Design of New Dispersants Using Machine Learning and Visual Analytics.

ABSTRACT: Artificial intelligence (AI) is an emerging technology that is revolutionizing the discovery of new materials. One key application of AI is virtual screening of chemical libraries, which enables the accelerated discovery of materials with desired properties. In this study, we developed computational models to predict the dispersancy efficiency of oil and lubricant additives, a critical property in their design that can be estimated through a quantity named blotter spot. We propose a comprehensive approach that combines machine learning techniques with visual analytics strategies in an interactive tool that supports domain experts' decision-making. We evaluated the proposed models quantitatively and illustrated their benefits through a case study. Specifically, we analyzed a series of virtu

SUBMITTER: Martinez MJ 

PROVIDER: S-EPMC10007083 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature