Microfluidics in separation science: Fabrication, applications and intelligent systems.

Area of Science:

• Analytical Chemistry
• Biomolecular Diagnostics
• Microfluidics Engineering

Background:

• Microfluidic devices offer miniaturized, automated, and efficient analytical separation and diagnostic solutions.
• Advances in fabrication (e.g., 3D printing) enable customizable platforms for techniques like GC, HPLC, and electrophoresis.
• These systems provide rapid, high-resolution analyses with reduced sample/reagent needs, enhancing sensitivity and portability.

Purpose of the Study:

• To review the convergence of microfluidics and artificial intelligence (AI) in analytical separation techniques.
• To elaborate on technological innovations, fabrication strategies, and applications of AI-enabled microfluidics.
• To provide a forward-looking perspective on intelligent analytical separation systems.

Main Methods:

• Review of recent advancements in microfluidic device fabrication and integration with analytical techniques.
• Exploration of AI applications (machine learning, neural networks) in microfluidic data processing, optimization, and control.
• Comprehensive analysis of microfluidic-electrophoretic and chromatographic separation techniques.

Main Results:

• AI integration transforms microfluidics into intelligent systems for real-time optimization, anomaly detection, and autonomous control.
• AI-enabled microfluidics facilitates dynamic experimentation and reshapes personalized diagnostics.
• Synergy of AI and microfluidics enhances automation, scalability, and customization for analytical separations.

Conclusions:

• The fusion of AI and microfluidics represents a paradigm shift in analytical separations and diagnostics.
• AI enhances microfluidic capabilities, leading to more intelligent, efficient, and adaptable systems.
• Future intelligent analytical separation systems will be shaped by AI-driven microfluidic advancements.