Ionic Liquid-Derived Imidazolium Cation Linkers for the Layer-by-Layer Assembly of Polyoxometalate-MWCNT Composite Electrodes with High Power Capability
Bibliographic record
Abstract
Imidazolium cations derived from ionic liquids were demonstrated as effective linker molecules for the layer-by-layer (LbL) deposition of polyoxometalates (POMs) to increase the charge storage of multi-walled carbon nanotube (MWCNT) electrodes. MWCNTs modified with GeMo12O40(4-) (GeMo12) via an imidazolium cation linker demonstrated highly reversible redox reactions and a capacitance of 84 F cm(-3), close to 4 times larger than bare CNT. Compared to CNT-GeMo12 composites fabricated with a conventional polyelectrolyte linker poly(diallyldimethylammonium chloride), (PDDA), the imidazolium cations resulted in lower POM loading, but higher conductivity and in turn superior performance at fast charge-discharge conditions. A polymerized imidazolium linker (PIL) was also synthesized based on the ethyl-vinyl-imidazolium monomer. CNT-GeMo12 composites fabricated with this PIL achieved high POM loading comparable to PDDA, while still maintaining the good conductivity and high rate capabilities shown by the monomer imidazolium units. The high conductivity imparted by the PIL is especially valuable for the fabrication of multilayer POM composites. Dual-layer GeMo12 O40(4-)-SiMo12O40(4-) (GeMo12-SiMo12) electrodes built with this PIL demonstrated a combined contribution of the individual POMs resulting in a capacitance of 191 F cm(-3), over nine times larger than bare MWCNT. The PIL dual layer composites also maintained 72% of this capacitance at a fast rate of 2 V s(-1), compared to just over 50% retention for similar electrodes fabricated with PDDA.
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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 | 0.000 |
| 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".