Controlled viscoelastic particle encapsulation in microfluidic devices.


Journal

Soft matter
ISSN: 1744-6848
Titre abrégé: Soft Matter
Pays: England
ID NLM: 101295070

Informations de publication

Date de publication:
15 Sep 2021
Historique:
entrez: 15 9 2021
pubmed: 16 9 2021
medline: 16 9 2021
Statut: epublish

Résumé

The encapsulation of particles in droplets using microfluidic devices finds application across several fields ranging from biomedical engineering to materials science. The encapsulation process, however, is often affected by poor single encapsulation efficiency, quantified by the Poisson statistics, with droplets containing more than one particle or with several empty droplets. We here demonstrate that viscoelastic aqueous solutions of xanthan gum enable controlled single particle encapsulation in microfluidic devices with a single encapsulation efficiency up to 2-fold larger than the one predicted by the Poisson statistics. We achieved such a result by identifying viscoelastic xanthan gum aqueous solutions that could drive particle ordering before approaching the encapsulation area and simultaneously form uniform droplets. This is the first experimental evidence of viscoelastic encapsulation in microfluidic devices, the existing literature on the subject being focused on Newtonian suspending liquids. We first studied the process of viscoelastic droplet formation, and found that the droplet length normalised by the channel diameter scaled as predicted for Newtonian solutions. At variance with Newtonian solutions, we observed that the droplet formation mechanism became unstable above critical values of the Weissenberg number, which quantifies the elasticity of the xanthan gum solutions carrying the particles. In terms of controlled encapsulation, we discovered that the single encapsulation efficiency was larger than the Poisson values in a specific range of xanthan gum mass concentrations. Finally, we introduced an empirical formula that can help the design of controlled viscoelastic encapsulation systems.

Identifiants

pubmed: 34525163
doi: 10.1039/d1sm00941a
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

8068-8077

Auteurs

Keshvad Shahrivar (K)

Faculty of Science and Engineering, School of Engineering and Applied Science, Swansea University Fabian Way, Swansea, SA1 8EN, UK. francesco.delgiudice@swansea.ac.uk.

Francesco Del Giudice (F)

Faculty of Science and Engineering, School of Engineering and Applied Science, Swansea University Fabian Way, Swansea, SA1 8EN, UK. francesco.delgiudice@swansea.ac.uk.

Classifications MeSH