A polyimide based resistive humidity sensor
Bibliographic record
Abstract
Purpose To establish an accurate and sensitive method to characterize the moisture content of a particular environment. Design/methodology/approach This paper proposes a relatively simple humidity sensor design consisting of electrodes on a suitable substrate coated with a polyimide material. The changes in relative humidity are denoted by a corresponding change in the polyimide material's electrical resistance profile. The design proposed in this work can be microfabricated and integrated with electronic circuitry. This sensor can be fabricated on alumina or silicon substrates. The electrode material can be made up of nickel, gold or aluminum and the thickness of the electrodes ranges typically between 0.2 and 0.3 μm. The sensor consists of an active sensing layer on top of a set of electrodes. The design of the electrodes can be configured for both resistive and capacitive sensing. Findings The polyimide material's ohmic resistance changes significantly with humidity variations. Changes in resistance as large as 4‐6 orders of magnitude are attainable over the entire operational humidity range. Research limitations/implications As the sensitivity varies non‐linearly with the humidity, the measurement has to be carried out over a very wide range in order to calibrate the sensor. The sensitivity and output range of the sensor can be easily controlled by changing the electrode spacing or geometry. Practical implications The control of humidity is important in many applications ranging from bio‐medical to space exploration. Originality/value A simple, easy to fabricate and measure, and low cost resistive‐type humidity sensor was developed. The realized sensor is suitable for integrating with microfabrication. Hence, multiple sensors of varying sensitivities and output ranges could be integrated on the same chip. Over the last few years, newly emerging micro‐electro‐mechanical‐systems technology and micro‐fabrication techniques have gained popularity and importance in the miniaturization of a variety of sensors and actuators.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".