Victor Erokhin

ORGANIC MEMRISTOR DEVICES FOR LOGIC ELEMENTS WITH MEMORY

Memristors are promising next-generation memory candidates that are nonvolatile, possess low power requirements and are capable of nanoscale fabrication. In this article we physically realise and describe the use of organic memristors in designing statefull boolean logic gates for the AND OR and NOT operations. The output of these gates is analog and dependent on the length of time that suitable charge is applied to the inputs, displaying a learning property. Results may be also interpreted in a traditional binary manner through use of a suitable thresholding function at the output. The memristive property of the gate allows the for the production of analog outputs that vary based on the charge-dependent nonvolatile state of the memristor. We provide experimental results of physical fabrication of three types of logic gate. A simulation of a one-bit full adder comprised of memristive logic gates is also included, displaying varying response to two distinct input patterns.

A bio-inspired memory device based on interfacing Physarum polycephalum with an organic semiconductor

The development of devices able to detect and record ion fluxes is a crucial point in order to understand the mechanisms that regulate communication and life of organisms. Here, we take advantage of the combined electronic and ionic conduction properties of a conducting polymer to develop a hybrid organic/living device with a three-terminal configuration, using the Physarum polycephalum Cell (PPC) slime mould as a living bio-electrolyte. An over-oxidation process induces a conductivity switch in the polymer, due to the ionic flux taking place at the PPC/polymer interface. This behaviour endows a current-depending memory effect to the device.

First steps towards the realization of a double layer perceptron based on organic memristive devices

Memristors are widely considered as promising elements for the efficient implementation of synaptic weights in artificial neural networks (ANNs) since they are resistors that keep memory of their previous conductive state. Whereas demonstrations of simple neural networks (e.g., a single-layer perceptron) based on memristors already exist, the implementation of more complicated networks is more challenging and has yet to be reported. In this study, we demonstrate linearly nonseparable combinational logic classification (XOR logic task) using a network implemented with CMOS-based neurons and organic memrisitive devices that constitutes the first step toward the realization of a double layer perceptron. We also show numerically the ability of such network to solve a principally analogue task which cannot be realized by digital devices. The obtained results prove the possibility to create a multilayer ANN based on memristive devices that paves the way for designing a more complex network such as the double layer perceptron.

On chirality of slime mould

Left-right patterning and lateralised behaviour is an ubiquitous aspect of plants and animals. The mechanisms linking cellular chirality to the large-scale asymmetry of multicellular structures are incompletely understood, and it has been suggested that the chirality of living cells is hardwired in their cytoskeleton. We examined the question of biased asymmetry in a unique organism: the slime mould Physarum polycephalum, which is unicellular yet possesses macroscopic, complex structure and behaviour. In laboratory experiment using a T-shape, we found that Physarum turns right in more than 74% of trials. The results are in agreement with previously published studies on asymmetric movement of muscle cells, neutrophils, liver cells and growing neural filaments, and for the first time reveal the presence of consistently-biased laterality in the fungi kingdom. Exact mechanisms of the slime moulds direction preference remain unknown.

A SPICE MODEL OF THE PEO-PANI MEMRISTOR

The memristor is a novel circuit element which is capable of maintaining an activity-dependent nonvolatile resistance and is therefore a candidate for use in next-generation storage and logic circuits. In this article, we present a model of the PEO-PANI memristor for use in the SPICE circuit simulation program which is especially suited to analog logic applications. Two variants are presented herein; accompanying each is a short description that explains any design decisions made, as well as elucidating on preferred simulation settings. It is shown that the model accurately replicates corresponding experimental results found in the literature. Simple simulations are used to show the suitability of each variant to specific experimental usage. Appendices contain verbatim implementations of the SPICE models.

