ReviewNanomaterials (Basel, Switzerland)2026
Self-Powered Triboelectric Biofluid Sensors for Early Disease Screening and Diagnosis: A Review.
Review in Nanomaterials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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4 authors.
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Abstract
With the growing demand for continuous health assessment and early disease screening, biofluids have attracted increasing attention because they provide molecular information that cannot be obtained from conventional physical signals alone. However, practical biofluid analysis remains constrained by limited sample volumes, unstable wet interfaces, complex fluid transport, and dependence on external power sources. Triboelectric nanogenerators and triboelectric nanosensors offer a promising solution by combining mechanical energy harvesting with direct signal transduction. This review provides a critical overview of the theoretical basis of triboelectric biofluid sensing, including working modes, figures of merit, charge-transfer mechanisms, and the differences between solid-solid and solid-liquid electrification. Material selection, interfacial functionalization, fluid collection, wearable configurations, and multimodal integration are further discussed. Recent applications involving sweat, tears, saliva, urine, interstitial fluid, blood, and wound exudate are summarized to clarify how triboelectric devices function as either power sources or active sensing interfaces. Particular attention is given to their potential in early screening, risk assessment, and auxiliary diagnosis. Current limitations associated with biofouling, charge dissipation, individual variability, biosafety, durability, calibration, and clinical validation are also evaluated. Finally, future directions are proposed to improve analytical reliability and accelerate the translation of self-powered biofluid sensors from laboratory prototypes to clinically meaningful healthcare platforms.
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