"Gloppiness" Phenomena and a Computer Vision Method to Quantify It.
Gels
; 9(7)2023 Jun 30.
Article
en En
| MEDLINE
| ID: mdl-37504411
ABSTRACT
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 strong correlation with the extent of "gloppiness". To measure the "gloppiness" level of laboratory-produced shower gel samples, we employed the rupture time of jetting flow and found a significant correlation with data gathered from the technical insight panelist team. While fully comprehending the "gloppiness" phenomenon remains a complex challenge, the Python-based computer vision technique utilizing jetting flow offers a promising, efficient, and affordable solution for assessing the degree of "gloppiness" for commercial liquid and gel products in the industry.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Gels
Año:
2023
Tipo del documento:
Article
País de afiliación:
Estados Unidos