数据驱动研制发光材料的策略与挑战

Strategies and Challenges of Data-driven Research and Discovery in Luminescent Materials

人工智能在高效处理数据、精准预测、自动化执行任务以及个性化服务等方面为人类的生产、生活和科学研究带来了极大的便利。机器学习与高通量计算在材料领域的广泛渗透与成功应用,也为发光材料的研制开辟了新路径——通过算法进行高效挖掘和大规模数据处理,加速新材料的筛选与设计,进而推动材料的创新发现与应用进程。本文综述了近年来基于数据驱动发光材料研究的前沿进展,从相关研究案例出发,对数据驱动材料研究进行全流程梳理,详细阐述发光材料研制场景下数据获取阶段的重要性及实施策略,并对如何提取表征材料性能的核心特征进行分析,同时探讨发光材料领域适用的模型选择与优化方案。最后,就当前数据驱动式发光材料研究面临诸如高质量数据匮乏、复杂结构-性能关联模型构建困难的问题,从发光材料数据库平台的构建、高通量实验的实施以及相应数据生产规范的建立等方向提出突破设想。

Artificial intelligence has been bringing a great of convenience for human in manufacture,life,science and technology,for its abilities of efficient data analyses,accurate prediction,automatic task executing,and personalized service.Machine learning and high-throughput computing have extensively permeated and successfully applied in the field of materials,opening up new horizons for innovative research and design methods in luminescent materials.By employing efficient algorithms for mining and processing large-scale data,the screening and design process of new materials is accelerated,thereby driving the discovery and application progress of novel materials.This article provides an overview of the recent advances in data-driven research on luminescent materials.Based on relevant research cases,it outlines the entire process of data-driven material research and elaborates on the importance and implementation strategies of data acquisition in the development of luminescent materials.It also conducts a thorough analysis of how to accurately extract core features that characterize material performance,while exploring algorithm selection strategies applicable to the field of luminescent materials.Finally,the bottleneck of the current research on data-driven luminescent materials is pointed out,such as a lack of high-quality data and difficulties in constructing complex structure-performance correlation models.It also provides an outlook on future development directions,with a particular emphasis on the construction of luminescent material database platforms,implementation of high-throughput experiments,and establishment of corresponding data production standards.