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Record W2952480911 · doi:10.1109/lsens.2019.2922951

Coplanar waveguide techno TEMPO Oxidized Thermomechanical Pulp-Based Microwave Humidity Sensor

2019· article· en· W2952480911 on OpenAlexafffund
Guy Ayissi Eyebe, David Myja, Benoît Bideau, Robert Lanouette, Éric Loranger, Frédéric Domingue

Bibliographic record

VenueIEEE Sensors Letters · 2019
Typearticle
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersCanada Research Chairs
KeywordsMicrowaveMaterials sciencePulp (tooth)DielectricHumidityRelative humidityResonatorComposite materialAbsorption of waterChemical engineeringOptoelectronicsTelecommunicationsMeteorologyComputer science

Abstract

fetched live from OpenAlex

The thermomechanical pulp (TMP) is a product of lignocellulosic biomass. This article investigates TEMPO oxidized TMP (TO-TMP) as an ecofriendly, low-cost, and highly sensitive dielectric material for humidity sensing applications. The TEMPO oxidation was used to increase the water absorption of TMP while overcoming the adverse hydrophobic effects imparted from lignin. The physical and the dielectric effects of TEMPO oxidation on a TMP sheet having a carboxyl rate of 80 mmol/kg were studied. An experimental validation with an original sensing scheme in frequency shift paradigm involving a microwave resonator in coplanar waveguide technology was proposed. In the 52%–75.3%RH range, the sensitivity rose from 7.76 MHz/%R to 9.04 MHz/%RH after the TEMPO oxidation increased the carboxyl content to 1164 mmol/kg, and to 12.1 MHz/%RH when the carboxyl content was enhanced up to 2233 mmol/kg. The effects of the TEMPO oxidation degree and the thickness variation are also studied.

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 score0.003

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 science0.0010.000
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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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