Facile synthesis of urchin-like LaWO<sub>4</sub>Cl assemblies and their near-infrared photothermal conversion
Bibliographic record
Abstract
The construction of the hierarchical nanostructures of inorganic materials with high stability has attracted great attention for photothermal therapy. In this paper, we presented the preparation of urchin-like LaWO4Cl nanostructures assembled with nanoribbons via a facile solvothermal reaction. X-ray diffraction (XRD) analysis confirmed the formation of good crystalline urchin-like LaWO4Cl assemblies. Energy dispersive X-ray spectroscopy (EDX) and X-ray photoelectron spectroscopy (XPS) revealed the element composition of the prepared urchin-like nanostructures. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) investigations showed that the urchin-like LaWO4Cl assemblies were composed of single crystalline nanoribbons with diameters less than 10 nm. When excited with an 808 nm near-infrared (NIR) laser at the power density of 1.91 W cm-2 for 5 min, the temperature quickly increased to 52 °C. The in vitro cytotoxicity of urchin-like LaWO4Cl was tested with human cervical cancer cells (HeLa), revealing excellent biocompatibility. More importantly, the photothermal treatment with urchin-like LaWO4Cl displayed great therapeutic efficacy in vitro. Thus, urchin-like LaWO4Cl would be a new promising NIR light-driven photothermal agent, which can also pave a new way for the material design of PTT agents.
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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".