CHEMICAL ENGINEERING JOURNAL
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2024
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IF 13.3
Huacui Xiang,Zhijian Li,Zhou Bai,Haiwei Wu,Guodong Liu,Hongwei Zhou,Hanbin Liu
Wearable human–machine interaction remains a huge challenge when various flexible electronics have been developed to date, for which the information input seems more difficult than the information output such as display devices. Here in this work, an e-skin for handwriting input was disclosed based on a double network hydrogel of gluten protein and polyvinyl alcohol (PVA) that is cross-linked by borax. The hydrogel can tightly adhere onto human skin, being stretchable, self-healable, and working properly even under breakage, which perfectly match the requirements of the e-skin for human–machine interaction. Under the assistant of deep learning, the handwriting of letter and words on it can be recognized with high accuracy of above 89%, even under tensile state or destruction. In addition, this flexible device is biocompatible and biodegradable benefiting from the protein and PVA networks, which make it suitable as a wearable e-skin and being free of electronic wastes. The finding of this work may open a window for the development of e-skin for the two-way human–machine interaction.
研究领域:
材料科学
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生物医学工程
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人工智能
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DOI
高影响因子
Journal of Materials Chemistry C
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2025
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IF 5.1
Jian Liu,Ying Nie,Xiaolong Zhou,Juanjuan Qi,Dongke Li,Jianqiang Luo,Ke Wang
Lead-free Cs3Bi2Br9 perovskite has emerged as a promising candidate for memristor and artificial synapse devices due to its high environmental stability and low toxicity compared to lead-based alternatives. In this work, we successfully prepared a high-quality Cs3Bi2Br9 perovskite film via simple spin-coating method combined with low-pressure assisted treatment. Based on the obtained Cs3Bi2Br9 film, a memristor with the structure of W/Cs3Bi2Br9/ITO was fabricated. The memristor demonstrated excellent resistive switching performance, including analog-switching behavior, high environmental stability (> 11 months), low operating voltages (VFORMING ~ 0.65 V, VSET ~ 0.53 ± 0.08 V, and VRESET ~ −0.83 ± 0.11 V), fast switching speed (< 1 μs), and long switching endurance (> 1100 cycles). Furthermore, the synaptic plasticity such as short-term plasticity, long-term plasticity, and synaptic weight potentiation and depression were successfully simulated by pulse-train measurement. Finally, a Fully Connected Neural Network built with the W/Cs3Bi2Br9/ITO memristor can obtain an accuracy of about 90% in recognizing handwritten digits. The results indicate that the lead-free Cs3Bi2Br9-based memristor has great potential for high-stability, cost-effective, eco-friendly, and low-power consumption nonvolatile memory and neuromorphic computing applications.
研究领域:
材料科学
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神经形态计算
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电子工程
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DOI
高影响因子
Small Science
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2024
·Vol. 4
·期 11
·2400241
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IF 11.1
Mingli Liu,Shuai Liu,Jian Yao,Yu Teng,Lin Geng,Alei Li,Lin Wang,Yunfei Li,Qing Guo,Zongjie Shen,Lixing Kang,Mingsheng Long
In recent years, wide-bandgap semiconductor β-Ga 2 O 3 material has been widely studied because of its excellent properties. Simultaneously, 2D metal oxides (2DMOs) have also become a focus of research owing to their superior stability and unique physical properties arising from quantum confinement effects. Therefore, the exploration of 2D β-Ga 2 O 3 is expected to reveal its novel electrical properties in electronic applications. However, the synthesis of high-quality 2D β-Ga 2 O 3 remains a formidable challenge. Herein, a confined space is constructed to synthesize high-quality 2D β-Ga 2 O 3 nanoflakes by enhancing the control of the kinetics of chemical vapor deposition process. In the device results, it is shown that the grown nanoflakes have excellent switching properties and potential artificial synaptic response characteristics. Based on this premise, an artificial recognition system for handwritten numerals is developed, achieving a peak recognition accuracy of approximately 96%. This system holds significant potential for application within an emerging neuromorphic recognition framework tailored for advanced driver-assistance systems. In this work, a new feasible pathway is provided for the synthesis of 2D non-layered oxides and the potential of 2D oxides in the field of neuroanalog electronics and recognition is shown, thereby advancing the fields of 2D β-Ga 2 O 3 electronics and 2DMOs electronics.
