分子世界的关键时刻。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Machine learning advancements in organic synthesis: A focused exploration of artificial intelligence applications in chemistry

Artificial intelligence (AI) is driving a revolution in chemistry, reshaping the landscape of molecular design. This review explores AI’s pivotal roles in the field of organic synthesis applications. AI accurately predicts reaction outcomes, controls chemical selectivity, simplifies synthesis planning, accelerates catalyst discovery, and fuels material innovation and so on. It seamlessly integrates data-driven algorithms with chemical intuition to redefine molecular design. As AI chemistry advances, it promises accelerated research, sustainability, and innovative solutions to chemistry’s pressing challenges. The fusion of AI and chemistry is poised to shape the field’s future profoundly, offering new horizons in precision and efficiency. This review encapsulates the transformation of AI in chemistry, marking a pivotal moment where algorithms and data converge to revolutionize the world of molecules.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Artificial intelligence chemistry
Artificial intelligence chemistry Chemistry (General)
自引率
0.00%
发文量
0
审稿时长
21 days
期刊最新文献
Molecular similarity: Theory, applications, and perspectives Large-language models: The game-changers for materials science research Conf-GEM: A geometric information-assisted direct conformation generation model Top 20 influential AI-based technologies in chemistry User-friendly and industry-integrated AI for medicinal chemists and pharmaceuticals
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1