pH-Response Mechanism of a Redox Reaction between Silver Ions and Hydroquinone
Bibliographic record
Abstract
Studying chemical reactions at the nanoscale level could aid to better understand and control reaction processes. In this paper, the redox reaction between hydroquinone and Ag + via gold nanoparticles as a suitable surface was taken as an example, where its thermochemical values were computed by using density functional theory (DFT) methods with the 6-31G(d) basis set. The calculated results exhibited that the reaction kinetics was related to pH values and concluded as three different kinds of processes. Assisted by the gold nanoparticles, we tracked the reduction of Ag + in real time by plasmon resonance Rayleigh scattering spectroscopy and dark-field microscopy. Moreover, discrete dipole approximation and transmission electron microscope images were also conducted, and the calculated results were in good agreement with the experimental ones. In addition, we utilized the pH response of the redox reaction to distinguish cancer cells from the normal ones, which showed promising applications in promoting the development of disease diagnosis.
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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) | 0.001 | 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".