提出功能单元新概念，打通材料结构与性能的跨尺度设计桥梁。
Functional Unit: A New Perspective on Materials Science Research Paradigms
- 引入功能单元（FUs）概念，重构材料结构-性能关联理解。
- 推动从传统工艺-结构-性能范式向数据驱动AI范式转型。
- 适合材料设计、人工智能与多尺度模拟方向研究者参考。
新材料长期标志文明水平，是技术进步与社会变革的动力。经典结构-性能关联曾是材料科学的核心，但现有知识难以适应纯粹数据驱动的新材料发现需求。本文提出功能单元（Functional Units, FUs）的概念，填补材料结构-性能关联理解与知识传承的空白，应对“成分-微观结构”范式向数据驱动人工智能范式转型的挑战。首先，概述了从早期“工艺-结构-性能-性能”范式到当前数据驱动AI趋势的研究范式演变。其次，总结了各类材料体系中功能单元表征的最新进展，强调其在多尺度材料设计中的关键作用。最后，探讨功能单元如何融入新兴的AI驱动材料科学范式，分析计算材料创新中的机遇与挑战。
原文摘要 · Abstract (English)
New materials have long marked the civilization level, serving as an impetus for technological progress and societal transformation. The classic structure-property correlations were key of materials science and engineering. However, the knowledge of materials faces significant challenges in adapting to exclusively data-driven approaches for new material discovery. This perspective introduces the concepts of functional units (FUs) to fill the gap in understanding of material structure-property correlations and knowledge inheritance as the "composition-microstructure" paradigm transitions to a data-driven AI paradigm transitions. Firstly, we provide a bird's-eye view of the research paradigm evolution from early "process-structure-properties-performance" to contemporary data-driven AI new trend. Next, we highlight recent advancements in the characterization of functional units across diverse material systems, emphasizing their critical role in multiscale material design. Finally, we discuss the integration of functional units into the new AI-driven paradigm of materials science, addressing both opportunities and challenges in computational materials innovation.
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