Evidence map›Paper›PMID 38826539›Full record

ArticleACS omega2024

Visualization and Analysis of Mapping Knowledge Domain of Fluid Flow Related to Microfluidic Chip.

Kai Fan, Chang Guo, Nan Liu, Xiaoyu Liang, Kan Jin, Zedong Wang, Chuanjie Zhu

Abstract read
In one paragraph

Article in ACS omega, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Kai FanCollege of Energy Environment and Safety Engineering, China Jiliang University, Hangzhou 310018, China.
Chang GuoCollege of Energy Environment and Safety Engineering, China Jiliang University, Hangzhou 310018, China.ORCID https://orcid.org/0000-0001-6527-6989
Nan LiuCollege of Energy Environment and Safety Engineering, China Jiliang University, Hangzhou 310018, China.ORCID https://orcid.org/0000-0002-9717-2137
Xiaoyu LiangCollege of Energy Environment and Safety Engineering, China Jiliang University, Hangzhou 310018, China.
Kan JinCollege of Energy Environment and Safety Engineering, China Jiliang University, Hangzhou 310018, China.
Zedong WangCollege of Energy Environment and Safety Engineering, China Jiliang University, Hangzhou 310018, China.
Chuanjie ZhuSchool of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microfluidic chips are important tools to study the microscopic flow of fluid. To better understand the research clues and development trends related to microfluidic chips, a bibliometric analysis of microfluidic chips was conducted based on 1115 paper records retrieved from the Web of Science Core Collection database. CiteSpace and VOSviewer software were used to analyze the distribution of annual paper quantity, country/region distribution, subject distribution, institution distribution, major source journals distribution, highly cited papers, coauthor cooperation relationship, research knowledge domain, research focuses, and research frontiers, and a knowledge domain map was drawn. The results show that the number of papers published on microfluidic chips increased from 2010 to 2023, among which China, the United States, Iran, Canada, and Japan were the most active countries in this field. The United States was the most influential country. Nanoscience, energy, and chemical industry and multidisciplinary materials science were the main fields of microfluidic chip research.

Identifiers

PMID38826539
PMCPMC11137721

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.