Reconfigurable, non-volatile neuromorphic photovoltaics.
Tangxin LiJinshui MiaoXiao FuBo SongBin CaiXun GeXiaohao ZhouPeng ZhouXiaomu WangDeep JariwalaWei-Da HuPublished in: Nature nanotechnology (2023)
The neural network image sensor-which mimics neurobiological functions of the human retina-has recently been demonstrated to simultaneously sense and process optical images. However, highly tunable responsivity concurrent with non-volatile storage of image data in the neural network would allow a transformative leap in compactness and function of these artificial neural networks. Here, we demonstrate a reconfigurable and non-volatile neuromorphic device based on two-dimensional semiconducting metal sulfides that is concurrently a photovoltaic detector. The device is based on a metal-semiconductor-metal (MSM) two-terminal structure with pulse-tunable sulfur vacancies at the M-S junctions. By modulating sulfur vacancy concentrations, the polarities of short-circuit photocurrent can be changed with multiple stable magnitudes. The bias-induced motion of sulfur vacancies leads to highly reconfigurable responsivities by dynamically modulating the Schottky barriers. A convolutional neuromorphic network is finally designed for image processing and object detection using the same device. The results demonstrated that neuromorphic photodetectors can be the key components of visual perception hardware.
Keyphrases
- neural network
- deep learning
- gas chromatography
- endothelial cells
- signaling pathway
- high glucose
- blood pressure
- convolutional neural network
- artificial intelligence
- high speed
- machine learning
- electronic health record
- big data
- magnetic resonance imaging
- working memory
- diabetic rats
- high resolution
- diabetic retinopathy
- mass spectrometry
- oxidative stress
- hepatitis c virus
- room temperature
- computed tomography
- pluripotent stem cells
- hiv infected
- image quality
- rectal cancer
- contrast enhanced
- sensitive detection
- ionic liquid
- network analysis