Evidence map›Paper›PMID 40863800›Full record

ArticleNanomaterials (Basel, Switzerland)2025

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

Antonella Macagnano, Fabricio Nicolas Molinari, Simone Serrecchia, Paolo Papa, Anna Rita Taddei, Fabrizio De Cesare

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Antonella MacagnanoInstitute of Atmospheric Pollution Research (IIA), National Research Council (CNR), Montelibretti, 00010 Rome, Italy.ORCID 0000-0002-6015-4832
Fabricio Nicolas MolinariInstitute of Atmospheric Pollution Research (IIA), National Research Council (CNR), Montelibretti, 00010 Rome, Italy.ORCID 0000-0002-2132-7155
Simone SerrecchiaInstitute of Atmospheric Pollution Research (IIA), National Research Council (CNR), Montelibretti, 00010 Rome, Italy.ORCID 0009-0007-4648-4329
Paolo PapaInstitute of Atmospheric Pollution Research (IIA), National Research Council (CNR), Montelibretti, 00010 Rome, Italy.ORCID 0000-0003-3794-3988
Anna Rita TaddeiElectron Microscopy Section, High Equipment Centre, University of Tuscia, Building D, 01100 Viterbo, Italy.
Fabrizio De CesareInstitute of Atmospheric Pollution Research (IIA), National Research Council (CNR), Montelibretti, 00010 Rome, Italy.ORCID 0000-0001-9810-8746

Funding

European Regional Development Fund POR FESR Lazio 2014-2020 T0002E0001
6 · The paper itself

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.

Indexed as

agricultureB-VOCelectrospun nanofibresenvironmenthumidity-tolerant sensorlinalool sensingMIP-nanoparticlesMWCNT-PVP nanocompositesplant volatile monitoringselectivity

Identifiers

PMID40863800
PMCPMC12388757

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.