Alkali Ion-Accelerated Gelation of MXene-Based Conductive Hydrogel for Flexible Sensing and Machine Learning-Assisted Recognition
Conductive hydrogels are promising active materials for wearable flexible electronics, yet it is still challenging to fabricate conductive hydrogels with good environmental stability and electrical properties. In this work, a conductive MXene/LiCl/poly(sulfobetaine methacrylate) hydrogel system was...
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MDPI AG
2024-11-01
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| Series: | Gels |
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| Online Access: | https://www.mdpi.com/2310-2861/10/11/720 |
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| author | Weidan Na Chao Xu Lei An Changjin Ou Fan Gao Guoyin Zhu Yizhou Zhang |
| author_facet | Weidan Na Chao Xu Lei An Changjin Ou Fan Gao Guoyin Zhu Yizhou Zhang |
| author_sort | Weidan Na |
| collection | DOAJ |
| description | Conductive hydrogels are promising active materials for wearable flexible electronics, yet it is still challenging to fabricate conductive hydrogels with good environmental stability and electrical properties. In this work, a conductive MXene/LiCl/poly(sulfobetaine methacrylate) hydrogel system was successfully prepared with an impressive conductivity of 12.2 S/m. Interestingly, the synergistic effect of MXene and a lithium bond can significantly accelerate the polymerization process, forming the conductive hydrogel within 1 min. In addition, adding LiCl to the hydrogel not only significantly increases its water retention ability, but also enhances its conductivity, both of which are important for practical applications. The flexible strain sensors based on the as-prepared hydrogel have demonstrated excellent monitoring ability for human joint motion, pulse, and electromyographic signals. More importantly, based on machine learning image recognition technology, the handwritten letter recognition system displayed a high accuracy rate of 93.5%. This work demonstrates the excellent comprehensive performance of MXene-based hydrogels in health monitoring and image recognition and shows potential applications in human–machine interfaces and artificial intelligence. |
| format | Article |
| id | doaj-art-63c2cb9a97144d408664baa08e7e9011 |
| institution | OA Journals |
| issn | 2310-2861 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Gels |
| spelling | doaj-art-63c2cb9a97144d408664baa08e7e90112025-08-20T02:28:10ZengMDPI AGGels2310-28612024-11-01101172010.3390/gels10110720Alkali Ion-Accelerated Gelation of MXene-Based Conductive Hydrogel for Flexible Sensing and Machine Learning-Assisted RecognitionWeidan Na0Chao Xu1Lei An2Changjin Ou3Fan Gao4Guoyin Zhu5Yizhou Zhang6College of Chemistry and Chemical Engineering, Xuzhou University of Technology, Xuzhou 221111, ChinaInstitute of Advanced Materials and Flexible Electronics (IAMFE), School of Chemistry and Materials Science, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaInstitute of Advanced Materials and Flexible Electronics (IAMFE), School of Chemistry and Materials Science, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaInstitute of Advanced Materials and Flexible Electronics (IAMFE), School of Chemistry and Materials Science, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaInstitute of Advanced Materials and Flexible Electronics (IAMFE), School of Chemistry and Materials Science, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaInstitute of Advanced Materials and Flexible Electronics (IAMFE), School of Chemistry and Materials Science, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaInstitute of Advanced Materials and Flexible Electronics (IAMFE), School of Chemistry and Materials Science, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaConductive hydrogels are promising active materials for wearable flexible electronics, yet it is still challenging to fabricate conductive hydrogels with good environmental stability and electrical properties. In this work, a conductive MXene/LiCl/poly(sulfobetaine methacrylate) hydrogel system was successfully prepared with an impressive conductivity of 12.2 S/m. Interestingly, the synergistic effect of MXene and a lithium bond can significantly accelerate the polymerization process, forming the conductive hydrogel within 1 min. In addition, adding LiCl to the hydrogel not only significantly increases its water retention ability, but also enhances its conductivity, both of which are important for practical applications. The flexible strain sensors based on the as-prepared hydrogel have demonstrated excellent monitoring ability for human joint motion, pulse, and electromyographic signals. More importantly, based on machine learning image recognition technology, the handwritten letter recognition system displayed a high accuracy rate of 93.5%. This work demonstrates the excellent comprehensive performance of MXene-based hydrogels in health monitoring and image recognition and shows potential applications in human–machine interfaces and artificial intelligence.https://www.mdpi.com/2310-2861/10/11/720conductive hydrogelMXenealkali ionwater-retention abilitymachine learning |
| spellingShingle | Weidan Na Chao Xu Lei An Changjin Ou Fan Gao Guoyin Zhu Yizhou Zhang Alkali Ion-Accelerated Gelation of MXene-Based Conductive Hydrogel for Flexible Sensing and Machine Learning-Assisted Recognition Gels conductive hydrogel MXene alkali ion water-retention ability machine learning |
| title | Alkali Ion-Accelerated Gelation of MXene-Based Conductive Hydrogel for Flexible Sensing and Machine Learning-Assisted Recognition |
| title_full | Alkali Ion-Accelerated Gelation of MXene-Based Conductive Hydrogel for Flexible Sensing and Machine Learning-Assisted Recognition |
| title_fullStr | Alkali Ion-Accelerated Gelation of MXene-Based Conductive Hydrogel for Flexible Sensing and Machine Learning-Assisted Recognition |
| title_full_unstemmed | Alkali Ion-Accelerated Gelation of MXene-Based Conductive Hydrogel for Flexible Sensing and Machine Learning-Assisted Recognition |
| title_short | Alkali Ion-Accelerated Gelation of MXene-Based Conductive Hydrogel for Flexible Sensing and Machine Learning-Assisted Recognition |
| title_sort | alkali ion accelerated gelation of mxene based conductive hydrogel for flexible sensing and machine learning assisted recognition |
| topic | conductive hydrogel MXene alkali ion water-retention ability machine learning |
| url | https://www.mdpi.com/2310-2861/10/11/720 |
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