98%
921
2 minutes
20
Optoelectronic memristors have broad application prospects in the fields of artificial intelligence (AI) and the internet of things (IOT) because they can dynamically process a large number of spatiotemporal optoelectronic signals in complex environments. However, it is still a challenge to develop optoelectronic memristors with low power consumption and fast response while maintaining the efficiency and robustness of the system. Here, a photoelectric memristor based on BiSeO thin film is proposed. This device has an ultra-fast resistance switching speed (≈9.5 ns) and ultra-low synaptic event power consumption (≈1.36 fJ). The stable instantaneous light on/off response behavior within 4000 cycles and the very fast photoresponse speed (≈28 ns) also confirm the excellent applicability of the device as a photodetector. More importantly, a bionic visual perception and computing system is designed. The system not only uses devices as photodetectors to achieve wireless communication with a speed of more than 160 kb s, but also uses the synaptic effect of devices under bias voltage to realize the optical reservoir computing (RC) network at the hardware level. The accuracy rate of digital recognition is 90.5%, which provides an ultra-fast and low-power method for developing widely used and performance enhanced bionic visual systems.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1002/adma.202509174 | DOI Listing |
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 PDFLight Sci Appl
September 2025
State Key Laboratory of Flexible Electronics, Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications (NUPT), Nanjing, 210023, China.
As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components.
View Article and Find Full Text PDFAdv Sci (Weinh)
September 2025
State Key Laboratory of Integrated Optoelectronics, Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education, Northeast Normal University, Changchun, Jilin, 130024, China.
Neuromorphic multimodal perception of sensory systems can integrate the stimulation from different senses, thus enhancing the perception accuracy of organisms to understand the external environment. An optoelectronic memristor with the capability to combine multidimensional sensing and processing functions is highly desirable for developing efficient neuromorphic multimodal sensory systems (MSSs). In this work, a tellurene (Te) nanoflake-based optoelectronic memristor relying on solution plasma process (SPP) treatment is demonstrated for the first time, which is capable of combining infrared (IR) optical and electrical stimuli in a single synaptic device for a multisensory integration function.
View Article and Find Full Text PDFNano Lett
September 2025
Institute of Marine Science and Technology, Shandong University, Qingdao, Shandong 266237, China.
Multimodal recognition techniques are pivotal for advancing contemporary artificial intelligence, particularly in enhancing visual perception. However, research on electronic devices capable of robust multimodal recognition remains limited. In this study, we employ an InSe/AlO/ Pb(Zr·Ti·)O (PZT) heterostructure as a dynamic memristor.
View Article and Find Full Text PDFSmall
September 2025
Hybrid Materials Center (HMC), Sejong University, Seoul, 05006, Republic of Korea.
2D chalcogenide-based memristors have the potential to be used in artificial biological visual systems since their synaptic behavior can be optically and electrically modulated. Furthermore, 2D van der Waals materials such as SnS can be used to integrate multifunctional optoelectronic devices by employing a rational design. Here, the simulation of a human biological visual system is reported by using multifunctional optoelectronic synaptic devices.
View Article and Find Full Text PDF