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Record W4226175298 · doi:10.1063/5.0087379

Ge-Ge$_{0.92}$Sn$_{0.08}$ core-shell single nanowire infrared photodetector with superior characteristics for on-chip optical communication

2022· article· en· W4226175298 on OpenAlexaff
Sudarshan Singh, Subhrajit Mukherjee, Samik Mukherjee, Simone Assali, Lu Luo, Samaresh Das, Oussama Moutanabbir, S. K. Ray

Bibliographic record

VenuearXiv (Cornell University) · 2022
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsNanowirePhotodetectorResponsivityMaterials scienceOptoelectronicsPhotoconductivityChemical vapor depositionPhotonics

Abstract

fetched live from OpenAlex

Recent development on Ge$_{1-x}$Sn$_x$ nanowires with high Sn content, beyond its solid solubility limit, make them attractive for all group-IV Si-integrated infrared photonics at nanoscale. Herein, we report a chemical vapour deposition-grown high Sn-content Ge-Ge$_{0.92}$Sn$_{0.08}$ core-shell based single nanowire photodetector operating at the optical communication wavelength of 1.55 $\mu$m. The atomic concentration of Sn in nanowires has been studied using X-ray photoelectron and Raman spectroscopy data. A metal-semiconductor-metal based single nanowire photodetector, fabricated via electron beam lithography process, exhibits significant room-temperature photoresponse even at zero bias. In addition to the high-crystalline quality and identical shell composition of the nanowire, the efficient collection of photogenerated carriers under an external electric field result in the superior responsivity and photoconductive gain as high as ~70.8 A/W and ~57, respectively at an applied bias of -1.0 V. The extra-ordinary performance of the fabricated photodetector demonstrates the potential of GeSn nanowires for future Si CMOS compatible on-chip optical communication device applications.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.043
GPT teacher head0.170
Teacher spread0.127 · 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.

Study designSimulation or modeling
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

Citations18
Published2022
Admission routes1
Has abstractyes

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