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WEB Memsensors: Merging memristive switching and sensing functionalities

Tuesday (22.09.2020)
15:55 - 16:10 F: Functional Materials, Surfaces, and Devices 2
Part of:

Despite an unprecedented progress in neuromorphic engineering with memristive devices within the past decade, one particular aspect of complex neuronal systems has been mostly overlooked: The close connection between sensing (i.e. the detection of environmental signals) and data processing. In biological neuronal networks however, the incoming data are processed already at the location of data detection (e.g. by adaptation), which is an essential part of the high efficiency of neuronal networks.

A recent approach to bridge this gap is the concept of memsensors, which combine memristive switching and sensing properties. In this work we report on a simple three-component memsensor model, which is capable of describing the inherited properties, pinched I-V hysteresis and stimulus dependent resistivity, as well as stimulus dependent hysteresis and a potential adaptation to an external stimulus. This adaptation shows striking similarities to adaptation in biological neuronal systems, making memsensors ideal candidates for applications in neuromorphic engineering. Furthermore, different switching characteristics of memristive devices (e.g. bipolar and diffusive switching) will be put into the context of the memsensor concept and potential applications will be discussed. In this context, noble metal alloy nanoparticles will be discussed as building blocks for memristive devices with threshold switching characteristics.

Additional Authors:
  • Niko Carstens
    Kiel University
  • Dr. Jürgen Carstensen
    Kiel University
  • Dr. Sören Kaps
    Kiel University
  • Dr. Thomas Strunskus
    Kiel University
  • Prof. Dr. Rainer Adelung
    Kiel University
  • Prof. Dr. Franz Faupel
    Kiel University