An insertion loss based fully inkjet-printed flexible chipless RFID tag and its application in concentration measurements of liquids and gases
Bibliographic record
Abstract
This thesis presents the design and application of the flexible printed chipless radio frequency identification tag (RFID). Specifically, the insertion loss based technique is followed in this work. Firstly, it explores the challenges in the printed transmission line design, particularly, microstrip line and coplanar waveguide (CPW). Secondly, with these two transmission line topology as the skeleton, different ultrawideband (UWB) antenna and resonator circuit designs are studied and compared. Thirdly, the reader antennas are designed using a novel methodology proposed in a research paper. In the end, a fully inkjet-printed flexible CPW chipless RFID tag shows promising performance. The chipless RFID tag comes with a CPW transmission line that is coupled to the multiresonator circuit to encode the information in the frequency domain. Two cross-polarized UWB antennas connected to the CPW receive and transmit the signals. As a proof-of-concept, three spiral resonators are used to encode a 3-bit signature, which can be easily expanded to more bits by adding more resonators. It will be shown that by shorting resonators, one has the freedom to encode different frequency signatures. The RFID tag is used for the concentration measurements of different binary liquid mixtures by characterizing the frequency response of the sensor, in both wired and wireless experiments. A capillary tube is placed on one of the resonators to allow the interaction between the sensor and the solutions. Correlations between the concentration and the frequency response are extracted from the change of the insertion loss at the resonant frequency |∆S21|, the half-power 3-dB bandwidth ∆BW, and the shift of the resonant frequency |∆fres|. In addition, the sensor is applied for the concentration measurement of acetic acid vapor, varied from 20 to 120 ppm. The applications of this chipless RFID include but are not limited to logistic tracking, chemical and biomedical sensing, and environment monitoring
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".