Phase-separating Active Materials in Lithium-ion Batteries: Implications for Fast-charging and Material Characterisation
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".