Evidence map›Paper›PMID 39968049›Full record

ArticleJournal of chemical and engineering data2025

Entropy Scaling of Viscosity IV-Application to 124 Industrially Important Fluids.

Viktor Martinek, Ian Bell, Roland Herzog, Markus Richter, Xiaoxian Yang

Abstract read
In one paragraph

Article in Journal of chemical and engineering data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

5 authors.

Viktor MartinekInterdisciplinary Center for Scientific Computing, Heidelberg University, 69120 Heidelberg, Germany.ORCID https://orcid.org/0000-0001-6215-4783
Ian BellApplied Chemicals and Materials Division, National Institute of Standards and Technology, Boulder, Colorado 80305, United States.
Roland HerzogInterdisciplinary Center for Scientific Computing, Heidelberg University, 69120 Heidelberg, Germany.
Markus RichterFaculty of Mechanical Engineering, Applied Thermodynamics, Chemnitz University of Technology, 09107 Chemnitz, Germany.ORCID https://orcid.org/0000-0001-8120-5646
Xiaoxian YangFaculty of Mechanical Engineering, Applied Thermodynamics, Chemnitz University of Technology, 09107 Chemnitz, Germany.ORCID https://orcid.org/0000-0003-4655-3156

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In our previous work [Yang X.J. Chem. Eng. Data2021, 66, 1385-1398], a residual entropy scaling (RES) approach was developed to link viscosity to residual entropy using a 4-term power function for 39 refrigerants. In further research [Yang X.Int. J. Thermophys.2022, 43, 183], this RES approach was extended to 124 pure fluids containing fluids from light gases (hydrogen and helium) to dense fluids (e.g., heavy hydrocarbons) and fluids with strong association force (e.g., water). In these previous research studies, the model was developed by manual optimization of the power function. The average absolute relative deviation (AARD) of experimental data from the RES model is approximately 3.36%, which is higher than the 2.74% obtained with the various models in REFPROP 10.0. In the present work, the power function was optimized by iteratively fitting the global (fluid-independent power terms) and local parameters (fluid-specific and group-specific parameters) and screening the experimental data. The resulting equation has only three terms instead of four. Most notably, the AARD of the new RES model is reduced down to 2.76%; this is very close to the various multiparameter models in REFPROP 10.0, while the average relative deviation (ARD) amounts to 0.03%, which is smaller than REFPROP 10.0's 0.7%. A Python package is provided for the use of the developped model.

Identifiers

PMID39968049
PMCPMC11831593

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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.