Apple Pectin Based Hydrogel Electrolyte for Energy Storage Application
Bibliographic record
Abstract
With the increase of portable power sources demand, new technologies, e.g. wearable and flexible electronics, are projected to generate $1.25 billion market by 2022. [1] New storage energy devices are more than ever in demand which requires new specifications in order to be used in those future applications. To achieve this development, we have to minimize the environmental impact in the whole battery life cycle, from conception to degradation of the system, and reduce production costs. Polymer hydrogel electrolyte are one of the promising alternative for processing new flexible batteries. [2] A great hydrogel electrolyte should promise excellent ionic transport pathways and sufficient mechanical strength, not to cause short-circuits. As a matter of fact, hydrogel electrolytes are well-known for their good ionic conductivity. Nevertheless, the original polymers used in these systems don’t take into account the cost of the environmental impact and safety due to the processing or biodegradability of those hydrogels. [3] In this study, we report a new hydrogel-based electrolyte material made by apple pectin. This presentation will mainly focus on the interactions between pectin functional groups, water and ions using solid NMR spectroscopy. Thermal properties will be discussed based on differential scanning calorimetry analysis. Electrical and electrochemical characterisctics obtained by electrochemical impedance spectroscopy, galvanostatic cycling and cyclic voltametry will demonstrate the applicability of such hydrogel electrolyte. This study could promote a great innovation in the energy storage field, by recycling one of apple peel’s component (which is the main waste in preserves manufacturing [4] ) into a hydrogel electrolyte. References [1] N. R. C. Canada in Environmentally friendly printed batteries , Vol. Boucherville, Quebec, 2021 . [2] C. Y. Chan, Z. Wang, H. Jia, P. F. Ng, L. Chow and B. Fei, Journal of Materials Chemistry A 2021 , 9 , 2043-2069. [3] Y. Huang, M. Zhong, F. Shi, X. Liu, Z. Tang, Y. Wang, Y. Huang, H. Hou, X. Xie and C. Zhi, Angewandte Chemie International Edition 2017 , 56 , 9141-9145. [4] B. S. Virk and D. S. Sogi, International Journal of Food Properties 2004 , 7 , 693-703.
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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 | 0.001 | 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 | 0.001 | 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".