Fully Inkjet‐Printed, Flexible TIPS‐Pentacene Photodetector for Photoplethysmogram
Bibliographic record
Abstract
Abstract Organic photodetectors (OPDs) have emerged as promising candidates for non‐invasive medical monitoring and wearable optoelectronic devices, attributed to their cost‐effectiveness, adjustable optoelectronic properties, excellent performance, and solution‐processible fabrication techniques. Interestingly, no fully inkjet‐printed photodetector based on 6, 13 ‐ bis (triisopropylsilylethynyl) pentacene (TIPS‐pentacene) has been reported. Here, an inkjet‐printed OPD utilizing TIPS‐pentacene for a photoplethysmogram is introduced. The flexible photodetector with 200 µm channel length exhibits a high photo‐to‐dark current ratio over 9.6 × 10 2 , a responsivity of 0.23 A W −1 , and a detectivity of 1.8 × 10 11 Jones under 532 nm illumination (8.2 µW cm −2 ) at 5 V bias, achieves through systematic optimization of channel length, illumination intensity, and applied bias, and demonstrates fast photoresponse speed of 0.22 sec (rise) and 0.46 sec (decay). At a lower intensity of 1.1 µW cm −2 , the OPD demonstrates an improved responsivity of 0.54 A W −1 and detectivity of 4.2 × 10 11 Jones, indicating its capability to detect weak‐light signals. This device maintains strong photodetection performance, showing a 53.7% reduction in photocurrent at a severe bending radius of 1 cm. It is successfully demonstrated real‐time heart rate monitoring, which highlighted the practical applicability of the fabrication approach for wearable applications. By investigating the photoresponse behavior, this study establishes a foundation for advancing printed OPDs for low‐power, low‐cost, biomedical, and wearable electronics.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".