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| Natura: | Preprint |
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2026
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2605.00639 |
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| _version_ | 1866913080603049984 |
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| author | Spurgeon, Steven R. Abolhasani, Milad Baddour, Frederick Comes, Ryan B. Dravid, Vinayak P. Egan, Hilary Emami, Patrick Epps, Robert W. Fébba, Davi M. Gannon, Renae Gaulding, E. Ashley Ghosh, Ayana Gruchalla, Kenny Guinan, Grace Hitosugi, Taro Holden, Michael Kalinin, Sergei V. Liang, Yangang Mangum, John S. Olszta, Matthew J. Park, Nathaniel H. Palmstrom, Axel Smeaton, Michelle A. Tellekamp, Brooks Thornburg, Nicholas E. Unocic, Raymond R. Ushizima, Daniela Vasudevan, Rama K. White, Robert Young, Andrew Zakutayev, Andriy |
| author_facet | Spurgeon, Steven R. Abolhasani, Milad Baddour, Frederick Comes, Ryan B. Dravid, Vinayak P. Egan, Hilary Emami, Patrick Epps, Robert W. Fébba, Davi M. Gannon, Renae Gaulding, E. Ashley Ghosh, Ayana Gruchalla, Kenny Guinan, Grace Hitosugi, Taro Holden, Michael Kalinin, Sergei V. Liang, Yangang Mangum, John S. Olszta, Matthew J. Park, Nathaniel H. Palmstrom, Axel Smeaton, Michelle A. Tellekamp, Brooks Thornburg, Nicholas E. Unocic, Raymond R. Ushizima, Daniela Vasudevan, Rama K. White, Robert Young, Andrew Zakutayev, Andriy |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_00639 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Born-Qualified: An Autonomous Framework for Deploying Advanced Energy and Electronic Materials Spurgeon, Steven R. Abolhasani, Milad Baddour, Frederick Comes, Ryan B. Dravid, Vinayak P. Egan, Hilary Emami, Patrick Epps, Robert W. Fébba, Davi M. Gannon, Renae Gaulding, E. Ashley Ghosh, Ayana Gruchalla, Kenny Guinan, Grace Hitosugi, Taro Holden, Michael Kalinin, Sergei V. Liang, Yangang Mangum, John S. Olszta, Matthew J. Park, Nathaniel H. Palmstrom, Axel Smeaton, Michelle A. Tellekamp, Brooks Thornburg, Nicholas E. Unocic, Raymond R. Ushizima, Daniela Vasudevan, Rama K. White, Robert Young, Andrew Zakutayev, Andriy Materials Science Artificial Intelligence 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. |
| title | Born-Qualified: An Autonomous Framework for Deploying Advanced Energy and Electronic Materials |
| topic | Materials Science Artificial Intelligence |
| url | https://arxiv.org/abs/2605.00639 |