研究领域:
材料科学
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电子工程
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神经网络
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DOI
高影响因子
COLLOIDS AND SURFACES A-PHYSICOCHEMICAL AND ENGINEERING ASPECTS
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2024
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IF 4.9
Junfang Zhang,Zhenming Li,Zhongxu Hao,Haoyang Jiang,Jianguo Tang
Hydrogel sensors for flexible touch-sensing devices have sparked tremendous research interest in wearable electronics for broad applications such as artificial intelligence, information secrecy, and interactive control devices. Although many achievements have been reached in the hydrogel touch-sensing devices, profound challenges remain in the establish of new sensing system and the improvement on the sensitivity to ensure smooth and sensitive touching experience. Herein, a flexible hydrogel sensor as the touchable panel was developed and showed excellent tough-sensing performance for handwriting with high sensitivity. With the flexible and tough hydrogel as the contact layers, the sandwiched hydrogel panel was prepared and showed good touch-sensing performance with high sensitivity (∼500 % ΔI/I 0 , 12.65 N −1 ). This improvement on the sensitivity was ascribed to the increasement of current during the touching process originated from the formation of new circuit branch. Furthermore, it could be used as a portable touchpad for the wearable handwriting. This hydrogel sensor with the high sensitivity for handwriting has great potential in the fields of intelligent screen and wearable electronic device.
研究领域:
材料科学
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生物医学工程
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电子信息
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产品关联
DOI
高影响因子
JOURNAL OF COLLOID AND INTERFACE SCIENCE
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2024
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IF 9.4
Liangliang Cui,Chunyan Hu,Wei Wang,Jian Zheng,Zhijia Zhu,Baojiang Liu
Wearable electronics based on conductive hydrogels (CHs) offer remarkable flexibility, conductivity, and versatility. However, the flexibility, adhesiveness, and conductivity of traditional CHs deteriorate when they freeze, thereby limiting their utility in challenging environments. In this work, we introduce a PHEA-NaSS/G hydrogel that can be conveniently fabricated into a freeze-resistant conductive hydrogel by weakening the hydrogen bonds between water molecules. This is achieved through the synergistic interaction between the charged polar end group (−SO 3 − ) and the glycerol-water binary solvent system. The conductive hydrogel is simultaneously endowed with tunable mechanical properties and conductive pathways by the modulation caused by varying material compositions. Due to the uniform interconnectivity of the network structure resulting from strong intermolecular interactions and the enhancement effect of charged polar end-groups, the resulting hydrogel exhibits 174 kPa tensile strength, 2105 % tensile strain, and excellent sensing ability (GF = 2.86, response time: 121 ms), and the sensor is well suited for repeatable and stable monitoring of human motion. Additionally, using the Full Convolutional Network (FCN) algorithm, the sensor can be used to recognize English letter handwriting with an accuracy of 96.4 %. This hydrogel strain sensor provides a simple method for creating multi-functional electronic devices, with significant potential in the fields of multifunctional electronics such as soft robotics, health monitoring, and human-computer interaction.
研究领域:
材料科学
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生物医学工程
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电子工程
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产品关联
DOI
PubMed
高影响因子
INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
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2025
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IF 8.5
Hao Dong,Chuanliu Liu,Xu Zhang,Dongyu Si,Yiming Luo,Jiale Jia,Menglu Han,Ying Su,Hanyu Zhou,Wei Zeng
With the rapid development of flexible electronics technology, high-performance flexible sensors have shown great potential in wearable devices and human-computer interaction fields. In this study, a hydrogel (PMAGZ) reinforced by gelatin and Zn 2+ was prepared using a one-pot method, which formed a triple-bonded cross-linked network structure through covalent, hydrogen, and ligand bonds to exhibit excellent mechanical properties and sensing characteristics, and can be applied to multimodal sensors and handwriting recognition. The introduction of gelatin and Zn 2+ strengthens the cross-linked structure inside the hydrogel, which can effectively improve the tensile strength, strain, and toughness of the hydrogel. Additionally, the addition of ethylene glycol and lithium chloride endowed the hydrogel with good frost resistance and electrical conductivity. The PMAGZ hydrogel sensor has a fast response time, high sensitivity, wide sensing range, and excellent fatigue resistance, and is capable of accurately monitoring human movements and handwriting information. Combined with machine learning algorithms (ML), the sensor can effectively recognize different handwritten letters with an accuracy of 99.8 %. This study provides a new approach for developing high-performance, multifunctional flexible sensors, which have broad application prospects in flexible wearable devices and human-computer interaction fields.
