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Record W4377115911 · doi:10.1038/s41598-023-35131-6

Intra-pulse difference frequency generation in ZnGeP2 for high-frequency terahertz radiation generation

2023· article· en· W4377115911 on OpenAlexafffund
B. N. Carnio, Mingjie Zhang, Kevin T. Zawilski, Peter G. Schunemann, Oussama Moutanabbir, A. Y. Elezzabi

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsPolytechnique MontréalUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaDefence Research and Development Canada
KeywordsTerahertz radiationPulse (music)RadiationComputer scienceOptoelectronicsPhysicsOpticsTelecommunications

Abstract

fetched live from OpenAlex

Abstract The highly-nonlinear chalcopyrite crystal family has experienced remarkable success as source crystals in the mid-infrared spectral range, such that these crystals are primary candidates for producing high terahertz frequency (i.e., $$\gtrsim$$ ≳ 10 THz) electric fields. A phase-resolved terahertz electric field pulse is produced via intra-pulse difference frequency generation in a chalcopyrite (110) ZnGeP2 crystal, with phase-matching being satisfied by the excitation electric field pulse having polarizations along both the ordinary and extraordinary crystal axes. While maximum spectral power is observed at the frequency of 24.5 THz (in agreement with intra-pulse phase-matching calculations), generation nonetheless occurs across the wide spectral range of 23–30 THz. To our knowledge, this is the first time a chalcopyrite ZnGeP2 crystal has been used for the generation of phase-resolved high-frequency terahertz electric fields.

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 score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.020
GPT teacher head0.240
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

Citations6
Published2023
Admission routes2
Has abstractyes

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