ABSTRACT
With the rapid development of wearable electronics, low-cost, multifunctional, ultrasensitive touch-free wearables for human-machine interaction and human/plant healthcare management have attracted great attention. The experience of fighting the COVID-19 epidemic has also confirmed the great significance of contactless sensation. Herein, a wearable smart-sensing platform using silk fibroin-reduced graphene oxide (SF-rGO) as bifunctional sensing active layers has been fabricated and integrated with a noncontact moisture/thermo sensor and Joule heater. As a result, the as-prepared smart sensor operated at 0.1 V exhibits good stability and sensitivity (sensor response of 60 for 97% RH) under a wide linear range of 6-97% RH, fast response/recover speed (real test: 21.51 s/85.62 s) toward touch-free humidity/temperature sensing for wearables, and thermal readings that can be accurately corrected by Joule heater. Impressively, it can achieve breath monitoring, mental state prediction, or elevator switching by identifying fingertip humidity variation. Prospectively, this all-in-one wearable smart sensor would set an example for improving sensing performance from structure-function relationship points of view and building a noncontact sensing system for daily life.
Subject(s)
COVID-19 , Fibroins , Graphite , Wearable Electronic Devices , Humans , ElectronicsABSTRACT
Magnesium rechargeable batteries (MRBs) are presently attracting much attention due to their low cost, high safety, and high theoretical volumetric capacity. Traditionally, pure magnesium metal has been used as an anode for MRBs, but its poor cycle performance, modest compatibility with conventional electrolytes, and sluggish kinetics limit the further development of MRBs. In this work, eutectic and hypereutectic Mg-Sn alloys were designed and studied as anodes for MRBs. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) results confirmed that these alloys contained unique microstructures consisting of α-Mg, Mg2Sn, and eutectic phases. The dissolution processes of the Mg-Sn alloys were studied in an all-phenyl-complex (APC) electrolyte. A multiple-step electrochemical dissolution process and a special adsorption interface layer were established for the Mg-Sn alloy anodes with an eutectic phase. Hypereutectic alloys with mixed phases showed better battery performance than the eutectic alloy owing to their superior mechanical properties. In addition, the morphology and Mg dissolution mechanism of the Mg-Sn alloys during the 1st dissolution process were characterized and discussed.
ABSTRACT
The purposes are to recognize and classify different music characteristics and strengthen the copyright protection system for original digital music in the big data era. Deep learning (DL) and blockchain technology are applied and researched herein. Based on CNN (Convolutional Neural Network), a music recognition method combined with hashing learning is proposed. The error generated when outputting the binary hash code is considered, and the semantic similarity of the hash code is ensured. Besides, the application of blockchain technology in the current intellectual property protection in original music is discussed. According to digital music property rights protection needs, the system is divided into modules, and its functions are designed. The system ensures its various functions by applying the application protocol designed in the Algor and network. In the experiments, the MagnaTagATune dataset is selected to verify the performance of the proposed CRNNH (Convolutional Recurrent Neural Network Hashing) algorithm. The algorithm shows the best music recognition performance under different bit numbers. When the number of connections is about 100, the QPS value of the blockchain-based music property rights protection system can be stabilized at about 20,000. At any number of threads, the system pressure will increase dramatically with the increase in the number of analog connections. The music recognition algorithm based on DL and hash method discussed is of great significance in improving the classification accuracy of music recognition. The application of blockchain technology in the copyright protection platform of original music works can protect the copyright of digital music and ensure the operation performance of the system.
