| Literature DB >> 24177330 |
Jian Shi1, Sieu D Ha, You Zhou, Frank Schoofs, Shriram Ramanathan.
Abstract
Inspired by biological neural systems, neuromorphic devices may open up new computing paradigms to explore cognition, learning and limits of parallel computation. Here we report the demonstration of a synaptic transistor with SmNiO₃, a correlated electron system with insulator-metal transition temperature at 130°C in bulk form. Non-volatile resistance and synaptic multilevel analogue states are demonstrated by control over composition in ionic liquid-gated devices on silicon platforms. The extent of the resistance modulation can be dramatically controlled by the film microstructure. By simulating the time difference between postneuron and preneuron spikes as the input parameter of a gate bias voltage pulse, synaptic spike-timing-dependent plasticity learning behaviour is realized. The extreme sensitivity of electrical properties to defects in correlated oxides may make them a particularly suitable class of materials to realize artificial biological circuits that can be operated at and above room temperature and seamlessly integrated into conventional electronic circuits.Entities:
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Year: 2013 PMID: 24177330 DOI: 10.1038/ncomms3676
Source DB: PubMed Journal: Nat Commun ISSN: 2041-1723 Impact factor: 14.919