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Berlin 2018 – scientific programme

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DS: Fachverband Dünne Schichten

DS 17: Poster Session I

DS 17.58: Poster

Tuesday, March 13, 2018, 18:15–20:15, Poster B

Memsensors: emerging properties for neuromorphic engineering — •Alexander Vahl1, Jürgen Carstensen2, Sören Kaps2, Thomas Strunskus1, Oleg Lupan2, Rainer Adelung2, and Franz Faupel11Christian-Albrechts University at Kiel, Institute for Materials Science, Chair for Multicomponent Materials, Kaiserstr. 2, 24143, Kiel, Germany — 2Christian-Albrechts University at Kiel, Institute for Materials Science, Chair for Functional Nano Materials, Kaiserstr. 2, 24143 Kiel, Germany

In biological neuronal systems such as the human brain, adaptation is very important for efficient use of neuronal capabilities and learning. In this work we present a concept to translate adaptation into neuromorphic engineering at the example of memsensors. Memsensors are a class of two terminal devices that combine the basic features of memristive devices (pinched hysteresis) and sensors (change in electrical resistivity depending on an external stimulus). Apart from their inherited properties, memsensors have the capability to adapt to the external stimulus as well as a strongly stimulus dependent I-V characteristic. The electrical behavior of a general memsensor was modelled by a three component equivalent circuit, based on two memristive elements in series and in parallel to a sensitive element respectively.

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