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Record W2806597462 · doi:10.1038/s41598-018-25711-2

Naked Gold Nanoparticles and hot Electrons in Water

2018· article· en· W2806597462 on OpenAlexaff
Khashayar Ghandi, Furong Wang, Cody Landry, Mehran Mostafavi

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsMount Allison University
FundersUniversité Paris-SaclayCentre National de la Recherche Scientifique
KeywordsRadiolysisColloidal goldNanoparticleAqueous solutionPhotochemistryOxidizing agentSolvated electronChemistryIonic bondingElectronChemical physicsMaterials scienceNanotechnologyIonOrganic chemistry

Abstract

fetched live from OpenAlex

The ionizing radiation in aqueous solutions of gold nanoparticles, stabilized by electrostatic non-covalent intermolecular forces and steric interactions, with antimicrobial compounds, are investigated with picosecond pulse radiolysis techniques. Upon pulse radiolysis of an aqueous solution containing very low concentrations of gold nanoparticles with naked surfaces available in water (not obstructed by chemical bonds), a change to Cerenkov spectrum over a large range of wavelengths are observed and pre-solvated electrons are captured by gold nanoparticles exclusively (not by ionic liquid surfactants used to stabilize the nanoparticles). The solvated electrons are also found to decay rapidly compared with the decay kinetics in water. These very fast reactions with electrons in water could provide an enhanced oxidizing zone around gold nanoparticles and this could be the reason for radio sensitizing behavior of gold nanoparticles in radiation therapy.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2018
Admission routes1
Has abstractyes

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