Automated robotic platforms in design and development of formulations
Automated robotic platforms in design and development of formulations
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DOI：
10.1002/aic.17248
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发表时间：
2021-03-03
期刊：
影响因子：
3.7
通讯作者：
Lapkin，Alexei A.
中科院分区：
文献类型：
--
作者：
Cao，Liwei;Russo，Danilo;Lapkin，Alexei A.
针对配方的产品设计是一个活跃且具有挑战性的研究领域。快节奏的市场、日益复杂的产品以及可持续发展范式的实际转换带来的新挑战要求重新审查现有的理论框架，以纳入商业和研究数字化这一新现实带来的优势。在这项工作中，我们审查了现有的方法，清楚地阐述了自动化和机器学习指导的优化在更广泛的框架中的作用。从这一点出发，我们回顾了用于配方产品设计的自动化硬件和软件的发展现状，并确定了未来研究的开放挑战。对自动发现、扩大规模和多阶段优化等新兴领域进行了展望，并在完全数字化的研发工作流程的一般背景下提供了现有连接的统一图景。
Product design for formulations is an active and challenging area of research. The new challenges of a fast‐paced market, products of increasing complexity, and practical translation of sustainability paradigms require to re‐examine the existing theoretical frameworks to include the advantages deriving from the new reality of digitalization of business and research. In this work, we review the existing approaches, clearly stating the role of automation and machine‐learning‐guided optimization in the broader framework. Moving from this, we review the state of the art of automated hardware and software for formulated product design, and identify the open challenges for future research. Perspectives are given on the emerging fields of automated discovery, scale‐up, and multistage optimization, and a unitary picture of the existing connections is provided, in the general context of a completely digital R&D workflow.