Computational pipeline for the accelerated discovery of organic materials with high refractive index via high-throughput screening and machine learning.

<div><i>ChemML</i> is an open machine learning and informatics program suite that is designed to support and advance the data-driven research paradigm that is currently emerging in the chemical and materials domain. <i>ChemML</i> allows its users to perform various data science tasks and execute machine learning workflows that are adapted specifically for the chemical and materials context. Key features are automation, general-purpose utility, versatility, and user-friendliness in order to make the application of modern data science a viable and widely accessible proposition in the broader chemistry and materials community. <i>ChemML</i> is also designed to facilitate methodological innovation, and it is one of the cornerstones of the software ecosystem for data-driven <i>in silico</i> research outlined in our recent publication¹.</div>