Abstract:Intelligent sensors have attracted substantial attention for various applications, including wearable electronics, artificial intelligence, healthcare monitoring, and human−machine interactions. However, there still remains a critical challenge in developing a multifunctional sensing system for complex signal detection and analysis in practical applications. Here, we develop a machine learning-combined flexible sensor for real-time tactile sensing and voice recognition through laser-induced graphitization. The… Show more
“…[25][26][27][28] Perovskite materials are incredibly adaptable for solar cell applications due to their exceptional optical and electronic characteristics. [29][30][31][32][33][34][35][36] There have been signicant improvements in perovskite materials' stability, scalability, and durability. With continued research and development, PSC's long-term stability and performance are anticipated to advance, bringing them closer to commercial viability.…”
Perovskite solar cells (PSCs) are promising photovoltaic (PV) technologies due to their high-power conversion efficiency (PCE) and low fabrication cost. This review article delves into the changing PSC landscape by...
“…[25][26][27][28] Perovskite materials are incredibly adaptable for solar cell applications due to their exceptional optical and electronic characteristics. [29][30][31][32][33][34][35][36] There have been signicant improvements in perovskite materials' stability, scalability, and durability. With continued research and development, PSC's long-term stability and performance are anticipated to advance, bringing them closer to commercial viability.…”
Perovskite solar cells (PSCs) are promising photovoltaic (PV) technologies due to their high-power conversion efficiency (PCE) and low fabrication cost. This review article delves into the changing PSC landscape by...
“…As an alternative to developing novel materials, enhancing the robustness, durability, and functionality of existing materials offers a feasible strategy for achieving our sustainability objectives. On the other hand, significant attention has been dedicated to wearable electronics, − which play a pivotal role in advancing motion recognition and detection, , human–machine interaction, , and intelligent robotics . Exploring innovative sensitive materials and structural designs represents a time and cost-efficient approach to developing advanced wearable devices with properties of high sensitivity, wide detection range, and enhanced stability and durability. ,− Various sensitive materials have been documented, including zero-dimensional metal nanoparticles, one-dimensional conductive polymer fibers and metal nanowires, , as well as two-dimensional graphene and graphene-like materials. , …”
Enhancing the durability and functionality of existing materials through sustainable pathways and appropriate structural design represents a time-and costeffective strategy for the development of advanced wearable devices. Herein, a facile graphene oxide (GO) modification method via the hydroxyl-yne click reaction is present for the first time. By the click coupling between propiolate esters and hydroxyl groups on GO under mild conditions, various functional molecules are successfully grafted onto the GO. The modified GO is characterized by FTIR, XRD, TGA, XPS, and contact angle, proving significantly improved dispersibility in various solvents. Besides the high efficiency, high selectivity, and mild reaction conditions, this method is highly practical and accessible, avoiding the need for prefunctionalizations, metals, or toxic reagents. Subsequently, a rGO-PDMS sponge-based piezoresistive sensor developed by modified GO-P2 as the sensitive material exhibits impressive performance: high sensitivity (335 kPa −1 , 0.8−150 kPa), wide linear range (>500 kPa), low detection limit (0.8 kPa), and long-lasting durability (>5000 cycles). Various practical applications have been demonstrated, including body joint movement recognition and real-time monitoring of subtle movements. These results prove the practicality of the methodology and make the rGO-PDMS sponge-based pressure sensor a real candidate for a wide array of wearable applications.
“…Xie ey al. built a voice recognition sensor and recognized sensor data through machine learning to achieve accurate recognition of speech . The application of machine learning is reflected not only in the analysis of data but also in the prediction of data.…”
At present, the preparation of laser-induced graphene (LIG) has become an important technology in sensor manufacturing. In the conventional preparation process, the CO 2 laser is widely used; however, its experimental period is long and its efficiency needs to be improved. We propose an innovative strategy to improve the experimental efficiency. We use the machine learning method to accurately predict the preparation parameters of LIG, so as to optimize the experimental process. Different structures can lead to different sensor performances. The structure constructed by the CO 2 laser is rough and has a large size, which can affect the performance of the sensor. Therefore, we propose for the first time an innovative method for intramembrane structure construction that combines the advantages of the CO 2 laser and fiber laser (CF-L). With this CF-L method, we have successfully prepared a biomimetic, flexible strain sensor. This sensor not only maintains a high degree of sensitivity, but also has a more refined and optimized structure. The manufacturing process of the whole sensor is simple, economical, and durable and can be prepared in large quantities and can be used to detect the extension and bending of human joints.
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