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Record W2888933437 · doi:10.1063/1.5046652

Anisotropic stress in laser-written LaBGeO5 glass-ceramic composites

2018· article· en· W2888933437 on OpenAlexafffund
Alexander L. Paterson, Josef W. Zwanziger

Bibliographic record

VenueJournal of Applied Physics · 2018
Typearticle
Languageen
FieldMaterials Science
TopicGlass properties and applications
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaCompute Canada
KeywordsMaterials scienceCrystal (programming language)Residual stressStress (linguistics)Composite materialAnisotropyRaman spectroscopyCeramicPhase (matter)Thermal expansionLaserIsotropyOpticsChemistry

Abstract

fetched live from OpenAlex

LaBGeO5 glass-ceramic composite materials are of interest because the LaBGeO5 crystal phase is ferroelectric and can be grown in single-crystal form within the glass by localized heating from femtosecond laser irradiation. The crystals formed are expected to exhibit residual stress, due to the different mechanical properties of the glass and crystal phases. Recent micro-Raman data on these crystals have been interpreted as showing an isotropic stress field in the crystals. Here, we reinterpret these data in light of detailed density functional perturbation calculations of the Raman spectra of the crystal phase under different stress conditions. Our results support a model where the stress in the ab plane of the LaBGeO5 crystal is compressive and the stress along the c axis of the crystal is tensile. This model is consistent with the linear thermal expansion coefficients of the LaBGeO5 crystal, which are anisotropic and of differing sign. These results indicate the complexity of crystal formation in this system and possible limitations of using it in optical devices where a uniform stress state would be required.

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 score0.008
Threshold uncertainty score0.361

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 head0.013
GPT teacher head0.241
Teacher spread0.228 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

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