Topologically Engineered Strain Redistribution in Elastomeric Substrates for Dually Tunable Anisotropic Plasmomechanical Responses.

The prompt visual response is considered to be a highly intuitive tenet among sensors. Therefore, plasmomechanical strain sensors, which exhibit dynamic structural color changes, have recently been developed by using mechanical stimulus-based elastomeric substrates for wearable sensors. However, the reported plasmomechanical strain sensors either lack directional sensitivity or require complex signal processing and device design strategies to ensure anisotropic optical responses. To the best of our knowledge, there have been no reports on utilizing anisotropic mechanical substrates to obtain directional optical responses. Herein, we propose an anisotropic plasmomechanical sensor to distinguish between the applied force direction and the force magnitude. We employ a simple strain-engineered topological elastomer to mechanically transform closely packed metallic nanoparticles (NPs) into anisotropic directional rearrangements depending on the applied force direction. The proposed structure consists of a heterogeneous-modulus elastomer that exhibits a highly direction-dependent Poisson effect owing to the periodically line-patterned local strain redistribution occurring due to the same magnitude of applied external force. Consequently, the reorientation of the self-assembled gold (Au)-NP array manifests dual anisotropy, i.e., force- and polarization-direction-dependent plasmonic coupling. The cost-effectiveness and simple design of our proposed heterogeneous-modulus platform pave the way for numerous optical applications based on dynamic transformation and topological inhomogeneities.

Development of Shoelace Tensile Test System Based on Micro Sensors and Reliability Study / 医用生物力学

Objective To design and verify the reliability of a shoelace tensile test system. Methods Incremental loads of 0-196 N were applied to three tension sensors, each load was repeated nine times, with the load removed and interval of 30 s during the repeated tests. Then output voltage of the sensors under each load was collected. Linear regression analysis was used to explore linear relationship between the collected voltage signal and the incremental load. Accuracy, precision and consistency intervals were used to verify consistency of the measured values with the true load. Bland-Altman analysis and intra-group correlation coefficient (ICC) analysis were used to verify the repeatability and reliability of the tensile sensor. Results There was a significant linear correlation between output voltage signal of the sensors and the load (P< 0. 000 1, R2= 0. 999 9), and ICC of three sensors was above 0. 999 (P<0. 000 1). The mean values of the coefficients of variation of the measured values for three tensile sensors under different loads were 0. 003 8, 0. 002 2 and 0. 003 5, respectively. Conclusions The shoelace tensile test system has high reliability and can be used for real-time acquisition of shoelace tension.