Evidence map›Paper›PMID 35056171›Full record

ArticleMicromachines2021

A Systematic Approach for Developing 3D High-Quality PDMS Microfluidic Chips Based on Micromilling Technology.

Amin Javidanbardan, Ana M Azevedo, Virginia Chu, João P Conde

Abstract read
In one paragraph

Article in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

4 authors.

Amin JavidanbardanIBB-Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal.ORCID 0000-0001-5146-4698
Ana M AzevedoIBB-Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal.ORCID 0000-0001-5659-466X
Virginia ChuInstituto de Engenharia de Sistemas e Computadores-Microsistemas e Nanotecnologias (INESC MN), 1000-029 Lisboa, Portugal.
João P CondeDepartment of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal.ORCID 0000-0002-5677-3024

Funding

European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie 812909Fundação para a Ciência e Tecnologia UID/05367/202 of the Research Unit INESC MN through plurianual BASE and PROGRAMATICO financingFundação para a Ciência e Tecnologia UIDB/04565/2020 and UIDP/04565/2020 of the Research Unit Institute for Bioengineering and Biosciences - iBB and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy - i4HB
6 · The paper itself

Abstract

In recent years, there has been an increased interest in exploring the potential of micro-and mesoscale milling technologies for developing cost-effective microfluidic systems with high design flexibility and a rapid microfabrication process that does not require a cleanroom. Nevertheless, the number of current studies aiming to fully understand and establish the benefits of this technique in developing high-quality microsystems with simple integrability is still limited. In the first part of this study, we define a systematic and adaptable strategy for developing high-quality poly(methyl methacrylate) (PMMA)-based micromilled structures. A case study of the average surface roughness (

Indexed as

3D microfluidic structuredouble castingmicromachining strategiesmicro/mesoscale millingmicrosystem integrationoptimizationPDMSPMMAsensor integrationsurface quality

Identifiers

PMID35056171
PMCPMC8779272

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.