Improvements to Single Particle ICPMS by the Online Coupling of Ion Exchange Resins
Why this work is in the frame
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Bibliographic record
Abstract
Single particle ICPMS (SP-ICPMS) is becoming a very promising technique for nanoparticle detection and characterization, especially at very low concentrations (~10(-12)-10(-10) M). Nonetheless, the ability of the technique to detect smaller nanoparticles is presently limited by the setting of threshold values for the discrimination of nanoparticles from the dissolved metal background. In this study, a new approach to attaining lower particle size detection limits has been developed by the online coupling of an ion exchange column (IEC) with SP-ICPMS (IEC-SP-ICPMS). The IEC effectively removes the continuous signal of dissolved metal, allowing for both lower detection limits and an improved resolution of solutions containing multiple particles. The feasibility and the efficiency of this coupling were investigated using silver nanoparticles in the presence of various concentrations of Ag(+) and other major ions (Mg(2+), Ca(2+), Na(+), K(+), and Cl(-)). The online elimination of the dissolved metal made data processing simpler and more accurate. Following the addition of 1 to 4 μg L(-1) of Ag(+) spikes, symmetric particle size distributions were obtained using IEC-SP-ICPMS, whereas the use of SP-ICPMS alone led to asymmetric distributions, especially for nanoparticle sizes below 60 nm. Although this proof of principle study focused on nanosilver, the technique should be particularly useful for any of the metal based nanoparticles with high solubilities.
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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 it