Self-driving laboratory for accelerated discovery of thin-film materials.

ABSTRACT: Discovering and optimizing commercially viable materials for clean energy applications typically takes more than a decade. Self-driving laboratories that iteratively design, execute, and learn from materials science experiments in a fully autonomous loop present an opportunity to accelerate this research process. We report here a modular robotic platform driven by a model-based optimization algorithm capable of autonomously optimizing the optical and electronic properties of thin-film materials by modifying the film composition and processing conditions. We demonstrate the power of this platform by using it to maximize the hole mobility of organic hole transport materials commonly used in perovskite solar cells and consumer electronics. This demonstration highlights the possibilities of us

SUBMITTER: MacLeod BP 

PROVIDER: S-EPMC7220369 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature