Making of Memrestor
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- Date Submitted: 03/12/2011 07:05 AM
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Electrochemically controlled polymeric device: a memristor (and more) found two years ago
Victor Erokhin1,2 & M.P. Fontana1
1Department of Physics, University of Parma and CRS SOFT CNR-INFM, Viale Usberti 7A, Parma (PR) 43100 Italy 2Institute of Crystallography, Russian Academy of Sciences, Leninsky pr. 59, Moscow, 119333 Russia
In the last few decades, the age old dream of building an artificial brain, i.e. using biological cognitive systems as a benchmark and inspiration to fabricate complex material assemblies which can learn, make decisions, analyse information in a highly parallel way: in other words, highly efficient bio-inspired information processors, has acquired the concreteness of real life research. Many programs and projects in materials science, nanotechnologies, ICT, biosciences use the relevant biological systems and processes as the basic paradigm for the research. However the enormous complexity of even the simplest brains still puts a barrier to the realization of such ambitions. Hence most of the current research (apart from theoretical modelling and simulations) deals with the fabrication and characterization of specific components which are expected to mimic in their functional behaviour neurons, synapses, or use biological molecules to build innovative sensing or electronic components1-5. Recently a non-linear inorganic thin film two electrode device has been reported6 which the Authors claim to be the very first memristor, i.e. a resistor with memory or which can learn. The 1
device was based on a spatially graded ion doped TiO2 thin (12nm) film. In this Letter we wish to show that a totally different “memristor” with even better characteristics (learning, memory) was reported in the literature since 20057-9 and discuss its properties and functioning principles, in the framework of using it as a main building block in complex functional networks for bio-inspired information processing.
In the general framework of circuit...
Victor Erokhin1,2 & M.P. Fontana1
1Department of Physics, University of Parma and CRS SOFT CNR-INFM, Viale Usberti 7A, Parma (PR) 43100 Italy 2Institute of Crystallography, Russian Academy of Sciences, Leninsky pr. 59, Moscow, 119333 Russia
In the last few decades, the age old dream of building an artificial brain, i.e. using biological cognitive systems as a benchmark and inspiration to fabricate complex material assemblies which can learn, make decisions, analyse information in a highly parallel way: in other words, highly efficient bio-inspired information processors, has acquired the concreteness of real life research. Many programs and projects in materials science, nanotechnologies, ICT, biosciences use the relevant biological systems and processes as the basic paradigm for the research. However the enormous complexity of even the simplest brains still puts a barrier to the realization of such ambitions. Hence most of the current research (apart from theoretical modelling and simulations) deals with the fabrication and characterization of specific components which are expected to mimic in their functional behaviour neurons, synapses, or use biological molecules to build innovative sensing or electronic components1-5. Recently a non-linear inorganic thin film two electrode device has been reported6 which the Authors claim to be the very first memristor, i.e. a resistor with memory or which can learn. The 1
device was based on a spatially graded ion doped TiO2 thin (12nm) film. In this Letter we wish to show that a totally different “memristor” with even better characteristics (learning, memory) was reported in the literature since 20057-9 and discuss its properties and functioning principles, in the framework of using it as a main building block in complex functional networks for bio-inspired information processing.
In the general framework of circuit...