Rapid Nucleation of Iron Oxide Nanoclusters in Aqueous Solution by Plasma Electrochemistry
Bibliographic record
Abstract
Progresses in cold atmospheric plasma technologies have made possible the synthesis of nanoparticles in aqueous solutions using plasma electrochemistry principles. In this contribution, a reactor based on microhollow cathodes and operating at atmospheric pressure was developed to synthesize iron-based nanoclusters (nanoparticles). Argon plasma discharges are generated at the tip of the microhollow cathodes, which are placed near the surface of an aqueous solution containing iron salts (FeCl2 and FeCl3) and surfactants (biocompatible dextran). Upon reaction at the plasma-liquid interface, reduction processes occur and lead to the nucleation of ultrasmall iron-based nanoclusters (IONCs). The purified IONCs were investigated by XPS and FTIR, which confirmed that the nucleated clusters contain a highly hydrated form of iron oxide, close to the stoichiometric constituents of α-FeOOH (goethite) or Fe5O3(OH)9 (ferrihydrite). Relaxivity values of r1 = 0.40 mM(-1) s(-1) and r2/r1 = 1.35 were measured (at 1.41 T); these are intermediate values between the relaxometric properties of superparamagnetic iron oxide nanoparticles used in medicine (USPIO) and those of ferritin, an endogenous contrast agent. Plasma-synthesized IONCs were injected into the mouse model and provided positive vascular signal enhancement in T1-w. MRI for a period of 10-20 min. Indications of rapid and strong elimination through the urinary and gastrointestinal tracts were also found. This study is the first to report on the development of a compact reactor suitable for the synthesis of MRI iron-based contrast media solutions, on site and upon demand.
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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".