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Record W4408578382 · doi:10.1016/j.asems.2025.100149

Mid-infrared integrated spectroscopic sensor based on chalcogenide glasses: Optical characterization and sensing applications

2025· article· en· W4408578382 on OpenAlexfundno aff
Sofiane Meziani, Abdelkader Hammouti, Loïc Bodiou, Nathalie Lorrain, R. Chahal, Albane Bénardais, Rémi Courson, J. Trolès, Catherine Boussard‐Plédel, Virginie Nazabal, Joël Charrier

Bibliographic record

VenueAdvanced Sensor and Energy Materials · 2025
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsnot available
FundersHORIZON EUROPE Framework ProgrammeAgence Nationale de la RechercheInstitute of Circulatory and Respiratory HealthEuropean Commission
KeywordsChalcogenideCharacterization (materials science)InfraredMaterials scienceOptical sensingChalcogenide glassOptoelectronicsNanotechnologyOpticsPhysics

Abstract

fetched live from OpenAlex

A mid-infrared (mid-IR) spectroscopic sensor is developed using a chalcogenide glasses (ChGs) platform with a broad transmission band. The ridge ChGs waveguides were patterned via standard i-line photolithography and reactive ion etching, following the deposition of guiding and confinement layers through RF magnetron sputtering. The waveguides exhibit a wide transparency range from λ ​= ​3.94–8.95 ​μm, with minimum propagation losses value of 2.5 ​dB/cm at λ ​= ​7.58 ​μm. To validate the feasibility of the suggested sensor, a spectroscopic gas sensing experiment was performed using CO 2 , resulting in an estimated limit of detection (LoD) of 1.16%v at λ ​= ​4.28 ​μm, achieved with an external confinement factor Γ of 6.5%. Additionally, liquid sensing experiment was carried out using isopropanol, obtaining a LoD of 300 ppmv at λ ​= ​7.25 ​μm.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
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 science0.0000.000
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 head0.006
GPT teacher head0.244
Teacher spread0.238 · 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 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

Citations4
Published2025
Admission routes1
Has abstractyes

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