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Record W2325239987 · doi:10.1021/la3010689

Ultraclean Derivatized Monodisperse Gold Nanoparticles through Laser Drop Ablation Customization of Polymorph Gold Nanostructures

2012· article· en· W2325239987 on OpenAlex
Carlos J. Bueno-Alejo, Claudio D’Alfonso, Natalia L. Pacioni, María González‐Béjar, Michel Grenier, Osvaldo Lanzalunga, Emilio I. Alarcón, J. C. Scaiano

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLangmuir · 2012
Typearticle
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDispersityLaser ablationColloidal goldNanoparticleDrop (telecommunication)Materials scienceLaser ablation synthesis in solutionNanotechnologyNanostructureReducing agentLaserChemical engineeringPolymer chemistryOptics

Abstract

fetched live from OpenAlex

We report a novel nanosecond laser ablation synthesis for spherical gold nanoparticles as small as 4 nm in only 5 s (532 nm, 0.66 J/cm(2)), where the desired protecting agent can be selected in a protocol that avoids repeated sample irradiation and undesired exposure of the capping agent during ablation. This method takes advantage of the recently developed synthesis of clean unprotected polymorph and polydisperse gold nanostructures using H(2)O(2) as a reducing agent. The laser drop technique provides a unique tool for delivering controlled laser doses to small drops that undergo assisted fall into a solution or suspension of the desired capping agent, yielding monodisperse custom-derivatized composite materials using a simple technique.

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.

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 score0.032
Threshold uncertainty score0.770

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)0.0000.000

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 head0.013
GPT teacher head0.220
Teacher spread0.206 · 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