机器学习潜能探索未知的第三种金属氧化物的稳定性和平衡结构
Seungwoo Hwang1, Jisu Jung1, Changho Hong1
1Department of Materials Science and Engineering and Research Institute of Advanced Materials, Seoul National University, Seoul 08826, Korea.
Journal of the American Chemical Society
|August 11, 2023
概括
研究人员使用先进的计算方法探索了新的三元金属氧化物. 他们发现了45种新的稳定氧化物系统,其中许多含有贵金属,进步了材料的发现.
科学领域:
- 材料科学
- 计算化学
- 固态化学
背景情况:
- 三级金属氧化物在众多应用中至关重要,并且在实验数据库中进行了目录.
- 然而,许多潜在的三元氧化物化合物的稳定性和结构仍然未被探索.
- 确定新的稳定三元氧化物对于技术进步至关重要.
研究的目的:
- 探究三元金属氧化物的未知化学空间.
- 预测新型三元氧化物中最低能量的晶体结构和稳定性.
- 使用计算方法发现新的稳定三元氧化物系统.
主要方法:
- 使用广泛的晶体结构预测方法.
- 使用机器学习潜力加速模拟.
- 检查了181个三元金属氧化物系统,确定了最低能量结构和代表性石化学.
主要成果:
- 发现了45个具有稳定化合物的三元氧化物系统.
- 大多数新发现的稳定氧化物都含有贵金属.
- 将发现与其他理论数据库进行比较,强调基于信息学的搜索的优点和局限性.
结论:
- 由机器学习加速的基于启发式结构的搜索对于发现新材料是有效的.
- 这种方法需要适度的计算资源, 使其成为未来材料发现的有希望的途径.
- 确定了稳定的三元氧化物,特别是那些含有贵金属的氧化物,需要进一步的实验研究.
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