Interactions between gold, thiol and As(<scp>iii</scp>) for colorimetric sensing
Bibliographic record
Abstract
As(iii) or arsenite is extremely toxic, and various colorimetric sensors were reported for its on-site detection. A highly cited example was based on gold nanoparticles (AuNPs) modified with a few thiol-containing compounds including dithiothreitol (DTT), reduced glutathione (GSH), and cysteine (Cys). As(iii) was believed to crosslink these surface ligands to aggregate AuNPs and produce a red-to-blue color change. Since As(iii) can also adsorb on AuNPs, we herein carefully studied this effect on these ligand-capped AuNPs. For citrate-capped AuNPs, 10 mM free citrate resulted in a strong blue color in the presence of As(iii) attributable to the elevated ionic strength, while common divalent cations resulted in no color change due to the chelation effect of free citrate. For AuNPs capped with the three thiol compounds, more than 5 mM As(iii) was needed to produce a color change, which was very different from the previously reported color change with nanomolar concentration of As(iii). Our color change was attributed to the displacement of the surface ligands by As(iii) instead of crosslinking by it. This conclusion was made based on the irreversibility of the color change, kinetics of the reaction, and high As(iii) concentration needed. This work has revealed that any two species from AuNPs, thiol and As(iii) can react. It also calls for care in the interpretation of related colorimetric sensing mechanisms, and the need to consider the previously overlooked As(iii) adsorption onto AuNPs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".