MétaCan
Menu
Back to cohort
Record W7005149000

Phase-separating Active Materials in Lithium-ion Batteries: Implications for Fast-charging and Material Characterisation

2024· article· en· W7005149000 on OpenAlexfundno aff

Bibliographic record

VenueCINECA IRIS Institutial research information system (University of Pisa) · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
FundersH2020 Marie Skłodowska-Curie ActionsPrecursory Research for Embryonic Science and TechnologyBasic Energy SciencesDivision of Materials ResearchBasic and Applied Basic Research Foundation of Guangdong ProvincePhilippine-California Advanced Research InstitutesFundamental Research Funds for the Central UniversitiesAgencia Estatal de InvestigaciónPhilippine Council for Industry, Energy, and Emerging Technology Research and DevelopmentJapan Society for the Promotion of ScienceGuangdong Provincial Pearl River Talents ProgramMaterials Research Science and Engineering Center, Harvard UniversityUniversity of California, IrvineOffice of Nuclear EnergyOffice of Energy Efficiency and Renewable EnergySamsungUniversitat Politècnica de ValènciaAlliance de recherche numérique du CanadaAdvanced Low Carbon Technology Research and Development ProgramKorea Institute of Ceramic Engineering and TechnologyMinistry of Science and ICT, South KoreaRWTH Aachen UniversityUK Research and InnovationTotalJapan Science and Technology AgencyAmerican Chemical Society Petroleum Research FundInnovation and Technology CommissionChristian Doppler ForschungsgesellschaftLatvijas Zinātnes PadomeÖsterreichische ForschungsförderungsgesellschaftDeutsche Akademie der Naturforscher Leopoldina - Nationale Akademie der WissenschaftenDeutsche ForschungsgemeinschaftPolitechnika GdańskaAgència per a la Competitivitat de l’EmpresaOffice of ScienceNarodowym Centrum NaukiNarodowe Centrum NaukiNational Natural Science Foundation of ChinaNational Research Foundation of KoreaKorea Institute for Advancement of TechnologyCore Research for Evolutional Science and TechnologyNatural Science Foundation of Guangdong ProvinceImperial College LondonGeneralitat de CatalunyaGeneralitat ValencianaNatural Sciences and Engineering Research Council of CanadaMinistry of Education, Culture, Sports, Science and TechnologyBundesministerium für Bildung und ForschungChina Scholarship CouncilEusko JaurlaritzaMinistry of Trade, Industry and EnergyAgence Nationale de la RechercheShenzhen Municipal Science and Technology Innovation CouncilUniversity of SheffieldWestlake UniversityBundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und TechnologieCommission on Higher EducationChina Postdoctoral Science FoundationNational Science FoundationToyota Research InstituteInternational Institute for Carbon-Neutral Energy Research, Kyushu UniversityAustrian Science FundNational Research FoundationMax Kade FoundationSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungOffice of Energy EfficiencyCurtin University of TechnologyColorado School of MinesNorthwestern UniversitySamsung Advanced Institute of TechnologyNorges ForskningsrådAlexander von Humboldt-StiftungU.S. Department of EnergyU.S. Department of Homeland SecurityBundesministerium für Digitalisierung und WirtschaftsstandortCentres de Recerca de CatalunyaMinisterio de Ciencia e InnovaciónEngineering and Physical Sciences Research CouncilEuropean Commission
KeywordsPhase (matter)DiafiltrationNoise (video)Work (physics)Measure (data warehouse)
DOInot available

Abstract

fetched live from OpenAlex

Some active materials used in lithium-ion battery (LIB) electrodes undergo phase separation into Li-rich and Li-poor phases upon lithium intercalation. Typical examples include LiFePO4 (LFP) at the cathode and graphite at the anode. While phase separation enables useful features, such as a constant equilibrium potential as a function of state-of-charge, such behaviour poses challenges during material characterisation and for high-rate operation. \nThis study provides a perspective of phase separation in LIB active materials by combining non-equilibrium thermodynamics principles [1] with in-operando techniques [2]. The results show that classical techniques used to estimate solid-state diffusion coefficients, such as the galvanostatic intermittent titration technique (GITT) [3], must be revisited for this class of materials. In fact, although the rapid equilibration of the interface between Li-rich and Li-poor phases within a particle leads to a quick voltage relaxation, the solid-state diffusivity can be significantly lower than what this fast dynamics may suggest. This has significant implications on the distribution of lithium within secondary particles because, upon fast lithiation, the Li-rich phase grows at the particle surface and prevents further lithiation. This is especially critical for graphite anodes, since the Li-rich phase (also known as stage I) at the particle surface is the primary cause for the plating of metallic lithium outside the particle, as quantified in in-operando experiments [2]. Nevertheless, experiments also show that Li plating is not irreversible and part of the plated lithium can be stripped and back-intercalated in graphite when the current is interrupted. This discovery opens opportunities for alternative fast-charging protocols as long as the particle size distribution is well controlled to prevent excessive plating on small particles. On the other hand, experimental characterisation and simulation of a disordered carbon, which does not undergo phase separation, reveal an effectively faster solid-state diffusion and a more significant resistance to lithium plating even at high C-rate [4], thus enabling for a comprehensive comparison between solid-solution and phase-separating active materials when it comes to characterisation and fast-charging capabilities. \n \n \nReferences \n[1] 10.1021/ar300145c. Bazant, M.Z. Theory of Chemical Kinetics and Charge Transfer Based on Nonequilibrium Thermodynamics. Acc. Chem. Res. 2013, 46, 1144-1160 \n[2] 10.1038/s41467-023-40574-6. Lu, X.; Lagnoni, M.; Bertei, A.; Das, S.; Owen, R.E.; Li, Q.; O'Regan, K.; Wade, A.; Finegan, D.P.; Kendrick, E.; Bazant, M.Z.; Brett, D.J.L.; Shearing, P.R. Multiscale Dynamics of Charging and Plating in Graphite Electrodes Coupling Operando Microscopy and Phase-field Modelling. Nat. Commun. 2023, 14, 5127 \n[3] 10.1149/1.2133112. Weppner, W.; Huggins, R.A. Determination of the Kinetic Parameters of Mixed-Conducting Electrodes and Application to the System Li3Sb. J. Electrochem. Soc. 1977, 124, 1569-1578 \n[4] 10.1021/acsaem.3c01280. Ahn, S.; Lagnoni, M.; Yuan, Y.; Ogarev, A.; Vavrinyuk, E.; Voynov, G.; Barrett, E.; Pelli, A.; Atrashchenko, A.; Platonov, A.; Gurevich, S.; Gorokhov, M.; Rupasov, D.; Robertson, A.W.; House, R.A.; Johnson, L.R.; Bertei, A.; Chernyshov, D.V. Chemical Origins of a Fast-Charge Performance in Disordered Carbon Anodes. ACS Appl. Energy Mater. 2023, 6, 8455-8465 \n \nAcknowledgements \nThis study received funding from the National Recovery and Resilience Plan, Mission 4 Component 2 Investment 1.3 - Call for tender No. 1561 of 11.10.2022 of Ministero dell’Università e della Ricerca, according to attachment E of Decree No. 1561/2022, Project title “Network 4 Energy Sustainable Transition – NEST”, CUP I53C22001450006; funded by the European Union–NextGenerationEU. This paper reflects only the authors’ views and opinions; neither the European Union nor the European Commission can be considered responsible for them.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.341
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCINECA IRIS Institutial research information system (University of Pisa)Same topicCell Image Analysis TechniquesFrench-language works237,207