Artificial Intelligence in the Discovery of Deep Eutectic Solvents with Lubricant Applications.

ABSTRACT: Following evidence suggesting that deep eutectic solvents (DESs) can potentially replace conventional mineral-based lubricants, this study aims to leverage artificial intelligence to discover, and then experimentally prepare and characterize, novel DES-based lubricants. To do so, Gaussian processes (GPs) were employed to describe and predict relevant physicochemical properties of DESs, specifically density, viscosity, and melting temperature. This was accomplished by using a comprehensive data set encompassing nearly 400 different binary and ternary DESs and including 3985, 4197, and 2003 independent data points (different DES compositions and temperatures) for density, viscosity, and melting temperature, respectively. GPs were trained and rigorously evaluated, attaining testing set coeffi

SUBMITTER: Santos JP 

PROVIDER: S-EPMC12461321 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature