用于从粉末X射线衍射数据中确定无机晶体结构的等价扩散溶液
Dongfang Yu1,2, Zhewen Zhu1,2, Fucheng Leng3
1School of Materials Science and Engineering, Zhejiang University, Hangzhou, China.
Nature communications
|February 27, 2026
概括
我们开发了一个快速的人工智能模型,从X射线衍射模式确定无机晶体结构,提高材料发现的准确性和速度.
科学领域:
- 材料科学 材料科学 材料科学
- 晶体学 晶体学是指结晶学.
- 人工智能的人工智能
背景情况:
- 确定晶体结构对于理解材料特性至关重要.
- 从粉末X射线衍射 (PXRD) 数据中解决结构是具有挑战性的,通常需要人工专家解释.
- 现有的数据库包含许多不完整或不准确的结构模型.
研究的目的:
- 开发一种自动化方法,从PXRD模式中直接推断原子坐标.
- 为了显著加快晶体结构溶液的过程.
- 提高材料数据库中结构模型的准确性和完整性.
主要方法:
- 开发基于神经网络的等价图形扩散模型.
- 从PXRD数据直接推断原子坐标,从随机噪声开始.
- 坐标的代精细化,以产生与实验模式相匹配的化学有效结构.
主要成果:
- 该模型的成功率很高:模拟数据集的成功率为82.3%,实验数据集的成功率为81.6%.
- 晶体结构解决方案在单个GPU上平均0.6秒内实现,比以前的方法快了数量级.
- 成功纠正了39个不利的数据库条目,并完成了912个缺少原子位置的条目.
结论:
- 开发的AI模型提供了一个强大的和自动化的解决方案,用于从衍射数据中确定晶体结构.
- 这种方法显著提高了材料表征的速度和准确性.
- 它为通过闭环系统的自主材料发现铺平了道路.
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