A self-driving laboratory designed to accelerate the discovery of adhesive materials. (7th June 2022)

• Record Type: Journal Article
• Authors: Rooney, Michael B.; MacLeod, Benjamin P.; Oldford, Ryan; Thompson, Zachary J.; White, Kolby L.; Tungjunyatham, Justin; Stankiewicz, Brian J.; Berlinguette, Curtis P.
• Is Part Of: Digital discovery. Volume 1:Number 4(2022)
• Page Start: 382
• Page End: 389
• Publication Date: 2022-06-07
• Subjects: Chemistry -- Data processing -- Periodicals; Medical sciences -- Data processing -- Periodicals; Machine learning -- Periodicals; 542.85
• DOI: 10.1039/d2dd00029f
• Languages: English
• ISSNs: 2635-098X

Abstract

Abstract : This self-driving laboratory combines a robot for preparing and testing adhesive bonds with an optimizer to rapidly improve adhesive formulations. Abstract : We report a self-driving laboratory for adhesive material optimization. This autonomous laboratory combines a robot for preparing and testing adhesive bonds with a Bayesian optimizer to rapidly improve adhesive formulations. This system uses a single robot to perform a complex sequence of eight tasks including surface preparation, test specimen assembly, and bond strength evaluation. To enable automated strength testing, we developed an automated pull test method that correlates linearly with a single-lap-joint shear test method. This work demonstrates how flexible automation accelerates complex, multi-step experimental workflows for which commercial automation solutions are not available.