With the advent of the big data era and the Internet of Things, promising hardware
techniques for data storage and energy-efficient data processing are in great demand. This …

The doping of perovskites with mixed cations and mixed halides is an effective strategy to
optimize phase stability. In this study, we introduce a cubic black phase perovskite Cs y FA …

Electrocardiograph signals reflect the current state of the heart and have great significance
to the clinical diagnosis of the heart. Convolutional neural networks perform excellently in …

Photoelectric artificial synapses based on memristors is an effective method to realize
neuromorphic computation. This study presents an optoelectronic responsive artificial …

Multimodal machine learning, as a prospective advancement in artificial intelligence,
endeavors to emulate the brain's multimodal learning abilities with the objective to enhance …

The advent of big data and the Internet of Things has created urgent demands for in‐sensor
computing hardware with multimodal perception that can effectively resolve the inefficiency …

A bioinspired in-sensing computing paradigm using emerging photoelectronic memristors
pursues multifunctionality with low power consumption and high efficiency for processing …

A breakthrough in this field is the introduction of vertical resistive random-access memory
(VRRAM), which features stacked electrodes capable of incorporating multiple devices in …

Pain-perceptual nociceptors play a crucial role as sensory neurons, detecting noxious
stimuli and enabling the human body to respond effectively while accurately perceiving …

Recently, memristors have garnered widespread attention as neuromorphic devices that can
simulate synaptic behavior, holding promise for future commercial applications in …