First mention about the experimental realization of memristor
Inorganic memristive devices
Memristive devices with organic materials
Chapter 2: Organic memristive device
Basic materials
Structure and working principle of the device
Electrical characteristics of the device
Device working mechanism
Spectroscopy
X-ray fluorescence
Electrical characteristics in a pulse mode
Optimization of properties and stability of the device
Stability of organic memristive device properties
Optimization of the device architecture
Role of the electrolyte
Organic memristive devices with channels, formed by Layer-by-Layer technique
Chapter 3: Oscillators based on organic memristive devices
Chapter 4: Models
Phenomenological model
Simplified model of the organic memristive device function
Electrochemical model
Optical monitoring of the resistive states
Chapter 5: Logic elements and neuron networks
Logic elements with memory
Element “OR” with memory
Element “AND” with memory
Element “NOT” with memory
Comparison of logic elements with memory, based on organic and inorganic memristive devices
Perceptrons
Single layer perceptron
Double layer perceptron
Chapter 6: Neuromorphic systems
Learning of circuits, based on a single memristive device
DC mode
Pulse mode
Training of networks with several memristive elements
Training algorithms
Electronic analog of the part of the nervous system of pond snail Lymnaea stanìgnalis
Biological benchmark
Experimentally realized circuit, mimicking the architecture and properties of the pond snail nervous system part
Cross-talk of memristive devices during pathways formation process
Effect of noise
Frequency driven short-term memory and long-term potentiation
Spike Timing Dependent Plasticity (STDP) learning in memristive systems
STDP in circuits with polyaniline-based memristive devices
STDP in circuits with parylene-based memristive devices
Classic conditioning of polyaniline-based memristive devices systems
Classic conditioning of parylene-based memristive devices systems
Coupling with living beings
Chapter 7: 3D systems with stochastic architecture
Free-standing fibrillar systems
Stochastic networks on frames with developed structure
3D stochastic networks, based on phase separation of materials
Stabilized gold nanoparticles
Block copolymer
Fabrication of 3D stochastic network
Training of stochastic 3D network, based on phase separation of materials
Evidence of 3D nature of the realized stochastic system
Modeling of adaptive electrical characteristics of stochastic 3D network
Single memristive device
Structure of the network
Network dynamics
Modeling of experimental results, obtained on 3D stochastic networks
Conclusions
References
Victor Erokhin received his MS degree in physics and engineering in 1983 in Moscow Institute of Physics and Technology; PhD in Physical and Mathematical Sciences in 1990 in the Institute of Crystallography, Russian Academy of Sciences. After MS degree (1983-1987) he worked as an engineer in the applied research institute “Delta” (Moscow, Russia). In the period 1990-1992 (after PhD thesis) he was a researcher in the Institute of Crystallography, Russian Academy of Sciences. In 1992 he was invited to work in Genoa University (Italy) and during the period 1992-2003 he worked in different industry-oriented companies, nucleated around Genoa University (initially, senior scientist, later head of research units). After the Genoa period, during 2003-2011 he was leading scientist in INFM (National Institute of Physics of Matter) and visiting professor of Parma University (Italy). Since 2011 he works in the Institute of Materials for Electronics and Magnetism, Italian National Research Council (Parma, Italy). His current position is Director of Research and Head of the Research unit “Smart and Neuromorphic Biointerfacing Systems” in the same institute. Victor Erokhin is an author of more than 200 research papers in international referred scientific journals, 19 book chapters and 13 patents. He is an editor-in-chief of BioNanoScience (Springer Nature); member of editorial board: International Journal of Parallel, Emergent and Distributed Systems; Electronics. Victor Erokhin was principal investigator in numerous national and international research projects, chairman and co-chairman of International Symposia, and member of numerous national and international committees, including evaluation panels of ESRF (European Synchrotron Radiation Facilities, Grenoble, France) and Nano-Tera Projects (Switzerland).
This book describes the essential requirements for the realization of neuromorphic systems, where memristive devices play a key role. A comprehensive description to organic memristive devices, including working principles and models of the function, preparation methods, properties and different applications is presented. A comparative analysis of organic and inorganic systems is given. The author discusses all aspects of current research in organic memristive devices: fabrication techniques, properties, synapse mimicking circuits, and neuromorphic systems (including perceptrons), etc.
Describes requirements of electronic circuits and systems to be considered as neuromorphic systems;
Provides a single-source reference to the state-of-the-art in memristive devices as key elements of neuromorphic systems;
Provides a comparative analysis of advantages and drawbacks between organic and inorganic devices and systems;
Includes a systematic overview of organic memristive devices, including fabrication methods, properties, synapse mimicking circuits, and neuromorphic systems;
Discusses a variety of unconventional applications, based on bio-inspired circuits and neuromorphic systems.