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Record W2914270493 · doi:10.1149/ma2018-02/31/1077

Atomistic and Optical Properties of Group IV Ultrathin Superlattices

2018· article· en· W2914270493 on OpenAlex
Samik Mukherjee, Matthias Bauer, Anis Attiaoui, Oussama Moutanabbir

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials Characterization Techniques
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceOptoelectronicsMolecular beam epitaxySuperlatticeSemiconductorWaferNanotechnologyThin filmSiliconQuantum wellEngineering physicsEpitaxyOpticsLaserPhysicsLayer (electronics)

Abstract

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Engineering atomically abrupt interfaces between multi-layered thin films of different material have yielded some significant fundamental and technological breakthroughs in the past. For example, the Nobel Prize winning integral and quantum Hall effect owes its discovery to abrupt semiconductor interfaces grown by molecular beam epitaxy. On the other hand, the functionalization of many modern-day semiconductor devices depend critically on the quality of interface of the various thin films, which constitute the device. Silicon (Si)/Germanium (Ge) and Si/SiGe based materials have emerged in the recent years as an integral part to the Si semiconductor industry, promising a wide range of devices ranging from Fin-field effect transistors, quantum cascade lasers, quantum dots, near and mid-infrared photodetectors, resonant tunnel diodes, to name a few. 1–3 To this end, a continuous feedback from post-growth characterization techniques elucidating the intermixing of atoms at the interface, the interfacial width and roughness, the defect density at the interfaces as a function of the growth conditions and integration parameters is therefore crucial for optimizing the ultimate performance of these devices. Not surprising that the semiconductor industry is directing a significant amount of its resources and efforts towards enriching our current understanding of the buried interfaces of these materials. In this work, we use a combination of scanning transmission electron microscopy (STEM) and atom probe tomography (APT) to present an atomistic understanding of the nature of interfaces in Si/Ge and Si/SiGe superlattices, grown on 300 mm Si wafers using chemical vapor deposition. The APT investigations were done using the state-of-the-art LEAP 5000 providing a supreme mass sensitivity and a detection efficiency of 80%, a 30% improvement compared to its predecessor. Figure 1(a) shows the STEM-APT of the last six bi-layers of a sixteen period Si/SiGe superlattice. Figure 1(b) shows the one-dimensional (1D) concentration profile obtained from the 3D APT reconstruction of the sample along the growth (analysis) direction. While the STEM data reveals the average Si and SiGe layer thickness to be about 1.3 nm and 2.2 nm respectively, the concentration profile from the APT data reveals the Ge content within the SiGe layers to be 25.0 +/- 0.5 at.%. The average interfacial width, evaluated as the separation between the 10.0 at.% and 90.0 at.% Ge concentration points, revealed the Si to SiGe transition to be about 1.4 +/- 0.3 nm wide while the width of the SiGe to Si transition to be narrower than 1.0 nm. The possible role of Ge diffusion on the observed interfacial thicknesses shall be discussed in details in this work. Figure 1(c) shows the Si/SiGe hetero-interfaces drawn as isoconcentration surfaces at 12.0 at.% Ge concentration. The work shall also highlight the results obtained from the STEM-APT measurements on superlattices of different period lengths, layer thicknesses and growth conditions from that shown in Figure 1. Alongside the structural aspects, the vibrational properties of these superlattices as obtained from Raman spectroscopic measurements and optical properties as obtained from the ellipsometry and absorption measurements shall be highlighted. Such superlattices holds tremendous prospect for Si semiconductor industry wherein a magic sequence of the number of monolayers within each period can render the whole superlattice to be direct gap 4 for optoelectronic applications or an array of ultrathin free-standing nanowires could be fabricated by selective etching of the Ge layers in a Si/Ge superlattice for nanoelectronic applications. (1) Tan, K.-M.; Liow, T.-Y.; Lee, R. T. P.; Hoe, K. M.; Tung, C.-H.; Balasubramanian, N.; Samudra, G. S.; Yeo, Y.-C. IEEE Electron Device Lett. 2007 , 28 (10), 905–908. (2) Dehlinger, G.; Diehl, L.; Gennser, U.; Sigg, H.; Faist, J.; Ensslin, K.; Grutzmacher, D.; Muller, E. Science 2000 , 290 (5500), 2277–2280. (3) Maune, B. M.; Borselli, M. G.; Huang, B.; Ladd, T. D.; Deelman, P. W.; Holabird, K. S.; Kiselev, A. A.; Alvarado-Rodriguez, I.; Ross, R. S.; Schmitz, A. E.; Sokolich, M.; Watson, C. A.; Gyure, M. F.; Hunter, A. T. Nature 2012 , 481 (7381), 344–347. (4) d’Avezac, M.; Luo, J.-W.; Chanier, T.; Zunger, A. Phys. Rev. Lett. 2012 , 108 (2), 27401. Figure 1

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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 score0.009
Threshold uncertainty score0.447

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 head0.014
GPT teacher head0.221
Teacher spread0.207 · 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