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Record W2102330496 · doi:10.1017/s0263034609990589

Evidence of strong contribution from neutral atoms in intense harmonic generation from nanoparticles

2010· article· en· W2102330496 on OpenAlex
T. Ozaki, L. B. Elouga Bom, J. Abdul-Hadi, R. A. Ganeev

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLaser and Particle Beams · 2010
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHarmonicsNanoparticlePlasmaMaterials scienceHarmonicHigh harmonic generationAtomic physicsHarmonic spectrumAtom (system on chip)LaserMolecular physicsNanotechnologyPhysicsOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract We show experimental evidence that, for the intense high-order harmonics from nanoparticles, there is a strong contribution from neutral atoms. We present the results of studies on the harmonics generated in laser-produced plasmas containing various nanoparticles, including Cr 2 O 3 , In 2 O 3 , Ag, MnTiO 3 , Sn, Cu, and Au. These results are compared with the harmonics generated from plasma produced on the surface of bulk targets. The harmonic spectrum from nanoparticle and bulk In 2 O 3 show that there is a lack in the resonant enhancement of the 13th harmonic for the former. Along with the relatively low cut-off for nanoparticle harmonics, these results show that it is the neutral atom in the nanoparticle that emits the intense harmonics. Structural studies of plasma debris confirm the presence and integrity of nanoparticles in the plasma plumes.

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 score0.130
Threshold uncertainty score0.396

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)0.0000.000

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 head0.023
GPT teacher head0.243
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