Soft Matter Informatics: Current Progress and Challenges
Soft Matter Informatics: Current Progress and Challenges
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DOI：
10.1002/adts.201800129
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发表时间：
2018-11
影响因子：
3.3
通讯作者：
James S. Peerless;Nina J. B. Milliken;Thomas J. Oweida;Matthew D. Manning;Yaroslava G. Yingling
中科院分区：
文献类型：
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作者：
James S. Peerless;Nina J. B. Milliken;Thomas J. Oweida;Matthew D. Manning;Yaroslava G. Yingling
信息学或数据驱动发现的应用在许多领域都在增长，包括材料科学。大量现成的数据，结合高层次的统计算法，被证明在开发复杂的预测模型时非常有用，几乎没有人为监督或偏见。然而，在软物质领域，包括聚合物、液体、乳液、胶体和凝胶等复杂材料，采用信息学策略的速度比邻近领域要慢。本文讨论了软物质信息学的研究现状。软材料所面临的挑战，包括数据分类、多种长度尺度的不同程度的组织以及过程依赖的特性，需要研究人员采用独特的方法来开发软物质中强大的信息学方法。通过对几种聚合物的玻璃化转变温度的Flory-Fox方程的拟合，证明了目前从PoLyInfo数据库中提取和分析信息的能力。本进展报告旨在介绍和激发科学界关于信息学在探索软材料特性方面的显着潜力。
The number of applications of informatics or data‐driven discovery is growing in many fields, including materials science. The large amount of data that is readily available, combined with high‐level statistical algorithms, is proving to be extremely useful in developing complex predictive models with little to no human supervision or bias. However, in the field of soft matter, which includes complex materials such as polymers, liquids, emulsions, colloids, and gels, there is a slower adoption of informatics strategies than in adjacent fields. Here, the current state of soft matter informatics is discussed. Challenges specific to soft materials, including data classification, various degrees of organization at multiple length scales, and process‐dependent properties require unique approaches by researchers in order to develop robust informatics approaches in soft matter. The current ability to extract and analyze the information from the PoLyInfo database is demonstrated by the fitting of the Flory–Fox equation for glass transition temperature for several polymers. This Progress Report serves to introduce and excite the scientific community about the remarkable potential of informatics for exploring the properties of soft materials.