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Self-limited single nanowire systems combining all-in-one memristive and neuromorphic functionalities

Gianluca MilanoCenter for Sustainable Future Technologies, Istituto Italiano di Tecnologia, C.so Trento 21, 10129, Torino, ItalyMichael LuebbenInstitute for Materials in Electrical Engineering 2, RWTH Aachen University, Sommerfeldstrasse 24, 52074, Aachen, GermanyZheng MaErnst Ruska-Centre for Microscopy and Spectroscopy with Electrons Peter Gruenberg Institute Research Centre Juelich, 52425, Jülich, GermanyRafal E. Dunin‐BorkowskiErnst Ruska-Centre for Microscopy and Spectroscopy with Electrons Peter Gruenberg Institute Research Centre Juelich, 52425, Jülich, GermanyLuca BoarinoNanoscience and Materials Division, INRiM (Istituto Nazionale di Ricerca Metrologica), Strada delle Cacce 91, 10135, Torino, ItalyCandido Fabrizio PirriCenter for Sustainable Future Technologies, Istituto Italiano di Tecnologia, C.so Trento 21, 10129, Torino, ItalyRainer WaserInstitute for Materials in Electrical Engineering 2, RWTH Aachen University, Sommerfeldstrasse 24, 52074, Aachen, GermanyCarlo RicciardiDepartment of Applied Science and Technology, Politecnico di Torino, C.so Duca degli Abruzzi 24, 10129, Torino, Italy. [email protected]Ilia ValovJARA - Fundamentals for Future Information Technology, 52425, Jülich, Germany. [email protected]
2018en
ABI

Аннотация

Abstract The ability for artificially reproducing human brain type signals’ processing is one of the main challenges in modern information technology, being one of the milestones for developing global communicating networks and artificial intelligence. Electronic devices termed memristors have been proposed as effective artificial synapses able to emulate the plasticity of biological counterparts. Here we report for the first time a single crystalline nanowire based model system capable of combining all memristive functions – non-volatile bipolar memory, multilevel switching, selector and synaptic operations imitating Ca 2+ dynamics of biological synapses. Besides underlying common electrochemical fundamentals of biological and artificial redox-based synapses, a detailed analysis of the memristive mechanism revealed the importance of surfaces and interfaces in crystalline materials. Our work demonstrates the realization of self-assembled, self-limited devices feasible for implementation via bottom up approach, as an attractive solution for the ultimate system miniaturization needed for the hardware realization of brain-inspired systems.

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