4.8 Article

Enhanced Multiwavelength Response of Flexible Synaptic Transistors for Human Sunburned Skin Simulation and Neuromorphic Computation

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ADVANCED MATERIALS
卷 -, 期 -, 页码 -

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WILEY-V C H VERLAG GMBH
DOI: 10.1002/adma.202303699

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enhanced multiwavelength light response; flexible organic transistors; multiresponse synaptic electronics; neuromorphic computation and learning; sunburned skin simulation

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This study reports on flexible organic light-stimulated synaptic transistors (LSSTs) enabled by alumina oxide (AlOX), which exhibit multiwavelength optical signal response and multifunctional simulation. Embedding AlOX nanoparticles improves the excitons separation efficiency, allowing for multiple wavelength responses. Optimized LSSTs can respond to multiple optical and electrical signals in a highly synaptic manner. The prepared flexible transistors exhibit mechanical flexibility and improved photosynaptic plasticity, facilitating the development of neuromorphic computing and multifunction integration systems at the device-level.
In biological species, optogenetics and bioimaging work together to regulate the function of neurons. Similarly, the light-controlled artificial synaptic system not only enhances computational speed but also simulates complex synaptic functions. However, reported synaptic properties are mainly limited to mimicking simple biological functions and single-wavelength responses. Therefore, the development of flexible synaptic devices with multiwavelength optical signal response and multifunctional simulation remains a challenge. Here, flexible organic light-stimulated synaptic transistors (LSSTs) enabled by alumina oxide (AlOX), with a simple fabrication process, are reported. By embedding AlOX nanoparticles, the excitons separation efficiency is improved, allowing for multiple wavelength responses. Optimized LSSTs can respond to multiple optical and electrical signals in a highly synaptic manner. Multiwavelength optical synaptic plasticity, electrical synaptic plasticity, sunburned skin simulation, learning efficiency model controlled by photoelectric cooperative stimulation, neural network computing, deer picture learning and memory functions are successfully proposed, which promote the development for future artificial intelligent systems. Furthermore, as prepared flexible transistors exhibit mechanical flexibility with bending radius down to 2.5 mm and improved photosynaptic plasticity, which facilitating development of neuromorphic computing and multifunction integration systems at the device-level.

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