Quantitative Analysis of Structural Parameters Importance of Helical Temperature Microfiber Sensor by Artificial Neural Network by Juan Liu, Minghui Chen, Hang Yu, Jinjin Han, Hongyi Jia, Zhili Lin, Zhijun Wu, Jixiong Pu, Xining Zhang, Hao Dai

“…With the assistance of the evaluation algorithms based on the well-performed backpropagation neural network (BPNN), we quantitatively analyze the importance of the structural parameters of the supported helical microfiber (HMF) temperature sensor. The relative output intensities of HMF sensor at different temperatures are predicted by the BPNN with the HMF’s structural parameters as the input variables. …”
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Cellulose-reinforced natural rubber microfibers with low mechanical hysteresis for wireless physiological monitoring by Epsita Kar, Arti Singh, Bokyeoung Kang, Jinhwan Yoon

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Investigation of 3D Printed Self-Sensing UHPC Composites Using Graphite and Hybrid Carbon Microfibers by Han Liu, Simon Laflamme, Bin Cai, Ping Lyu, Sri Sritharan, Kejin Wang

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Real-Time Precise Prediction Dispersion Turning Point of Optical Microfiber Coupler Biosensor with Ultra-High Sensitivity and Wide Linear Dynamic Range by Haiyang Yu, Yue Wang, Yang Xu, Wenchao Zhou, Yihui Wu

“…In addition, the concentration, temperature, and solvent used for the sensor’s biofunctional layer are optimized. Finally, in refractive index sensing, a maximum sensitivity of 1.17 × 105 ± 0.038 × 105 nm/RIU is achieved. …”
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