Born-Qualified: An Autonomous Framework for Deploying Advanced Energy and Electronic Materials
Organizations: National Laboratory of the Rockies, Golden, CO, USA · Metallurgical and Materials Engineering Department, Colorado School of Mines, Golden, CO, USA · University of Colorado–Boulder, Boulder, CO, USA · North Carolina State University, Raleigh, NC, USA · Department of Materials Science and Engineering, University of Delaware, Newark, DE, USA · Northwestern University, Evanston, IL, USA · Department of Physics, Indian Institute of Technology Madras, Chennai 600036, India · Department of Chemistry, School of Science, The University of Tokyo, Tokyo, Japan · Pacific Northwest National Laboratory, Richland, WA, USA · University of Tennessee, Knoxville, TN, USA · IBM Research-Almaden, San Jose, CA, USA · Applied Mathematics and Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA · Oak Ridge National Laboratory, Oak Ridge, TN, USA
Abstract
Autonomous science is transforming how we discover materials and chemical systems for advanced energy technologies. However, many initially promising systems never reach deployment. This "valley of death" stems from optimization that prioritizes laboratory metrics over industrial viability. We propose a new strategy: "born-qualified" autonomous development, which embeds manufacturability, cost, and durability constraints from the outset. This approach is enabled by four pillars, including the development of multi-objective metrics, causal models, a modular infrastructure, and embedding manufacturing in the discovery loop. Realizing this vision will require sustained, community-wide commitment, but the potential return on that investment is commensurate with the scale of the challenge.