机器学习破解过渡金属双金属配合物的隐秘行为
Deciphering Cryptic Behavior in Bimetallic Transition Metal Complexes with Machine Learning
摘要：
过渡金属配合物的合理定制对于解决能源利用和储存方面的突出挑战是必要的。在堆叠的“双层”配体结构中表现出金属-金属键合的杂环过渡金属络合物是一种新兴的、有吸引力的催化平台，但是在费力的合成努力之前预测它们的性质是具有挑战性的。我们展示了一种替代的，数据驱动的方法来揭示结构-性能的关系，合理的复杂的设计。我们定制基于图形表示的金属局部环境中使用的多元线性回归和核岭回归（KRR）模型的训练，这些杂原子络合物。专注于氧化电位，我们得到了一组28个实验表征的配合物，开发一个多元线性回归模型。在这个训练集上，我们实现了良好的准确性（平均绝对误差，MAE，为0.25 V），并保留了与新的配体结构看不见的实验数据的可转移性。我们在330种结构特征的异双金属化合物的子集上训练了KRR模型，以预测金属-金属键合的程度。该KRR模型预测测试集中的相对金属-金属键长在5%以内，并且对关键特征的分析揭示了基本原子贡献（例如，价电子构型）对复合物的行为影响最大。我们的工作提供了合理的设计指导，建议属性，包括正式的短比应该从一个时期转移到另一个。
英文摘要：
The rational tailoring of transition metal complexes is necessary to address outstanding challenges in energy utilization and storage. Heterobimetallic transition metal complexes that exhibit metal-metal bonding in stacked "double decker" ligand structures are an emerging, attractive platform for catalysis, but their properties are challenging to predict prior to laborious synthetic efforts. We demonstrate an alternative, data-driven approach to uncovering structure-property relationships for rational bimetallic complex design. We tailor graph-based representations of the metal-local environment for these heterobimetallic complexes for use in training of multiple linear regression and kernel ridge regression (KRR) models. Focusing on oxidation potentials, we obtain a set of 28 experimentally characterized complexes to develop a multiple linear regression model. On this training set, we achieve good accuracy (mean absolute error, MAE, of 0.25 V) and preserve transferability to unseen experimental data with a new ligand structure. We trained a KRR model on a subset of 330 structurally characterized heterobimetallics to predict the degree of metal-metal bonding. This KRR model predicts relative metal-metal bond lengths in the test set to within 5%, and analysis of key features reveals the fundamental atomic contributions (e.g., the valence electron configuration) that most strongly influence the behavior of complexes. Our work provides guidance for rational bimetallic design, suggesting that properties including the formal shortness ratio should be transferable from one period to another.
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