Microstructure Scale Lithium-Ion Battery Modeling, Part IV: The Representativity of Microstructure Parameters and Electrochemical Response Article Swipe
Francois L. E. Usseglio‐Viretta
,
Andrew M. Colclasure
,
Jeffery M. Allen
,
Peter J. Weddle
,
Donal P. Finegan
,
Peter Gräf
,
Kandler Smith
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1149/1945-7111/adee50
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1149/1945-7111/adee50
Lithium-ion battery electrochemical models require an accurate description of the electrodes microstructures to be predictive, that can be achieved through nanoscale imaging. Such observations are however limited by their field of view (FOV), as they provide only a subset of the whole electrode volume that does not necessarily represent the whole electrode microstructure heterogeneity, and therefore can bias the analysis. A representativity analysis has been performed on the microstructure parameters and, in a novel way, on the full cell electrochemical response to evaluate the predictions representativeness, and thus relevance, of a microstructure scale electrochemical model. The microstructure parameter deviation propagations to the electrochemical response have been quantified for different charge rates. This defines a threshold for the microstructure parameters FOV for a desired maximum deviation of the electrochemical response. Electrochemical model shows cell representative section areas are increasing with C-rate, due to higher in-plane heterogeneities, indicating larger FOVs are required specifically for fast charge modeling. Representativity analysis determines a cell FOV of 144.4 × 154.4 μm 2 is large enough to establish a convergence on the representative section areas for low-intermediate C-rate (≤2.5 C), therefore positively concludes on the model representativeness for these rates, but is not large enough to conclude for higher rates.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1149/1945-7111/adee50
- OA Status
- hybrid
- Cited By
- 2
- References
- 31
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- OpenAlex ID
- https://openalex.org/W4412183633
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4412183633Canonical identifier for this work in OpenAlex
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https://doi.org/10.1149/1945-7111/adee50Digital Object Identifier
- Title
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Microstructure Scale Lithium-Ion Battery Modeling, Part IV: The Representativity of Microstructure Parameters and Electrochemical ResponseWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-07-01Full publication date if available
- Authors
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Francois L. E. Usseglio‐Viretta, Andrew M. Colclasure, Jeffery M. Allen, Peter J. Weddle, Donal P. Finegan, Peter Gräf, Kandler SmithList of authors in order
- Landing page
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https://doi.org/10.1149/1945-7111/adee50Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1149/1945-7111/adee50Direct OA link when available
- Concepts
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Microstructure, Electrochemistry, Lithium (medication), Materials science, Battery (electricity), Ion, Lithium-ion battery, Scale (ratio), Metallurgy, Chemistry, Electrode, Physics, Thermodynamics, Physical chemistry, Power (physics), Psychology, Psychiatry, Quantum mechanics, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2025: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.FOV | 119, 160 |
| abstract_inverted_index.The | 95 |
| abstract_inverted_index.and | 54, 86 |
| abstract_inverted_index.are | 24, 136, 148 |
| abstract_inverted_index.but | 194 |
| abstract_inverted_index.can | 16, 56 |
| abstract_inverted_index.due | 140 |
| abstract_inverted_index.for | 107, 115, 120, 151, 179, 191, 201 |
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| abstract_inverted_index.not | 46, 196 |
| abstract_inverted_index.the | 9, 40, 49, 58, 67, 76, 83, 101, 116, 126, 175, 188 |
| abstract_inverted_index.μm | 165 |
| abstract_inverted_index.FOVs | 147 |
| abstract_inverted_index.Such | 22 |
| abstract_inverted_index.This | 111 |
| abstract_inverted_index.and, | 70 |
| abstract_inverted_index.been | 64, 105 |
| abstract_inverted_index.bias | 57 |
| abstract_inverted_index.cell | 78, 132, 159 |
| abstract_inverted_index.does | 45 |
