Converging pathways of microfluidic metal-organic framework and artificial intelligence: A novel research frontier

The synergistic integration of microfluidics, metal-organic frameworks (MOF), and artificial intelligence (AI) represents a groundbreaking approach to redefine materials science, chemical engineering, and smart system design. This convergence addresses urgent challenges in sustainable chemistry, precision manufacturing, and adaptive sensing by considering the unique strengths of each domain: microfluidics enables unprecedented control over reactive environments, MOF offer tunable architectures for catalysis and separation, and AI unlocks data-driven optimization of complex processes. In this review, we systematically examine how these fields intersect to revolutionize MOF synthesis, characterization, and applications. We highlight breakthroughs in microfluidic platforms that enable real-time monitoring of MOF nucleation, growth, and phase transitions, alongside innovative strategies for creating tailored synthesis environments with spatiotemporal precision. The ability to scale MOF production while maintaining uniformity—a longstanding bottleneck—is critically assessed, emphasizing microfluidics role in advancing industrial throughput. Furthermore, we explore how AI integration transforms these systems from passive reactors to intelligent, self-optimizing platforms capable of accelerating MOF discovery, predicting structure-property relationships, and dynamically controlling chemical processes with feedback loops. This review serves as a catalyst for interdisciplinary innovation, bridging theory, experimentation, and machine intelligence to unlock the full potential of MOF-based technologies in the next decade. • Integration of microfluidics, MOFs, and AI revolutionizes smart materials design. • Real-time monitoring of MOF growth achieved via advanced microfluidic techniques. • Microfluidics significantly enhances industrial scalability of uniform MOFs. • AI transforms passive reactors into intelligent, self-optimizing MOF platforms. • New frontiers emerge by combining microfluidics precision with AI-driven MOFs.