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Record W1988726474 · doi:10.1139/cjp-2014-0403

Far-infrared properties of helium-doped silicon

2015· article· en· W1988726474 on OpenAlexvenueno aff
Wei Ren, Qingyan Zhou, Bing Li, Hongxiang Deng, Shaobo Han, Wei Liu, Yong Jiang, Xia Xiang, Xiaotao Zu

Bibliographic record

VenueCanadian Journal of Physics · 2015
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsAttenuation coefficientRefractive indexAbsorption (acoustics)SiliconMaterials scienceAtomic physicsAnalytical Chemistry (journal)HeliumSemiconductorAtmospheric temperature rangeInfraredOpticsMolecular physicsPhysicsOptoelectronicsChemistry

Abstract

fetched live from OpenAlex

Single crystal silicon is an important material used for semiconductor devices and also a potential material in device research. Far-infrared optical properties are studied for the helium ion implanted samples with different fluences of 5.0 × 10 16 , 1.0 × 10 17 , 2.0 × 10 17 , and 4.0 × 10 17 cm −2 . The absorption coefficient and refractive index of silicon with different helium concentrations are measured in the wave number range from 4 to 85 cm −1 and temperature range from 145 to 520 K. The results show that the absorption coefficient increases with increasing fluence of helium ions, but the refractive index decreases. The correlations between absorption coefficient and refractive index and temperature of all samples are similar. The refractive index increases with temperature in the whole measurement temperature range, but the absorption coefficient has different trends in the different wavebands. The absorption coefficient decreases with the increase of temperature in the region below 12 cm −1 ; however, the absorption coefficient increases when the wave number is larger than 30 cm −1 . The absorption coefficient curves at different wavebands are well fitted by the Drude model. A large number of helium bubbles and defects, such as voids and dislocations have been observed in the implanted area by transmission electron microscopy (TEM), which contributes to the increase of optical absorption.

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 score0.224
Threshold uncertainty score0.408

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 head0.031
GPT teacher head0.189
Teacher spread0.158 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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