Phthalocyanine-Based Organic Thin Film Transistors as a Platform for Cannabinoid Sensors
Bibliographic record
Abstract
With a growing international trend of Cannabis legalization, there is a present need for on-the-spot, low cost, and rapid differentiation of cannabinoids. The two primary cannabinoids, Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD), obtained from Cannabis, elicit very different pharmacological effects necessitating consumer and industry methods for their detection and rapid speciation. CuPc and F16-CuPc, well characterized p- and n-type semiconductors respectively, are used as the OTFT semiconducting layer in combination with a cannabinoid-sensitive chromophore allowing for the differentiation of THC and CBD. Device analysis of pre- and post-pyrolyzed rapid plant extract samples was able to predict the THC/CBD ratio with HPLC accuracy. Spectroelectrochemistry was used to probe molecular interactions between cannabinoids with and without a cannabinoid sensitive chromophore against a variety of Pcs. Spectroelectrochemical changes to the Q-band region of the Pc spectra in the presence of analytes was related to modified ratios of Pc-Pc orientations in solution, streamlining material selection, reducing manufacturing burden, and expediting sensor development. 2D-NMR was used to further elucidate unique Pc-Pc and Pc-analyte interactions, providing additional insight on atomic level interactions. Through altered Pc-Pc orientations, analytes can induce physical alterations to Pc thin-film morphology and structure, consequently, modifying electrical performance beyond charge trapping effects. Pc peripheral and axial substitutions allow an additional level of Pc tunability and their relationship with analyte interactions, film structure, and OTFT sensing performance was explored. We established relationships between thin-films of phthalocyanines (Pcs) with a variety of central, peripheral, and axial substituents and their response to THC. X-Ray diffraction and UV–vis absorption spectroscopy measurements demonstrate significantly altered film morphologies and the formation of new crystal orientations in response to analytes, which are corroborated by scanning electron microscopy. With exposure to THC, aluminium chloride Pc generates the largest physical film changes as well as the largest changes in OTFT performance. These findings have implications for Pc-based OTFT sensor design, suggesting that the semiconducting Pc thin-film morphologies are not static in the presence of analytes, and that the sensing response is driven both by strong analyte-Pc coordination and bulk film restructuring to accommodate these interactions. References Advanced Functional Materials, 2021, ASAP, doi:10.1002/adfm.202107138 ACS Appl. Mater. Interfaces, 2020, 12, 45, 50692–50702 ACS Sensors, 2019, 4, 10, 2706-2715. Figure 1
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".