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Record W4401699137 · doi:10.1149/ma2024-01221326mtgabs

Optical Properties of Europium-Doped Silicon-Based Thin Films

2024· article· en· W4401699137 on OpenAlexaff
Fahmida Azmi, Paramita Bhattacharyya, Peter Mascher

Bibliographic record

VenueECS Meeting Abstracts · 2024
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceSiliconOptoelectronicsDopingEuropiumThin filmSilicon oxideNanotechnologyLuminescenceSilicon nitride

Abstract

fetched live from OpenAlex

The integration of a silicon-based light emitter into existing CMOS technology has long been intriguing due to its optoelectronic compatibility with microelectronics [1]. However, the indirect band gap nature of bulk silicon has hindered its effectiveness as a light emitter. In addressing this limitation, rare earth ions have emerged as significantly interesting candidates owing to their unique optical and electronic properties. Rare earth-doped silicon structures have earned special attention as they exhibit sharp light emission in different spectral regions [2] . This notable feature is attributed to the effective excitation of rare earth ions within the host matrix. Efficiently excited rare earth ions can produce visible emissions ranging from infrared to ultraviolet, presenting possibilities in diverse applications such as solid-state lighting, displays, lasers, photovoltaics, and optical communication. The incorporation of rare earth-doped silicon structures presents a promising solution to overcome the challenges posed by silicon's intrinsic properties, thereby paving the way for improved performance across a diverse range of optoelectronic applications. Europium is a attractive rare earth material with two optically active states, Eu2+ and Eu3+, enabling it to generate a diverse range of color emissions extending from blue to red depending on the surrounding matrix [3]. In this study, we investigated the optical properties and compositions of europium (Eu)-doped thin films including silicon oxide, silicon oxynitride, and silicon carbonitride. For this purpose, thin films were fabricated by electron cyclotron resonance plasma-enhanced chemical vapor deposition (ECR-PECVD) with in-situ magnetron sputtering on p-type 3" Si (100) substrates. In-situ Eu doping was performed by a radio frequency (RF) magnetron sputtering gun, using a 0.25 in. thick, 2 in. (diameter) 99.9% pure Eu sputtering target. Precursor gases, including silane (diluted in 90% argon), oxygen (diluted in 90% argon), nitrogen (diluted in 90% argon), and ethane were utilized. Annealing was performed on the as-deposited films over a broad temperature range, from 600° to 1100°C, in a nitrogen (N2) environment. Rutherford backscattering spectrometry (RBS) was performed to determine the atomic concentration of the film constituents. Variable angle spectroscopic ellipsometry (VASE) analysis was conducted to investigate the optical properties of the films. Room temperature photoluminescence (PL) experiments were performed using a laser diode excitation source operating at a wavelength of 375nm. Notably, bright visible emission was observed in some of the thin films. Finally, we discuss the influence of the atomic concentration of Eu and the annealing temperature on the emission properties observed in the photoluminescence experiments. [1] F. Azmi, Y. Gao, Z. Khatami, and P. Mascher, “ Tunable emission from Eu:SiOxNy thin films prepared by integrated magnetron sputtering and plasma enhanced chemical vapor deposition ,” J. Vac. Sci. Technol. A, vol. 40, no. 4, p. 043402, 2022, doi: 10.1116/6.0001761. [2] A. Brik et al., “Annealing Effects on Structural Characteristics of Europium Doped Silicon-Rich Silicon Nitride,” Silicon, vol. 14, no. 14, pp. 8417–8425, 2022, doi: 10.1007/s12633-021-01636-w. [3] D. Li, X. Zhang, L. Jin, and D. Yang, “Structure and luminescence evolution of annealed Europium-doped silicon oxides films,” Opt. Express, vol. 18, no. 26, p. 27191, 2010, doi: 10.1364/oe.18.027191.

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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 head0.020
GPT teacher head0.241
Teacher spread0.221 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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