Design and Fabrication of High-Performance Organic Photodetector for Ambient Light PPG Sensor
Bibliographic record
Abstract
Organic photodetectors (OPDs) developed using novel semiconductor materials and well-designed device architectures have been rapidly progressing in recent years. In this article, we report the design, fabrication, and characterization of a high-performance OPD for detecting green light. The OPD is based on [Poly (3-hexylthiophene-2, 5-diyl)] (P3HT): PC61BM ( <xref ref-type="bibr" rid="ref6" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[6]</xref> , <xref ref-type="bibr" rid="ref6" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[6]</xref> -phenyl-C61-butyric acid methyl ester) active layer and an innovative hole transport layer (HTL) made from combination of polyethylenimine (PEI) interlayer and Copper (I) thiocyanate (CuSCN) interface layer. The innovative HTL significantly reduces the dark current and improves other optoelectronic properties of OPDs, including linear dynamic range (LDR) and specific detectivity. Results show that the newly designed OPDs have an extremely low dark current ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim $ </tex-math></inline-formula> 100 pA), high detectivity ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim $ </tex-math></inline-formula> 1013 Jones), and a large LDR of 180 dB. Compared to the conventional OPDs the newly designed OPDs show the capability to detect light at intensities two order of magnitude lower values. Application of the OPDs for photoplethysmography (PPG) sensing demonstrates that the newly designed photodetectors can successfully acquire PPG signal under ambient light condition without turning on any light-emitting diode (LED) and can have potential for development of low power PPG sensing wearables.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.000 | 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".