Colorimetric detection of amino acids enabled by functional nanomaterials: mechanisms, performance evaluation, and translational perspectives.

Amino acids, as the fundamental building blocks of proteins and vital participants in biological activities, play a key role in biomedical, food science, and clinical diagnostics, where rapid and sensitive detection is of great importance. The colorimetric method is widely favored due to its simplicity, low cost, and ability to achieve visual or portable detection. Over the past decade (approximately 2014-2025), the integration of functional nanomaterials has fundamentally transformed colorimetric amino acid detection by enabling efficient transduction of molecular recognition events into amplified optical signals. This review provides a mechanism-oriented and performance-driven critical assessment of nanomaterial-enabled colorimetric sensors for amino acid detection. Rather than presenting a descriptive inventory, we systematically classify sensing strategies according to their dominant signal-generation mechanisms, including localized surface plasmon resonance modulation, nanozyme-mediated catalytic reactions, aggregation and anti-aggregation processes, intrinsic color and redox-responsive behaviors, as well as hybrid and cascade amplification schemes. Major nanomaterial platforms-metal-based nanomaterials, carbon-based nanomaterials, crystalline porous materials, single-atom nanomaterials, and hybrid systems-are comparatively evaluated in terms of structure-function relationships, detection sensitivity, selectivity toward structurally similar amino acids, response kinetics, matrix tolerance, and operational complexity. Beyond analytical performance, this review discusses key challenges that currently limit practical deployment, such as nonspecific interference, reproducibility, environmental stability, and device integration. By correlating sensing mechanisms with material design and application scenarios, we highlight emerging design principles and outline future directions for translating nanomaterial-based colorimetric amino acid sensors from laboratory demonstrations toward robust, real-world applications.