Bimodal pressure sensors capable of simultaneously detecting static and dynamic forces are essential to medical detection and bio-robotics. However, conventional pressure sensors typically integrate multiple operating mechanisms to achieve bimodal detection, leading to complex device architectures and challenges in signal decoupling. In this work, we address these limitations by leveraging the unique piezotronic effect of Y-ion-doped ZnO to develop a bimodal piezotronic sensor (BPS) with a simplified structure and enhanced sensitivity. Through a combination of finite element simulations and experimental validation, we demonstrate that the BPS can effectively monitor both dynamic and static forces, achieving an on/off ratio of 1029, a gauge factor of 23,439 and a static force response duration of up to 600 s, significantly outperforming the performance of conventional piezoelectric sensors. As a proof-of-concept, the BPS demonstrates the continuous monitoring of Achilles tendon behavior under mixed dynamic and static loading conditions. Aided by deep learning algorithms, the system achieves 96% accuracy in identifying Achilles tendon movement patterns, thus enabling warnings for dangerous movements. This work provides a viable strategy for bimodal force monitoring, highlighting its potential in wearable electronics.

Researchers have developed a revolutionary non-invasive method combining 3D laser scanning technology and sensor data time-series analysis for identifying defective water treatment filters, achieving significant reductions in inspection time and labor costs while eliminating operational disruptions. Published in Smart Construction, this breakthrough has the potential to transform water treatment facility maintenance, ensuring safer and more efficient water processing by detecting subsurface structural defects through surface geometric changes and operational anomalies.

A comprehensive review reveals that blocking natural killer cell checkpoints and employing precision strategies like gene editing and engineered cell therapies could significantly enhance cancer immunotherapy outcomes for solid tumors and blood cancers.

A research team led by Prof. WAN Yinhua from the Institute of Process Engineering of the Chinese Academy of Sciences has uncovered a surprising new mechanism that fundamentally alters our understanding of ion transport in nanofiltration (NF) membranes and provides critical insights into improving lithium recovery from high-magnesium brines.

In the first study of its kind, researchers at the RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS) in Japan have used artificial intelligence to dramatically speed up the processing time when simulating galaxy evolution coupled with supernova explosion. This approach could help us understand the origins of our own galaxy, particularly the elements essential for life in the Milky Way.

Published in Smart Construction, this study investigates the cyclic bond behavior of fiber reinforced polymer (FRP) bars—an area vital to seismic design yet previously underexplored. By examining carbon (CFRP), glass (GFRP), and basalt (BFRP) fiber reinforced polymer bars under reversed cyclic loading, the research quantifies how bar diameter, embedment length, concrete strength, and rib geometry influence initial bond stiffness, unloading strength, frictional resistance, and energy dissipation. A unified bond stress–slip constitutive model and hysteresis framework are developed to capture interfacial degradation mechanisms under cyclic loads. These contributions offer key insights for improving the seismic performance and reliability of FRP-reinforced concrete structures in earthquake-prone regions.