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Size-Selective Detection of Nanoparticles in Solution and Air by Imprinting.

Linoy DeryNitzan ShauloffYury TurkuletsIlan ShalishRaz JelinekDaniel Mandler
Published in: ACS sensors (2022)
Monitoring of nanoparticles (NPs) in air and aquatic environments is an unmet challenge accentuated by the rising exposure to anthropogenic or engineered NPs. The inherent heterogeneity in size, shape, and the stabilizing shell of NPs makes their selective recognition a daunting task. Thus far, only a few technologies have shown promise in detecting NPs; however, they are cumbersome, costly, and insensitive to the NPs morphology or composition. Herein, we apply an approach termed nanoparticle-imprinted matrices (NAIM), which is based on creating voids in a thin layer by imprinting NPs followed by their removal. The NAIM was formed on an interdigitated electrode (IDE) and used for the size-selective detection of silica NPs. Three- and 5-fold increases in capacitance were observed for the reuptake of NPs with similar diameter, compared to smaller or larger NPs, in air and liquid phase, respectively. En masse, the proposed approach lays the foundation for the emergence of field-effective, inexpensive, real-life applicable sensors that will allow online monitoring of NPs in air and liquids.
Keyphrases
  • oxide nanoparticles
  • risk assessment
  • machine learning
  • high resolution
  • deep learning
  • quantum dots
  • solid state