Evidence map›Paper›PMID 38617685›Full record

ArticleACS omega2024

Simultaneous Rapid Detection of Multiple Physicochemical Properties of Jet Fuel Using Near-Infrared Spectroscopy.

Ke Li, Xin Zhang, Jing Zhang, Biao Du, Xiaoping Song, Guixuan Wang, Qi Li, Yinglan Zhang, Fan Liu, Zhengdong Zhang

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Ke LiCenter for Environmental Metrology, National Institute of Metrology, Beijing 100029, China.ORCID https://orcid.org/0000-0001-9015-7279
Xin ZhangCollege of Environmental and Chemical Engineering, Dalian University, Dalian 116622, China.
Jing ZhangCollege of Environmental and Chemical Engineering, Dalian University, Dalian 116622, China.
Biao DuBeijing Yixingyuan Petrochemical Technology Co., Ltd., Beijing 101301, China.
Xiaoping SongCenter for Environmental Metrology, National Institute of Metrology, Beijing 100029, China.
Guixuan WangBeijing Yixingyuan Petrochemical Technology Co., Ltd., Beijing 101301, China.
Qi LiCenter for Environmental Metrology, National Institute of Metrology, Beijing 100029, China.
Yinglan ZhangLeibniz Institut für Polymerforschung Dresden e.V., Hohe Straße 6, Dresden 01069, Germany.
Fan LiuCenter for Environmental Metrology, National Institute of Metrology, Beijing 100029, China.
Zhengdong ZhangCenter for Environmental Metrology, National Institute of Metrology, Beijing 100029, China.ORCID https://orcid.org/0000-0001-8754-3822

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Jet fuel is the primary fuel used in the aviation industry, and its quality has a direct impact on the safety and operational efficiency of aircraft. The accurate quantitative detection and analysis of various physicochemical property indicators are important for improving and ensuring the quality of jet fuel in the domestic market. This study used near-infrared (NIR) spectroscopy to establish a suitable model for the simultaneous and rapid detection of multiple physicochemical properties in jet fuel. Using more than 40 different sources of jet fuel, a rapid detection model was established by optimizing the spectral processing methods. The measurement models were separately built using the partial least-squares (PLS) and orthogonal PLS algorithms, and the model parameters were optimized. The results show that after the Savitzky-Golay second derivative preprocessing, the PLS model built using the feature spectra selected by the uninformative variable elimination wavelength algorithm achieved the best measurement performance. Compared with the PLS model without preprocessing, the range of the resulting accuracy improvement was at least 15.01%. Under the optimal model parameters, the calibration set regression coefficient (

Identifiers

PMID38617685
PMCPMC11007685

What Socratic holds

Textmetadata
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 Socratic graph.