Reliable Memristive Synapses Based on Parylene-MoOx Nanocomposites for Neuromorphic Applications

Photosensitive resistive switching in parylene-PbTe nanocomposite memristors for neuromorphic computing

Resistive switching (RS) memory devices with incorporated capabilities of in situ data sensing, storing and processing are promising for artificial intelligence applications. In this respect, controlling resistance not only by electrical but also optical stimulations provides attractive opportunities for the development of novel neuromorphic sensing and computing systems. Here, we demonstrate the RS of Cu/parylene-PbTe/ITO memristive devices and the dependence of RS on optical excitation for efficient neuromorphic computing with high classification accuracy. The main memristive characteristics (multilevel resistive states, RS voltages, endurance, retention, RS time, RS energy, etc.) are evaluated with account of temporal and spatial variations. Additionally, the devices demonstrate a range of synaptic plasticity behaviors, such as spike-timing (amplitude, width)-dependent plasticity, long-term potentiation and depression. A qualitative model that describes photosensitive RS and takes into account the influence of photogenerated charge carriers on conductive filament growth is proposed based on the experimental results. This work presents an appealing approach towards the development of photosensitive memristive devices for upcoming neuromorphic sensing and computing systems.

Parylene-MoOx crossbar memristors as a volatile reservoir and non-volatile readout: a homogeneous reservoir computing system

From the very beginning, the emulation of biological principles has been the primary avenue for the development of energy-efficient artificial intelligence systems. Reservoir computing, which has a solid biological basis, is particularly appealing due to its simplicity and efficiency. So-called memristors, resistive switching elements with complex dynamics, have proved beneficial for replicating both principal parts of a reservoir computing system. However, these parts require distinct behaviors found in differing memristive structures. The development of a homogeneous memristive reservoir computing system will significantly facilitate and reduce the fabrication process cost. The following work employs the co-existence of volatile and non-volatile regimes in parylene-MoOx crossbar memristors controlled by compliance current for this aim. The stable operation of the memristors under study is confirmed by low cycle-to-cycle and device-to-device variations of the switching voltages. For the transition between the volatile and non-volatile regimes, factors such as compliance current and reading voltage along with possible intrinsic origins are discussed. The results provide a foundation for the future hardware development of a homogeneous parylene-based reservoir computing system, considering high MNIST dataset classification accuracy (∼96%).

Modulation of polyaniline memristive device switching voltage by nucleotide-free analogue of vitamin B12

Memristive devices offer essential properties to become a part of the next-generation computing systems based on neuromorphic principles. Organic memristive devices exhibit a unique set of properties which makes them an indispensable choice for specific applications, such as interfacing with biological systems. While the switching rate of organic devices can be easily adjusted over a wide range through various methods, controlling the switching potential is often more challenging, as this parameter is intricately tied to the materials used. Given the limited options in the selection conductive polymers and the complexity of polymer chemical engineering, the most straightforward and accessible approach to modulate switching potentials is by introducing specific molecules into the electrolyte solution. In our study, we show polyaniline (PANI)-based device switching potential control by adding nucleotide-free analogue of vitamin B12, aquacyanocobinamide, to the electrolyte solution. The employed concentrations of this molecule, ranging from 0.2 to 2 mM, enabled organic memristive devices to achieve switching potential decrease for up to 100 mV, thus providing a way to control device properties. This effect is attributed to strong aromatic interactions between PANI phenyl groups and corrin macrocycle of the aquacyanocobinamide molecule, which was supported by ultraviolet-visible spectra analysis.

Emulating biological synaptic characteristics of HfOx/AlN-based 3D vertical resistive memory for neuromorphic systems

Here, we demonstrate double-layer 3D vertical resistive random-access memory with a hole-type structure embedding Pt/HfOx/AlN/TiN memory cells, conduct analog resistive switching, and examine the potential of memristors for use in neuromorphic systems. The electrical characteristics, including resistive switching, retention, and endurance, of each layer are also obtained. Additionally, we investigate various synaptic characteristics, such as spike-timing dependent plasticity, spike-amplitude dependent plasticity, spike-rate dependent plasticity, spike-duration dependent plasticity, and spike-number dependent plasticity. This synapse emulation holds great potential for neuromorphic computing applications. Furthermore, potentiation and depression are manifested through identical pulses based on DC resistive switching. The pattern recognition rates within the neural network are evaluated, and based on the conductance changing linearly with incremental pulses, we achieve a pattern recognition accuracy of over 95%. Finally, the device's stability and synapse characteristics exhibit excellent potential for use in neuromorphic systems.