An inexpensive, automated and reproducible method to conduct quality control in nanoparticles

• Published in: Chemical papers Vol. 74; no. 9; pp. 2821 - 2824
• Main Authors: Ribeiro, Gabrielly Pereira, Valotto, Rafaela Spessemille, de Oliveira, Jairo Pinto, Guimarães, Marco Cesar Cunegundes, Lenz, Dominik
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.09.2020; Springer Nature B.V
• Subjects: Automation; Biochemistry; Biotechnology; Chemistry; Chemistry and Materials Science; Chemistry/Food Science; Control methods; Gold; Image transmission; Industrial Chemistry/Chemical Engineering; Machine learning; Materials Science; Medicinal Chemistry; Nanoparticles; Original Paper; Quality control; Sodium citrate; Nanoparticles; Automated analysis; Transmission electron microscopy; CellProfiler
• ISSN: 2585-7290; 0366-6352; 1336-9075
• DOI: 10.1007/s11696-020-01123-3

Multiple methods have been developed to estimate size and shape of nanoparticles from transmission electron microscopy images. However, some of them have limiting characteristics such as hard to use, expensive or have steps that make the results unreal. We present here a comparison of a manual (IMAGEJ) and an automated analysis, both free methods. The gold nanoparticles were synthesized by the traditional Turkevich method using sodium citrate. We used 23 images of gold nanoparticles. The results of our study show that the conglomerated particles can be excluded—given that a sufficient amount of particles is included in the analysis. We show that CellProfiler can be highly efficient to assumptions about size and shape of nanoparticles. These findings provide a new approach of free software that can be applied as machine learning and therefore automate the processing of nanoparticles data.