Sensitivity-Enhanced CMOS Phase Luminometry System Using Xerogel-Based Sensors
Bibliographic record
Abstract
We present the design and implementation of a phase luminometry sensor system with improved and tunable detection sensitivity achieved using a complementary metal-oxide semiconductor (CMOS) integrated circuit. We use sol-gel derived xerogel thin films as an immobilization media to house oxygen (O2) responsive luminescent molecules. The sensor operates on the principal of phase luminometry wherein a sinusoidal modulation signal is used to excite the luminophores encapsulated in the porous xerogel films and the corresponding phase shift of the emission signals is monitored. The phase shift is directly related to excited state lifetimes of the luminophores which in turn are related to the concentration of the target analyte species present in the vicinity of the luminophores. The CMOS IC, which consists of a 16 times 16 high-gain phototransistor array, current-to-voltage converter, amplifier and tunable phase shift detector, consumes an average power of 14 mW with 5-V power supply operating at a 38-kHz modulation frequency. The output of the IC is a dc voltage that corresponds to the detected luminescence phase shift with respect to the excitation signal. As a prototype, we demonstrate an oxygen sensor system by encapsulating the luminophore tris(4,7-diphenyl-1,10-phenanthroline)ruthenium(II) within the xerogel matrices. The sensor system showed a fast response on the order of few seconds and we obtained a detection sensitivity of 118 mV per 1% change in O2 concentration. The system demonstrates a novel concept to tune and improve the detection sensitivity for specific concentrations of the target analyte in many biomedical monitoring applications.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".