Lab-on-a-chip microfluidic devices for the analysis of trace metals: foundational principles, technological...

Microfluidic lab-on-a-chip (LOC) technologies provide a versatile framework for integrating sample handling, chemical recognition, separation, and detection within miniaturized analytical systems. Among their diverse applications, trace-metal analysis provides a particularly instructive model for evaluating the development and practical maturity of LOC technologies because it combines stringent sensitivity and selectivity requirements with complex sample matrices and well-defined analytical and regulatory demands. This review examines the fundamental principles governing LOC platforms for trace-metal analysis and traces the evolution of device design over the past twenty-five years. The historical development of the field is organized into four partially overlapping engineering phases: integrated glass/silicon microfabrication (ca. 2000-2008), PDMS-based soft lithography and rapid prototyping (ca. 2006-2015), diversification toward paper, thermoplastics, and additive or digital fabrication (ca. 2012-2022), and system-level hybrid integration with portable electronics and connected data analysis (ca. 2020-2026). These phases represent shifts in dominant design priorities rather than discrete technological replacements, as earlier materials and fabrication strategies continue to support later-generation devices. Across these developments, LOC platforms are examined through three core functional elements: fluid manipulation, recognition chemistry, and signal transduction. A worked design framework further shows how an analytical problem can be translated into an LOC platform, beginning with the definition of the measurand and sample matrix and progressing through sample preparation, detection, calibration, and validation. The accumulated evidence indicates that sensitivity alone is no longer the principal constraint on progress, since many reported platforms already achieve detection limits below application-relevant thresholds under controlled conditions. More persistent challenges include matrix effects, surface fouling, incomplete sample preparation, device-to-device variability, manufacturing reproducibility, long-term stability, and the limited availability of interlaboratory and field-validation data. The central challenge has therefore shifted from demonstrating feasibility to achieving robust and reproducible performance in complex real samples under realistic operating conditions. By linking fundamental principles with advances in materials, fabrication strategies, detection approaches, and system integration, this review identifies the developments that have shaped the field, the design concepts that have persisted across successive generations, and the unresolved issues that continue to limit translation toward practical deployment.