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Droplet Impact-Based Microliter Viscometry

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Abstract

Characterizing liquid viscosity and rheological properties with small sample volumes is crucial in fields where liquid samples are often limited, such as biological fluids for biomedical diagnostics and trace chemical products. However, traditional viscometers often require large sample volumes, and many existing small-volume viscometry techniques fall short in analyzing non-Newtonian fluids due to their limited shear rate range. While microfluidics-based viscometers offer flexibility in shear rate control, they are generally associated with intricate fabrication processes and high costs. Here, we introduce a droplet impact-based microliter viscometry (DI-μV), building on a quantitative relationship between viscosity and the maximum spreading factor of droplets impacting super-repellent surfaces. Leveraging the sufficient viscous effect during droplet impact, DI-μV can measure effective viscosity across varying effective shear rates and probe the rheological properties of liquids, using only μL-scale volumes. As a tool for viscosity measurement, DI-μV exhibits minimal sample consumption, adjustable effective shear rate, self-cleaning capabilities, operational simplicity, and cost-effectiveness, thereby offering relevant practical implications. © 2025 American Chemical Society

Original languageEnglish
Pages (from-to)13076-13085
JournalAnalytical Chemistry
Volume97
Issue number25
Online published16 Jun 2025
DOIs
Publication statusPublished - 1 Jul 2025

Bibliographical note

Publisher Copyright:
© 2025 American Chemical Society.

Funding

This research was supported by the Research Grants Council of Hong Kong (21213621), City University of Hong Kong (7006097), and National Natural Science Foundation of China (12332016). Peng Yu would like to thank the finance supports from the Natural Science Foundation of Guangdong (Grant No. 2024A1515011811), and Shenzhen Science and Technology Innovation Commission (Grant No. JSGG20220831101400002). Xiewen Wen thanks Research Grants Council of the Hong Kong Special Administrative Region, China under the grant 21206223.

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

RGC Funding Information

  • RGC-funded

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