English(EN)Beyond Structure: Revolutionising Materials Discovery via AI-Driven Synthesis Protocol-Property Relationships
人工智能通过关注合成协议和可制造性来革新材料发现。
作者PulseAugur 编辑部·[5 个来源]·
两篇新的arXiv论文提出将AI驱动的材料发现从以结构为中心的方法转变为以合成为先的方法。第一篇论文“超越结构”概述了一个将合成过程表示为机器可读协议的路线图，并使用生成模型来提出反应路径。第二篇论文“天生合格”引入了一个框架，该框架从自主开发的最初就嵌入了可制造性、成本和耐用性约束，以弥合实验室指标与工业可行性之间的差距。
AI
arXiv:2605.00313v1 Announce Type: cross Abstract: The current structure-centric paradigm in artificial intelligence (AI)-driven materials discovery, despite delivering thousands of candidate structures, is stalling at a critical barrier: the synthesizability gap. We argue that cl…
arXiv cs.AI
TIER_1English(EN)·Steven R. Spurgeon, Milad Abolhasani, Frederick Baddour, Ryan B. Comes, Vinayak P. Dravid, Hilary Egan, Patrick Emami, Robert W. Epps, Davi M. F\'ebba, Renae Gannon, E. Ashley Gaulding, Ayana Ghosh, Kenny Gruchalla, Grace Guinan, Taro Hitosugi, Michael Ho·
arXiv:2605.00639v1 Announce Type: cross Abstract: Autonomous science is transforming how we discover materials and chemical systems for advanced energy technologies. However, many initially promising systems never reach deployment. This "valley of death" stems from optimization t…
Autonomous science is transforming how we discover materials and chemical systems for advanced energy technologies. However, many initially promising systems never reach deployment. This "valley of death" stems from optimization that prioritizes laboratory metrics over industrial…
The current structure-centric paradigm in artificial intelligence (AI)-driven materials discovery, despite delivering thousands of candidate structures, is stalling at a critical barrier: the synthesizability gap. We argue that closing this gap demands a pivot to a synthesis-firs…
