Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

The rapid development of artificial intelligence and the increasing volume of generated data have heightened the demand for computational power. However, the traditional von Neumann architecture encounters performance bottlenecks due to frequent data transfers and high energy consumption. A promising solution is integrating functions such as perception, storage, and processing into a single device, known as neuromorphic devices. Currently, most neuromorphic devices rely on fully electronic or electro-optic hybrid control, which limits their speed and energy efficiency. In contrast, all-optical-controlled neuromorphic devices provide faster data transmission, lower energy consumption, and better scalability. This review analyzes the latest advancements in all-optical-controlled neuromorphic devices, with a particular focus on the exploration of materials. It also presents a detailed analysis of the physical mechanisms that underpin all-optical-controlled neuromorphic computing, offering insights into the fundamental operation of these devices. Unlike previous reviews, which primarily focus on the general characteristics of neuromorphic devices, this work examines the contributions of materials and all-optical-controlled mechanisms in improving efficiency and scalability. Additionally, the diverse applications of all-optical-controlled neuromorphic devices in optical logic gates, visual perception, and brain-inspired computing are discussed, illustrating their potential to influence computational paradigms.

Download full-text PDF

Source
http://dx.doi.org/10.1021/acsnano.5c05240DOI Listing

Publication Analysis

Top Keywords

neuromorphic devices
24
all-optical-controlled neuromorphic
16
neuromorphic
8
neuromorphic computing
8
devices
8
energy consumption
8
all-optical-controlled
6
advancing intelligent
4
intelligent neuromorphic
4
computing progress
4

Similar Publications

Near-infrared Artificial Synapse Based on a Pristine InGaAs Nanowire Synaptic Transistor.

Nanotechnology

September 2025

Beijing University of Technology, Key Laboratory of Optoelectronics Technology, School of Information Science and Technology., Beijing, 100124, CHINA.

The rapid advancements in the field of artificial intelligence have intensified the urgent need for low-power, high-speed artificial synaptic devices. Here, a near-infrared (NIR) artificial synaptic device is successfully realized based on pristine InGaAs nanowires (NWs), which achieves a paired-pulse facilitation (PPF) of up to 119%. Additionally, a postsynaptic current (PSC) in memory storage behavior has been implemented by applying different voltage pulses along with continuous illumination of 1064 nm NIR light due to the memristor characteristics of the device.

View Article and Find Full Text PDF

Van der Waals Epitaxy of CsPbI/MoS Heterojunction Phototransistors for Neuromorphic Computing.

J Phys Chem Lett

September 2025

Hunan Key Laboratory of Nanophotonics and Devices, Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics, Central South University, Changsha, Hunan 410083, China.

The optoelectronic properties of perovskite/two-dimensional (2D) material van der Waals heterojunctions provide greater potential for innovative neuromorphic devices. However, the traditional growth of heterojunctions still relies on strict lattice matching and high-temperature processes, which hinder high-quality interface construction and efficient carrier transport. Here, the 2D CsPbI/MoS heterojunction is realized via the van der Waals epitaxy process, overcoming lattice matching limitations.

View Article and Find Full Text PDF

Optically Controlled Memristor Enabling Synergistic Sensing-Memory-Computing for Neuromorphic Vision Systems.

Adv Mater

September 2025

Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Hebei University, Baoding, 071002, China.

Neuromorphic Visual Devices hold considerable promise for integration into neuromorphic vision systems that combine sensing, memory, and computing. This potential arises from their synergistic benefits in optical signal detection and neuro-inspired computational processes. However, current devices face challenges such as insufficient light/dark resistance ratios, mismatched transient photo-response, and volatile retention characteristics, limiting their adaptability to complex artificial vision systems.

View Article and Find Full Text PDF

Mimicking human brain functionalities with neuromorphic devices represents a pivotal breakthrough in developing bioinspired electronic systems. The human somatosensory system provides critical environmental information and facilitates responses to harmful stimuli, endowing us with good adaptive capabilities. However, current sensing technologies often struggle with insufficient sensitivity, dynamic response, and integration challenges.

View Article and Find Full Text PDF

UVA/B-Selective Skin-Inspired Nociceptors Based on Green Double Perovskite QDs-Sensitized 2D Semiconductor toward Reliable Human Somatosensory System Simulation.

J Phys Chem Lett

September 2025

Tianjin Key Laboratory of Film Electronic and Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, Tianjin 300384, China.

Achieving UVA/B-selective, skin-inspired nociceptors with perception and blockade functions at the single-unit device level remains challenging. This is because the device necessitates distinct components for every performance metric, thereby leading to complex preparation processes and restricted performance, as well as the absence of deep UV (UVB and below)-selective semiconductors. Here, to address this, we develop a structure-simplification skin-inspired nociceptor using a reverse type-II CuAgSbI/MoS heterostructure.

View Article and Find Full Text PDF