Highly Dispersed Poly(vinylidene fluoride) and Carbon Black in NMC Cathodes Produced Via Non-NMP Electrovaya Superpolymer 2.0 Processing Method
Bibliographic record
Abstract
The development of low cost lithium ion batteries using a non-toxic, non-NMP and low cost production process stands as one of the most promising technology breakthroughs, especially with the surging demand for cost effective solutions for energy storage and electric mobility. We demonstrate for the first time that NMP is not required for achieving a microstructure comprising carbon black and PVDF binder with substantial uniform dispersion throughout the active materials. In turn, well-dispersed conductive additive and binder in the electrode, prepared via Electrovaya’s non-aqueous SuperPolymer 2.0 processing method, is observed via performing extensive microstructure characterization using TOF-SIMS, HAADF, and SEM/EDS techniques. These techniques provide information about the carbon black and PVDF binder distribution and uniformity within the cathode material which turn out to be intimately linked to the electrochemical performance of the battery. The composite cathode NMC material when coupled with graphite in a full cell shows an excellent electrochemical performance on par with other commercial lithium ion batteries that utilize conventional toxic NMP coating methods.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".