Alternatives assessment of polyvinylidene fluoride-compatible solvents for N-methyl pyrrolidone substitution in lithium-ion battery cathodes
Bibliographic record
Abstract
Lithium-ion batteries (LIBs) are central to electrification yet, to increase the efficiency and scalability of electric systems, energy storage technologies must integrate sustainability concepts into their design. Notably, the incumbent LIB technology uses the reprotoxic solvent N-methyl pyrrolidone (NMP) to dissolve polyvinylidene fluoride (PVdF) as a binder. This solvent, of concern to human and ecological health, must be replaced with less toxic alternatives. Accordingly, the objective of this study was to determine which potential solvents, compatible with PVdF binder within the cathode processing of LIBs, could replace NMP. This study followed the U.S. National Research Council’s Framework to Guide Selection of Chemical Alternatives, and thus assembled and compared data concerning ecological and human hazards, performance, and cost. Five solvents were assessed as alternatives to NMP, derived from an analysis of 948 cells of data (708 cells of hazard data, 54 cells of performance data, and 186 cells of cost data). Triethyl phosphate (TEP) and N-N’-dimethylpropyleneurea (DMPU) are found to exhibit reprotoxic properties, and dimethylsulfoxide (DMSO) raised concerns in all three data categories studied. The most promising alternatives to NMP were dihydrolevoglucosenone (Cyrene) and γ-valerolactone (GVL). With demand for sustainable energy storage growing, the results of this study aim to guide research and innovation of LIB technologies while avoiding regrettable substitutions in developing NMP-free LIBs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".