MétaCan
Menu
Back to cohort
Record W7117131936 · doi:10.1007/s10762-025-01107-y

Investigation of High-Transmission 100-GHz Bands Between 1 and 3 THz Using a Nonlinear Upconversion Technique

2025· article· en· W7117131936 on OpenAlexafffund
Eeswar Kumar Yalavarthi, Wei Cui, Aswin Vishnuradhan, Nicolas Couture, M. Betz, Angela Gamouras, Jean-Michel Ménard

Bibliographic record

VenueJournal of Infrared Millimeter and Terahertz Waves · 2025
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsNational Research Council CanadaUniversity of Ottawa
FundersNational Research Council Canada
KeywordsTerahertz radiationPhoton upconversionUSableWirelessTransmission (telecommunications)Nonlinear systemParametric statisticsData transmission

Abstract

fetched live from OpenAlex

The ever-increasing demand for high-speed data transmission continues to drive research toward sixth generation (6G) wireless technologies and beyond. Terahertz (THz) carrier frequencies are considered promising for achieving data rates up to terabits per second, yet their feasibility is strongly affected by environmental factors such as water vapor absorption. In this work, the propagation distances of several 100 GHz-wide THz channels between 1 and 3 THz were investigated under 35% relative humidity conditions using a table-top spectroscopy apparatus with a nonlinear parametric upconversion detection scheme. This approach avoids temporal scanning and is therefore more practical for wireless communications, while also demonstrating that selected spectral windows can support meaningful propagation distances despite water vapor absorption. We further estimate the usable ranges for seven distinct transmission bands, each offering bandwidths sufficiently broad to sustain high data transfer rates. These results highlight the relevance of THz transmission windows for short-, mid-, and long-range wireless applications and provide timely insight into the exploration of unallocated spectral bands in the THz range.

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 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 score0.213
Threshold uncertainty score0.555

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 head0.018
GPT teacher head0.235
Teacher spread0.217 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Infrared Millimeter and Terahertz WavesSame topicMillimeter-Wave Propagation and ModelingFrench-language works237,207