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Record W3025607346 · doi:10.1149/ma2020-01522934mtgabs

Characterization of Europium Doped Silicon Oxide, Silicon Oxynitride, and Silicon Nitride Films Prepared By Integrated Ecr-PECVD and Magnetron Sputtering

2020· article· en· W3025607346 on OpenAlexaff
Fahmida Azmi, Yuxuan Gao, Zahra Khatami, Peter Mascher

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsUniversity of New BrunswickMcMaster University
Fundersnot available
KeywordsMaterials sciencePlasma-enhanced chemical vapor depositionSilicon oxynitrideSputter depositionSiliconSputteringPassivationSilicon nitrideThin filmDopingSilicon oxideAnalytical Chemistry (journal)OptoelectronicsNanotechnologyChemistryLayer (electronics)

Abstract

fetched live from OpenAlex

The compatibility of Si-based light sources with mainstream metal-oxide semiconductor technology has become very interesting over the past decades due to their potential in integrated optoelectronics circuits of monolithic Si [1]. A very promising approach to improve the light emission from silicon-based materials is doping silicon with rare earth elements, and numerous research is involved in this field [1]. However, there are only a few works on europium (Eu) doped silicon-based matrix. In this work, Eu doped silicon oxide, silicon oxynitride, and silicon nitride thin films were deposited on P (100) Si substrates using integrated electron cyclotron resonance plasma enhanced chemical vapor deposition (ECR-PECVD) and magnetron sputtering. Silane (SiH 4 ), oxygen (O 2 ), and Nitrogen(N 2 ) gases were used as precursors and solid Eu as the sputtering target. The integrated ECR-PECVD and sputtering system allows tunable and highly consistent Eu doping concentration, better control of the layer stoichiometry along with less hydrogen incorporation in the deposited film compared to conventional CVD systems [2]. Several thin films were investigated using room temperature photoluminescence (PL) and X-ray diffraction (XRD). A detailed investigation of the effect of annealing on the PL was performed. The annealing temperature was varied from 500 O C to 1200 O C in nitrogen and a mixture of nitrogen and hydrogen atmospheres. It was observed that the intensity of the PL spectra increased with increasing annealing temperature. Besides, the hydrogen passivation effect has been studied in this work, which shows that hydrogen passivation increases the intensity of the peak. Based on the XRD measurements, we have found that the amorphous silicon oxide structure changes to a crystalline structure by adding nitrogen in the film. Interestingly silicon oxynitride and silicon nitride films do not show any luminescence at room temperature. The influence of the precursors' gases in the atomic percentage of the thin films was analyzed by Rutherford Backscattering spectrometry (RBS). In addition to it, the thickness and the index of refraction were characterized by variable angle spectroscopic ellipsometry (VASE). Reference: 1. Lin, Z., Huang, R., Wang, H., Wang, Y., Zhang, Y., Guo, Y., ... & Li, H. (2017). Dense nanosized europium silicate clusters induced light emission enhancement in Eu-doped silicon oxycarbide films. Journal of Alloys and Compounds , 694 , 946-951. 2. Miller, J. W., Khatami, Z., Wojcik, J., Bradley, J. D. B., & Mascher, P. (2018). Integrated ECR-PECVD and magnetron sputtering system for rare-earth-doped Si-based materials. Surface and Coatings Technology , 336 , 99-105.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
GPT teacher head0.212
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2020
Admission routes1
Has abstractyes

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