SRR-Based Disposable Microwave-Microfluidic Sensor for Assessing Liquid Carrier Influence on Microplastic Detection
Bibliographic record
Abstract
Efficient monitoring of Microplastics (MPs) in water systems, particularly in agricultural runoff and irrigation sources, is crucial for assessing their impact on soil and crop health. This work proposed a double split-ring resonator (SRR) based microwave-microfluidic sensor that minimizes the effects of liquid carrier composition on MP detection in aqueous samples. To simulate agricultural conditions, deionized water, tap water, and solutions of urea, sodium chloride, potassium nitrate, and sodium nitrate were tested as liquid carriers. The sensor was validated using polyethylene particles in the$\mathbf{2 5 0 - 3 0 0} \boldsymbol{\mu}$m size range. Average frequency shifts of 374 kHz and 691 kHz were observed for each SRR, highlighting their high sensitivity and consistent performance across varying liquid carriers. The results demonstrated that the liquid carrier composition significantly influences sensor efficiency, which is a necessary step in adapting the sensor for real-world environmental conditions, establishing a foundation for scalable technologies to support sustainable agriculture and protect water quality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".