Liu Jiaming, Qian Jingui, Adil Murtazt, Bi Yali, Wu Haoyi, Hu Xuefeng, Wang Zuankai, Zhang Wei
Anhui Province Key Laboratory of Measuring Theory and Precision Instruments, School of Instrumental Science and Optoelectronics Engineering, Hefei University of Technology, 230009 Hefei, Anhui China.
School of Physics and Optoelectronic Engineering, Guangdong University of Technology, 510006 Guangzhou, Guangdong China.
Microsyst Nanoeng. 2024 May 8;10:57. doi: 10.1038/s41378-024-00690-9. eCollection 2024.
An electronic tongue (E-tongue) comprises a series of sensors that simulate human perception of taste and embedded artificial intelligence (AI) for data analysis and recognition. Traditional E-tongues based on electrochemical methods suffer from a bulky size and require larger sample volumes and extra power sources, limiting their applications in in vivo medical diagnosis and analytical chemistry. Inspired by the mechanics of the human tongue, triboelectric components have been incorporated into E-tongue platforms to overcome these limitations. In this study, an integrated multichannel triboelectric bioinspired E-tongue (TBIET) device was developed on a single glass slide chip to improve the device's taste classification accuracy by utilizing numerous sensory signals. The detection capability of the TBIET was further validated using various test samples, including representative human body, environmental, and beverage samples. The TBIET achieved a remarkably high classification accuracy. For instance, chemical solutions showed 100% identification accuracy, environmental samples reached 98.3% accuracy, and four typical teas demonstrated 97.0% accuracy. Additionally, the classification accuracy of NaCl solutions with five different concentrations reached 96.9%. The innovative TBIET exhibits a remarkable capacity to detect and analyze droplets with ultrahigh sensitivity to their electrical properties. Moreover, it offers a high degree of reliability in accurately detecting and analyzing various liquid samples within a short timeframe. The development of a self-powered portable triboelectric E-tongue prototype is a notable advancement in the field and is one that can greatly enhance the feasibility of rapid on-site detection of liquid samples in various settings.
电子舌由一系列模拟人类味觉感知的传感器和用于数据分析与识别的嵌入式人工智能组成。基于电化学方法的传统电子舌体积庞大,需要更大的样本量和额外的电源,这限制了它们在体内医学诊断和分析化学中的应用。受人类舌头力学原理的启发,摩擦电组件已被纳入电子舌平台以克服这些限制。在本研究中,在单个玻璃载片芯片上开发了一种集成多通道摩擦电生物启发电子舌(TBIET)装置,通过利用大量传感信号提高装置的味觉分类准确率。使用包括代表性人体、环境和饮料样本在内的各种测试样本进一步验证了TBIET的检测能力。TBIET实现了极高的分类准确率。例如,化学溶液的识别准确率达到100%,环境样本的准确率达到98.3%,四种典型茶叶的准确率达到97.0%。此外,五种不同浓度的NaCl溶液的分类准确率达到96.9%。创新的TBIET具有以超高灵敏度检测和分析液滴电学性质的显著能力。此外,它在短时间内准确检测和分析各种液体样本方面具有高度可靠性。自供电便携式摩擦电电子舌原型的开发是该领域的一项显著进展,能够极大地提高在各种环境中快速现场检测液体样本的可行性。