研究领域:
材料科学
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生物医学工程
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柔性电子学
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产品关联
DOI
PubMed
高影响因子
CHEMICAL ENGINEERING JOURNAL
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2024
·
IF 13.3
Wenlong Wu,Tianyi Jiang,Ming Li,Shanguo Zhang,Yu Li,Hongyuan Jiang
With the advancement of flexible ionic conductors, various wearable ionic conductor-based sensors have emerged. However, improving the sensitivity for specific targets and application scenarios remains a significant challenge. Here, a topology optimization strategy for organohydrogel tactile sensing was proposed. This study first prepared conductivity-tunable organohydrogels and investigated their sensing mechanisms. Using Arabic numerals as an example, this study then performs a topology optimization of the ionic tactile sensing structures based on handwriting probability distribution. A wearable identity authenticator was developed based on this structure, capable of recognizing personal characteristics, as well as handwriting speed and trajectory of users, enabling accurate recognition of handwritten digits for specific users with multi-encryption. Compared to traditional fully-covered sensing structures, the optimized sensing structure improved the accuracy of handwritten digit recognition by 107.91%. These findings provide a novel approach for optimizing the tactile sensing structures to adapt to various application scenarios.
研究领域:
材料科学
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生物医学工程
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柔性电子
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产品关联
DOI
高影响因子
ACS Applied Materials & Interfaces
·
2023
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IF 9.5
Chunqing Yang,Dongzhi Zhang,Dongyue Wang,Huixin Luan,Xiaoya Chen,Weiyu Yan
Flexible strain sensors have significant progress in the fields of human–computer interaction, medical monitoring, and handwriting recognition, but they also face many challenges such as the capture of weak signals, comprehensive acquisition of the information, and accurate recognition. Flexible strain sensors can sense externally applied deformations, accurately measure human motion and physiological signals, and record signal characteristics of handwritten text. Herein, we prepare a sandwich-structured flexible strain sensor based on an MXene/polypyrrole/hydroxyethyl cellulose (MXene/PPy/HEC) conductive material and a PDMS flexible substrate. The sensor features a wide linear strain detection range (0–94%), high sensitivity (gauge factor 357.5), reliable repeatability (>1300 cycles), ultrafast response–recovery time (300 ms), and other excellent sensing properties. The MXene/PPy/HEC sensor can detect human physiological activities, exhibiting excellent performance in measuring external strain changes and real-time motion detection. In addition, the signals of English words, Arabic numerals, and Chinese characters handwritten by volunteers measured by the MXene/PPy/HEC sensor have unique characteristics. Through machine learning technology, different handwritten characters are successfully identified, and the recognition accuracy is higher than 96%. The results show that the MXene/PPy/HEC sensor has a significant impact in the fields of human motion detection, medical and health monitoring, and handwriting recognition.
研究领域:
材料科学
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生物医学工程
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人工智能
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产品关联
DOI
PubMed
高影响因子
Nano Energy
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2025
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IF 17.1
Lina Zhou,Dongzhi Zhang,Kangshuai Li,Hao Zhang,Chunqing Yang
Wearable electronic devices are required to overcome the traditional limitations of rigidity and unsustainable power sources, thereby endowing complex electronics with advantageous characteristics such as stability, high output, and flexibility. Flexible triboelectric nanogenerators (TENGs) based on hydrogels have been demonstrated as stable and sustainable wearable power sources and self-powered sensing devices, achieving significant progress in human-machine interaction, handwriting recognition, and medical monitoring. In this work, a conductive hydrogel (PHK hydrogel) doped with boric acid and KCl was developed as a strain sensor, exhibiting high stretchability (1520%), high sensitivity (GF=1.58), and rapid response (0.35 s). A triboelectric nanogenerator (PHK TENG) based on the PHK hydrogel was assembled, demonstrating dual functionality of energy harvesting and pressure sensing. Furthermore, a four-channel smart wristband incorporating PHK TENG was designed, showcasing exceptional performance in handwritten text monitoring. With the assistance of deep learning technology, the PHK TENG based smart wristband achieved effective recognition of Arabic numerals with an accuracy of 98.21%. The results indicated that this work excels in wearable comfort and functionality, demonstrating significant potential in the field of intelligent wearable sensing and contributing to steering human life toward a more convenient and intelligent future.
