Evaluation of Redox Chemistries for Single-Use Biodegradable Capillary Flow Batteries
Bibliographic record
Abstract
The rate of battery waste generation is rising dramatically worldwide due to increased use and consumption of electronic devices. A new class of portable and biodegradable capillary flow batteries was recently introduced as a solution for single-use disposable applications. The concept utilizes stored organic redox species and supporting electrolytes inside a dormant capillary flow cell which is activated by the dropwise addition of aqueous liquid. Herein, various organic redox species are systematically evaluated for prospective use in disposable capillary flow cells with regards to their electrochemical characteristics, solubility, storability and biodegradability. Qualitative ex-situ techniques are first applied to assess half-cell solubility, redox potential and kinetics, followed by quantitative in-situ measurements of discharge performance of selected redox chemistries in a microfluidic cell with flow-through porous electrodes. Para-benzoquinone in oxalic acid and either hydroquinone sulfonic acid or ascorbic acid in potassium hydroxide are identified for the positive and negative half-cells, respectively, yielding a maximum discharge power density of 50 mW/cm 2 . A prototype capillary flow battery using the same redox chemistries demonstrates robust cell voltages above 1.0 V and maximum discharge power of 1.9 mW. These results show that practical primary battery performance can be achieved with biodegradable chemistries in a disposable device.
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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 | 0.001 |
| 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".