(Invited) Coordinatively Cross-Linked Binders for Silicon-Based Electrodes for Lithium Ion Batteries
Bibliographic record
Abstract
We have proposed a simple and versatile preparation of Cu(II)- or Zn(II)-poly(carboxylates) reticulated binders by the addition of Cu(II) or Zn(II) precursors into a pre-optimized carboxymethyl cellulose / citric acid binder solution. These binders lead systematically to a significantly improved electrochemical performance when used for the formulation of silicon-based negative electrodes [1,2]. Mechanical characterizations reveal that the coordinated binders offer a better electrode coating cohesion and adhesion to the current collector, as well as higher hardness and elastic modulus, which are even preserved in presence of a carbonate solvent (i.e. in battery operation conditions). Ultimately, as shown from operando dilatometry experiments, the electrode expansion during lithiation is reduced, mitigating electrode mechanical failure [2]. In complement, we used scanning transmission electron microscopy coupled with energy dispersive X-ray spectroscopy to probe the nanoscale morphology of such electrodes. This technique reveals the homogeneous coordination of carboxylated binder with Zn cations and its layering on the silicon surface. The SEI formed after the first cycle is denser with Zn-coordinated binder and preferentially observed on binder-depleted zones [3]. In summary, the superiority of coordinated binders can be attributed to their capacity to better stabilize the electrode and the SEI layer due to improved mechanical properties. This resulted in a lower SEI impedance, a higher first cycle coulombic efficiency, and a 40% improvement of capacity retention after 60 cycles for highly loaded electrodes of over 6 mAh.cm-2. Noteworthy, this formulation principle allows for better reproducibility and manufacturing quality of the electrodes [4]. [1] D. Mazouzi, R. Grissa, M. Paris, Z. Karkar, L. Huet, D. Guyomard, L. Roué, T. Devic, B. Lestriez, Electrochimica Acta, 304 (2019) 495-504 [2] L. Huet, D. Mazouzi, P. Moreau, N. Dupré, M. Paris, S. Mittelette, D. Laurencin, T. Devic, L. Roué, B. Lestriez, ACS Applied Materials & Interfaces, 15 (2023) 15509-15524 [3] L. Huet, P. Moreau, N. Dupré, T. Devic, L. Roué, B. Lestriez, Small Methods, 2022, 2200827 [4] L. Huet, H. Houisse, N. Herkendaal, T. Devic, L. Roué, B. Lestriez, Energy Technology, 2023, 2201483 Figure 1
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".