构建多模态模型，实现电子显微镜中材料原子结构的自主分析
Mind the Gap: Bridging the Divide Between AI Aspirations and the Reality of Autonomous Characterization
- 基于领域知识设计多模态模型，理解复杂原子系统
- 实现对电子显微图像的自动描述与分析
- 适合材料智能表征与自主实验系统研究者
材料科学在‘人工智能时代’呈现出不同面貌：合成、表征与建模各具挑战。本文聚焦电子显微镜中自主表征的巨大潜力，提出具备领域感知能力的多模态模型，可对复杂原子体系进行分析与描述。我们揭示了理论愿景与实际应用间的差距，展示近期进展的同时，指出实现真实世界鲁棒自主性所需的关键改进方向。
原文摘要 · Abstract (English)
What does materials science look like in the "Age of Artificial Intelligence?" Each materials domain-synthesis, characterization, and modeling-has a different answer to this question, motivated by unique challenges and constraints. This work focuses on the tremendous potential of autonomous characterization within electron microscopy. We present our recent advancements in developing domain-aware, multimodal models for microscopy analysis capable of describing complex atomic systems. We then address the critical gap between the theoretical promise of autonomous microscopy and its current practical limitations, showcasing recent successes while highlighting the necessary developments to achieve robust, real-world autonomy.
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