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Synapses

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Dynamic Instability and Time Domain Response of a Model Halide Perovskite Memristor for Artificial Neurons.

The journal of physical chemistry letters
Memristors are candidate devices for constructing artificial neurons, synapses, and computational networks for brainlike information processing and sensory-motor autonomous systems. However, the dynamics of natural neurons and synapses are challengin...

An adaptive synaptic array using Fowler-Nordheim dynamic analog memory.

Nature communications
In this paper we present an adaptive synaptic array that can be used to improve the energy-efficiency of training machine learning (ML) systems. The synaptic array comprises of an ensemble of analog memory elements, each of which is a micro-scale dyn...

A Fully Solution-Printed Photosynaptic Transistor Array with Ultralow Energy Consumption for Artificial-Vision Neural Networks.

Advanced materials (Deerfield Beach, Fla.)
Photosynaptic organic field-effect transistors (OFETs) represent a viable pathway to develop bionic optoelectronics. However, the high operating voltage and current of traditional photosynaptic OFETs lead to huge energy consumption greater than that ...

Emulation of synaptic functions with low voltage organic memtransistor for hardware oriented neuromorphic computing.

Scientific reports
Here, various synaptic functions and neural network simulation based pattern-recognition using novel, solution-processed organic memtransistors (memTs) with an unconventional redox-gating mechanism are demonstrated. Our synaptic memT device using con...

Versatile memristor for memory and neuromorphic computing.

Nanoscale horizons
The memristor is a promising candidate to implement high-density memory and neuromorphic computing. Based on the characteristic retention time, memristors are classified into volatile and non-volatile types. However, a single memristor generally prov...

Organic electrochemical neurons and synapses with ion mediated spiking.

Nature communications
Future brain-machine interfaces, prosthetics, and intelligent soft robotics will require integrating artificial neuromorphic devices with biological systems. Due to their poor biocompatibility, circuit complexity, low energy efficiency, and operating...

Flexible Neural Network Realized by the Probabilistic SiO Memristive Synaptic Array for Energy-Efficient Image Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The human brain's neural networks are sparsely connected via tunable and probabilistic synapses, which may be essential for performing energy-efficient cognitive and intellectual functions. In this sense, the implementation of a flexible neural netwo...

Integrated In-Sensor Computing Optoelectronic Device for Environment-Adaptable Artificial Retina Perception Application.

Nano letters
With the development and application of artificial intelligence, there is an appeal to the exploitation of various sensors and memories. As the most important perception of human beings, vision occupies more than 80% of all the received information. ...

Site-Specific Regulated Memristors via Electron-Beam-Induced Functionalization of HfO.

Small (Weinheim an der Bergstrasse, Germany)
Emerging nonvolatile resistive switching, also known as the memristor, works with a distinct concept that relies mainly on the change in the composition of the active materials, rather than to store the charge. Particularly for oxide-based memristors...

Activating Silent Synapses in Sulfurized Indium Selenide for Neuromorphic Computing.

ACS applied materials & interfaces
The transformation from silent to functional synapses is accompanied by the evolutionary process of human brain development and is essential to hardware implementation of the evolutionary artificial neural network but remains a challenge for mimickin...