Computers from Plants We Never Made: Speculations

Plants are highly intelligent organisms. They continuously make distributed processing of sensory information, concurrent decision making and parallel actuation. The plants are efficient green computers per se. Outside in nature, the plants are programmed and hardwired to perform a narrow range of tasks aimed to maximize the plants’ ecological distribution, survival and reproduction. To ‘persuade’ plants to solve tasks outside their usual range of activities, we must either choose problem domains which homomorphic to the plants natural domains or modify biophysical properties of plants to make them organic electronic devices. We discuss possible designs and prototypes of computing systems that could be based on morphological development of roots, interaction of roots, and analog electrical computation with plants, and plant-derived electronic components. In morphological plant processors data are represented by initial configuration of roots and configurations of sources of attractants and repellents; results of computation are represented by topology of the roots’ network. Computation is implemented by the roots following gradients of attractants and repellents, as well as interacting with each other. Problems solvable by plant roots, in principle, include shortest-path, minimum spanning tree, Voronoi diagram, \(\alpha \)-shapes, convex subdivision of concave polygons. Electrical properties of plants can be modified by loading the plants with functional nanoparticles or coating parts of plants of conductive polymers. Thus, we are in position to make living variable resistors, capacitors, operational amplifiers, multipliers, potentiometers and fixed-function generators. The electrically modified plants can implement summation, integration with respect to time, inversion, multiplication, exponentiation, logarithm, division. Mathematical and engineering problems to be solved can be represented in plant root networks of resistive or reaction elements. Developments in plant-based computing architectures will trigger emergence of a unique community of biologists, electronic engineering and computer scientists working together to produce living electronic devices which future green computers will be made of.

Polyaniline-based memristive microdevice with high switching rate and endurance

Polyaniline (PANI) based memristive devices have emerged as promising candidates for hardware implementation of artificial synapses (the key components of neuromorphic systems) due to their high flexibility, low cost, solution processability, three-dimensional stacking capability, and biocompatibility. Here, we report on a way of the significant improvement of the switching rate and endurance of PANI-based memristive devices. The reduction of the PANI active channel dimension leads to the increase in the resistive switching rate by hundreds of times in comparison with the conventional one. The miniaturized memristive device was shown to be stable within at least 104 cyclic switching events between high- and low-conductive states with a retention time of at least 103 s. The obtained results make PANI-based memristive devices potentially widely applicable in neuromorphic systems.

Organic Memristor Based Elements for Bio-inspired Computing

Bio-based/bio-inspired systems are attracting the interest of many studies even if we are far from reproducing the simplest living cell property. The concept of memory is particularly well suited for mimicking learning behavior in biosystems and in information processing systems being capable of coupling inherently memory and logic capabilities. Bio-electronics is another challenging platform, mostly if we consider organic devices based on conductive and biocompatible polymers. This chapter deals with several examples of devices developed by joining unconventional computing, organic memristors and living being. Starting from organic memristors we realized logic gates with memory and a single layer perceptron. We developed hybrid systems based on living beings as key elements for the proper device working, in particular with Phyarum polycephalum and neurons. These devices enable new and unexplored opportunities in such emerging field of research.

Physarum in Hybrid Electronic Devices

We discuss hybrid systems where the slime mould is interfaced with organic electronics devices. We demonstrate the realisation of slime mould Schottky diode and organic electrochemical transistor . A central part of the chapter is dedicated to the integration of the Physarum into organic memristive device , an electronic element with synapse-like properties. We describe an architecture and working principles of the hybrid devices and variations of their electrical and optical properties as a result of the interaction with slime mould. We demonstrate that the slime mould is a smart candidate for the implementation of functional properties of smart living systems into electronic devices.

PhyChip: Growing Computers with Slime Mould

Slime mould Physarum polycephalum is a large single cell capable of distributed sensing, concurrent information processing, parallel computation, and decentralised actuation. The ease of culturing and experimenting with Physarum makes this slime mould an ideal substrate for real-world implementations of unconventional sensing and computing devices. In the last decade Physarum has become a popular inspiration for mathematical and algorithmic models and philosophical concepts of unconventional computing: give the slime mould a problem and it will solve it. We provide a concise summary of computing and sensing operations implemented with live slime mould and evaluate the feasibility of slime mould-based computing.