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Big Data Approach on Polymer Materials: Fundamental, Progress and Challenge
- ACTA POLYMERICA SINICA Vol. 53, Issue 6, Pages: 564-580(2022)
- 作者机构：
1.中国科学院长春应用化学研究所 高分子化学与物理国家重点实验室 长春 130022
2.中国科学技术大学应用化学与工程学院 合肥 230026
- 作者简介：
- 基金信息：
DOI：10.11777/j.issn1000-3304.2021.21360
CLC：Published：20 June 2022，
Published Online：14 March 2022，
Received：23 November 2021，
Revised：07 January 2022，
- 稿件说明：
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刘伦洋,丁芳,李云琦.高分子材料大数据研究：共性基础、进展及挑战[J].高分子学报,2022,53(06):564-580.
Liu Lun-yang,Ding Fang,Li Yun-qi.Big Data Approach on Polymer Materials: Fundamental, Progress and Challenge[J].ACTA POLYMERICA SINICA,2022,53(06):564-580.
刘伦洋,丁芳,李云琦.高分子材料大数据研究：共性基础、进展及挑战[J].高分子学报,2022,53(06):564-580. DOI： 10.11777/j.issn1000-3304.2021.21360.
Liu Lun-yang,Ding Fang,Li Yun-qi.Big Data Approach on Polymer Materials: Fundamental, Progress and Challenge[J].ACTA POLYMERICA SINICA,2022,53(06):564-580. DOI： 10.11777/j.issn1000-3304.2021.21360.
摘要
介绍了作为一种新的认知范式，大数据研究常见和前沿算法及其应用在高分子材料研究中的共性基础，围绕材料的基础与应用研究聚焦的定量组成-工艺-结构-性质-性能关系，剖析了该关系中的要素和可数值化、定量化的资源和途径. 进而系统介绍近4年在高分子材料的合成与自组装、机械热性质、光电声磁性质、分离性质和加工性质等方面大数据研究的一些典型进展，梳理了当前高分子材料大数据研究的难题和挑战，对这一新兴快速发展方向和一段时间内可能的突破进行了展望.
Abstract
Big data approach
a new paradigm for data-driven wisdom paces together with conventional experimental
theoretical and simulation ways. The core in the application of big data study in material researches is at the composition-process-structure-property-performance relationship (CPSPPr). The digitalization and computational efforts
concepts
tools and resources to enable the subterms in the CPSPPr to cover fundamental research and scalable production will be presented. The big data approach can fully utilize the merits for the "black-box" of emerging machine learning algorithms
which allows for the construction of much more quantitative correlations beyond conventional rationality. It provides fantastic wisdom in reward for the discovery and the manufacture of new materials from the inherently frustrated multiple scales
broadly distributed
weak but accumulatively-strong response of polymers. We hereby reviewed such representative progresses in the innovation of polymer materials wholly or partially using big data approach in the last four years. These progresses are grouped as: polymer synthesis and self-assembly
mechanical and thermal properties
optic-electric-magnetic-acoustic properties and membranes for separation. The overall progress for the application of big data approach in the research of polymer materials is lagging in the comparison with that in inorganic or small-molecular materials. We then enumerated a number of challenges and possible short-term breakthroughs before the dawn of burst for big data in the reshape of the research and the production of polymer materials.
关键词
高分子材料大数据组成-工艺-结构-性质-性能关系计算辅助材料设计
Keywords
Polymer materialBig dataComposition-process-structure-property-performance relationshipComputer aided material design
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