MétaCan
Menu
← Back to cohort
Record W2889433001 · doi:10.1149/ma2018-02/31/1089

Mapping Strain and Composition Effects on Gesn Band Structure Using Spectroscopic Ellipsometry

2018· article· en· W2889433001 on OpenAlexaff
Anis Attiaoui, Simone Assali, Jérôme Nicolas, Oussama Moutanabbir

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceOptoelectronicsSiliconEllipsometryBand gapPhotonicsTernary operationInfraredFabricationOpticsThin filmNanotechnologyComputer science

Abstract

fetched live from OpenAlex

One of the most interesting research areas in silicon photonics has been the development of silicon-compatible electro-optical devices including detectors, modulators, and light sources, to name a few. IN this regard, the binary alloy Ge1-xSn x has been of particular importance due its bandgap directness in contrast to silicon and germanium.[1-2] As a matter of fact, great efforts have been expended in recent years towards the development of the epitaxial growth of high-quality GeSn crystals on silicon platform and their introduction in design and fabrication of optoelectronic devices.[3] This interest has been nurtured by the ability to manipulate the GeSn band structure by controlling Sn composition and strain. These two degrees of freedom provide flexibility to tune the optoelectronic properties relevant to a variety of devices. For instance, GeSn is attractive material system for photodetectors with absorption edge extending over a broad wavelength range from the short wavelength infrared (SWIR, 1.6-2 µm) to the mid-infrared (MIR, 2-5 µm). In this perspective, this work reports detailed investigations of the influence of both strain and composition on the band structure above 1 eV of GeSn ternary alloys through a spectroscopic ellipsometry study. Understanding the individual influence of each parameter is highly critical to establish and optimize the properties of GeSn device layers. GeSn thin films investigated in this work were grown using a low-pressure Chemical Vapor Deposition (LP-CVD) at different Sn compositions in the 7-18 at.% range.[4] A graded growth process on Ge-virtual substrates was used. Figure A shows a typical example of the investigated samples. The figure exhibits a schematic representation where the bottom layer (BL- 6.3% of Sn) and the top layer (TL- 12.5% of Sn) have different Sn composition. Furthermore, High-Resolution X-Ray Diffraction (HR-XRD) was used to characterize the compressive strain present in each layer. In the sample shown in Figure A, the strain was found to be respectively equal to -0.65% and -1.503%, for the BL and TL. Next, a rotating-analyzer spectroscopic ellipsometry system measures the following parameters (Ψ and Δ) for different incidence angles from 45 to 70° as shown in Figure B. These parameters are then coupled with an optical model to allow for an accurate determination of the complex dielectric (ε=ε1+iε2) of the sample. The developed optical model is presented in Figure A where the different constituting layers are shown: GeSn(BL/ML)/ Ge(VS)/Si. Furthermore, two additional surface layers were introduced to simulate the surface roughness as well as the presence of the native GeO2 oxide. The optical properties of the GeO2 oxide were used in their tabulated form from Reference [5]. The optical model is shown as a dashed line in Figure B, and the accuracy is measured by a very low MSE of 0.598. Consequently, the dielectric constant can be extracted. Having extracted the dielectric constant from the ellipsometry measurement, it becomes now possible to quantify the contributions from the E1, E1 + Δ1, E0’, E2, and E1’ critical points in the joint density of electronic states which they will be enhanced by computing numerical second derivatives of the already measured dielectric function. The numerical second derivative is often coupled with the Savitsky-Golay smoothing filter to reduce noise while maintaining the shape and the height of waveform peaks. The resulting lineshapes were fitted with model expressions from which the critical point energies Ej, amplitudes, broadenings Aj, and phases ϕj were determined. The model lineshapes have been well established in literature. [6] In Figure C, a lineshape fit for the E2 critical point energy for the Bottom layer (BL) was undertaken. The accuracy of the fit was confirmed with a coefficient of determination (R2) higher than 0.97. The Levenberg-Marquardt fit gave an E2 energy of 4.06±0.20 eV for the BL, whereas for the Top layer (TL), E2 was equal to 4.10±0.30 eV. After finding the energy for each sample, it becomes possible to map the effect of strain on the bang gap energies. Based on these systematic studies, this presentation will describe the individual influence of strain and composition on the optical properties of Sn-rich GeSn semiconductors. References: [1] A. Attiaoui and O. Moutanabbir, J. Appl. Phys. 116 63712 (2014) [2] S. Gupta et al, J. Appl. Phys. 113 073707 (2013) [3] S. Wirth et al., Progress in Crystal Growth and Characterization of Materials 62, 1 (2016).. [4] S. Assali, Under Review (2017) [5] Nunley et al, J. Vac. Sci. Technol. B 34(6), 061205 (2016) [6] P. Lautenschlager, M. Garriga, L. Vina, and M. Cardona, Phys. Rev. B 36, 4821 (1987) Figure 1

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueECS Meeting Abstracts→Same topicPhotonic and Optical Devices→French-language works237,207→