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has been cited by the following article:

• TITLE: Particles Size Estimation of Polydopamine Based Polymeric Nanoparticles Using Near-Infrared Spectroscopy Combined with Linear Regression Method

  AUTHORS: Nahla Rahoui, Mohammad Hegazy, Bo Jiang, Nadia Taloub, Yu Dong Huang

  KEYWORDS: Near Infrared Spectroscopy, Particle Size Effect, Nanoparticles, Linear Regression

  JOURNAL NAME: American Journal of Analytical Chemistry, Vol.9 No.5, May 24, 2018

  ABSTRACT: The particle size is considered as a fundamental property of nanoparticles used for cargo delivery (CDS) purpose. The objective of this study was the particles size quantification of polydopamine nanoparticles (PDANS) via the near infrared spectroscopy (NIRS) combined with chemometrics tools. The successful synthesis of PDANS was proved using several characterization methods. Compared with the model extracted using raw spectral data, the accuracy and stability of the new model extracted from pre-processed data were significantly improved. The PDANS particle size samples have been predicted with acceptable accuracy. The correlation (R2) between NIRS and the TEM granulometrie data was 99.81%, while the root mean square error of calibration RMSEC was 0.196 nm. This research shows that NIRS combined with a regression method is a viable tool for the quality determination of CD system.