High-sensitivity omnidirectional recognition strain sensor based on two-dimensional materials

Resistive strain sensors hold significant potential in wearable sensing devices due to their lightweight nature, simple structure, and rapid response. Two-dimensional (2D) materials, particularly MXenes, have emerged as ideal candidates for strain sensing applications owing to their high specific surface area, electrical conductivity, mechanical strength, flexibility, and tunable composition. These properties significantly enhance strain sensor performance and expand their applications in human motion monitoring, soft robotics, health tracking, and human-machine interactions. However, despite notable progress in improving wearable strain sensor performance, existing sensors can only detect uniaxial strain and cannot distinguish multidirectional strains—a critical limitation that restricts their application in dynamic skin motion sensing and complex environments. Consequently, there is a pressing need to develop multidirectional strain sensors with high-precision directional recognition capabilities to meet the demands of complex strain sensing scenarios.

A research team led by Professors Bowei Zhang and Fu-Zhen Xuan at East China University of Science and Technology recently proposed a bioinspired spider-web-structured omnidirectional strain sensor array. Using Ti3C2Tx (MXene) conductive ink and 3D printing technology, the team successfully fabricated the sensor array. This innovative design leverages the isotropic strain response characteristics of spider-web structures combined with a multi-class, multi-output neural network to decouple sensor array signals, enabling accurate identification and differentiation of both strain direction and magnitude.

The team published their findings on omnidirectional strain recognition sensors in Nano Research on May 14, 2025.

The research integrates bioinspired spider-web-structured sensor arrays with machine learning algorithms. While the spider-web architecture provides the physical foundation for omnidirectional strain response, the machine learning algorithm decouples signals from individual sensor units. This synergistic combination of biomimetic structure and computational intelligence achieves precise detection of both strain direction and intensity. The study is expected to advance the development of next-generation multidirectional strain sensors, offering a novel approach for simultaneously achieving high sensitivity and multidirectional detection capability. It demonstrates considerable potential for applications in human motion monitoring and multidirectional strain sensing, with promising prospects for intelligent robotics and wearable health monitoring devices.

This work was supported by the National Natural Science Foundation of China (Grants 52422505 and 12274124), the Shanghai Pilot Program for Basic Research (Grant 22TQ1400100-6), the Fundamental Research Funds for the Central Universities, and the Innovative Research Group Project of the National Natural Science Foundation of China (Grant 52321002).

About the Authors

Bowei Zhang, Professor at the School of Mechanical and Power Engineering, East China University of Science and Technology, is primarily engaged in research on intelligent sensing and micro-energy devices, as well as the design and manufacturing of key electrode components for hydrogen production equipment. He has been selected for the National Excellent Young Scientists Fund and the Shanghai High-Level Overseas Talent Program, and has received prestigious awards such as the National Award for Outstanding Self-Financed International Students and the Zaffarano Prize from the American Sigma Xi. He has published over 40 SCI-indexed papers with more than 1,200 citations and an h-index of 21. In the past five years, as the first or corresponding author, he has published over 20 SCI papers in renowned journals such as Nature Communications, Advanced Materials, Nano Letters (2), ACS Energy Letters, Materials Horizons, and Nano Energy, including three ESI Highly Cited Papers. Additionally, he has filed/obtained 8 patents. For more information, please pay attention to his research homepage https://www.x-mol.com/groups/zhang_bowei

Fu-Zhen Xuan, Professor at East China University of Science and Technology, is a recipient of the National Outstanding Young Scientist Fund and a "Ten Thousand Talents Program" Leading Talent. He currently serves as the President of East China University of Science and Technology. He has received the National Science and Technology Progress Award (First Class) once, the National Science and Technology Progress Award (Second Class) once, the Provincial and Ministerial Special Prize once, the First Prize four times, and the Second Prize once. He was also awarded the China Petroleum and Chemical Industry Federation Youth Science and Technology Outstanding Contribution Award. Professor Xuan has led and completed major national projects, including the National Nuclear Power Major Project (Topic), National Instrumentation Project, 863 Program, National Science and Technology Support Program, and National Natural Science Foundation projects. He has participated in the development and research of several national/industry standards, including "Safety Assessment of Pressure Vessels in Service with Defects" and "Evaluation of the Fitness for Use of Pressure Equipment.

About Nano Research

Nano Research is a peer-reviewed, open access, international and interdisciplinary research journal, sponsored by Tsinghua University and the Chinese Chemical Society, published by Tsinghua University Press on the platform SciOpen. It publishes original high-quality research and significant review articles on all aspects of nanoscience and nanotechnology, ranging from basic aspects of the science of nanoscale materials to practical applications of such materials. After 18 years of development, it has become one of the most influential academic journals in the nano field. Nano Research has published more than 1,000 papers every year from 2022, with its cumulative count surpassing 7,000 articles. In 2024 InCites Journal Citation Reports, its 2024 IF is 9.0 (8.7, 5 years), and it continues to be the Q1 area among the four subject classifications. Nano Research Award, established by Nano Research together with TUP and Springer Nature in 2013, and Nano Research Young Innovators (NR45) Awards, established by Nano Research in 2018, have become international academic awards with global influence.