Fermentation endpoint detection of Soybean using specially designed Pd-coated FBG stress sensor
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".