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Ultrasensitive and Highly Selective o-Phenylenediamine Molecularly Imprinted Polymer for the Detection of 2,4-Dichlorophenoxyacetic Acid

  • Angelo Tricase
  • , Verdiana Marchianò
  • , Eleonora Macchia
  • , Nicoletta Ditaranto
  • , Luisa Torsi
  • , Paolo Bollella*
  • *Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArtikkeliTieteellinenvertaisarvioitu

13 Sitaatiot (Scopus)
281 Lataukset (Pure)

Abstrakti

Herein, we report an ultrasensitive and highly selective analytical methods to detect 2,4-dichlorophenoxyacetic acid (2,4-D) using an o-phenylenediamine based molecularly imprinted polymer (o-PD-MIP) sensor. Electrochemical Quartz Crystal Microbalance (EQCM) is used to investigate both the kinetics and the mass of the electropolymerized o-phenylenediamine. Additionally, successful removal of the template from the imprinted cavities is confirmed by comparing the XP spectra of imprinted and o-PD-MIPs after various template removal procedures. The most effective method involves a 70:30 mixture of MeOH:H2O for 15 min under stirring. The o-PD-MIP sensor exhibits high sensitivity with a LoD of (3 ± 1) × 10−12 M, which is below the EU regulation limits for drinking water by six orders of magnitude, a linear range between 10 and 100pM, and an excellent selectivity. These results proved the effectiveness of template removal procedure by using a 70:30 MeOH:H2O mixture and are a proof-of-concept for ultrasensitive and selective 2,4-D detection in real samples.

AlkuperäiskieliEnglanti
Artikkeli144430
JulkaisuElectrochimica Acta
Vuosikerta494
DOI - pysyväislinkit
TilaJulkaistu - 1 elok. 2024
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

Rahoitus

The following funding agencies are acknowledged: Centro di Innovazione in Single-Molecule Digital Assay – “Digital Assay” from Regione Puglia DGR N. 218 of 21/02/2022; 1LIVEXYLELLA - ID01 - Trasmissione D. M. n. 664519 del 28/12/2022; NoOne-A binary sensor with single-molecule digit to discriminate biofluids enclosing zero or at least one biomarker, ERC Stg2021, GA:101040383; CSGI is acknowledged for partial financial support.

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