Evidence map›Paper›PMID 30424094›Full record

ReviewMicromachines2018

Passive Mixing inside Microdroplets.

Chengmin Chen, Yingjie Zhao, Jianmei Wang, Pingan Zhu, Ye Tian, Min Xu, Liqiu Wang, Xiaowen Huang

Abstract readReview
In one paragraph

Review in Micromachines, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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  14. Adsorption and superficial transport of oil on biological and bionic superhydrophobic surfaces: a novel technique for oil-water separation.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2020
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Chengmin ChenEnergy Research Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China. chencm@sderi.cn.
Yingjie ZhaoKey Laboratory of Biobased Polymer Materials, Shandong Provincial Education Department, School of Polymer Science and Engineering, Qingdao University of Science and Technology, Qingdao 266042, China. yz@qust.edu.cn.
Jianmei WangEnergy Research Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China. wangjm@sderi.cn.ORCID 0000-0003-1694-6848
Pingan ZhuEnergy Research Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China. zhupa@sderi.cn.
Ye TianDepartment of Mechanical Engineering, The University of Hong Kong, Hong Kong, China. tianye@hku.hk.
Min XuEnergy Research Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China. xumin@sderi.cn.
Liqiu WangEnergy Research Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China. lqwang@hku.hk.
Xiaowen HuangEnergy Research Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China. huangxiaowen2013@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Droplet-based micromixers are essential units in many microfluidic devices for widespread applications, such as diagnostics and synthesis. The mixers can be either passive or active. When compared to active methods, the passive mixer is widely used because it does not require extra energy input apart from the pump drive. In recent years, several passive droplet-based mixers were developed, where mixing was characterized by both experiments and simulation. A unified physical understanding of both experimental processes and simulation models is beneficial for effectively developing new and efficient mixing techniques. This review covers the state-of-the-art passive droplet-based micromixers in microfluidics, which mainly focuses on three aspects: (1) Mixing parameters and analysis method; (2) Typical mixing element designs and the mixing characters in experiments; and, (3) Comprehensive introduction of numerical models used in microfluidic flow and diffusion.

Indexed as

microdropletsmultiphasepassive mixingsimulation model

Identifiers

PMID30424094
PMCPMC6187237

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.