“Gloppiness” Phenomena and a Computer Vision Method to Quantify It

In this study, we present a rapid, cost-effective Python-driven computer vision approach to quantify the prevalent “gloppiness” phenomenon observed in complex fluids and gels. We discovered that rheology measurements obtained from commercial shear rheometers do show some hints, but do not exhibit a...

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Detalles Bibliográficos
Autores principales: Wu, Shijian, Mintel, Mark, Teoman, Baran, Jensen, Stephanie, Potanin, Andrei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10379414/
https://www.ncbi.nlm.nih.gov/pubmed/37504411
http://dx.doi.org/10.3390/gels9070532

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10379414/
https://www.ncbi.nlm.nih.gov/pubmed/37504411
http://dx.doi.org/10.3390/gels9070532

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