This review describes various types of low-power memristors, demonstrating their potential for a wide range of applications. This review summarizes low-power memristors for multi-level storage, ...

Neuromorphic computers, inspired by the architecture of the human brain, are proving surprisingly adept at solving complex mathematical problems that underpin scientific and engineering challenges.

Brain-inspired computing promises cheaper, faster, more energy efficient processing, according to experts at a Beijing conference, who discussed everything from reverse engineering insect brains to ...

New research shows that advances in technology could help make future supercomputers far more energy efficient. Neuromorphic computers are modeled after the structure of the human brain, and researche ...

The review emphasizes the switching mechanisms of organic neuromorphic materials. In addition to these switching mechanisms, the capabilities of organic neuromorphic materials in tunable, conformable, ...

Tested against a dataset of handwritten images from the Modified National Standards and Technology database, the interface-type memristors realized a high image recognition accuracy of 94.72%. (Los ...

A recent study published in npj 2D Materials and Applications explores hexagonal boron nitride (h-BN) atomristors, highlighting their notable memory window, low leakage current, and minimal power ...

A new technical paper titled “An Ultra-Robust Memristor Based on Vertically Aligned Nanocomposite with Highly Defective Vertical Channels for Neuromorphic Computing” was published by researchers at ...

The first GRAIN device that Frontgrade Gaisler will premiere – the Gr801 SoC – integrates Akida™ neuromorphic technology from BrainChip, the world’s first commercial producer of ultra-low power, fully ...

A new technical paper titled “Neuromorphic Computing: A Theoretical Framework for Time, Space, and Energy Scaling” was published by researchers at Sandia National Laboratories. “Neuromorphic computing ...