MétaCan
Menu
Back to cohort
Record W4311910680 · doi:10.1149/2162-8777/aca9fb

A Comparative Study of a:SiCN:H Thin Films Fabricated with Acetylene and Methane

2022· article· en· W4311910680 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueECS Journal of Solid State Science and Technology · 2022
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsUniversity of New BrunswickMcMaster University
Fundersnot available
KeywordsElastic recoil detectionMaterials scienceThin filmNanoindentationCarbon filmAnalytical Chemistry (journal)AcetylenePlasma-enhanced chemical vapor depositionChemical vapor depositionEllipsometryRaman spectroscopyComposite materialNanotechnologyOrganic chemistryOpticsChemistry

Abstract

fetched live from OpenAlex

In this paper we present a comparative study of the properties of amorphous hydrogenated silicon carbonitride (SiCN:H) thin films deposited by electron cyclotron resonance plasma enhanced chemical vapor deposition (ECR-PECVD). The elemental composition, growth rate, density, and refractive index values of the SiCN:H thin films were analyzed as functions of flow rates of pure acetylene (C 2 H 2 ) and methane (CH 4 ) hydrocarbon precursors. The mechanical properties were studied with nanoindentation measurements to compare hardness and Young’s modulus of the SiCN:H thin films deposited with different carbon sources. Variable angle spectroscopic ellipsometry (VASE), elastic recoil detection (ERD), and Rutherford backscattering spectrometry (RBS) were used to determine thin film properties. Higher carbon content in the thin films was achieved by acetylene compared to methane at the same flow rate due to its lower ionization energy during the deposition. Infrared (IR) absorption spectra of the thin films deposited with acetylene precursor were analyzed to determine the correlation between the hydrocarbon flow rate and the intra-molecular bond intensities in the thin films. We found that the major contribution to the hardness comes from hydrogen (H) in the SiCN matrix which makes the films less dense. Carbon improves the hardness, however, H introduced by the hydrocarbon reduces the mechanical strength.

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.

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)0.002
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 score0.026
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.306
Teacher spread0.286 · 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