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Record W2100291526 · doi:10.1115/1.4023227

Sizing of Molybdenum Nanoparticles Using Time-Resolved Laser-Induced Incandescence

2013· article· en· W2100291526 on OpenAlex

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

VenueJournal of Heat Transfer · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsIncandescenceNanoparticleMolybdenumSizingMaterials scienceParticle (ecology)LaserNanotechnologyChemical engineeringOpticsChemistryCombustionMetallurgyPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Aerosolized metal nanoparticles have numerous existing and emerging applications in materials science, but their functionality in these roles is strongly size-dependent. Very recently, time-resolved laser-induced incandescence (TiRe-LII) has been investigated as a candidate for sizing aerosolized metal nanoparticles, which requires an accurate model of the heat transfer through which the laser-energized particles re-equilibrate with the bath gas. This paper presents such a model for molybdenum nanoparticles, which is then used to analyze experimental TiRe-LII data made on aerosols of molybdenum nanoparticles in helium, argon, nitrogen, and carbon dioxide. While it is possible to estimate the particle size distribution width, recovering particles sizes requires independent knowledge of the thermal accommodation coefficient, which is presently unknown.

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 categoriesInsufficient payload (model declined to judge)
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 score0.067
Threshold uncertainty score0.997

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)0.0040.000

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 head0.027
GPT teacher head0.237
Teacher spread0.210 · 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