Delta-9-tetrahydrocannabinol (Δ<sup>9</sup>-THC) sensing using an aerosol jet printed organic electrochemical transistor (OECT)
Bibliographic record
Abstract
Recreational use of marijuana/cannabis was legalized in Canada in 2018 and has been decriminalized in several other countries; however, the detection of impairment has remained elusive for law enforcement. The psychoactive ingredient in cannabis, delta-9-tetrahydrocannabinol (Δ9-THC), can be detected in saliva and be correlated well with the intake of cannabis. Organic electrochemical transistors (OECTs) have been used for a variety of biosensing applications like glucose, pH, ions, etc. In this work, we demonstrate the use of unfunctionalized OECTs for the detection of Δ9-THC down to 0.1 nM and 1 nM diluted in DI water and synthetic saliva buffer, respectively. These OECTs have been aerosol jet printed entirely with PEDOT:PSS as the channel material. Using a platinum gate coupled with an aerosol jet printed OECT, Δ9-THC concentration can be detected due to its oxidation reaction at the gate. These results were consistent with cyclic voltammetry measurements of Δ9-THC using Pt as the working and counter electrode. Utilizing these OECT based sensors, we have achieved high sensitivity of detection of Δ9-THC in the range from 0.1 nM to 5 μM. These OECT based Δ9-THC sensors demonstrate less than 3% error indicating good repeatability which is averaged over 15 measurements on multiple devices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".