Recent developments of artificial intelligence in MXene-based devices: from synthesis to applications

Area of Science:

• Materials Science
• Nanotechnology
• Artificial Intelligence

Background:

• Two-dimensional transition metal carbides, nitrides, or carbonitrides (MXenes) exhibit excellent properties like high electrical conductivity and large surface area, making them promising for various applications.
• Artificial intelligence (AI) is increasingly utilized in materials science for its efficiency and precision in analyzing complex data and predicting material behavior.

Purpose of the Study:

• To review the role and latest research directions of AI-based technology in MXene-based devices.
• To discuss the application of AI modeling tools in energy storage devices, sensors, and memristors utilizing MXenes.
• To provide recommendations for future research in AI-assisted MXene device fabrication for practical applications.

Main Methods:

• Comprehensive literature review focusing on AI applications in MXene research.
• Analysis of recent advancements in MXene synthesis methods, including their pros and cons.
• Discussion of AI-based modeling tools for optimizing MXene device performance.

Main Results:

• AI significantly enhances the design, fabrication, and performance prediction of MXene-based devices.
• AI-driven modeling shows promise for optimizing MXene applications in energy storage, sensing, and memristors.
• Recent progress in MXene synthesis offers diverse material options with varying properties.

Conclusions:

• AI is a transformative technology for advancing MXene-based devices in energy and environmental sectors.
• Further integration of AI in MXene research will accelerate the development of practical, high-performance devices.
• Guidelines for future research are provided to leverage AI for fabricating novel MXene-based technologies.