An Insight into Synthesis of the Antifreeze Alkaline Hydrogel Electrolyte: Fine‐Tuning Chemistries for Efficient Ion Transport
Bibliographic record
Abstract
Abstract Herein, the chemical compatibility of the hydrogel electrolyte in highly alkaline pH was evaluated. Through simple experiments, we demonstrated that the frequently used polymer compound, acrylamide, is not stable at a high pH. The addition of glycerol as a cryoprotectant in highly alkaline hydrogels was also problematic due to the possible base‐initiated decomposition of glycerol to polyglycerols. Hence, a quick and simple one‐pot synthesis of highly alkaline potassium poly(acrylate) hydrogel with 1 vol % glycerol was proposed. The ionic conductivities of the hydrogel are 46.48 mS/cm and 8.67 mS/cm at 22 and −23 °C, respectively. One important benefit from the addition of the cryoprotectant is that the hydrogel sustained its mechanical features at temperatures as low as −80 °C. We also reported here for the first time the diffusion coefficients ( D at ∼10 −8 cm 2 /s), ionic mobilities ( μ at ∼10 −7 cm 2 /Vs), and ion density ( n at ∼10 −7 cm −3 ) of the hydrogel electrolyte used in flexible alkaline batteries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".