Ethylene Glycol as an Antifreeze Additive and Corrosion Inhibitor for Aqueous Zinc‐Ion Batteries
Bibliographic record
Abstract
Abstract Aqueous zinc‐ion batteries are promising candidates for portable and large‐scale applications because of their intrinsically high safety, low cost and high theoretical energy density. However, existing aqueous zinc‐ion batteries usually suffer from zinc corrosion and poor performance at subzero temperatures. Herein, to address these problems, the electrolyte in aqueous zinc‐ion batteries (1 M ZnSO4) is modified by adding suitable amounts of ethylene glycol. The addition of ethylene glycol improves the antifreezing ability of the aqueous electrolyte and increases the conductivity of electrolyte at low temperatures. Ethylene glycol serves two purposes, as an antifreeze additive to significantly enhance the capacity of batteries at low temperatures and as a corrosion inhibitor to suppress zinc corrosion and byproduct precipitation. This work offers a facile strategy to realize aqueous zinc‐ion batteries with good performance at low temperatures.
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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) | 0.000 | 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".