Nanohydroxyapatite (n-HAp) as a pickering stabilizer in oil-in-water (O/W) emulsions: a stability study

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Andreia Ribeiro (Author) FEUP; Manrique, Y.A. (Author) FEUP; Ferreira, ICFR (Author) Other; Barreiro, MF (Author) Other; Lopes, JCB (Author) Other; Madalena M. Dias (Author) FEUP

Journal

Title: Journal of Dispersion Science and Technology

Pages: 1-13

ISSN: 0193-2691

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 7 Citations

Scopus - 5 Citations

Associated Projects

LA LSRE-LCM - Financiamento Plurianual 2020-2023 para a Unidade LA LSRE-LCM Laboratório de Processos de Separação e Reacção - Laboratório de Catálise e Materiais

Other information

Authenticus ID: P-00T-1Y8

DOI: 10.1080/01932691.2020.1845199

Abstract (EN): Surfactant-free emulsions, such as Pickering emulsions, have been gaining an increased interest. They constitute green alternatives to the current industrial practices in emulsion technology finding diverse technological uses. In this work, nano-hydroxyapatite (n-HAp) was tested as an oil-in-water (O/W) Pickering stabilizer using a chemical system comprising sunflower oil at different O/W ratios (10/90 to 60/40) and n-HAp at concentrations ranging from 0.5 to 15 wt%. The produced emulsions were characterized, and stability evaluated over a two-month period. Based on the results achieved for the 20/80 series, a model to predict the emulsion stability taking into account the O/W ratio, total solids content, droplet diameter, and n-HAp dimensions, was developed. Cryo-SEM evidenced the attachment of n-HAp particles at the oil surface (oil core-n-HAp shell morphology), corroborating their role as Pickering stabilizers. The experimental results, versus the predicted results were compared using a ternary phase diagram, which evidenced the formation of three zones (unstable, stable and gel) depending on the used O/W ratio and n-HAp concentration. Moreover, the comparison of the predicted with the obtained experimental data validated the model predictability.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13