Most of my research activities are located in the exciting and productive fields of spintronic and neuromorphic devices. We use memristive systems to mimic the synaptic functionality of the brain with a simple device. In spintronics, we utilize the spin or the magnetic moment of the (quasi-)particles in solids to store and manipulate information.
We can utilize memristors to pave the way to computer architectures that are more similar to the (human) brain than von-Neumann computers. In principle, neural networks work as a combination of neurons and synapses. Electronic devices can easily emulate the neurons and their behavior, however, it turned out to be more difficult to mimic the synaptic functionality. The memristor can fill this gap and also allows the access to analog values.
Another research direction explores the physics in spin dependent devices exposed to a temperature gradient, which is called spin caloritronics. In particular, we look into the magneto Seebeck effect in magnetic tunnel junctions. This is done in the framework of the DFG priority program SpinCaT.
Please send emails to Andy Thomas (firstname.lastname@example.org).
For my research profile please go to my ResearcherID page or visit my research id:
Z. Jin, A. Tkach, F. Casper, V. Spetter, H. Grimm, A. Thomas, T. Kampfrath, M. Bonn, M. Kläui & D. Turchinovich: Accessing the fundamentals of magnetotransport in metals with terahertz probes, Nature Phys. (2015) doi:10.1038/nphys3384
A. Thomas A, S. Niehörster, S. Fabretti, N.Shepheard, O. Kuschel, K. Küpper, J. Wollschläger, P. Krzysteczko and E. Chicca: Tunnel junction based memristors as artificial synapses, Front. Neurosci. 9 (2015) 241
Andy Thomas receives the physics prize 2014 of the Göttingen Academy of Sciences and Humanities „für seine Arbeiten, in denen er die memristiven Eigenschaften von Tunnelkontakten nutzt, um künstliche neuronale Strukturen zu schaffen.“