研究领域:
材料科学
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生物医学工程
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人工智能
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产品关联
DOI
高影响因子
CERAMICS INTERNATIONAL
·
2022
·
IF 5.532
Tong Wei,Yongchao Shi,Xiangyu Wang,Jiao Cui,Liwei Wu,Liyan Liu,Jiawei Yan,Zhihong Lv,Yingdong Han,Yanyan Guo
Inorganic luminescence materials with intelligent response to external stimuli have drawn considerable interest owing to their alluring applications. Photochromic (PC) is a reversible process which can be adopted to construct subtle luminescence regulation. However, the PC effect is commonly weak for most inorganic materials. It is still challenging to realize strong luminescence switching and PC effect in general inorganic compounds. To fill this gap, tetragonal tungsten bronze (TTB) oxides with ingenious upconversion (UC) luminescence modulation and prominent PC phenomenon were designed by introducing variable valence ion (Mo 6+ ). Under this decorating, the UC luminescence switching ratio and PC contrast could be increased up to 2 and 4 times, respectively. The real-time information encoding based on PC and UC modulation was realized in TTB wafer, confirming the instant handwriting dual-mode display capacity. It is believed that this work will shed new light on the designing of terminal display devices.
研究领域:
材料科学
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光学工程
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产品关联
DOI
高影响因子
ACS Applied Materials & Interfaces
·
2024
·
IF 8.3
Junming Cao,Xueguang Yuan,Yangan Zhang,Qi Wang,Qi He,Shaohua Guo,Xiaomin Ren
The combination of wearable sensors with machine learning enables intelligent perception in human–machine interaction and healthcare, but achieving high sensitivity and a wide working range in flexible strain sensors for signal acquisition and accurate recognition remains challenging. Herein, we introduced carboxymethyl cellulose (CMC) into a carbon nanotubes (CNTs)/MXene hybrid network, forming tight anchoring among the conductive materials and, thus, bringing enhanced interaction. The silicone-rubber-encapsulated CMC-anchored CNTs/MXene (CCM) strain sensor exhibits an excellent sensitivity (maximum gauge factor up to 71 294), wide working range (200%), ultralow detection limit (0.05%), and outstanding durability (over 10 000 cycles), which is superior to most of the recently reported counterparts also based on a conductive composite film. Moreover, the sensor achieves seamless integration with human skin with the help of a poly(acrylic acid) adhesive layer, successfully obtaining stable and clear waveforms with meaningful profiles from the human body. On this basis, we proposed and realized a novel in-air handwriting recognition method via extracting multiple features of high-quality strain signals assisted by deep neural networks, achieving a high classification accuracy of 98.00 and 94.85% for Arabic numerals and letters, respectively. Our work provides an effective approach for significantly improving strain sensing performance, thereby facilitating innovative applications of flexible sensors.
研究领域:
材料科学
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生物医学工程
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人工智能
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产品关联
DOI
PubMed
高影响因子
ACS Applied Materials & Interfaces
·
2023
·
IF 9.5
Yanhua Ma,Dongzhi Zhang,Zihu Wang,Hao Zhang,Hui Xia,Ruiyuan Mao,Haolin Cai,Huixin Luan
Flexible strain sensors based on self-adhesive, high-tensile, super-sensitive conductive hydrogels have promising application in human–computer interaction and motion monitoring. Traditional strain sensors have difficulty in balancing mechanical strength, detection function, and sensitivity, which brings challenges to their practical applications. In this work, the double network hydrogel composed of polyacrylamide (PAM) and sodium alginate (SA) was prepared, and MXene and sucrose were used as conductive materials and network reinforcing materials, respectively. Sucrose can effectively enhance the mechanical performance of the hydrogels and improve the ability to withstand harsh conditions. The hydrogel strain sensor has excellent tensile properties (strain >2500%), high sensitivity with a gauge factor of 3.76 at 1400% strain, reliable repeatability, self-adhesion, and anti-freezing ability. Highly sensitive hydrogels can be assembled into motion detection sensors that can distinguish between various strong or subtle movements of the human body, such as joint flexion and throat vibration. In addition, the sensor can be applied in handwriting recognition of English letters by using the fully convolutional network (FCN) algorithm and achieved the high accuracy of 98.1% for handwriting recognition. The as-prepared hydrogel strain sensor has broad prospect in motion detection and human–machine interaction, which provides great potential application of flexible wearable devices.
研究领域:
材料科学
·
生物医学工程
·
柔性电子
✓ 已验证
产品关联
DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）