MétaCan
Menu
Back to cohort
Record W1984334247 · doi:10.1116/1.1722271

Stress-assisted nickel-induced crystallization of silicon on glass

2004· article· en· W1984334247 on OpenAlexaff
Pouya Hashemi, Jaber Derakhshandeh, S. Mohajerzadeh, M. Robertson, A. Tonita

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2004
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsAcadia University
Fundersnot available
KeywordsMaterials scienceCrystallizationSiliconAnnealing (glass)Amorphous siliconComposite materialAmorphous solidPolycrystalline siliconTransmission electron microscopyScanning electron microscopeNanocrystalline siliconAmorphous metalCrystalliteMetallurgyCrystallographyLayer (electronics)Crystalline siliconChemical engineeringNanotechnologyThin-film transistorChemistryAlloy

Abstract

fetched live from OpenAlex

The effect of external mechanical stress on the crystallization of amorphous silicon deposited on thin, flexible glass substrates has been studied. A thin, 5–10 Å, layer of nickel deposited on the surface of the amorphous silicon layer acted as the seed of crystallization and the crystallization was observed to initiate at the top surface and proceed down towards the glass substrate. Application of a tensile stress during the annealing stage led to a uniform, partial crystallization of the amorphous silicon for annealing temperatures as low as 310 °C. In contrast, the application of compressive stress led to buckling of the silicon films during annealing under mechanical stress and crystallization was nonuniform over the surface of the sample. The crystalline quality of the films was investigated using scanning electron microscopy, x-ray diffraction, and transmission electron microscopy analyses. In addition, lateral polycrystalline growth of the silicon was observed for the case in which the nickel seed layer was less than 5 Å thick.

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 score0.016
Threshold uncertainty score0.921

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.232
Teacher spread0.219 · 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

Citations18
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Vacuum Science & Technology A Vacuum Surfaces and FilmsSame topicThin-Film Transistor TechnologiesFrench-language works237,207