Could We Realize the Fully Flexible System by Real-Time Computing with Thin-Film Transistors?

• Main Authors: Qin Li, Zheyu Liu, Fei Qiao, Qi Wei, Huazhong Yang
• Format: Article
• Language: English
• Published: MDPI AG 2017-11-01
• Series: Applied Sciences
• Subjects: flexible electronics; thin-film transistors; image signal processing; machine learning; analog-to-information processing; physical computing
• Online Access: https://www.mdpi.com/2076-3417/7/12/1224

Flexible electronic devices, such as the typical thin-film transistors, are widely adopted in the area of sensors, displayers, wearable equipment, and such large-area applications, for their features of bending and stretching; additionally, in some applications of lower-resolution data converters recently, where a trend appears that implementing more parts of system with flexible devices to realize the fully flexible system. Nevertheless, relatively fewer works on the computation parts with flexible electronic devices are reported, due to their poor carrier mobility, which blocks the way to realize the fully flexible systems with uniform manufacturing process. In this paper, a novel circuit architecture for image processing accelerator using Oxide Thin-film transistor (TFT), which could realize real-time image pre-processing and classification in the analog domain, is proposed, where the performance and fault-tolerance of image signal processing is exploited. All of the computation is done in the analog signal domain and no clock signal is needed. Therefore, certain weaknesses of flexible electronic devices, such as low carrier mobility, could be remedied dramatically. In this paper, Simulations based on Oxide TFT device model have demonstrated that the flexible computing parts could perform 5 × 5 Gaussian convolution operation at a speed of 3.3 MOPS/s with the energy efficiency of 1.83 TOPS/J, and realize image classification at a speed of 10 k fps, with the energy efficiency of 5.25 GOPS/J, which means that the potential applications to realize real-time computing parts of complex algorithms with flexible electronic devices, as well as the future fully flexible systems containing sensors, data converters, energy suppliers, and real-time signal processing modules, all with flexible devices.