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ECE Ph.D. Student wins Best Paper Award for Ultrasonic Fingerprint Reader

Tuesday, February 21, 2017

Justin Kuo, a graduate student from Prof. Amit Lal’s SonicMEMS research group, received an Outstanding Student Paper Award for the paper titled “64-Pixel Solid State CMOS Compatible Ultrasonic Fingerprint Reader” at the IEEE International Conference on Micro Electro Mechanical Systems (MEMS) 2017 conference.

The work, which was done in collaboration with Intel Corporation, describes a novel approach which uses GHz ultrasound to image the acoustic impedance of skin to enable a high resolution sensor that can potentially image fingerprints with 20 um or better resolution – a resolution much greater than current commercial devices.

This technology pushes the frontier for biometric security by combining the potential of ultrasound for subdermal imaging, the high resolution offered by high frequency ultrasound, and the possibility for a single chip CMOS integrated solution due to the compatibility the devices with CMOS processing and low actuation voltages of <1V. Applications made possible by this device include high resolution imaging for infant fingerprinting and integrated biometric sensors for space/power constrained applications such as in credit cards. 

Prof. Lal’s SonicMEMS Laboratory works on very diverse topics aimed at transforming the way world can be viewed. Topics include linear and nonlinear effects of ultrasound for microfluidics, applications of radioactive thin films for power and lithography, microprobes for surgery and bioinstrumentation, nanoelectromechanical effects, hybrid insect microsystems, micromechanical solar energy, chip scale particle accelerators, self-calibrating inertial sensors, and gas sensing devices.

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