Modeling Single-Crystal Battery Materials: From Fundamental Understanding to Performance Evaluation.
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| Title: | Modeling Single-Crystal Battery Materials: From Fundamental Understanding to Performance Evaluation. |
|---|---|
| Authors: | Yuan, Suyue1,2 (AUTHOR), Weitzner, Stephen E.1,2 (AUTHOR), Jeong, Wonseok3 (AUTHOR), Zhang, Shenli1,2,4 (AUTHOR), Wang, Bo1,2,5 (AUTHOR), Feng, Longsheng1,2,6 (AUTHOR), Kaufman, Jonas L.1,2 (AUTHOR), Kim, Kwangnam1,2 (AUTHOR), Qi, Yue7 (AUTHOR), Wan, Liwen F.1,2 (AUTHOR) wan6@llnl.gov |
| Source: | Chemical Reviews. 1/14/2026, p80-148. 69p. |
| Abstract: | The performance of rechargeable batteries is fundamentally influenced by the physicochemical properties and microstructural features of their key material components. Recent experimental advancements have highlighted the potential of single-crystal (SC) morphologies to address inherent limitations of polycrystalline (PC) electrodes and solid-state electrolytes, offering tunable charge transport kinetics and improved cell cycling performance. This review examines how state-of-the-art computational modeling, from atomistic and mesoscale to continuum-level approaches, including machine learning methodologies, has been utilized to investigate the critical factors governing the electrochemical behavior of SC battery materials. We explore how predictive modeling can elucidate the processing–structure–property–performance relationships of SC cathodes, anodes, and solid-state electrolytes, with a focus on unique SC characteristics such as crystallographic anisotropy, size effects, and facet-dependent properties. Additionally, we identify limitations in commonly used modeling techniques and discuss strategies to address these challenges. By integrating high-fidelity simulations with experimental insights, this review aims to outline a clear path for the rational design and optimization of SC battery components, paving the way for accelerated advancements in energy storage technologies. [ABSTRACT FROM AUTHOR] |
| Copyright of Chemical Reviews is the property of American Chemical Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 190889857 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Modeling Single-Crystal Battery Materials: From Fundamental Understanding to Performance Evaluation. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yuan%2C+Suyue%22">Yuan, Suyue</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Weitzner%2C+Stephen+E%2E%22">Weitzner, Stephen E.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jeong%2C+Wonseok%22">Jeong, Wonseok</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Shenli%22">Zhang, Shenli</searchLink><relatesTo>1,2,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Bo%22">Wang, Bo</searchLink><relatesTo>1,2,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Feng%2C+Longsheng%22">Feng, Longsheng</searchLink><relatesTo>1,2,6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kaufman%2C+Jonas+L%2E%22">Kaufman, Jonas L.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kim%2C+Kwangnam%22">Kim, Kwangnam</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Qi%2C+Yue%22">Qi, Yue</searchLink><relatesTo>7</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wan%2C+Liwen+F%2E%22">Wan, Liwen F.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> wan6@llnl.gov</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Chemical+Reviews%22">Chemical Reviews</searchLink>. 1/14/2026, p80-148. 69p. – Name: Abstract Label: Abstract Group: Ab Data: The performance of rechargeable batteries is fundamentally influenced by the physicochemical properties and microstructural features of their key material components. Recent experimental advancements have highlighted the potential of single-crystal (SC) morphologies to address inherent limitations of polycrystalline (PC) electrodes and solid-state electrolytes, offering tunable charge transport kinetics and improved cell cycling performance. This review examines how state-of-the-art computational modeling, from atomistic and mesoscale to continuum-level approaches, including machine learning methodologies, has been utilized to investigate the critical factors governing the electrochemical behavior of SC battery materials. We explore how predictive modeling can elucidate the processing–structure–property–performance relationships of SC cathodes, anodes, and solid-state electrolytes, with a focus on unique SC characteristics such as crystallographic anisotropy, size effects, and facet-dependent properties. Additionally, we identify limitations in commonly used modeling techniques and discuss strategies to address these challenges. By integrating high-fidelity simulations with experimental insights, this review aims to outline a clear path for the rational design and optimization of SC battery components, paving the way for accelerated advancements in energy storage technologies. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Chemical Reviews is the property of American Chemical Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1021/acs.chemrev.5c00360 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 69 StartPage: 80 Titles: – TitleFull: Modeling Single-Crystal Battery Materials: From Fundamental Understanding to Performance Evaluation. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yuan, Suyue – PersonEntity: Name: NameFull: Weitzner, Stephen E. – PersonEntity: Name: NameFull: Jeong, Wonseok – PersonEntity: Name: NameFull: Zhang, Shenli – PersonEntity: Name: NameFull: Wang, Bo – PersonEntity: Name: NameFull: Feng, Longsheng – PersonEntity: Name: NameFull: Kaufman, Jonas L. – PersonEntity: Name: NameFull: Kim, Kwangnam – PersonEntity: Name: NameFull: Qi, Yue – PersonEntity: Name: NameFull: Wan, Liwen F. IsPartOfRelationships: – BibEntity: Dates: – D: 14 M: 01 Text: 1/14/2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 00092665 Titles: – TitleFull: Chemical Reviews Type: main |
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