Evidence map›Paper›PMID 37563492›Full record

ArticleNature food2023

Dual-sensory fusion self-powered triboelectric taste-sensing system towards effective and low-cost liquid identification.

Xuelian Wei, Baocheng Wang, Xiaole Cao, Hanlin Zhou, Zhiyi Wu, Zhong Lin Wang

Abstract read
PubMed Publisher
In one paragraph

Article in Nature food, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
9.1field-weighted citation impact, top 1% of its field
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

12 citing papers in PubMed, 83 citations in OpenAlex.

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  12. Bioinspired integrated triboelectric electronic tongue.Microsystems & nanoengineering · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 3 countries.

Xuelian WeiBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China.
Baocheng WangBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China.
Xiaole CaoBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China.
Hanlin ZhouBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China.
Zhiyi WuBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China. wuzhiyi@binn.cas.cn.ORCID http://orcid.org/0000-0002-3215-0092
Zhong Lin WangBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China. zhong.wang@mse.gatech.edu.ORCID http://orcid.org/0000-0002-5530-0380
Chinese Academy of Sciences · CNGeorgia Institute of Technology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Infusing human taste perception into smart sensing devices to mimic the processing ability of gustatory organs to perceive liquid substances remains challenging. Here we developed a self-powered droplet-tasting sensor system based on the dynamic morphological changes of droplets and liquid-solid contact electrification. The sensor system has achieved accuracies of liquid recognition higher than 90% in five different applications by combining triboelectric fingerprint signals and deep learning. Furthermore, an image sensor is integrated to extract the visual features of liquids, and the recognition capability of the liquid-sensing system is improved to up to 96.0%. The design of this dual-sensory fusion self-powered liquid-sensing system, along with the droplet-tasting sensor that can autonomously generate triboelectric signals, provides a promising technological approach for the development of effective and low-cost liquid sensing for liquid food safety identification and management.

Indexed as

TasteTaste PerceptionFood SafetyHumansRecognition, PsychologySense Organs

Identifiers

PMID37563492
OpenAlexW4385737666

What OpenQuestion holds

Textmetadata
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.