Self-driving laboratory for accelerated discovery of thin-film materials
By B. MacLeod, F. G. L. Parlane, T. Morrissey, Florian Hase, Loïc M. Roch, Kevan E Dettelbach, R. Moreira, L. Yunker, M. Rooney, J. R. Deeth and 10 more. Science Advances, 2019
633 citations recorded by the source corpus.
An autonomous laboratory for thin film discovery is used to optimize the doping and annealing of organic semiconductors. 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 using autonomous laboratories to discover organic and inorganic materials relevant to materials sciences and clean energy technologies.
Subfields: Electrical and Electronic Engineering, Materials Chemistry
View Paper: https://www.semanticscholar.org/paper/eeb6305630a5142f0f98c6098b6f0488aa8444c6
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In Electrical and Electronic Engineering
In Materials Chemistry
- Shyue Ping Ong
- Chi Chen
- Anubhav Jain
- Alok N. Choudhary
- Chris Wolverton
- Simon J. L. Billinge
- Kamal Choudhary
- Brian L. DeCost
Citations in the corpus
- Recent advances and applications of deep learning methods in materials science (2021, background): “Finally, we note an important technological challenge is to make a “closedloop” autonomous materials design and synthesis process [348, 349] that can include both machine learning and experimental components in a “self-driving laboratory” [350].”
- An autonomous laboratory for the accelerated synthesis of inorganic materials (2023, neutral): “Pioneering efforts have demonstrated autonomy in several aspects of materials research, including robotic and Bayesian-driven optimization of carbon nanotube yield 3,4 , photo-voltaic performance 5 and photocatalysis activity 6 .”