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《工程(英文)》 >> 2023年 第24卷 第5期 doi: 10.1016/j.eng.2022.06.027

科学中的第五范式——以智能驱动的材料设计为例

a Science and Technology on Parallel and Distributed Processing Laboratory, National University of Defense Technology, Changsha 410073, China
b Laboratory of Software Engineering for Complex Systems, National University of Defense Technology, Changsha 410073, China
c National Supercomputing Center in Changsha, Changsha 410082, China
d College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China
e Institute of Chemical Biology and Nanomedicine, State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China
f Department of Applied Physics, School of Physics and Electronics, Hunan University, Changsha 410082, China
g Department of Computer Science, State University of New York, New Paltz, NY 12561, USA

收稿日期: 2021-12-08 修回日期: 2022-06-06 录用日期: 2022-06-29 发布日期: 2023-04-14

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摘要

材料科学研究正在进入“机器学习+大数据”为标志的数据驱动范式阶段,预示着以机器学习为代表的智能系统融入传统的材料科学计算,具备数据挖掘和知识发现的智能驱动能力。在此,本研究通过在天河一号超级计算机系统上构建的为催化材料专门设计的典型平台案例,生动地阐明了第五范式的本质,旨在促进第五范式在其他领域的发展。第五范式平台主要包括模型自动构建(原始数据提取)、指纹自动构建(神经网络特征选择)以及跨学科知识串联的重复迭代(“火山图”)。与分解一起进行的是对迭代中实现的体系结构的性能评估。通过讨论,第五范式的智能驱动平台可以极大地简化和改进研究中极其繁琐和具有挑战性的工作,并通过补偿机器学习中样本的不足,以及替代一些计算资源不足导致的数值计算,实现数值计算与机器学习的相互反馈,加快探索过程。跨学科专家的协同作用和对实时数据需求的急剧增长仍然是一个挑战。我们相信,对第五范式平台的关注可以为其在其他领域的应用铺平道路。

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