Evidence map›Paper›PMID 35515237›Full record

ArticleRSC advances2019

Using magnetic levitation for density-based detection of cooking oils.

Chengxian Zhu, Lei Gao, Yaojie Han, QiRan OuYang, Lijun Zong, Lin Li, Chengwu Zhang, Jinhua Liu, Hai-Dong Yu, Wei Huang

Abstract read
In one paragraph

Article in RSC advances, 2019. 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

10 authors.

Chengxian ZhuInstitute of Advanced Materials (IAM), Key Laboratory of Flexible Electronics (KLOFE), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing Tech University (NanjingTech) 30 South Puzhu Road Nanjing 211816 Jiangsu PR China iamhdyu@njtech.edu.cn.
Lei GaoInstitute of Advanced Materials (IAM), Key Laboratory of Flexible Electronics (KLOFE), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing Tech University (NanjingTech) 30 South Puzhu Road Nanjing 211816 Jiangsu PR China iamhdyu@njtech.edu.cn.
Yaojie HanInstitute of Advanced Materials (IAM), Key Laboratory of Flexible Electronics (KLOFE), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing Tech University (NanjingTech) 30 South Puzhu Road Nanjing 211816 Jiangsu PR China iamhdyu@njtech.edu.cn.
QiRan OuYangInstitute of Advanced Materials (IAM), Key Laboratory of Flexible Electronics (KLOFE), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing Tech University (NanjingTech) 30 South Puzhu Road Nanjing 211816 Jiangsu PR China iamhdyu@njtech.edu.cn.
Lijun ZongInstitute of Advanced Materials (IAM), Key Laboratory of Flexible Electronics (KLOFE), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing Tech University (NanjingTech) 30 South Puzhu Road Nanjing 211816 Jiangsu PR China iamhdyu@njtech.edu.cn.
Lin LiInstitute of Advanced Materials (IAM), Key Laboratory of Flexible Electronics (KLOFE), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing Tech University (NanjingTech) 30 South Puzhu Road Nanjing 211816 Jiangsu PR China iamhdyu@njtech.edu.cn.ORCID https://orcid.org/0000-0003-0426-6546
Chengwu ZhangInstitute of Advanced Materials (IAM), Key Laboratory of Flexible Electronics (KLOFE), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing Tech University (NanjingTech) 30 South Puzhu Road Nanjing 211816 Jiangsu PR China iamhdyu@njtech.edu.cn.
Jinhua LiuInstitute of Advanced Materials (IAM), Key Laboratory of Flexible Electronics (KLOFE), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing Tech University (NanjingTech) 30 South Puzhu Road Nanjing 211816 Jiangsu PR China iamhdyu@njtech.edu.cn.
Hai-Dong YuInstitute of Advanced Materials (IAM), Key Laboratory of Flexible Electronics (KLOFE), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing Tech University (NanjingTech) 30 South Puzhu Road Nanjing 211816 Jiangsu PR China iamhdyu@njtech.edu.cn.ORCID https://orcid.org/0000-0001-7124-3630
Wei HuangInstitute of Advanced Materials (IAM), Key Laboratory of Flexible Electronics (KLOFE), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing Tech University (NanjingTech) 30 South Puzhu Road Nanjing 211816 Jiangsu PR China iamhdyu@njtech.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adulterated cooking oils and the repeated use of frying cooking oils are harmful to human health. Current techniques for the quality control of cooking oils such as gas chromatography and high performance liquid chromatography usually require expensive facilities, and they are complicated to operate. This paper describes a simple technique that uses magnetic levitation (MagLev) to analyse cooking oils based on density. We have demonstrated the application of MagLev to detect the quality of cooking oil by simulating adulterated sesame oil using peanut oil and frying soybean oil for different times. We have also demonstrated the use of MagLev to differentiate secondhand cooking oil from certified cooking oil. MagLev provides a portable and inexpensive method for the on-site inspection of cooking oils, and it may be extended to many other applications in food safety, environmental monitoring, medical diagnosis, and so on. The advantages of high sensitivity, low cost, and convenience of operation make MagLev especially useful for

Identifiers

PMID35515237
PMCPMC9064766

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.