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Record W4414038747 · doi:10.1002/slct.202500580

Facile Synthesis and Photothermal Stability of Silica‐Coated Gold Nanoworms

2025· article· en· W4414038747 on OpenAlexaff
Maryam Yaqub, Ghazanfar Ali Khan, Hamza Qayyum, Mohamed A. Ghanem, Ali Nadeem, Qamar Abbas, Waqqar Ahmed

Bibliographic record

VenueChemistrySelect · 2025
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
FundersHigher Education Commision, PakistanKing Saud University
KeywordsPhotothermal therapyMaterials scienceNanotechnologyChemical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Silica‐coated Au nanoparticles (NPs) have attracted significant attention due to their unique plasmon properties and biocompatibility. This is especially significant for NPs with their plasmon peaks in the near‐infrared (NIR) and within the therapeutic window. In this study, we have synthesized worm‐shaped Au NPs, called nanoworms (NWs) with an intense surface plasmon absorbance peak in the NIR, which were subsequently coated with silica. These NPs were then exposed to a nanosecond pulsed laser with varying fluences at a wavelength of 1064 nm and their UV–visible (vis) spectra were recorded to analyze the effects. Upon laser exposure, the longitudinal plasmon peaks exhibited a blue shift, which was more pronounced in the unmodified NWs. The silica‐coated NWs retained their optical properties even at higher laser fluences. However, for both bare and silica‐coated NWs, the required fluences to induce the shape modification were significantly higher than those previously reported for Au nanorods. These experiments highlight that the silica‐coated NWs are highly promising for biomedical applications, e.g., for various therapeutic and diagnostic uses, where maintaining performance under higher laser fluences is crucial.

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 score0.005
Threshold uncertainty score0.614

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 communication0.0000.000
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 head0.011
GPT teacher head0.225
Teacher spread0.214 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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