Rahbani Noura, de Silva Piotr, Baudrin Emmanuel
Laboratoire de Réactivité et Chimie des Solides, CNRS UMR7314, Université de Picardie Jules Verne, 33 Rue St-Leu, 80039, Amiens, Cedex, France.
Department of Energy Conversion and Storage, Technical University of Denmark, Anker Engelunds Vej 301, 2800, Kongens Lyngby, Copenhagen, Denmark.
ChemSusChem. 2023 Sep 22;16(18):e202300482. doi: 10.1002/cssc.202300482. Epub 2023 Jul 18.
Transition metal complexes are a promising class of redox mediators for targeting redox flow batteries due to the tunability of their electrochemical potentials. However, reliable time-efficient tools for the prediction of their reduction potentials are needed. In this work, we establish a suitable density functional theory protocol for their prediction using an initial experimental data set of aqueous iron complexes with bidentate ligands. The approach is then cross-validated using different complexes found in the redox-flow literature. We find that the solvation model affects the prediction accuracy more than the functional or basis set. The smallest errors are obtained using the COSMO-RS solvation model (mean average error (MAE)=0.24 V). With implicit solvation models, a general deviation from experimental results is observed. For a set of similar ligands, they can be corrected using simple linear regression (MAE=0.051 V for the initial set of iron complexes).
过渡金属配合物因其电化学势的可调性,是一类很有前景的用于氧化还原液流电池的氧化还原介质。然而,需要可靠且高效的工具来预测它们的还原电位。在这项工作中,我们使用含双齿配体的水性铁配合物的初始实验数据集,建立了一种适用于预测其还原电位的密度泛函理论方法。然后,使用氧化还原液流文献中发现的不同配合物对该方法进行交叉验证。我们发现,溶剂化模型对预测准确性的影响大于泛函或基组。使用COSMO-RS溶剂化模型可获得最小误差(平均绝对误差(MAE)=0.24 V)。对于隐式溶剂化模型,观察到与实验结果存在一般偏差。对于一组相似的配体,可使用简单线性回归进行校正(对于初始的铁配合物集,MAE=0.051 V)。