An autonomous laboratory for the accelerated synthesis of inorganic materials

, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics.…

• NS
  National Science Foundation

  Awards: 1752814, DE-AC02-05CH11231
• UD
  U.S. Department of Energy

  Awards: -AC02-05CH11231, 05CH11231, KC23MP, 1752814, -AC02-05-CH11231, AC02-05CH11231, DE-AC02, AC02-05-CH11231, DE-AC02-05CH11231, DE-AC02-05-CH11231, DE-AC02-
• NE
  National Energy Research Scientific Computing Center

  Awards: 05CH11231, AC02-05CH11231
• OO
  Office of Science

  Awards: AC02-05CH11231, -AC02-05CH11231, DE-AC02, DE-AC02-05-CH11231
• BE
  Basic Energy Sciences

  Awards: DE-AC02, AC02-05CH11231, KCD2S2, AC02-05-CH11231, DE-AC02-05CH11231, KC23MP, DE-AC02-05-CH11231, -AC02-05CH11231
• LB
  Lawrence Berkeley National Laboratory

  Awards: DE-AC02-05CH11231, DE-AC02-05-CH11231, 05CH11231, AC02-05CH11231