Evidence map›Paper›PMID 33741935›Full record

ArticleNature communications2021

Flow-sensory contact electrification of graphene.

Xiaoyu Zhang, Eric Chia, Xiao Fan, Jinglei Ping

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Engineering two-dimensional electronic biosensors.Nature reviews electrical engineering · 2026
    Article
  2. Article
  3. Review
  4. Study of Single and MultipassSensors (Basel, Switzerland) · 2023
    Article
  5. 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.

Xiaoyu ZhangDepartment of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA, USA.ORCID 0000-0002-7052-6927
Eric Chia *Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA, USA.ORCID 0000-0003-3935-5100
Xiao Fan *Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA, USA.
Jinglei PingDepartment of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA, USA. ping@engin.umass.edu.ORCID 0000-0003-0386-8828

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

All-electronic interrogation of biofluid flow velocity by electrical nanosensors incorporated in ultra-low-power or self-sustained systems offers the promise of enabling multifarious emerging research and applications. However, existing nano-based electrical flow sensing technologies remain lacking in precision and stability and are typically only applicable to simple aqueous solutions or liquid/gas dual-phase mixtures, making them unsuitable for monitoring low-flow (~micrometer/second) yet important characteristics of continuous biofluids (such as hemorheological behaviors in microcirculation). Here, we show that monolayer-graphene single microelectrodes harvesting charge from continuous aqueous flow provide an effective flow sensing strategy that delivers key performance metrics orders of magnitude higher than other electrical approaches. In particular, over six-months stability and sub-micrometer/second resolution in real-time quantification of whole-blood flows with multiscale amplitude-temporal characteristics are obtained in a microfluidic chip.

Indexed as

MicroelectrodesAnimalsBlood Flow VelocityCattleCopperGraphiteLab-On-A-Chip DevicesMicrofluidic Analytical TechniquesPhysical PhenomenaPolymethyl MethacrylateCopperGraphitePolymethyl Methacrylate

Identifiers

PMID33741935
PMCPMC7979811

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.