Machine learning-based analysis of overall stability constants of metal-ligand complexes.

ABSTRACT: The stability constants of metal(M)-ligand(L) complexes are industrially important because they affect the quality of the plating film and the efficiency of metal separation. Thus, it is desirable to develop an effective screening method for promising ligands. Although there have been several machine-learning approaches for predicting stability constants, most of them focus only on the first overall stability constant of M-L complexes, and the variety of cations is also limited to less than 20. In this study, two Gaussian process regression models are developed to predict the first overall stability constant and the n-th (n > 1) overall stability constants. Furthermore, the feature relevance is quantitatively evaluated via sensitivity analysis. As a result, the electronegativities of both

SUBMITTER: Kanahashi K 

PROVIDER: S-EPMC9314427 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature