Metal doped polyaniline as neuromorphic circuit elements for in-materia computing.

Polyaniline-based atomic switches are material building blocks whose nanoscale structure and resultant neuromorphic character provide a new physical substrate for the development next-generation, nanoarchitectonic-enabled computing systems. Metal ion-doped devices consisting of a Ag/metal ion doped polyaniline/Pt sandwich structure were fabricated using an wet process. The devices exhibited repeatable resistive switching between high (ON) and low (OFF) conductance states in both Ag and Cu ion-doped devices.

Atomic switch networks-nanoarchitectonic design of a complex system for natural computing.

Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing.

Benchtop fabrication of memristive atomic switch networks.

Recent advances in nanoscale science and technology provide possibilities to directly self-assemble and integrate functional circuit elements within the wiring scheme of devices with potentially unique architectures. Electroionic resistive switching circuits comprising highly interconnected fractal electrodes and metal-insulator-metal interfaces, known as atomic switch networks, have been fabricated using simple benchtop techniques including solution-phase electroless deposition. These devices are shown to activate through a bias-induced forming step that produces the frequency dependent, nonlinear hysteretic switching expected for gapless-type atomic switches and memristors.

A theoretical and experimental study of neuromorphic atomic switch networks for reservoir computing.

Atomic switch networks (ASNs) have been shown to generate network level dynamics that resemble those observed in biological neural networks. To facilitate understanding and control of these behaviors, we developed a numerical model based on the synapse-like properties of individual atomic switches and the random nature of the network wiring. We validated the model against various experimental results highlighting the possibility to functionalize the network plasticity and the differences between an atomic switch in isolation and its behaviors in a network.

Neuromorphic atomic switch networks.

Efforts to emulate the formidable information processing capabilities of the brain through neuromorphic engineering have been bolstered by recent progress in the fabrication of nonlinear, nanoscale circuit elements that exhibit synapse-like operational characteristics. However, conventional fabrication techniques are unable to efficiently generate structures with the highly complex interconnectivity found in biological neuronal networks. Here we demonstrate the physical realization of a self-assembled neuromorphic device which implements basic concepts of systems neuroscience through a hardware-based platform comprised of over a billion interconnected atomic-switch inorganic synapses embedded in a complex network of silver nanowires.