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Record W1984333442 · doi:10.1121/1.3654628

Using light to probe hypersound in porous materials systems

2011· article· en· W1984333442 on OpenAlexaffabout
L. C. Parsons, Jordan Peckham, Anna Maria Polomska, G. Todd Andrews

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBrillouin SpectroscopyPorous siliconMaterials scienceSiliconPorous mediumBrillouin zoneBrillouin scatteringPorosityOpticsPhononOptoelectronicsComposite materialCondensed matter physicsOptical fiberPhysics

Abstract

fetched live from OpenAlex

An overview of the technique of Brillouin light scattering spectroscopy and its application to the study of hypersound in micro- and mesoporous materials systems will be presented. Particular emphasis will be placed on results obtained from light scattering experiments on porous silicon-based structures. For porous silicon films, it was found that the acoustic phonon velocities and elastic properties depend strongly on the film porosity and morphology. Brillouin studies of porous silicon superlattices with periodicity on the order of the hypersound wavelength reveal that these structures behave as hypersonic phononic crystals, while those with smaller modulation wavelengths act as effective elastic media. New results on localized acoustic modes in porous silicon multilayers will also be discussed. Collectively, these studies provide a detailed picture of hypersound propagation in porous silicon systems and demonstrate the utility of Brillouin spectroscopy for probing acoustic phonon behavior in this challenging class of materials. [This work was supported by the Canada Foundation for Innovation, Memorial University of Newfoundland, and the Natural Sciences and Engineering Research Council of Canada.]

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)0.001
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 score0.382
Threshold uncertainty score0.273

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.233
Teacher spread0.209 · 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".

Quick stats

Citations0
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicSmart Materials for ConstructionFrench-language works237,207