Hussain Talib, Chandio Imamdin, Ali Akbar, Hyder Ali, Memon Ayaz Ali, Yang Jun, Thebo Khalid Hussain
National Centre of Excellence in Analytical Chemistry, University of Sindh Jamshoro, Pakistan.
MOE Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Department of Chemistry, Tsinghua University, Beijing 100084, China.
Nanoscale. 2024 Oct 3;16(38):17723-17760. doi: 10.1039/d4nr03050h.
Two-dimensional transition metal carbides, nitrides, or carbonitrides (MXenes) have garnered remarkable attention in various energy and environmental applications due to their high electrical conductivity, good thermal properties, large surface area, high mechanical strength, rapid charge transport mechanism, and tunable surface properties. Recently, artificial intelligence has been considered an emerging technology, and has been widely used in materials science, engineering, and biomedical applications due to its high efficiency and precision. In this review, we focus on the role of artificial intelligence-based technology in MXene-based devices and discuss the latest research directions of artificial intelligence in MXene-based devices, especially the use of artificial intelligence-based modeling tools for energy storage devices, sensors, and memristors. In addition, emphasis is given to recent progress made in synthesis methods for various MXenes and their advantages and disadvantages. Finally, the review ends with several recommendations and suggestions regarding the role of artificial intelligence in fabricating MXene-based devices. We anticipate that this review will provide guidelines on future research directions suitable for practical applications.
二维过渡金属碳化物、氮化物或碳氮化物（MXenes）因其高电导率、良好的热性能、大表面积、高机械强度、快速电荷传输机制和可调节的表面性质，在各种能源和环境应用中受到了显著关注。最近，人工智能被视为一项新兴技术，因其高效性和精确性而在材料科学、工程和生物医学应用中得到广泛应用。在本综述中，我们重点关注基于人工智能的技术在基于MXene的器件中的作用，并讨论人工智能在基于MXene的器件中的最新研究方向，特别是基于人工智能的建模工具在储能器件、传感器和忆阻器中的应用。此外，还强调了各种MXene合成方法的最新进展及其优缺点。最后，本综述以关于人工智能在制造基于MXene的器件中的作用的若干建议作为结尾。我们预计本综述将为适用于实际应用的未来研究方向提供指导。
