Chemistry INformEd MAchine learning in emulsion polymerization processes and products

乳液聚合过程和产品中的化学信息机器学习

• 批准号: EP/X034763/1
• 负责人: Alexei Lapkin
• 金额: $ 33.8万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX034763%2F1
• 关键词: Chemistry; INformEd; MAchine; learning; emulsion

Machine learning (ML) systems continue to revolutionize many aspects of daily life, but despite their immense potential have yet to impact significantly in polymer science. One major issue that is hindering the more widespread use of machine learning in polymer science, and many other physical sciences, liesin the challenges in amassing sufficient data to efficiently train machine learning models. This in itself is not necessarily a problem, and is an issue frequently encountered in the machine learning field, but can only be resolved by a thorough understanding of the science behind the problem of interest. CINEMA aims to providing a training platform that will allow the next generation of polymer scientists to take polymer science into the 21st century through incorporating the fundamental knowledge gained over many years of research into the training of machine learning systems. Such a knowledge-driven machine learning approach puts the scientific issues of CINEMA at the forefront of the use of machine learning in fundamental scientific problems, and also provides the perfect training platform for the next generation of scientists, for whom the use of AI will be an invaluable tool.

机器学习（ML）系统继续革新日常生活的许多方面，但尽管它们具有巨大的潜力，但尚未对聚合物科学产生重大影响。阻碍机器学习在聚合物科学和许多其他物理科学中更广泛使用的一个主要问题在于积累足够数据以有效训练机器学习模型的挑战。这本身并不一定是一个问题，也是机器学习领域经常遇到的问题，但只有深入了解问题背后的科学才能解决。CINEMA旨在提供一个培训平台，使下一代聚合物科学家能够通过将多年研究获得的基础知识融入机器学习系统的培训中，将聚合物科学带入世纪。这种知识驱动的机器学习方法将CINEMA的科学问题置于机器学习在基础科学问题中的最前沿，并为下一代科学家提供了完美的培训平台，对他们来说，人工智能的使用将是一个宝贵的工具。