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Record W4411223653 · doi:10.1007/s00340-025-08504-0

Laser-induced incandescence of iron nanoparticles: effects of laser-induced sintering and coalescence

2025· article· en· W4411223653 on OpenAlexafffund
S. Robinson-Enebeli, Christof Schulz, Kyle J. Daun

Bibliographic record

VenueApplied Physics B · 2025
Typearticle
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaUniversität Duisburg-EssenDeutsche Forschungsgemeinschaft
KeywordsMaterials scienceIncandescenceLaserNanoparticleCoalescence (physics)Absorption (acoustics)FluenceWavelengthAbsorption cross sectionSPHERESOpticsMolecular physicsAnalytical Chemistry (journal)OptoelectronicsCross section (physics)NanotechnologyComposite materialSootChemistryCombustion

Abstract

fetched live from OpenAlex

While time-resolved laser-induced incandescence is a promising technique for characterizing metal nanoparticles in the gas phase, there remain several commonly observed and unexplained features in the data, including larger-than-predicted absorption cross-sections (excessive absorption) and faster-than-predicted cooling rates immediately following peak emission (apparent anomalous cooling). In the case of low melting point metals such as iron, laser-heated aggregates coalesce into spheres (i.e., fully sinter) before the peak of the LII signal is reached. Coalescence may affect the observed TiRe-LII signals in two ways: (i) the transition from aggregates to spheres reduces the absorption cross-section, which affects both the total absorbed laser energy and the intensity of the emitted incandescence in a wavelength-dependent manner; and (ii) surface energy is converted into sensible energy of the nanoparticles, which increases their peak temperature. While the revised LII model does not completely account for the rapid signal decay immediately following the peak signal, the predicted curves align more closely with the measured intensities from coalesced particles during the later cooling times. Supplementary Information: The online version contains supplementary material available at 10.1007/s00340-025-08504-0.

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 score0.030
Threshold uncertainty score0.831

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 head0.008
GPT teacher head0.213
Teacher spread0.205 · 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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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