Networks and interfaces as catalysts for polymer materials innovation
Networks and interfaces as catalysts for polymer materials innovation
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DOI：
10.1016/j.xcrp.2022.101126
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发表时间：
2022-11-16
影响因子：
8.9
通讯作者：
Olsen, Bradley D.
中科院分区：
文献类型：
--
作者：
Deagen, Michael E.;Walsh, Dylan J.;Olsen, Bradley D.
自主实验系统让我们得以一睹未来的风采，闭环迭代循环（由机器执行并由人工智能 (AI) 和机器学习 (ML) 引导）在材料研究和开发中发挥基础作用。这种观点引起人们对网络和接口（人与机器之间以及人与机器之间）的作用的关注，以产生知识和加速创新。聚合物是一类具有巨大全球影响力的材料，为应用信息学和自动化应对紧迫的社会挑战提供了独特的机会。为了开发聚合物科学中的这些网络和接口，引入了聚合物技术创新社区资源 (CRIPT)——一个基于新型聚合物数据模型、表示、搜索和可视化技术的聚合物数据生态系统。正在进行的协同设计工作吸引了工业界、学术界和政府的利益相关者，以发现可快速采取行动、具有高影响力的机会，以建立网络、桥接接口并促进聚合物技术的创新。
Autonomous experimental systems offer a compelling glimpse into a future where closed-loop, iterative cycles-performed by machines and guided by artificial intelligence (AI) and machine learning (ML)-play a foundational role in materials research and development. This perspective draws attention to the roles of networks and interfaces-of and between humans and machines-for the purpose of generating knowledge and accelerating innovation. Polymers, a class of materials with massive global impact, present a unique opportunity for the application of informatics and automation to pressing societal challenges. To develop these networks and interfaces in polymer science, the Community Resource for Innovation in Polymer Technology (CRIPT)-a polymer data ecosystem based on novel polymer data model, representation, search, and visualization technologies-is introduced. The ongoing co-design efforts engage stakeholders in industry, academia, and government to uncover rapidly actionable, high-impact opportunities to build networks, bridge interfaces, and catalyze innovation in polymer technology.