Yue HuangShaoxiong HuYing LiRui WangYuchen YangWei ZhuYuan Deng
Abstract Flexible pressure sensors are essential for human–machine interfaces and wearable devices, requiring accurate detection of diverse motion signals. However, challenges arise from material compressibility and mechanical limitations, hindering the development of sensors with both high sensitivity and wide sensing ranges, as well as the demand-driven designability. Here, iontronic sensors exhibiting distinct characteristics are developed via a skin-inspired gradient strategy with programmable performance of ultrahigh sensitivity (37,347.98 kPa−1) to 151.6 kPa or overall high sensitivity (130.93–1400.49 kPa−1) up to 956.7 kPa, capable of detecting both subtle arterial pulses and large motions like plantar pressure. Furthermore, the merit of ultrahigh sensitivity enables pressure sensors to record handwriting precisely and distinguish individual features, facilitating effective extraction of connotative information, and has been demonstrated in the proposed human-interactive system assisted with machine learning for individual authentication. The work provides valuable insight into reverse engineering of pressure sensors, promising benefits for broad intelligence applications.
Xuan LiOsman GulLei WuMorteza AmjadiShuying WuInkyu Park
Pei LiLei XieMin SuPengsai WangWei YuanChenhui DongJun Yang
Haonan TianYu JiangYanying SongTiantong WangJianming XueFeng ZhangYiliu LiuZhenyu XueKaifeng WangYunbiao Zhao
Ningning BaiLiu WangYiheng XueYan WangXingyu HouGang LiYuan ZhangMinkun CaiLingyu ZhaoFangyi GuanXueyong WeiChuan Fei Guo
Ningning Bai (3236778)Liu Wang (213066)Yiheng Xue (12184029)Yan Wang (15435)Xingyu Hou (10271879)Gang Li (34549)Yuan Zhang (41832)Minkun Cai (12184032)Lingyu Zhao (654367)Fangyi Guan (7512053)Xueyong Wei (1758454)Chuan Fei Guo (1440310)