Core–Double-Shell Fe<sub>2</sub>O<sub>3</sub>@SiO<sub>2</sub>@Jarosite Hybrid Nanoparticles Synthesized by Laser Ablation of Turquoise in Ethanol
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide This work highlights a facile green route for the one-step synthesis of iron oxide core–double-shell nanoparticles (NPs) and aluminum phosphide (AlP) nanosheets by pulsed laser ablation of the mineral turquoise target from Nishapur in the presence of an ethanol solvent. High-resolution transmission electron microscopy, selected-area electron diffraction pattern, and field emission scanning electron microscopy (FESEM) in combination with energy-dispersive X-ray mapping revealed the formation of NPs with a typical core@double-shell structure in which crystalline α-Fe 2 O 3 (iron oxide) formed the core, while SiO 2 (quartz) and (K, H 3 O)Fe 3 (SO 4 ) 2 (OH 6 ) (jarosite) participated as the inner and outer shell, respectively. However, the application of laser ablation on the turquoise phase of the target led to the formation of AlP nanosheets which was confirmed by the X-ray diffraction patterns and FESEM images. Strong absorption of the vein-ablated species in the UV region (250–360 nm) was the characteristic feature of α-Fe 2 O 3 and jarosite phases, while the absorption band at 250–300 nm for the turquoise-ablated species was related to the presence of Cu compound species and also the α-Fe 2 O 3 phase in the sample. Photoluminescence emission spectra for the vein-ablated species depicted a peak centered at 370 nm, while a peak located at 364 nm was ascribed to the turquoise-ablated species. In particular, these hybrid NPs with high purity and stability may offer new opportunities for bio-applications such as anticancer agents and water/wastewater applications.
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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".