| abstract_inverted_index.fast | 152 |
| abstract_inverted_index.full | 77 |
| abstract_inverted_index.have | 104 |
| abstract_inverted_index.only | 36 |
| abstract_inverted_index.that | 15, 44 |
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| abstract_inverted_index.thus | 87 |
| abstract_inverted_index.view | 31 |
| abstract_inverted_index.way, | 74 |
| abstract_inverted_index.with | 138 |
| abstract_inverted_index.144.4 | 162 |
| abstract_inverted_index.154.4 | 164 |
| abstract_inverted_index.areas | 135, 178 |
| abstract_inverted_index.field | 29 |
| abstract_inverted_index.large | 168, 197 |
| abstract_inverted_index.model | 130, 189 |
| abstract_inverted_index.novel | 73 |
| abstract_inverted_index.scale | 92 |
| abstract_inverted_index.shows | 131 |
| abstract_inverted_index.their | 28 |
| abstract_inverted_index.these | 192 |
| abstract_inverted_index.whole | 41, 50 |
| abstract_inverted_index.(FOV), | 32 |
| abstract_inverted_index.C-rate | 181 |
| abstract_inverted_index.charge | 109, 153 |
| abstract_inverted_index.enough | 169, 198 |
| abstract_inverted_index.higher | 142, 202 |
| abstract_inverted_index.larger | 146 |
| abstract_inverted_index.model. | 94 |
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| abstract_inverted_index.rates. | 110, 203 |
| abstract_inverted_index.subset | 38 |
| abstract_inverted_index.volume | 43 |
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| abstract_inverted_index.C-rate, | 139 |
| abstract_inverted_index.battery | 1 |
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| abstract_inverted_index.desired | 122 |
| abstract_inverted_index.however | 25 |
| abstract_inverted_index.limited | 26 |
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| abstract_inverted_index.require | 4 |
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| abstract_inverted_index.accurate | 6 |
| abstract_inverted_index.achieved | 18 |
| abstract_inverted_index.analysis | 62, 156 |
| abstract_inverted_index.conclude | 200 |
| abstract_inverted_index.evaluate | 82 |
| abstract_inverted_index.imaging. | 21 |
| abstract_inverted_index.in-plane | 143 |
| abstract_inverted_index.required | 149 |
| abstract_inverted_index.response | 80, 103 |
| abstract_inverted_index.analysis. | 59 |
| abstract_inverted_index.concludes | 186 |
| abstract_inverted_index.deviation | 98, 124 |
| abstract_inverted_index.different | 108 |
| abstract_inverted_index.electrode | 42, 51 |
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| abstract_inverted_index.modeling. | 154 |
| abstract_inverted_index.nanoscale | 20 |
| abstract_inverted_index.parameter | 97 |
| abstract_inverted_index.performed | 65 |
| abstract_inverted_index.represent | 48 |
| abstract_inverted_index.response. | 128 |
| abstract_inverted_index.therefore | 55, 184 |
| abstract_inverted_index.threshold | 114 |
| abstract_inverted_index.determines | 157 |
| abstract_inverted_index.electrodes | 10 |
| abstract_inverted_index.increasing | 137 |
| abstract_inverted_index.indicating | 145 |
| abstract_inverted_index.parameters | 69, 118 |
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| abstract_inverted_index.quantified | 106 |
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| abstract_inverted_index.Lithium-ion | 0 |
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| abstract_inverted_index.description | 7 |
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| abstract_inverted_index.predictions | 84 |
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| abstract_inverted_index.observations | 23 |
| abstract_inverted_index.propagations | 99 |
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| abstract_inverted_index.microstructure | 52, 68, 91, 96, 117 |
| abstract_inverted_index.representative | 133, 176 |
| abstract_inverted_index.Electrochemical | 129 |
| abstract_inverted_index.electrochemical | 2, 79, 93, 102, 127 |
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| abstract_inverted_index.Representativity | 155 |
| abstract_inverted_index.heterogeneities, | 144 |
| abstract_inverted_index.low-intermediate | 180 |
| abstract_inverted_index.representativity | 61 |
| abstract_inverted_index.representativeness | 190 |
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| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
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| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |