Project Summary
High-resolution fingerprint sensing with vertical Piezoelectric nanowire MATrices
PiezoMAT
The paradigm of societal uses protected by biometric identification (ID) – from national security and controlled access, to health care, banking and leisure – requires coming up with ever more reliable built-in ID detection systems. In this context, PiezoMAT proposes a new technology of high-resolution fingerprint sensors based on a matrix of interconnected piezoelectric nanowires (NWs). The long term objective of PiezoMAT is to offer high performance fingerprint sensors with minimal volume occupation for integration into built-in systems able to compete on the market with the best existing products. PiezoMAT proceeds by local deformation of an array of individually contacted piezoelectric NWs and reconstruction from generated potentials, whose amplitudes are proportional to the NW displacement. Each NW and its associated electronics constitute a sensor, or pixel. The sub-micron dimension of NWs allows for high spatial frequency sampling of every fingerprint feature, enabling extremely reliable fingerprint differentiation through detection of the smallest minutiae (pores and ridge shapes). Charge collection efficiency is very dependent on the electrode configuration on each NW. PiezoMAT explores several possible configurations associated with gradual levels of technological challenges and risks, with a strong focus on developing reliable device design tools for present and future application-related adaptability. For the purpose of the PiezoMAT research, it is foreseen to collect generated charges and analogue output signals via metal lines connected to deported electronics on a printed circuit board. This configuration does not allow for maximum NW integration density but is designed to yield sufficient resolution to demonstrate the concept, major technological achievements and actual performance increase as compared to the state-of-the-art. Long term developments will pursue full electronics integration for an optimal sensor resolution.
Small or medium-scale focused research project
2013-2017