Literature DB >> 31495858

An ultra-rapid acoustic micromixer for synthesis of organic nanoparticles.

M Reza Rasouli1, Maryam Tabrizian2.   

Abstract

Mixing is a crucial step in many chemical analyses and synthesis processes, particularly in nanoparticle formation, where it determines the nucleation rate, homogeneity, and physicochemical characteristics of the products. In this study, we propose an energy-efficient acoustic platform based on boundary-driven acoustic streaming, which provides the rapid mixing required to control nanoprecipitation. The device encompasses oscillatory bubbles and sharp edges in the microchannel to transform the acoustic energy into vigorous vortical fluid motions. The combination of bubbles and sharp edges at their immediate proximity induced substantially stronger acoustic microstreams than the simple superposition of their effects. The device could effectively homogenize DI water and fluorescein within a mixing length of 25.2 μm up to a flow rate of 116 μL min-1 at a driving voltage of 40 Vpp, corresponding to a mixing time of 0.8 ms. This rapid mixing was employed to mitigate some complexities in nanoparticle synthesis, namely controlling nanoprecipitation and size, batch to batch variation, synthesis throughput, and clogging. Both polymeric nanoparticles and liposomes were synthesized in this platform and showed a smaller effective size and narrower size distribution in comparison to those obtained by a hydrodynamic flow focusing method. Through changing the mixing time, the effective size of the nanoparticles could be fine-tuned for both polymeric nanoparticles and liposomes. The rapid mixing and strong vortices prevent aggregation of nanoparticles, leading to a substantially higher throughput of liposomes in comparison with that by the hydrodynamic flow focusing method. The straightforward fabrication process of the system coupled with low power consumption, high-controllability, and rapid mixing time renders this mixer a practical platform for a myriad of nano and biotechnological applications.

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Year:  2019        PMID: 31495858     DOI: 10.1039/c9lc00637k

Source DB:  PubMed          Journal:  Lab Chip        ISSN: 1473-0189            Impact factor:   6.799


  9 in total

Review 1.  Recent advances in acoustic microfluidics and its exemplary applications.

Authors:  Yue Li; Shuxiang Cai; Honglin Shen; Yibao Chen; Zhixing Ge; Wenguang Yang
Journal:  Biomicrofluidics       Date:  2022-06-13       Impact factor: 3.258

2.  Microfluidic synthesis as a new route to produce novel functional materials.

Authors:  Xinying Xie; Yisu Wang; Sin-Yung Siu; Chiu-Wing Chan; Yujiao Zhu; Xuming Zhang; Jun Ge; Kangning Ren
Journal:  Biomicrofluidics       Date:  2022-08-24       Impact factor: 3.258

Review 3.  Visible-light and near-infrared fluorescence and surface-enhanced Raman scattering point-of-care sensing and bio-imaging: a review.

Authors:  Yingjie Hang; Jennifer Boryczka; Nianqiang Wu
Journal:  Chem Soc Rev       Date:  2022-01-04       Impact factor: 60.615

4.  Investigation of the Dynamics of Cavitation Bubbles in a Microfluidic Channel with Actuations.

Authors:  Xiaopeng Shang; Xiaoyang Huang
Journal:  Micromachines (Basel)       Date:  2022-01-28       Impact factor: 2.891

5.  Mixing enhancement in T-junction microchannel with acoustic streaming induced by triangular structure.

Authors:  Sintayehu Assefa Endaylalu; Wei-Hsin Tien
Journal:  Biomicrofluidics       Date:  2021-05-07       Impact factor: 2.800

6.  Fabrication of tunable, high-molecular-weight polymeric nanoparticles via ultrafast acoustofluidic micromixing.

Authors:  Shuaiguo Zhao; Po-Hsun Huang; Heying Zhang; Joseph Rich; Hunter Bachman; Jennifer Ye; Wenfen Zhang; Chuyi Chen; Zhemiao Xie; Zhenhua Tian; Putong Kang; Hai Fu; Tony Jun Huang
Journal:  Lab Chip       Date:  2021-06-15       Impact factor: 7.517

7.  A Numerical Investigation of the Mixing Performance in a Y-Junction Microchannel Induced by Acoustic Streaming.

Authors:  Sintayehu Assefa Endaylalu; Wei-Hsin Tien
Journal:  Micromachines (Basel)       Date:  2022-02-21       Impact factor: 2.891

Review 8.  Machine learning for microfluidic design and control.

Authors:  David McIntyre; Ali Lashkaripour; Polly Fordyce; Douglas Densmore
Journal:  Lab Chip       Date:  2022-08-09       Impact factor: 7.517

9.  Mixing Performance of a Cost-effective Split-and-Recombine 3D Micromixer Fabricated by Xurographic Method.

Authors:  Ramezan Ali Taheri; Vahabodin Goodarzi; Abdollah Allahverdi
Journal:  Micromachines (Basel)       Date:  2019-11-16       Impact factor: 2.891

  9 in total

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