From E-Waste to Environmental Sensors: An Evidence-Based Recovery-to-Sensor Framework for Recycled Ag, Au, and Cu Functional Materials

Electronic waste is a concentrated secondary source of Ag, Au, and Cu. Still, its suitability for environmental sensing depends not only on extraction efficiency but also on material quality, processability, reproducibility, and demonstrated analytical performance. This review evaluates the recovery-to-sensor pathway using an evidence-based framework that distinguishes genuinely recycled-metal materials from waste-assisted syntheses, reused components, and commercial-precursor benchmarks. Recovery and purification routes are assessed according to material attributes relevant to sensing and printing, including elemental purity, residual lixiviants, phase composition, oxidation state, particle-size distribution, surface chemistry, colloidal stability, and batch reproducibility. The final evidence inventory comprised 88 publications and was classified by material provenance (P1–P6) and evidence level (E1–E6), from recovery-only studies to integrated pathways incorporating device fabrication, real-sample validation, sustainability metrics, and end-of-life management. Direct evidence is strongest for Cu-based systems, including NiO-doped CuO nanoflakes obtained from flexible printed circuit boards for room-temperature ammonia sensing, Cu2O recovered from waste electric cables for electrochemical sensing, Cu2O/CuO nano-skeletons produced from waste printed circuit boards, and recycled Cu electrodes and Cu(OH)2 nanostructures derived from spent lithium-ion batteries. Au recovered from discarded electronic components has also been converted into functional nanoparticles, while commercial-AuNP studies provide transferable evidence for recyclable colorimetric sensing. The review identifies major gaps in direct recycled-versus-virgin comparisons, ink rheology, multi-batch reproducibility, harmonized limits of detection, real-matrix validation, quantitative life-cycle data and recovery of used sensors. A circular-sensor assessment framework is proposed based on material yields, recycled content, process mass intensity, energy and water use, device lifetime, valid measurements per device and end-of-life recovery. None of the studies included in the final evidence inventory met all E6 criteria required for a fully validated circular-sensor claim.