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Record W4241858175 · doi:10.1149/ma2015-02/29/1083

(Invited) Challenges of Energy Band Engineering with New Sn-Related Group IV Semiconductor Materials for Future Integrated Circuits

2015· article· en· W4241858175 on OpenAlexaboutno aff
Shigeaki Zaima, Osamu Nakatsuka, Takashi Yamaha, Takanori Asano, Shinichi Ike, Akihiro Suzuki, Masashi Kurosawa, Wakana Takeuchi, Mitsuo Sakashita

Bibliographic record

VenueECS Meeting Abstracts · 2015
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceBand gapSemiconductorDirect and indirect band gapsOptoelectronicsMolecular beam epitaxyElectronic band structureTernary operationEpitaxyEngineering physicsNanotechnologyLayer (electronics)Condensed matter physicsComputer science

Abstract

fetched live from OpenAlex

Research and development of GeSn and related group-IV semiconductor materials have been widely extended in recent years for not only electronic transistors but also various optoelectronic applications [1,2]. Design and engineering of the energy band structure of group-IV semiconductor materials are swiftly blossoming with establishing the crystal growth technology of GeSn and related materials. We have successively developed the crystalline growth technology of GeSn and GeSiSn thin films on various substrates mainly by using molecular beam epitaxy [1-7]. Recently, we also achieved the epitaxial growth of GeSn layer by using metal organic chemical vapor deposition method [8]. In this presentation, we will report our recent achievements of our study for the crystalline growth and electronic properties including energy band structure of GeSn and related group-IV materials. Controlling the composition of elements and the strain structure of the group-IV semiconductor alloys promises prospective energy band engineering technology. Increasing in the Sn content over about 10% or tensile strain over about 1% achieve the indirect-to-direct crossover, which is a strong driving force of the optical applications of GeSn material. In addition, we recently achieved the formation of polycrystalline SiSn thin layers with a very high Sn content of 20%, and demonstrated that the direct bandgap decreases to 1.05 eV with Si-Sn alloying, which is just 0.22 eV higher than the indirect bandgap of the poly-SiSn even by using Si matrix material [9]. Also, the ternary alloy GeSiSn promises the control of the energy band structure independently on the lattice constant by changing each content of three elements. We found that unstrained GeSiSn/Ge heterostructure realizes a type-I energy band alignment without using strain structure, that promises various electronic and optoelectronic applications [10]. We will demonstrate the experimental results of the energy band engineering with GeSn and related materials. The energy band engineering also provides controlling technology of the electronic property at the interface such as metal/Ge contact. Recently, we found that the Sn/Ge or GeSn/Ge contacts effectively reduces the Schottky barrier height at the metal/n-Ge interface [11,12]. In our presentation, we will also discuss the influence of the energy band structure on the interface properties for Ge and GeSn. This work was partially supported by Grant-in-Aid for Scientific Researches of the JSPS and the JSPS Core-to-Core Program, A. Advanced Research Networks. References [1] S. Zaima, Jpn. J. Appl. Phys. 52, 030001 (2013). [2] S. Zaima et al., Sci. Technol. Adv. Mater., submitted. [3] S. Zaima et al., ECS Trans. 41, 231 (2011). [4] S. Zaima et al., ECS Trans. 50, 897 (2012). [5] O. Nakatsuka et al., ECS Trans. 58, 149 (2013). [6] S. Zaima et al. ECS Trans. 64, 147 (2014). [7] O. Nakatsuka et al. ECS Trans. 64, 793 (2014). [8] Y. Inuzuka et al., ECS Solid State Lett., submitted. [9] M. Kurosawa et al., Appl. Phys. Lett. 106, 171908 (2015). [10] T. Yamaha et al., in Abstr. of ICSI-9, Montreal, Canada, May, 2015. [11] Suzuki et al., Jpn. J. Appl. Phys. 53, 04EA06 (2014). [12] A. Suzuki et al., SSDM2015, Hokkaido, Japan, Sept. 2015, to be submitted.

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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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0400.014

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 head0.018
GPT teacher head0.204
Teacher spread0.186 · 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 designNot applicable
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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