Application of Polyoxometalate-based composites for sensor systems: A review
Bibliographic record
Abstract
Composites based on polyoxometalates (POMs) have been increasingly attracted by many researchers due to their multitudinous architectures and excellent redox activities as well as outstanding proton and electron transport capacities. Lately, much research has been done on POMs composited with well-porous framework materials (including ZIFs, MOFs) or conducting polymers, carbon quantum dot (CQD), graphene, carbon structures (e.g. carbon nanotubes (CNTs)), and metal nanoparticles (NPs). The results exhibited improved stability and enhanced electrochemical performances. Hence, developing POMs and POM-based composite materials (PCMs) has long been a topic of interest for chemical researchers. Herein, the properties and applications of pristine POMs, doped POMs, and composite-based POMs are reviewed in detail. The various compositions of POMs with sensing application such as POMs-nanocarbon composites (POMs-graphene composites and POMs-carbon nanotube composites), POMs-conductive polymer composites, and POMs-metal composites are also investigated in this review.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".