Evidence map›Paper›PMID 39430054›Full record

ArticleApplied physics letters2024

Neural network-enabled, all-electronic control of non-Newtonian fluid flow.

Huilu Bao, Xin Zhang, Xiaoyu Zhang, Xiao Fan, J William Boley, Jinglei Ping

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Applied physics letters, 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

6 authors.

Huilu BaoDepartment of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA.ORCID https://orcid.org/0000-0001-9815-833X
Xin ZhangDepartment of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA.ORCID https://orcid.org/0009-0009-0636-0959
Xiaoyu ZhangDepartment of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA.ORCID https://orcid.org/0000-0002-7052-6927
Xiao FanDepartment of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA.ORCID https://orcid.org/0000-0002-2620-3143
J William BoleyORCID https://orcid.org/0000-0003-0020-0988
Jinglei PingORCID https://orcid.org/0000-0003-0386-8828

Funding

Cell Control via Spatiotemporal Microenvironmental pH ModulationR35GM151128 · NIGMS · UNIVERSITY OF MASSACHUSETTS AMHERST · PI Jinglei Ping · 2023 to 2026
$1.5M
NIGMS NIH HHS R35 GM151128
6 · The paper itself

Abstract

Real-time, all-electronic control of non-Newtonian fluid flow through a microscale channel is crucial for various applications in manufacturing and healthcare. However, existing methods lack the sensitivity required for accurate measurement and the real-time responsiveness necessary for effective adjustment. Here, we demonstrate an all-electronic system that enables closed-loop, real-time, high-sensitivity control of various waveforms of non-Newtonian fluid flow (0.76

Identifiers

PMID39430054
PMCPMC11490316

What OpenQuestion holds

Textmetadata
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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.