Polyethylene glycol mediated synthesis of iron vanadate (FeVO<sub>4</sub>) nanoparticles with supercapacitive features
Bibliographic record
Abstract
Abstract Binary transition metal oxides, such as iron vanadate (FeVO4), possess unleashed potential to be the best electrode material for supercapacitor, owing to their high capacitance, stability and conductivity. This present work reports investigations on the influence of a surfactant, polyethylene glycol (PEG 4000), on the structure, morphology and electrochemical behaviour of FeVO4 nanoparticles. The P4-FeVO4 exhibited specific capacitance of 428.0 Fg−1 at a current density of 2.0 Ag−1, and arguably better performance and cyclic stability than FeVO4 synthesised without PEG 4000. Thus, PEG 4000 significantly influenced the morphological and electrochemical performance of the FeVO4. Furthermore, the assembled P4-FeVO4 based symmetric capacitor device had a specific capacitance of 101.0 Fg−1 with an energy density of 14.1 Whkg−1. This improved electrochemical performance of the P4-FeVO4 based devices is attributed to the physicochemical properties of P4-FeVO4 nanoparticles, mediated by the PEG 4000.
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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) | 0.000 | 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 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".