| Literature DB >> 30824846 |
Guk-Jin Jeon1, Seung-Hwan Lee2, Seung Hee Lee1, Jun-Bo Shim2, Jong-Hyun Ra2, Kyoung Woo Park1, Hye-In Yeom1, Yunyong Nam1, Oh-Kyong Kwon3, Sang-Hee Ko Park4.
Abstract
The fingerprint recognition has been widely used for biometrics in mobile devices. Existing fingerprint sensors have already been commercialized in the field of mobile devices using primarily Si-based technologies. Recently, mutual-capacitive fingerprint sensors have been developed to lower production costs and expand the range of application using thin-film technologies. However, since the mutual-capacitive method detects the change of mutual capacitance, it has high ratio of parasitic capacitance to ridge-to-valley capacitance, resulting in low sensitivity, compared to the self-capacitive method. In order to demonstrate the self-capacitive fingerprint sensor, a switching device such as a transistor should be integrated in each pixel, which reduces a complexity of electrode configuration and sensing circuits. The oxide thin-film transistor (TFT) can be a good candidate as a switching device for the self-capacitive fingerprint sensor. In this work, we report a systematic approach for self-capacitive fingerprint sensor integrating Al-InSnZnO TFTs with field-effect mobility higher than 30 cm2/Vs, which enable isolation between pixels, by employing industry-friendly process methods. The fingerprint sensors are designed to reduce parasitic resistance and capacitance in terms of the entire system. The excellent uniformity and low leakage current (<10-12) of the oxide TFTs allow successful capture of a fingerprint image.Entities:
Year: 2019 PMID: 30824846 PMCID: PMC6397235 DOI: 10.1038/s41598-019-40005-x
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Design and simulation to confirm the feasibility of fingerprint sensor. (a) Design scheme of unit cell of fingerprint sensor with a resolution of 500 ppi. (b) Cross-sectional device structure of fingerprint sensor with the assumption that the sensor has a back-channel etched oxide TFT. (c) Cross-sectional structure for simulation of capacitance difference between a ridge and a valley.
Figure 2Measurement method and results to confirm capacitance change from specific sensing nodes. (a) Schematic structure of system for measuring capacitance of specific nodes. (b) Real image of capacitance measurement system. (c) De-embedding method for accurately measuring the capacitance of a sensing node. (d) Comparison of simulation and experiment on the capacitance change of specific sensing electrodes in the sensors without a TFT in the pixel with a resolution of 500 ppi according to 5 μm and 7 μm metal contact holes. The inset shows the error bars of capacitance change.
Figure 3Structure of fingerprint sensor and performance of oxide TFTs. (a) Cross-sectional structure of fingerprint sensor in a pixel. (b) SEM image of fingerprint sensor. (c) TEM images of cross-sectional structure of fingerprint sensor. (d) Transfer characteristics (VD = 0.1 and 10 V) of Al-ITZO TFT. The inset displays the linear mobility as a function of VG. (e) Distribution histogram with turn-on voltage of 36 of TFT devices on a 10 cm × 10 cm glass substrate. (f) Output characteristics (VG = −5, 0, 5, 10, 15 and 20 V) of Al-ITZO TFT.
Figure 4Sensing mechanism and performance of fingerprint sensor. (a) Equivalent circuit of fingerprint sensor. (b) Change of digital data depending on capacitance change. The blue circles were the values obtained by connecting ceramic capacitors of 0.5 and 0.75 pF with a sensing line on the PCB of fingerprint sensor. Since we used the sensing ICs whose the output digital values were linearly changed depending on the input capacitance, the red dashed line was obtained by linearly fitting the blue circles. The previously simulated value on the capacitance change of a sensing electrode and the averaged maximum and minimum digital values, which were acquired by real finger touch, were displayed by the arrows. The Cridge-valley indicates the capacitance difference between a ridge and a valley. (c) Raw data (left) and processed image (right) acquired from fingerprint sensor with a resolution of 500 ppi.