Development of Flexible ReS2/MXene Based Electromechanical Sensor for Deep Learning Assisted Temporal Dependent Alphabet Pattern Recognition

Sohel Siraj,Naveen Bokka, Anurag Gade, Sarang Akella, Chandra Sekhar Reddy Kolli,Parikshit Sahatiya

IEEE Journal on Flexible Electronics(2023)

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摘要
This article demonstrates the fabrication of a flexible electromechanical sensor (pressure and strain) utilizing ReS2 as active material and patterned Ti3C2Tx metal carbide/nitride (MXene) as the contact for the amplitude- and time-dependent alphabet recognition pattern concerning high-security applications. The sensitivity of the pressure sensor is 0.139 kPa−1, and the gauge factor of the fabricated strain sensor is 0.436. The physical explanation for both pressure and strain stimuli is explained in terms of modulation of the Schottky barrier height of ReS2/MXene by extracting the band diagram using ultraviolet photoelectron spectroscopy (UPS) measurements. To demonstrate the real-time application of the fabricated device, characterization of each of the 26 English alphabets (individual) is performed by obtaining their current–time data, which also collects the speed and magnitude of the writing. A detailed architecture of the convolutional neural network is presented with an accuracy of 96.20%. The successful demonstration of a low-cost flexible electromechanical sensor for touch-pad applications finds numerous applications in security, signature forging, and medical devices.
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关键词
electromechanical sensor,deep learning,flexible res<sub>2</sub>/mxene
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