Listya Eka Anggraini , Muhammad Naeem Younis , Mohammed A. Abdalmwla , Ghadeer Ghannam Alharbi , Khaoula El Yanboui , Abdulaziz A. Al-Saadi , Chanbasha Basheer
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引用次数: 0
Abstract
The emergence of advanced, innovative microfluidic devices has reshaped analytical separation methodologies and biomolecular diagnostics by introducing highly integrated, miniaturized systems that enable next-generation fluid manipulation, enhanced automation, precision, cost efficiency, and high-throughput capabilities. Advances in fabrication methods, such as soft lithography, photolithography, and 3D printing, have enabled the production of customizable microfluidic platforms from materials such as PDMS, glass, and thermoplastics. These microfluidic systems support a range of analytical functionalities of the technologies, including gas chromatography (GC), high-performance liquid chromatography (HPLC), and electrophoresis, delivering rapid, high-resolution analyses with minimal sample and reagent requirements, quicker analysis, and enhanced uniformity and stability, facilitating high productivity screening, improved sensitivity and portability. Integration of micro-GC systems enables rapid, portable detection of volatile compounds, while microfluidic HPLC and electrophoresis provide precise biomolecular separations and real-time diagnostics. Recent advancements in artificial intelligence (AI) have now brought significant innovations in microfluidic devices, resulting in a new era of intelligent analytical separations, where machine learning algorithms and neural networks are applicable not only for data processing and pattern recognition but also for real-time optimization, anomaly detection, innovative read-out systems, and autonomous system control. The fusion of AI and microfluidics has enabled new approaches to dynamic experimentation, reshaping traditional microfluidics and personalized diagnostics and health care systems, where rapid, reliable analysis is paramount. In this review article, we comprehensively explain the progressive convergence of microfluidics and AI across various electrophoretic and chromatographic analytical separation techniques, elaborating on the latest technological innovations, fundamental fabrication strategies, and emergent applications. The article also presents a forward-looking perspective on how AI-enabled microfluidics enhances automation, scalability, and application-specific customization, which could shape the future of intelligent analytical separation systems.
期刊介绍:
The Journal of Chromatography A provides a forum for the publication of original research and critical reviews on all aspects of fundamental and applied separation science. The scope of the journal includes chromatography and related techniques, electromigration techniques (e.g. electrophoresis, electrochromatography), hyphenated and other multi-dimensional techniques, sample preparation, and detection methods such as mass spectrometry. Contributions consist mainly of research papers dealing with the theory of separation methods, instrumental developments and analytical and preparative applications of general interest.