Light-Assisted Synthesis of Pt−Zn Porphyrin Nanocomposites and Their Use for Electrochemical Detection of Organohalides
Bibliographic record
Abstract
Pt-Zn porphyrin nanocomposites have been synthesized using zinc porphyrin and dihydrogen hexachloroplatinate in the presence of light and ascorbic acid. TEM and AFM imaging revealed that Pt nanoparticles with an average diameter of approximately 3.5 nm were embedded within the Zn porphyrin matrix. The glassy carbon electrode was modified with Nafion-stabilized Pt-Zn porphyrin nanocomposites and used for dehalogenation of carbon tetrachloride, chloroform, pentachlorophenol, chlorobenzene, and hexachlorobenzene as five test models. The Pt-Zn porphyrin nanocomposite-modified electrode exhibited catalytic activity for the reduction of organohalides at -1.0 V versus Ag/AgCl. Raman signatures confirmed the dehalogenation of chlorobenzene by the nanocomposite-modified electrode. The above two aliphatic and three aromatic organohalides had detection limits of 0.5 microM with linearity up to 8 microM. The modified electrode was good for at least 80 repeated measurements of 4 microM chlorobenzene with a storage stability of 1 month at room temperature. The deactivation of the electrode activity was associated with the loss of platinum nanoparticles from the nanocomposite structure.
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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".