使用数据驱动的方法寻找冰的异质核化剂.
Zixuan Wang1, David E Oliver2, Andrew J Bissell2
1School of Chemistry and EaStCHEM Research School, University of Edinburgh, The King's Buildings, David Brewster Road, Edinburgh, EH9 3FJ, UK. c.morrison@ed.ac.uk.
Physical chemistry chemical physics : PCCP
|September 29, 2025
概括
一个新的高吞吐量工作流屏幕用于使用结构数据的冰核化剂. 该方法成功地确定了四个新的冰核子,为发现新材料提供了有效的第一步.
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.
- 物理化学 物理化学
背景情况:
- 异质核化对于像冰形成这样的相位过渡至关重要.
- 鉴定有效的核化剂是具有挑战性的,因为复杂的结构要求.
- 目前发现核化剂的方法往往是缓慢的和经验性的.
研究的目的:
- 开发一种高通量计算工作流程,用于识别潜在的异质冰核生成剂.
- 选一个庞大的无机化合物数据库以检查冰核化能力.
- 通过实验验证计算工作流程的预测.
主要方法:
- 开发了一个数据驱动的工作流程,以评估冰IH和潜在核子表面之间的结构合适性.
- 该模型考虑了晶体形态特征和米勒索引平面到 (333).
- 大量浸水实验被用来建立基于温度的核化行为标准,从而达到数值耐受性极限.
主要成果:
- 该工作流选了3500种金属氧化物和化物,根据几何匹配,预测了小比例的潜在冰核子.
- 对22种化合物的实验验证显示,预测准确率为64%.
- 确定了四个新的冰核子 (CeO2,WO3,Bi2O3,Ti2O3),铜管显示了冰核的特性.
结论:
- 开发的高通量工作流提供了一种高效的初始选方法,用于发现异质核化剂.
- 几何接口匹配,尽管简单,是冰核活动的有价值的预测器.
- 这种方法加速了用于相变应用的新材料的发现.
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