Tuning Nanofibrous Sensor Performance in Selective Detection of B-VOCs by MIP-NP Loading

Abstract

In this study, we investigate the effect of varying the loading of molecularly imprinted polymer nanoparticles (MIP-NPs) on the morphology and sensing performance of electrospun nanofibres for the selective detection of linalool, a representative plant-emitted monoterpene. The proposed strategy combines two synergistic technologies: molecular imprinting, to introduce chemical selectivity, and electrospinning, to generate high-surface-area nanofibrous sensing layers with tuneable architecture. Linalool-imprinted MIP-NPs were synthesized via precipitation polymerization using methacrylic acid (MAA) and ethylene glycol dimethacrylate (EGDMA), yielding spherical particles with an average diameter of ~135 nm. These were embedded at increasing concentrations into a polyvinylpyrrolidone (PVP) matrix containing multi-walled carbon nanotubes (MWCNTs) and processed into nanofibrous mats by electrospinning. Atomic force microscopy (AFM) revealed that MIP content modulates fibre roughness and network morphology. Electrical sensing tests performed under different relative humidity (RH) conditions showed that elevated humidity (up to 60% RH) improves response stability by enhancing ion-mediated charge transport. The formulation with the highest MIP-NP loading exhibited the best performance, with a detection limit of 8 ppb (±1) and 84% selectivity toward linalool over structurally related terpenes (α-pinene and R-(+)-limonene). These results demonstrate a versatile sensing approach in which performance can be precisely tuned by adjusting MIP content, enabling the development of humidity-tolerant, selective VOC sensors for environmental and plant-related applications.