Microfabricated sol-gel relative humidity sensors for soil suction measurement during laboratory tests
Bibliographic record
Abstract
Currently there are no small sensors that can be incorporated inside soil samples for laboratory testing, to monitor water transport during loading. This is an important limitation to a better understanding of the hydromechanical coupled behaviour of soils. A sol-gel relative humidity sensor (11 mm × 11 mm), microfabricated in a clean room environment, was conceived to be incorporated in soil specimens during standard laboratory tests. The sensor operates based on changes in electrical resistivity detected by a cerium-doped silica–titania film deposited using a sol-gel technique over interdigitated aluminium electrodes spaced at 300 μm. To the best of the authors’ knowledge, sol-gel sensors for relative humidity measurement have never been used in soils; therefore, this is a novel application. The water retention curve of compacted kaolin was measured with the sensors and compared with the curve found using water dewpoint potentiometer WP4-C. The sensors were also tested incorporated in an oedometer cell, in which load was applied under vapour equilibrium. It was possible to detect the increment of the degree of saturation during compression. The use of the developed sensors incorporated in soils is considered acceptable for suction ranges between 1 and 10 MPa, which extends the suction interval covered by tensiometers, normally operating up to 2 MPa. Although the sensors require improvements in terms of sol-gel deposition and calibration protocol, the results confirm their scientific potential for being used in testing and characterization of unsaturated soils.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".