Water-soluble binders for MCMB carbon anodes for lithium-ion batteries
Bibliographic record
Abstract
We have investigated the suitability of four different binders for the conventional mesocarbon microbeads (MCMBs) anode material in Li-ion batteries. Unlike the conventional polyvinylidene fluoride (PVDF), the binders were water soluble and were either cellulose based, such as the lithium and sodium salts of carboxymethyl cellulose (NaCMC, and LiCMC) and Xanthan Gum (XG), or the conjugated polymer: poly(3,4-ethylendioxythiophene) (PEDOT, a.k.a. Baytron). All binders were commercially available except LiCMC, which was synthesized and characterized by FTIR and NMR. Thermal studies of the binders by TGA and DSC showed that, in air, the binders have a broad melting event at 100–150 °C, with an onset temperature for decomposition above 220 °C. Li/MCMB half-cell batteries were assembled using the studied binders. Slow scan voltammograms of all cells showed characteristic lithium insertion and de-insertion peaks including that of the SEI formation which was found to be embedded into the insertion peaks during the first cycle. Cycling of the cells showed that the one containing XG binder gave the highest capacities reaching 350 mAh g−1 after 100 cycles at C/12, while the others gave comparable capacities to those of the conventional binder PVDF. The rate capabilities of cells were examined and found to perform well up to the studied C/2 rate with more than 50% capacity retained. Further studies of the XG-based MCMB electrodes were performed and concluded that an optimal thickness of 300–365 μm gave the highest capacities and sustained high C-rates.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".