Determining the Concentration Dependent Transformations of Ag Nanoparticles in Complex Media: Using SP-ICP-MS and Au@Ag Core–Shell Nanoparticles as Tracers
Bibliographic record
Abstract
The fate, behavior, and impact of engineered nanoparticles (NPs) in toxicological and environmental media are driven by complex processes which are difficult to quantify. A key limitation is the ability to perform measurements at low and environmentally relevant concentrations, since concentration may be a key factor determining fate and effects. Here, we use single particle inductively coupled mass spectroscopy (SP-ICP-MS) to measure directly NP diameter and particle number concentration of suspensions containing gold–silver core–shell (Au@Ag) NPs in EPA moderately hard water (MHW) and MHW containing 2.5 mg L –1 Suwannee River fulvic acid. The Au core of the Au@Ag NPs acts as an internal standard, and aids in the analysis of the complex Ag transformations. The high sensitivity of SP-ICP-MS, along with the Au@Ag NPs, enabled us to track the NP transformations in the range 0.01 and 50 μg L –1, without further sample preparation. On the basis of the analysis of both Au and Ag parameters (size, size distribution, and particle number), concentration was shown to be a key factor in NP behavior. At higher concentration, NPs were in an aggregation-dominated regime, while at the lower and environmentally representative concentrations, dissolution of Ag was dominant and aggregation was negligible. In addition, further formation of ionic silver as Ag NPs in the form of AgS or AgCl was shown to occur. Between 1 and 10 μg L –1, both aggregation and dissolution were important. The results suggest that, under realistic conditions, the role of NP homoaggregation may be minimal. In addition, the complexity of exposure and dose in dose–response relationships is highlighted.
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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 | 0.001 | 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 | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".