Rapid detection of perfluorooctanoic acid by surface enhanced Raman spectroscopy and deep learning.
Talanta
; 280: 126693, 2024 Aug 08.
Article
en En
| MEDLINE
| ID: mdl-39167934
ABSTRACT
Perfluorooctanoic acid (PFOA) has received increasing concerns in recent years due to its wide distribution and potential toxicity. Existing detection techniques of PFOA require complex pre-treatment, therefore often taking several hours. Here, we developed a rapid PFOA detection mode to detect approximate concentrations of PFOA (ranging from 10-15 to 10-3 mol/L) in deionized water, and detecting one sample takes only 20 min. The detection mode was achieved using a deep learning model trained by a large surface enhanced Raman spectra dataset, based on the agglomeration of PFOA with crystal violet. In addition, transfer learning approach was used to fine tune the model, the fine-tuned model was generalizable across water samples with different impurities and environments to determine whether meet the safety standards of PFOA, the accuracy was 96.25 % and 94.67 % for tap water and lake water samples, respectively. The mechanism and specificity of the detection mode were further confirmed by molecular dynamics simulation. Our work provides a promising solution for PFOA detection, especially in the context of the increasingly widespread application of PFOA.
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1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Talanta
Año:
2024
Tipo del documento:
Article
País de afiliación:
China