An improved drop casting electrochemical strategy for furosemide quantification in natural waters exploiting chemically reduced graphene oxide on glassy carbon electrodes
This work exploits the applicability of a chemically reduced graphene oxide (CRGO) modification on the electrochemical response of a glassy carbon electrode (GCE) for the first-time sensitive determination of furosemide in natural waters. The batch injection analysis (BIA) is proposed as an analytic...
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Published in: | Analytical and bioanalytical chemistry Vol. 412; no. 26; pp. 7123 - 7130 |
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Main Authors: | , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01-10-2020
Springer Springer Nature B.V |
Subjects: | |
Online Access: | Get full text |
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Summary: | This work exploits the applicability of a chemically reduced graphene oxide (CRGO) modification on the electrochemical response of a glassy carbon electrode (GCE) for the first-time sensitive determination of furosemide in natural waters. The batch injection analysis (BIA) is proposed as an analytical method, where CRGO-GCE is coupled to a BIA cell for amperometric measurements. Acetate buffer (0.1 μmol L
−1
, pH 5.2) was used as the background electrolyte. The modification provided an increase in sensitivity (0.024 μA/μmol L
−1
), low limit of detection (0.7 μmol L
−1
), RSD (< 4%), and broad linear range (1–600 μmol L
−1
). Recovery tests performed in two different concentration ranges resulted in values between 89 and 99%. Recovery tests were performed and compared with high-performance liquid chromatography (HPLC) with UV-Vis detection using Student’s
t
test at a 95% significance level, and no significant differences were found, confirming the accuracy of the method. The developed method is proven faster (169 h
−1
) compared with the HPLC analysis (5 h
−1
), also comparable with other flow procedures hereby described, offering a low-cost strategy suitable to quantify an emerging pharmaceutical pollutant.
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1618-2642 1618-2650 |
DOI: | 10.1007/s00216-020-02845-9 |