上海科技大学知识管理系统

["Artificial ears with intelligence, which can sensitively detect sound-a variant of pressure-and generate consciousness and logical decision-making abilities, hold great promise to transform life. However, despite the emerging flexible sensors for sound detection, most success is limited to very simple phonemes, such as a couple of letters or words, probably due to the lack of device sensitivity and capability. Herein, the construction of ultrasensitive artificial eardrums enabling intelligent song recognition is reported. This strategy employs novel geometric engineering of sensing units in the soft microstructure array (to significantly reduce effective modulus) along with complex song recognition exploration leveraging machine learning algorithms. Unprecedented pressure sensitivity (6.9 x 103 kPa-1) is demonstrated in a sensor with a hollow pyramid architecture with porous slants. The integrated device exhibits unparalleled (exceeding by 1-2 orders of magnitude compared with reported benchmark samples) sound detection sensitivity, and can accurately identify 100% (for training set) and 97.7% (for test set) of a database of the segments from 77 songs varying in language, style, and singer. Overall, the results highlight the outstanding performance of the hollow-microstructure-based sensor, indicating its potential applications in human-machine interaction and wearable acoustical technologies.","Artificial eardrums with ultra-piezoresistive sensitivity are realized via geometrically engineered microstructure units and machine learning for intelligent song recognition. The advanced hollow-pyramidal-based sensor achieves unprecedented pressure sensitivity and remarkable sound detection sensitivity, capable of identifying 100% (training data) and 97.7% (test data) of 77 diverse songs, indicating potentials in human-machine interaction and wearable acoustical technologies. image"]