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◆ Chemical Engineering Journal2026-03-14· Bioelectronics

Machine-learning-enabled starch/MXene moisture sensing bioelectronics for human monitoring and interaction

Ming Dong, Yansong Li, Subash Rai, Han Zhang, Emiliano Bilotti, Dimitrios G. Papageorgiou

原始摘要(英文原文)· Original abstract
The drive toward sustainable sensors demands materials and manufacturing routes that deliver high sensing performance without generating persistent waste. We report a water-based, blade-coating process to fabricate starch/Ti 3 C 2 Tₓ MXene nanocomposite films that operate as multifunctional, moisture-responsive bioelectronics. The films form a layered conductive architecture with a Young's modulus of 6.4 GPa and tensile strength of 82.3 MPa at only 1.36 vol% MXene, exceeding the mechanical performance of previously reported biodegradable conductive films. The composite films display a low percolation threshold of 0.48 vol% and offer tuneable conductivity over 9.6 × 10 −4 to 0.48 S/m. In combination with exceptional humidity sensitivity (>700% ΔR/R 0 at 95% RH), these features enable high-performance multimodal moisture sensing, including respiration analysis, speech detection, skin hydration monitoring, and non-contact human–machine interaction (HMI). When integrated with machine-learning classification, a single transient sensor can accurately distinguish breathing patterns and recognise spoken words with 97% accuracy. In addition, the films exhibit moisture-driven actuation, excellent biocompatibility (cell viability >97%), and fully biodegrade in soil within 30 days. By combining scalable processing, intelligent sensing and transient functionality, this work positions biodegradable bioelectronics as a credible alternative to conventional wearable sensor technologies. • We demonstrate, for the first time, that humidity-induced resistance signals from natural-biopolymer based, transient films can be processed using machine learning to accurately classify breathing modes and spoken words, enabling AI-assisted physiological monitoring and HMI. • The biobased nanocomposite films exhibit exceptional humidity sensitivity (>700% ΔR/R₀ at 95% RH), enabling precise detection of moisture variations for respiration monitoring, speech recognition, skin-hydration assessment, and contactless control of a smart-car. • In addition, the films combine a low percolation threshold (0.48 vol%), tuneable conductivity, and high mechanical strength (82.3 MPa), ensuring stable electrical performance and mechanical integrity during repeated operation. • The devices fully biodegrade in soil within a month, addressing the rapidly growing challenge of electronic waste from disposable sensors and short-lifetime wearables.
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