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Rational Solid-State Synthesis Routes for Inorganic Materials
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Abstract
Rational solid-state synthesis of inorganic compounds is formulated as catalytic nucleation on crystalline reactants, where contributions of reaction and interfacial energies to the nucleation barriers are approximated from high-throughput thermochemical data, and structural and interfacial features of crystals, respectively. Favorable synthesis reactions are then identified by a Pareto analysis of relative nucleation barriers and phase-selectivities of reactions leading to the target. We demonstrate the application of this approach in reaction planning for solid-state synthesis of a range of compounds, including the widely-studied oxides LiCoO2, BaTiO3 and YBa2Cu3O7, as well as other metal oxide, oxyfluoride, phosphate and nitride targets. Pathways for enabling retrosynthesis of inorganics are also discussed.
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The experimental strategy is impractical to scale owing to costs, throughput and synthesis complications.
“However, this strategy is impractical to scale owing to costs, throughput and synthesis complications19.”
From Scaling deep learning for materials discovery (2023) · cites this paper as [19]
The section headed “Majority of these reactions are likely to be impractical simply based on what is available to” says that many candidate synthesis reactions are impractical because suitable reactants may not be readily accessible. “Solid-state retrosynthetic pathways” also describes complications from making intermediates and transporting material between solids. Neither passage says that an experimental strategy is impractical to scale because of costs or throughput. (LLM, conf=0.76)
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Sorted by citations
Scaling deep learning for materials discovery
Merchant, A., Batzner, S., Schoenholz, S. S., Aykol, M., Cheon, G., & Cubuk, E. D. (2023) · Nature · doi:10.1038/s41586-023-06735-9 · Cited by 1,527
Self-citationAn autonomous laboratory for the accelerated synthesis of inorganic materials
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“We have established a pipeline for recommending synthesis recipes by using a knowledge base of 33,343 solid-state synthesis procedures extracted from 24,304 publications 16 .”
Text Mining the Literature to Inform Experiments and Rationalize Impurity Phase Formation for BiFeO3
Cruse, K., Baibakova, V., Abdelsamie, M., Hong, K., Bartel, C. J., Trewartha, A., Jain, A., Sutter-Fella, C. M., & Ceder, G. (2024) · Chemistry of Materials · doi:10.1021/acs.chemmater.3c02203 · Cited by 13
Metadata
- Authors
- Aykol, M., Montoya, J. H., & Hummelshøj, J.
- Affiliations
- Toyota Research Institute (US)
- Corresponding author
- Aykol, Muratahan
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2021-06-11
- Volume
- 143
- Issue
- 24
- Pages
- 9244-9259
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- OpenAlex
- W3168446231
- Cited by
- 117
- References
- 4
- Citations by year
- 2026: 22 · 2025: 22 · 2024: 25 · 2023: 26 · 2022: 18 · 2021: 4
- FWCI
- 5.20
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Journal of the American Chemical Society (publishedVersion)
- ChemRxiv (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Figshare (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Physical Sciences › Materials Science › Materials Chemistry › Thermal and Kinetic Analysis
- Physical Sciences › Chemistry › Inorganic Chemistry › Inorganic Chemistry and Materials
- Keywords
- solid-state synthesis, nucleation barrier, interfacial energy, Pareto analysis, phase selectivity, inorganic materials, LiCoO2, barium titanate, YBa2Cu3O7-δ, metal oxides, oxyfluorides, phosphate, nitrides, retrosynthesis
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