MétaCan
Menu
Back to cohort

Studying the kinetics of microstructure formation through dewetting of As-Se thin films

2021· article· en· W3123144837 on OpenAlexafffund
Y.N. Colmenares, Sandra Helena Messaddeq, Younès Messaddeq

Bibliographic record

VenuePhysical Review Materials · 2021
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Thin Films
Canadian institutionsUniversité Laval
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationMinistère du Développement Économique, de l’Innovation et de l’Exportation
KeywordsDewettingMaterials scienceChalcogenideMicroscale chemistryMicrostructurePhotonicsNanotechnologyThin filmKineticsChalcogenide glassOptoelectronicsChemical physicsComposite materialPhysics

Abstract

fetched live from OpenAlex

The chalcogenide glasses have always drawn attention in photonics for being the most suitable materials for applications in the infrared region. Although their use in integrated photonics is promising, there are yet many challenges to integrating optical components in nano- and microscale. The dewetting of thin films is a mostly unexplored and attractive alternative to produce self-assembled structures in solid substrates. Chalcogenide glasses are among the few materials to present dewetting below 300 \ifmmode^\circ\else\textdegree\fi{}C. We report the thermal-induced dewetting of ${\mathrm{As}}_{x}{\mathrm{Se}}_{100\text{--}x}$ thin films, deposited by electron beam. The activation energy for dewetting is obtained by analyzing the kinetics of dewetting at different temperatures. This energy is greatly affected by the number of homopolar bonds and the glass dimensionality. As a consequence, the higher activation energy is found in the composition with fewer degrees of freedom $({\mathrm{As}}_{40}{\mathrm{Se}}_{60})$. The rupture mechanism and the size of the droplets are also greatly affected by the glass composition. This study provides an insight on how to control and use dewetting as an alternative route for nano- and microfabrication in photonics.

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 score0.320

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 head0.017
GPT teacher head0.274
Teacher spread0.257 · 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

Citations9
Published2021
Admission routes2
Has abstractyes

Explore more

Same venuePhysical Review MaterialsSame topicFluid Dynamics and Thin FilmsFrench-language works237,207