MétaCan
Menu
Back to cohort
Record W4411430357 · doi:10.3389/fphy.2025.1595785

Fermentation endpoint detection of Soybean using specially designed Pd-coated FBG stress sensor

2025· article· en· W4411430357 on OpenAlexaff
Jawad Mirza, Ahmad Atieh, Benish Kanwal, Firdos Kanwal, Imran Aziz, Ahmad Almogren

Bibliographic record

VenueFrontiers in Physics · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsOptiwave Systems (Canada)
FundersKing Saud University
KeywordsAlgorithmMaterials scienceArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Determining the fermentation endpoint of organic compounds is critical for optimizing yield, ensuring the product consistency, and minimizing byproducts. However, conventional detection methods are slow, labor-intensive, and lack real-time monitoring, limiting their suitability for industrial automation. We propose a novel, non-destructive method for real-time detection of fermentation endpoint of Soybean using Palladium <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m2"><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mi>P</mml:mi><mml:mi>d</mml:mi></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:math> -coated fiber Bragg grating (FBG) stress sensor. The fermentation endpoint can be detected by monitoring the shift in Bragg wavelength caused by the stress in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m3"><mml:mrow><mml:mi>P</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:math> -coated FBG sensor due to the volume expansion of the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m4"><mml:mrow><mml:mi>P</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:math> coating upon the formation of Palladium Hydride <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m5"><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mi>P</mml:mi><mml:mi>d</mml:mi><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:math> after Hydrogen <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m6"><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:math> gas absorption, which is released as a byproduct during Soybean fermentation. The <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m7"><mml:mrow><mml:mi>P</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:math> -coated FBG stress sensor is analytically designed and validated using OptiSystem simulation tool, achieving a high sensitivity of 61.6 p.m./MPa. Our findings confirm that this method provides a simple, efficient, and real-time solution for monitoring the fermentation process of organic compounds that produce <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m8"><mml:mrow><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math> offering significant advantages over traditional techniques.

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: none
Teacher disagreement score0.498
Threshold uncertainty score0.732

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 head0.010
GPT teacher head0.231
Teacher spread0.221 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in PhysicsSame topicAdvanced Fiber Optic SensorsFrench-language works237,207