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Record W2953606412 · doi:10.1039/c9nr03082d

Facile synthesis of urchin-like LaWO<sub>4</sub>Cl assemblies and their near-infrared photothermal conversion

2019· article· en· W2953606412 on OpenAlexaff
Lin Sun, Yang Shi, Mingcong Tang, Dong Wang, Yaping Tian, Jing Li

Bibliographic record

VenueNanoscale · 2019
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsPetro-Canada
FundersNational Natural Science Foundation of China
KeywordsPhotothermal therapyInfraredMaterials scienceNanotechnologyOptoelectronicsOpticsPhysics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.202
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2019
Admission routes1
Has abstractyes

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