Evidence map›Paper›PMID 39479494›Full record

ArticleRSC advances2024

3D-printed shadow masks for micro-patterned electrodes.

Chanwook Cha, Eunhwa Jo, Yeongjun Kim, Andrew Jaeyong Choi, Koohee Han

Abstract read
In one paragraph

Article in RSC advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Chanwook ChaDepartment of Chemical Engineering, Kyungpook National University Daegu Republic of Korea han.koohee@knu.ac.kr.
Eunhwa JoDepartment of Chemical Engineering, Kyungpook National University Daegu Republic of Korea han.koohee@knu.ac.kr.
Yeongjun KimDepartment of Chemical Engineering, Kyungpook National University Daegu Republic of Korea han.koohee@knu.ac.kr.
Andrew Jaeyong ChoiSchool of Computing, Dept. of AI-SW, Gachon University 1342 Seongnam-daero, Sujeong-gu Seongnam 13306 Republic of Korea andrewjchoi@gachon.ac.kr.ORCID https://orcid.org/0000-0001-6507-3081
Koohee HanDepartment of Chemical Engineering, Kyungpook National University Daegu Republic of Korea han.koohee@knu.ac.kr.ORCID https://orcid.org/0000-0003-4942-9150

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microfabrication is critical to the advancement of lab-on-chip devices by enabling the creation of high-precision, complex electrode structures. Traditional photolithography, commonly used to fabricate micro-patterned electrodes, involves complex and multi-step processes that can be costly and time-consuming. In this research, we present a method using 3D-printed shadow masks for electrode fabrication, offering a simpler, cost-effective alternative to traditional methods. Specifically, by leveraging a fused deposition modeling 3D printer, we demonstrate that 3D-printed shadow masks streamline rapid prototyping of micro-patterned electrodes with a range of designs, from simple lines to complex patterns. To assess the lab-on-chip functionality of the electrodes fabricated from 3D-printed shadow masks, we investigate electric field-driven assembly of microparticles in the electrodes. The micro-patterned designs of the electrodes remotely guide the assembly patterns, resulting in the formation of well-defined, multiple chains and anisotropic structures. These results suggest that 3D-printed shadow masks not only simplify the fabrication process, but also maintain the precision required for advanced lab-on-chip applications. The proposed method could pave the way for more accessible and scalable manufacturing of the complex micro-patterned electrodes.

Identifiers

PMID39479494
PMCPMC11520313

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Registered trials

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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.