Charge transfer-enhanced OECT glucose sensor with superabsorbent polymer composites for non-invasive breath analysis
To address the limitations of traditional blood glucose monitoring in industrial environments, this study presents a charge transfer-enhanced glucose sensor based on organic electrochemical transistor, utilizing a carboxymethyl cellulose-modified PEDOT:PSS with aminated multi-walled carbon nanotubes/gold nanoparticles composite film. The sensor is integrated with superabsorbent polymer composites for non-invasive breath analysis. Molecular electrostatic potential calculations reveal that hydrogen-bond networks between carboxymethyl cellulose carboxyl groups and glucose hydroxyl moieties, together with π-π interactions of glucose molecules at the composite surface, enhance interfacial charge transfer efficiency by 2.5 % (0.236e→0.242e). Structural characterization confirms a honeycomb-like porous architecture (0.5–2 μm pore size) formed via carboxymethyl cellulose-mediated hydrogen bonding, accelerating glucose diffusion while suppressing interferent adsorption (response<1 %). The composite's three-dimensional conductive network combines PEDOT:PSS (p-type pathways), carbon nanotubes (surface area expansion) and gold nanoparticles (catalytic sites), achieving a linear detection range of 2–22 μmol·L⁻¹ (extendable up to 9 mM) in exhaled breath condensate with 56.656 μA·(mmol·L⁻¹·cm²)⁻¹ sensitivity, 0.2 μmol·L⁻¹ detection limit (S/N = 23.8), and < 4.8 s response time. The sensor-integrated facemask platform uses superabsorbent polymer to maintain 100 % relative humidity, stabilizing the electrolyte layer for real-time monitoring. Machine learning (random forest classifier processing 18 time-frequency features from transistor outputs) achieves 87.5 % accuracy in resolving glucose fluctuations. This work demonstrates the integration of hierarchical materials, interfacial charge control, and algorithmic processing for wearable biosensors in health monitoring.
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