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Research Papers: Lubricants

A Three-Dimensional Quantitative Structure Tribo-Ability Relationship Model

[+] Author and Article Information
Xinlei Gao, Zhan Wang, Hong Zhang

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

Kang Dai

College of Pharmacy,
South-Central University for Nationalities,
Wuhan, Hubei 430074, China
e-mail: kangdai1688@163.com

1Corresponding author.

Contributed by the Tribology Division of ASME for publication in the JOURNAL OF TRIBOLOGY. Manuscript received May 28, 2014; final manuscript received December 6, 2014; published online February 5, 2015. Assoc. Editor: Min Zou.

J. Tribol 137(2), 021802 (Apr 01, 2015) (8 pages) Paper No: TRIB-14-1119; doi: 10.1115/1.4029388 History: Received May 28, 2014; Revised December 06, 2014; Online February 05, 2015

The prediction of lubrication characteristics for compounds through tribological models would aid in the discovery of new lubricant additives and improved lubricant design. But until recently, the field of tribological prediction has been sparse and not systematic. Tribological processes are complex and involve molecular energy exchange as well as conformation transitions. We have developed a platform of a “quantitative structure tribo-ability relationship (QSTR),” which enables us to introduce well-developed quantitative structure–activity relationships (QSAR) methods into tribology systematically. The present study applies “evaluation of infrared vibration-based” (EVA) descriptors, which are three-dimensional (3D) QSAR descriptors to simulate infrared (IR) vibration properties of molecules, in order to establish the QSTR prediction model. As structural changes take place under friction loads, the EVA descriptors characterize both molecular energy and conformations. The results show a strong correlation and robust predictability of the EVA model to tribological parameters. The approach paves a way to a systematic QSTR.

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Figures

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Fig. 9

The increment of EVA–PLS model when propyl is substituted with allyl (DEVA: compound 31 versus compound 28). (a) The VS as a function of the vector DEVA (the EVA descriptors difference of compound pair). (b) The FF as a function of the vector DEVA (the EVA descriptors difference of compound pair).

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Fig. 8

The increment of EVA–PLS model when phenyl thiazole is substituted with benzimidazole (DEVA: compound 27 versus compound 28). (a) The VS as a function of the vector DEVA (the EVA descriptors difference of compound pair). (b) The FF as a function of the vector DEVA (the EVA descriptors difference of compound pair).

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Fig. 7

The increment of EVA–PLS model when phenyl thiazole is substituted with benzoxazole (DEVA: compound 29 versus compound 31). (a) The VS as a function of the vector DEVA (the EVA descriptors difference of compound pair). (b) The FF as a function of the vector DEVA (the EVA descriptors difference of compound pair).

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Fig. 6

The increment of EVA–PLS model when butyl is substituted with dodecyl (DEVA: compound 7 versus compound 9). (a) The VS as a function of the vector DEVA (the EVA descriptors difference of compound pair). (b) The FF as a function of the vector DEVA (the EVA descriptors difference of compound pair).

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Fig. 5

The increment of EVA–PLS model when butyl is substituted with decyl (DEVA: compound 33 versus compound 35). (a) The VS as a function of the vector DEVA (the EVA descriptors difference of compound pair). (b) The FF as a function of the vector DEVA (the EVA descriptors difference of compound pair).

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Fig. 4

The increment of EVA–PLS model when butyl is substituted with octyl (DEVA: compound 8 versus compound 9). (a) The VS as a function of the vector DEVA (the EVA descriptors difference of compound pair). (b) The FF as a function of the vector DEVA (the EVA descriptors difference of compound pair).

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Fig. 3

The PLS coefficients of antiwear and antifriction models. (a) The curve of antiwear model and (b) the curve of antifriction model. Horizontal axis denotes frequency ν; longitudinal axis denotes the value of PLS coefficient (defined in Eq. (5)).

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Fig. 2

Prediction performance of EVA model. (a) Prediction of VS. (b) Prediction of FF. (OBS: the observed or experimental scale of antiwear and antifriction; PRED: the predicted scale of antiwear and antifriction in the models).

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Fig. 1

Comparison of EVA spectra and observed IR spectra

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Fig. 10

The increment of EVA–PLS model with xanthionyl (DEVA: compound 13 versus compound 32). (a) The VS as a function of the vector DEVA (the EVA descriptors difference of compound pair). (b) The FF as a function of the vector DEVA (the EVA descriptors difference of compound pair).

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Fig. 11

The increment of EVA–PLS model with thiophosphoryl (DEVA: compound 17 versus compound 21). (a) The VS as a function of the vector DEVA (the EVA descriptors difference of compound pair). (b) The FF as a function of the vector DEVA (the EVA descriptors difference of compound pair).

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