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Record W4388998390 · doi:10.1038/s41598-023-47775-5

Manufacturing of quantum-tunneling MIM nanodiodes via rapid atmospheric CVD in terahertz band

2023· article· en· W4388998390 on OpenAlexafffund
Dogu Ozyigit, Farman Ullah, Ahmet Gülsaran, Bersu Baştuğ Azer, A.M. Shahin, Kevin P. Musselman, Michal Bajcsy, Mustafa Yavuz

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsUniversity of Waterloo
FundersCanada First Research Excellence FundCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaUniversity of WaterlooMitacsInnovation, Science and Economic Development CanadaNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsTerahertz radiationQuantum tunnellingOptoelectronicsFabricationNanoelectronicsMaterials scienceChemical vapor depositionElectronicsResponsivityNanotechnologyDiodeElectrical engineering

Abstract

fetched live from OpenAlex

Abstract Quantum-tunneling metal–insulator-metal (MIM) diodes have emerged as a significant area of study in the field of materials science and electronics. Our previous work demonstrated the successful fabrication of these diodes using atmospheric pressure chemical vapor deposition (AP-CVD), a scalable method that surpasses traditional vacuum-based methods and allows for the fabrication of high-quality Al 2 O 3 films with few pinholes. Here, we show that despite their extremely small size 0.002 µm 2 , the MIM nanodiodes demonstrate low resistance at zero bias. Moreover, we have observed a significant enhancement in resistance by six orders of magnitude compared to our prior work, Additionally, we have achieved a high responsivity of 9 AW −1 , along with a theoretical terahertz cut-off frequency of 0.36 THz. Our approach provides an efficient alternative to cleanroom fabrication, opening up new opportunities for manufacturing terahertz-Band devices. The results of our study highlight the practicality and potential of our method in advancing nanoelectronics. This lays the foundation for the development of advanced quantum devices that operate at terahertz frequencies, with potential applications in telecommunications, medical imaging, and security systems.

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)0.001
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 score0.010
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.214
Teacher spread0.201 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

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