Programmable droplet manipulation enabled by charged-surface pattern reconfiguration

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

15 Scopus Citations
View graph of relations

Author(s)

  • Duokui Fang
  • Wenhao Zhou
  • Xiaofeng Liu
  • Yubin Zeng
  • Zuankai Wang
  • Huai Zheng

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article numbere74
Journal / PublicationDroplet
Volume2
Issue number3
Online published11 Jul 2023
Publication statusPublished - Jul 2023

Link(s)

Abstract

Programmable droplet manipulation based on external stimulation is in high demand in various modern technologies. Despite notable progress, current manipulation strategies still suffer from a common drawback such as single control means of modulating the external stimulation input, which leads to huge challenges in sophisticated and large scale-up droplet handling. Herein, a unique pattern-reconfiguration-driven droplet manipulation method is developed on conductive/nonconductive pattern surfaces under charge deposition. Contactless charge deposition induces the “edge barrier” phenomenon at the boundaries of conductive/nonconductive patterns, analogous to an invisible and tunable wall guiding droplet behaviors. The edge barrier effect can be flexibly tuned by the nonconductive surface pattern. Thus, with charge deposition, surfaces are endowed with protean control functionality. The design of conductive/nonconductive patterns can effectively enable multifunction droplet manipulations, including track-guided sliding, sorting, merging, and mixing. Moreover, dynamical pattern reconfiguration drives programmable fluidics with sophisticated and large scale-up droplet handling capabilities in a low-cost and simple approach. © 2023 The Authors. Droplet published by Jilin University and John Wiley & Sons Australia, Ltd.

Research Area(s)

Citation Format(s)

Programmable droplet manipulation enabled by charged-surface pattern reconfiguration. / Fang, Duokui; Zhou, Wenhao; Jin, Yuankai et al.
In: Droplet, Vol. 2, No. 3, e74, 07.2023.

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

Download Statistics

No data available