LiNO<sub>3</sub>-Based Polymer Electrolytes for Solid Electrochemical Capacitors
Bibliographic record
Abstract
Solid-state, thin, and flexible electrochemical capacitors (ECs) are promising power sources for wearable electronics such as smart textiles and medical sensors. One of the key enablers for safe and high performance solid electrical double layer capacitors (EDLCs) is aqueous-based neutral pH polymer electrolytes (NPPEs) [1-2]. NPPEs containing chloride [3-5] or sulfate salts [6-8] as ion conductors, have been demonstrated high ionic conductivities with wide cell voltage window (>1.5 V, beyond the typical limit of aqueous-based systems). While nitrate solution can also offer similarly wide potential window (demonstrated in liquid electrolytes [9]), their polymer electrolytes may offer several additional advantages: (i) better compatibility with wide-range of polymers from its chaotropic nature, (ii) good thermal stability from deep eutectic temperature with water, and (iii) good water-retaining ability from hygroscopic nature that allows for higher retention than sulfates while maintaining better structural integrity than chlorides. In this study, we aim to: (i) develop a class of high performance LiNO3 based NPPEs, (ii) investigate the underlying material characteristics of the NPPE that support good electrochemical performance, and (iii) demonstrate its application in solid EDLC devices using carbon-based electrodes. The polymer electrolytes utilizing either polyacrylamide or poly(vinyl alcohol) host with various amount of LiNO3 have been systematically studied for their ionic conductivities and performance in solid capacitive devices. While increasing the salt content can lead to higher ionic conductivity, the mechanical properties may be compromised from excessive water absorption. The optimized electrolytes exhibited a high ionic conductivity (>20 mS cm-1) at ambient, relatively high conductivity retention at sub-zero temperatures, and long shelf-life (>30 days). These electrolytes maintained well-hydrated ions and would enable solid-state double layer capacitors, without any separator. References: [1] K. Fic et al., "Novel insight into neutral medium as electrolyte for high-voltage supercapacitors," Energy & Env. Sci., 2, 2012. [2] C. Zhong et al., "A review of electrolyte materials and compositions for electrochemical supercapacitors," Chem. Soc. Rev., 44, 2015. [3] G. Wang et al., “LiCl/PVA Gel Electrolyte Stabilizes Vanadium Oxide Nanowire Electrodes for Pseudocapacitors,” ACS Nano, 6, 2012. [4] X. Peng et al., “A zwitterionic gel electrolyte for efficient solid-state supercapacitors,” Nat. Comm., 7, 2016. [5] A. Virya and K. Lian, “Polyacrylamide-lithium chloride polymer electrolyte and its applications in electrochemical capacitors,” Electrochem. Comm., 74, 2016 [6] N. Batisse and E. Raymond- Piñero, “A self-standing hydrogel neutral electrolyte for high voltage and safe flexible supercapacitors,” J. Power Sources, 348, 2017. [7] A. Virya et al., "Na2SO4-polyacrylamide electrolytes and enabled solid-state electrochemical capacitors," Batteries & Supercaps, 2019. [8] T. Gu and B. Wei, “High-performance all-solid-state asymmetric stretchable supercapacitors based on wrinkled MnO2/CNT and Fe2O3/CNT macrofilms,” J. Mater. Chem. A, 4, 2016. [9] K. Fic et al., “Comparative operando study of degradation mechanisms in carbon-based electrochemical capacitors with Li2SO4 and LiNO3 electrolytes,” Carbon, 120, 2017.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".