Revealing Hidden Patterns through Chemical Intuition and Interpretable Machine Learning: A Case Study of Binary Rare-Earth Intermetallics RX,Chemistry of Materials

当前位置： X-MOL 学术 › Chem. Mater. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Revealing Hidden Patterns through Chemical Intuition and Interpretable Machine Learning: A Case Study of Binary Rare-Earth Intermetallics RX
Chemistry of Materials ( IF 7.2 ) Pub Date : 2023-01-30 , DOI: 10.1021/acs.chemmater.2c02425
Volodymyr Gvozdetskyi ₁ , Balaranjan Selvaratnam ₁ , Anton O. Oliynyk _{1,

2} , Arthur Mar ₁

Affiliation

Machine learning algorithms have been applied successfully in many areas of materials chemistry but often suffer from an inability to extract chemical insight. To demonstrate that an approach combining machine learning and chemical intuition can be effective in generating interpretable models, the structures of binary equiatomic rare-earth intermetallics RX, whose relationships have long defied understanding, were investigated as a case study. A structure map was developed based on only two parameters, which are derived from simple elemental descriptors (atomic number, period and group numbers, radii, and electronegativity) of the R and X components. This map reveals the previously hidden patterns of structural regularities of RX intermetallics. It explains the preference for CsCl-, TlI-, or FeB-type structures among these compounds, predicts the structures of missing members, rationalizes the occurrence of metastable phases and polymorphic transformations, and offers strategies for structure stabilization through the addition of a third component.

中文翻译：

通过化学直觉和可解释的机器学习揭示隐藏的模式：二元稀土金属间化合物 RX 的案例研究

机器学习算法已成功应用于材料化学的许多领域，但往往无法提取化学洞察力。为了证明结合机器学习和化学直觉的方法可以有效地生成可解释的模型，二元等原子稀土金属间化合物RX的结构作为案例研究进行了研究，其关系长期以来一直无法理解。结构图仅基于两个参数开发，这两个参数源自R和X组件的简单元素描述符（原子序数、周期和族数、半径和电负性）。该图揭示了RX之前隐藏的结构规律性模式金属间化合物。它解释了这些化合物对 CsCl-、TlI- 或 FeB 型结构的偏好，预测缺失成员的结构，合理化亚稳相和多晶型转变的发生，并提供通过添加第三种成分稳定结构的策略.

更新日期：2023-01-30

点击分享查看原文

点击收藏

阅读更多本刊最新论文本刊介绍/投稿指南11