研究目的
To develop a noncontact reflective large-area vein pattern imager for biometric authentication using near-infrared (NIR) organic photodetectors (OPDs).
研究成果
The developed noncontact reflective large-area vein pattern imager, based on state-of-the-art NIR OPD devices and an a-IGZO backplane, allows for the integration of NIR light source and sensor, facilitating large-area reflective vein detection in a compact form factor.
研究不足
The contrast obtained in reflection mode is lower than in transmission mode, requiring more stringent image processing to extract vein features. Further work is needed to scale the lens system and integrate it into a thin-film form factor.
1：Experimental Design and Method Selection:
The study involved the fabrication and optimization of NIR OPDs based on a bulk heterojunction (BHJ) structure, using a blend of the polymer PDPP3T with the fullerene derivative PC61BM. The devices were characterized for dark current, external quantum efficiency (EQE), and detectivity.
2：Sample Selection and Data Sources:
Discrete pixel OPD devices were fabricated and characterized to optimize the processing conditions and device architecture.
3：List of Experimental Equipment and Materials:
The OPD blend was mixed in a 1 to 2 ratio dissolved in chloroform (CHCl3) with 7.5% v/v of ortho-dichlorobenzene (o-DCB). The active layer was processed from solution by spin coating. MoCr and ITO were used as bottom and top electrodes, respectively, with MoOx and a-IGZO as hole and electron extraction layers.
4：5% v/v of ortho-dichlorobenzene (o-DCB). The active layer was processed from solution by spin coating. MoCr and ITO were used as bottom and top electrodes, respectively, with MoOx and a-IGZO as hole and electron extraction layers.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The OPD frontplane was combined with an a-IGZO TFT array backplane to create a large-area vein detection imager. The system was shielded to prevent undesirable parasitic light, and a LabVIEW custom-made software was used to process the data and display the obtained images in real time.
5：Data Analysis Methods:
The optical and electrical properties of the vein detection image array were characterized, including current density as a function of light power, modulation transfer function (MTF), and uniformity of the pixel response.
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