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Chimera: enabling hierarchy based multi-objective optimization for self-driving laboratories
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Abstract
Chimera enables multi-target optimization for experimentation or expensive computations, where evaluations are the limiting factor.
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“A mathematical function called CHIMERA was recently introduced to address these problems;169 it can be used with any optimizer, such as PHOENICS.”
From QSAR without borders (2020) · cites this paper as [169]
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Metadata
- Authors
- Häse, F., Roch, L. M., & Aspuru-Guzik, A.
- Affiliations
- Harvard University (US)
- Department of Chemistry and Chemical Biology
- Venue
- Chemical Science
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2018
- Volume
- 9
- Issue
- 39
- Pages
- 7642-7655
- ISSN
- 2041-6520 (ISSN-L)
- 2041-6539
- PMC
- PMC6182568
- OpenAlex
- W2889272453
- Cited by
- 161
- References
- 73
- Citations by year
- 2026: 20 · 2025: 21 · 2024: 20 · 2023: 29 · 2022: 22 · 2021: 28 · 2020: 15 · 2019: 6
- FWCI
- 9.06
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Chemical Science (publishedVersion, cc-by)
- ChemRxiv (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Royal College of Surgeons in Ireland (submittedVersion, cc-by-nc-nd)
- Funders
- Harvard University
- Tata Sons (A32391)
- FAS Division of Science, Harvard University
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Multi-Objective Optimization Algorithms
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Keywords
- chimeras, multi-objective optimization, self-driving laboratories, automated experimentation, self-calibration, inverse design, interpretability
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