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Record W2088625548 · doi:10.1149/06406.0869ecst

Optical and Electronic Propreties of GeSn and GeSiSn Heterostructures and Nanowires

2014· article· en· W2088625548 on OpenAlexaff
Anis Attiaoui, Oussama Moutanabbir

Bibliographic record

VenueECS Transactions · 2014
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsNanowireHeterojunctionMaterials scienceAlloyShell (structure)Ternary operationRADIUSCondensed matter physicsHamiltonian (control theory)Tight bindingCore (optical fiber)Effective mass (spring–mass system)Electronic structureNanotechnologyOptoelectronicsComposite materialPhysics

Abstract

fetched live from OpenAlex

The first part of this work reports on detailed studies of the influence of both strain and composition on the band structure of GeSiSn ternary alloys. First, we developed a simple yet rigorous semi-empirical second nearest neighbors tight binding sp 3 s * method that incorporates the effect of substitutional disorder. We have found that the composition of α-Sn at the direct to indirect crossover of the ternary alloy decreases from 11% in a fully relaxed alloy to 7% in tensile strained alloy (for a strain value of 0.71%). In the latter case, we have considered a thin GeSiSn layer is epitaxialy grown on a thin Ge substrate. The last section of this work addresses the behavior of GeSn/Ge core-shell nanowires. Herein, we have solved the effective mass Hamiltonian in cylindrical coordinates using a finite difference technique for the core-shell nanowires where the core and the shell are made of different alloys. We have found that above a critical doping concentration of 5×10 16 cm -3 and below a core radius of 20 nm, the electron density is localized in the Ge shell for the Ge 0.9 Sn 0.1 /Ge core-shell nanowire system.

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 score0.269
Threshold uncertainty score0.268

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 head0.003
GPT teacher head0.175
Teacher spread0.172 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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