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Research Papers: Lubricants

BPNN–QSTR Modeling to Develop Isosteres as Sulfur-Free, Anti-Wear Lubricant Additives

[+] Author and Article Information
Xinlei Gao, Tingting Wang, Ze Song

School of Chemical and
Environmental Engineering,
Wuhan Polytechnic University,
Wuhan 430023, Hubei Province, China

Zhan Wang

College of Food Science and Engineering,
Wuhan Polytechnic University,
Wuhan 430023, Hubei Province, China

Kang Dai

College of Pharmacy,
South-Central University for Nationalities,
Wuhan 430074, Hubei Province, China

Hao Chen

School of Chemical and
Environmental Engineering,
Wuhan Polytechnic University,
Wuhan 430023, Hubei Province, China
e-mail: lazychen@gmail.com

1Corresponding author.

Contributed by the Tribology Division of ASME for publication in the JOURNAL OF TRIBOLOGY. Manuscript received January 27, 2018; final manuscript received July 6, 2018; published online August 13, 2018. Assoc. Editor: Satish V. Kailas.

J. Tribol 141(1), 011801 (Aug 13, 2018) (14 pages) Paper No: TRIB-18-1041; doi: 10.1115/1.4040836 History: Received January 27, 2018; Revised July 06, 2018

The principle of isosterism was employed to design low- or zero-sulfur anti-wear lubricant additives. Thiobenzothiazole compounds and 2-benzothiazole-S-carboxylic acid esters were employed as templates. Sulfur in the thiazole ring or in the branched chain was exchanged with oxygen, CH2, or an NH group. Similarly, the template's benzimidazole ring was replaced with a quinazolinone group. Quantitative structure tribo-ability relationship (QSTR) models by back propagation neural network (BPNN) method were used to study correlations between additive structures and their anti-wear performance. The features of rubbing pairs with different additives were identified by energy dispersive spectrometer-scanning electron microscope analysis. A wide range of samples showed that sulfur substitution in additive molecules was found to be reasonable and feasible. Combined effects of the anti-wear additive and the base oil were able to improve anti-wear performance.

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Topics: Wear , Lubricants , Sulfur
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References

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Figures

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Fig. 1

The structure of lubricant additive

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Fig. 2

Prediction performance of anti-wear scar scale for bis(2-ethylhexyl) adipate model

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Fig. 3

Prediction performance of anti-wear scar scale for triisodecyl trimellitate model

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Fig. 4

Prediction performance of anti-wear scar scale for TMPTO model

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Fig. 5

Sensitivity of the descriptor for anti-wear performance for samples in bis(2-ethylhexyl) adipate

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Fig. 6

Sensitivity of the descriptor for anti-wear performance for samples in triisodecyl trimellitate

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Fig. 7

Sensitivity of the descriptor for anti-wear performance for samples in TMPTO

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Fig. 8

The formula structure of bis(2-ethylhexyl) adipate

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Fig. 9

The formula structure of triisodecyl trimellitate

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Fig. 10

The formula structure of TMPTO

Tables

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