AIMC Topic: Transistors, Electronic

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Junctionless Poly-GeSn Ferroelectric Thin-Film Transistors with Improved Reliability by Interface Engineering for Neuromorphic Computing.

ACS applied materials & interfaces
Ferroelectric HfZrO (Fe-HZO) with a larger remnant polarization () is achieved by using a poly-GeSn film as a channel material as compared with a poly-Ge film because of the lower thermal expansion that induces higher stress. Then two-stage interface...

Environment-Adaptable Artificial Visual Perception Behaviors Using a Light-Adjustable Optoelectronic Neuromorphic Device Array.

Advanced materials (Deerfield Beach, Fla.)
Emulating the biological visual perception system typically requires a complex architecture including the integration of an artificial retina and optic nerves with various synaptic behaviors. However, self-adaptive synaptic behaviors, which are frequ...

Gaussian synapses for probabilistic neural networks.

Nature communications
The recent decline in energy, size and complexity scaling of traditional von Neumann architecture has resurrected considerable interest in brain-inspired computing. Artificial neural networks (ANNs) based on emerging devices, such as memristors, achi...

A newly developed transparent and flexible one-transistor memory device using advanced nanomaterials for medical and artificial intelligence applications.

International journal of nanomedicine
 Artificial intelligence (AI) integrated circuits (IC) have memory devices as the key component. Due to more complex algorithms and architectures required by neuroscience and other medical applications, various memory structures have been widely prop...

Analysis and Simulation of Capacitor-Less ReRAM-Based Stochastic Neurons for the in-Memory Spiking Neural Network.

IEEE transactions on biomedical circuits and systems
The stochastic neuron is a key for event-based probabilistic neural networks. We propose a stochastic neuron using a metal-oxide resistive random-access memory (ReRAM). The ReRAM's conducting filament with built-in stochasticity is used to mimic the ...

Aligned Carbon Nanotube Synaptic Transistors for Large-Scale Neuromorphic Computing.

ACS nano
This paper presents aligned carbon nanotube (CNT) synaptic transistors for large-scale neuromorphic computing systems. The synaptic behavior of these devices is achieved via charge-trapping effects, commonly observed in carbon-based nanoelectronics. ...

Ultrasensitive flexible FET-type aptasensor for CA 125 cancer marker detection based on carboxylated multiwalled carbon nanotubes immobilized onto reduced graphene oxide film.

Analytica chimica acta
The development of a novel flexible and ultrasensitive aptasensor based on carboxylated multiwalled carbon nanotubes (MWCNTs)/ reduced graphene oxide-based field effect transistor (FET) has been reported for label-free detection of the ovarian cancer...

Master-slave exponential synchronization of delayed complex-valued memristor-based neural networks via impulsive control.

Neural networks : the official journal of the International Neural Network Society
This paper investigates master-slave exponential synchronization for a class of complex-valued memristor-based neural networks with time-varying delays via discontinuous impulsive control. Firstly, the master and slave complex-valued memristor-based ...

Memristor standard cellular neural networks computing in the flux-charge domain.

Neural networks : the official journal of the International Neural Network Society
The paper introduces a class of memristor neural networks (NNs) that are characterized by the following salient features. (a) The processing of signals takes place in the flux-charge domain and is based on the time evolution of memristor charges. The...

Convergence and Multistability of Nonsymmetric Cellular Neural Networks With Memristors.

IEEE transactions on cybernetics
Recent work has considered a class of cellular neural networks (CNNs) where each cell contains an ideal capacitor and an ideal flux-controlled memristor. One main feature is that during the analog computation the memristor is assumed to be a dynamic ...