Mr Gregor Scheipl, Scientist
USA 2017 Presentation - Joanneum Research*
USA 2017 Audio Presentation - Joanneum Research*
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JR-Materials has a long-term experience in the development, characterization, testing and demonstrator implementation of ferroelectric sensors. A screen printable, ferroelectric P(VDF:TrFE) paste, which is used to fabricate a fully printed 2D sensor structure, has successfully been developed and patented (PyzoFlex®). The sensor active material is sandwiched between two electrodes. PyzoFlex®-sensors are energy self-sufficient, large scale and flexible. They are able to detect dynamic pressure and temperature changes as well as vibration monitoring for e.g. predictive maintenance. Therefore, the PyzoFlex® transducers can also be used for microphone fabrication thus opening up a new field of application for optimised acoustic tuning of structural sounds based on specifically designed vibration sensors.
Speaker Biography (Gregor Scheipl)
Gregor Scheipl studied earth sciences with focus on petrology and geochemistry at the Karl-Franzens University in Graz. He finished his studies with the applied master thesis: "Purification and chemical characterization of organic semiconducting materials" in 2005. Since 2008 he is employed as a permanent scientist at JOANNEUM RESEARCH/Materials in Austria.
His main interests are fabrication and characterization of physical sensors as well as ferroelectric polymers, pyro‐ and piezoelectricity and printing/imprinting techniques.
Due to the exceptionally high potential and maturity of PyzoFlex® technology, Gregor's focus has shifted to business development in order to successfully commercialize PyzoFlex®.
Company Profile (Joanneum Research)
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PyzoFlex® is a technology by JOANNEUM RESEARCH, a leading international research organisation. PyzoFlex® allows the cost efficient production of large area, flexible and energy self-sufficient sensors for the detection of pressure and temperature changes as well as vibration monitoring and provides opportunities for new products or processes based on Intelligent Surfaces.