Artificial Synapses with Short- and Long-Term Memory for Spiking Neural Networks Based on Renewable Materials

Transient security transistors self-supported on biodegradable natural-polymer membranes for brain-inspired neuromorphic applications

Transient electronics, a new generation of electronics that can physically or functionally vanish on demand, are very promising for future "green" security biocompatible electronics. At the same time, hardware implementation of biological synapses is highly desirable for emerging brain-like neuromorphic computational systems that could look beyond the conventional von Neumann architecture. Here, a hardware-security physically-transient bidirectional artificial synapse network based on a dual in-plane-gate Al-Zn-O neuromorphic transistor was fabricated on free-standing laterally-coupled biopolymer electrolyte membranes (sodium alginate). The excitatory postsynaptic current, paired-pulse-facilitation, and temporal filtering characteristics from high-pass to low-pass transition were successfully mimicked. More importantly, bidirectional dynamic spatiotemporal learning rules and neuronal arithmetic were also experimentally demonstrated using two lateral in-plane gates as the presynaptic inputs. Most interestingly, excellent physically-transient behavior could be achieved with a superfast water-soluble speed of only ∼120 seconds. This work represents a significant step towards future hardware-security transient biocompatible intelligent electronic systems.

Synaptic Plasticity and Metaplasticity of Biological Synapse Realized in a KNbO3 Memristor for Application to Artificial Synapse

Amorphous KNbO₃ (KN) films were grown on a TiN/SiO₂/Si substrate to synthesize a KN memristor as a potential artificial synapse. The Pt/KN/TiN memristor exhibited typical and reliable bipolar switching behavior with multiple resistance levels. It also showed the transmission properties of a biological synapse, with a good conductance modulation linearity. Moreover, the KN memristor can emulate various biological synaptic plasticity characteristics including short-term plasticity, long-term plasticity, spike-rate dependent plasticity, paired-pulse facilitation, and post-tetanic potentiation by controlling the number and rate of the potentiation spike. Spike-timing-dependent plasticity (STDP), which is an essential property of biological synapses, is also realized in the KN memristor. The synaptic plasticity of the KN memristor can be explained by oxygen vacancy movement and oxygen vacancy filaments. The metaplasticity of biological synapses was also implemented in the KN memristor, including the metaplasticity of long-term potentiation and depression, and of STDP. Therefore, the KN memristor could be used as an artificial synapse in neuromorphic computing systems.

Biological Spiking Synapse Constructed from Solution Processed Bimetal Core-Shell Nanoparticle Based Composites

Inspired by the highly parallel processing power and low energy consumption of the biological nervous system, the development of a neuromorphic computing paradigm to mimic brain-like behaviors with electronic components based artificial synapses may play key roles to eliminate the von Neumann bottleneck. Random resistive access memory (RRAM) is suitable for artificial synapse due to its tunable bidirectional switching behavior. In this work, a biological spiking synapse is developed with solution processed Au@Ag core-shell nanoparticle (NP)-based RRAM. The device shows highly controllable bistable resistive switching behavior due to the favorable Ag ions migration and filament formation in the composite film, and the good charge trapping and transport property of Au@Ag NPs. Moreover, comprehensive synaptic functions of biosynapse including paired-pulse depression, paired-pulse facilitation, post-tetanic potentiation, spike-time-dependent plasticity, and the transformation from short-term plasticity to long-term plasticity are emulated. This work demonstrates that the solution processed bimetal core-shell nanoparticle-based biological spiking synapse provides great potential for the further creation of a neuromorphic computing system.

Programmable Synaptic Metaplasticity and below Femtojoule Spiking Energy Realized in Graphene-Based Neuromorphic Memristor

Memristors with rich interior dynamics of ion migration are promising for mimicking various biological synaptic functions in neuromorphic hardware systems. A graphene-based memristor shows an extremely low energy consumption of less than a femtojoule per spike, by taking advantage of weak surface van der Waals interaction of graphene. The device also shows an intriguing programmable metaplasticity property in which the synaptic plasticity depends on the history of the stimuli and yet allows rapid reconfiguration via an immediate stimulus. This graphene-based memristor could be a promising building block toward designing highly versatile and extremely energy efficient neuromorphic computing systems.

Chitosan-Based Polysaccharide-Gated Flexible Indium Tin Oxide Synaptic Transistor with Learning Abilities

Recently, environment-friendly electronic devices are attracting increasing interest. "Green" artificial synapses with learning abilities are also interesting for neuromorphic platforms. Here, solution-processed chitosan-based polysaccharide electrolyte-gated indium tin oxide (ITO) synaptic transistors are fabricated on polyethylene terephthalate substrate. Good transistor performances against mechanical stress are observed. Short-term synaptic plasticities are mimicked on the proposed ITO synaptic transistor. When applying presynaptic and postsynaptic spikes on gate electrode and drain electrode respectively, spike-timing-dependent plasticity function is mimicked on the synaptic transistor. Transitions from sensory memory to short-term memory (STM) and from STM to long-term memory are also mimicked, demonstrating a "multistore model" brain memory. Furthermore, the flexible ITO synaptic transistor can be dissolved in deionized water easily, indicating potential green neuromorphic platform applications.

An Organic Flexible Artificial Bio-Synapses with Long-Term Plasticity for Neuromorphic Computing

Artificial synapses, with synaptic plasticity, are the key components of constructing the neuromorphic computing system and mimicking the bio-synaptic function. Traditional synaptic devices are based on silicon and inorganic materials, while organic electronics can open up new opportunities for flexible devices. Here, a flexible artificial synaptic device with an organic functional layer was proposed. The organic device showed good switching behaviors such as ON/OFF ratio over 100 at low operation voltages. The set and reset voltages were lower than 0.5 V and -0.25 V, respectively. The long-term plasticity, spike-timing-dependent plasticity learning rules (STDP), and forgetting function were emulated using the device. The retention times of the excitatory and inhibitory post-synaptic currents were both longer than 60 s. The long-term plasticity was repeatable without noticeable degradation after the application of five voltage pulse cycles to the top electrode. These results indicate that our organic flexible device has the potential to be applied in bio-inspired neuromorphic systems.

Short-Term Plasticity and Long-Term Potentiation in Artificial Biosynapses with Diffusive Dynamics

The development of electronic devices possessing the functionality of biological synapses is a crucial step toward replicating the capabilities of the human brain. Of the various materials that have been used to realize artificial synapses, renewable natural materials have the advantages of being abundant, inexpensive, biodegradable, and ecologically benign. In this study, we report a biocompatible artificial synapse based on a matrix of the biopolymer ι-carrageenan (ι-car), which exploits Ag dynamics. This artificial synapse emulates the short-term plasticity (STP), paired-pulse facilitation (PPF), and transition from STP to long-term potentiation (LTP) of a biological synapse. The above-mentioned characteristics are realized by exploiting the similarities between the Ag dynamics in the ι-car matrix and the Ca²⁺ dynamics in a biological synapse. By demonstrating a method that uses biomaterials and Ag dynamics to emulate synaptic functions, this study confirms that ι-car has the potential for constructing neuromorphic systems that use biocompatible artificial synapses.