Laser-induced graphene interfaces for artificial taste and chemical perception: From interfacial transduction to high-dimensional interpretation

Artificial taste systems are emerging as analytical platforms for complex liquid environments, where chemically meaningful information is encoded in multicomponent response patterns rather than individual analyte signals. Conventional electronic tongues, however, remain constrained by limited signal dimensionality, matrix-induced drift, and insufficient interpretability. Laser-induced graphene (LIG) interfaces provide a versatile route for constructing high-dimensional chemical perception platforms because their porous, defect-rich, and engineerable structures can convert heterogeneous interfacial interactions into multidimensional electrical responses. Within this broader family, LIG-FET and LIG-EGFET architectures represent important subfamilies because field-effect readout enables amplified, modular, and interface-sensitive transduction. In this review, we frame LIG-based artificial taste as a transition from target-specific detection to system-level chemical perception. We discuss how interfacial physics, LIG structural heterogeneity, surface engineering, electrochemical readout, and extended-gate architectures regulate chemical information generation and encoding capacity. We further analyze how data-driven models act as nonlinear decoders of electrical response manifolds, and why physics-informed learning is needed for robust, interpretable, and transferable chemical interpretation. We critically evaluate representative applications using an evidence-level framework that separates direct artificial-taste demonstrations from multiplexed biosensing, matrix-tolerant single-target sensing, and peripheral portable, self-powered, or microfluidic integration platforms. Finally, we propose reporting criteria and design principles for developing LIG-based chemical perception platforms from high-performance sensors toward robust artificial taste systems.