Evidence map›Paper›PMID 26392833›Full record

ArticleBiomicrofluidics2015

Piezoelectric-driven droplet impact printing with an interchangeable microfluidic cartridge.

Baoqing Li, Jinzhen Fan, Jiannan Li, Jiaru Chu, Tingrui Pan

Abstract read
In one paragraph

Article in Biomicrofluidics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Hybrid 3D printed-paper microfluidics.Scientific reports · 2020
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
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

5 authors.

Baoqing Li
Jinzhen FanDepartment of Biomedical Engineering, University of California , Davis 95616, USA.
Jiannan LiDepartment of Biomedical Engineering, University of California , Davis 95616, USA.
Jiaru ChuDepartment of Precision Machinery and Precision Instrumentation, University of Science and Technology of China , Hefei, Anhui 230027, China.
Tingrui PanDepartment of Biomedical Engineering, University of California , Davis 95616, USA.

Funding

Workshop on Environmental Technology Transfer and EntrepreneurshipP42ES004699 · NIEHS · UNIVERSITY OF CALIFORNIA DAVIS · PI HAMMOCK, BRUCE D · 1987 to 2021
$50.1M
NIEHS NIH HHS P42 ES004699
6 · The paper itself

Abstract

Microfluidic impact printing has been recently introduced, utilizing its nature of simple device architecture, low cost, non-contamination, and scalable multiplexability and high throughput. In this paper, we have introduced an impact-based droplet printing platform utilizing a simple plug-and-play microfluidic cartridge driven by piezoelectric actuators. Such a customizable printing system allows for ultrafine control of droplet volume from picoliters (∼23 pl) to nanoliters (∼10 nl), a 500 fold variation. The high flexibility of droplet generation can be simply achieved by controlling the magnitude of actuation (e.g., driving voltage) and the waveform shape of actuation pulses, in addition to nozzle size restrictions. Detailed printing characterizations on these parameters have been conducted consecutively. A multiplexed impact printing system has been prototyped and demonstrated to provide the functions of single-droplet jetting and droplet multiplexing as well as concentration gradient generation. Moreover, a generic biological assay has also been tested and validated on this printing platform. Therefore, the microfluidic droplet printing system could be of potential value to establish multiplexed micro reactors for high-throughput life science applications.

Identifiers

PMID26392833
PMCPMC4560724

What OpenQuestion holds

Textmetadata
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.