数据丰富的动态优化流动实验

IF 9.3 2区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Current Opinion in Green and Sustainable Chemistry Pub Date : 2024-04-08 DOI:10.1016/j.cogsc.2024.100921
Jason D. Williams , Peter Sagmeister , C. Oliver Kappe
{"title":"数据丰富的动态优化流动实验","authors":"Jason D. Williams ,&nbsp;Peter Sagmeister ,&nbsp;C. Oliver Kappe","doi":"10.1016/j.cogsc.2024.100921","DOIUrl":null,"url":null,"abstract":"<div><p>Flow chemistry is having an increasing influence on manufacturing in the chemical industry, but significant barriers remain in the development of these continuous processes. Dynamic flow experiments have the potential to democratize and accelerate process development in a data-rich manner, reducing time and material wastage. Models based on the data gathered can also be leveraged to decrease waste in a manufacturing environment. Here, we summarize the literature reports of dynamic flow experiments (most of which are from the past 5 years), with a focus on experiment design, process analytics, and utilization of the resulting data. Finally, an example of dynamic experiments in pharmaceutical development is discussed in detail. A higher uptake of dynamic experiments in industrial environments in the coming years will undoubtedly facilitate greener manufacturing processes.</p></div>","PeriodicalId":54228,"journal":{"name":"Current Opinion in Green and Sustainable Chemistry","volume":"47 ","pages":"Article 100921"},"PeriodicalIF":9.3000,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452223624000427/pdfft?md5=c5a85c6dc4eeecf664fe0b5c554c3844&pid=1-s2.0-S2452223624000427-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Dynamic flow experiments for data-rich optimization\",\"authors\":\"Jason D. Williams ,&nbsp;Peter Sagmeister ,&nbsp;C. Oliver Kappe\",\"doi\":\"10.1016/j.cogsc.2024.100921\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Flow chemistry is having an increasing influence on manufacturing in the chemical industry, but significant barriers remain in the development of these continuous processes. Dynamic flow experiments have the potential to democratize and accelerate process development in a data-rich manner, reducing time and material wastage. Models based on the data gathered can also be leveraged to decrease waste in a manufacturing environment. Here, we summarize the literature reports of dynamic flow experiments (most of which are from the past 5 years), with a focus on experiment design, process analytics, and utilization of the resulting data. Finally, an example of dynamic experiments in pharmaceutical development is discussed in detail. A higher uptake of dynamic experiments in industrial environments in the coming years will undoubtedly facilitate greener manufacturing processes.</p></div>\",\"PeriodicalId\":54228,\"journal\":{\"name\":\"Current Opinion in Green and Sustainable Chemistry\",\"volume\":\"47 \",\"pages\":\"Article 100921\"},\"PeriodicalIF\":9.3000,\"publicationDate\":\"2024-04-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2452223624000427/pdfft?md5=c5a85c6dc4eeecf664fe0b5c554c3844&pid=1-s2.0-S2452223624000427-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Opinion in Green and Sustainable Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2452223624000427\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Green and Sustainable Chemistry","FirstCategoryId":"92","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2452223624000427","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

流动化学对化学工业生产的影响越来越大,但在这些连续工艺的开发过程中仍存在重大障碍。动态流动实验有可能以数据丰富的方式实现工艺开发的民主化和加速,从而减少时间和材料浪费。基于所收集数据的模型也可用于减少生产环境中的浪费。在此,我们总结了有关动态流程实验的文献报告(其中大部分是过去 5 年的报告),重点介绍了实验设计、流程分析和所得数据的利用。最后,我们详细讨论了制药开发中的动态实验实例。未来几年,动态实验在工业环境中的普及无疑将促进更环保的生产流程。
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
Dynamic flow experiments for data-rich optimization

Flow chemistry is having an increasing influence on manufacturing in the chemical industry, but significant barriers remain in the development of these continuous processes. Dynamic flow experiments have the potential to democratize and accelerate process development in a data-rich manner, reducing time and material wastage. Models based on the data gathered can also be leveraged to decrease waste in a manufacturing environment. Here, we summarize the literature reports of dynamic flow experiments (most of which are from the past 5 years), with a focus on experiment design, process analytics, and utilization of the resulting data. Finally, an example of dynamic experiments in pharmaceutical development is discussed in detail. A higher uptake of dynamic experiments in industrial environments in the coming years will undoubtedly facilitate greener manufacturing processes.

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
CiteScore
16.00
自引率
2.20%
发文量
140
审稿时长
103 days
期刊介绍: The Current Opinion journals address the challenge specialists face in keeping up with the expanding information in their fields. In Current Opinion in Green and Sustainable Chemistry, experts present views on recent advances in a clear and readable form. The journal also provides evaluations of the most noteworthy papers, annotated by experts, from the extensive pool of original publications in Green and Sustainable Chemistry.
期刊最新文献
Recent advances in plasma-based methane reforming for syngas production Green ammonia synthesis technology that does not require H2 gas: Reaction technology and prospects for ammonia synthesis using H2O as a direct hydrogen source Machine learning to support prospective life cycle assessment of emerging chemical technologies Plasma treating water for nitrate based nitrogen fertilizer - A review of recent device designs Atmospheric-pressure plasmas for NOx production: Short review on current status
×
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