Research Papers: Lubricants

Analyses of Tribological Properties of Castor Oil With Various Carbonaceous Micro- and Nano-Friction Modifiers

[+] Author and Article Information
Shubrajit Bhaumik

Department of Mechanical Engineering,
SRM University,
Chennai 603203, India
e-mail: shubrajit.b@ktr.srmuniv.ac.in

Shubhabrata Datta

Department of Mechanical Engineering,
SRM University,
Chennai 603203, India
e-mail: shubhabrata.p@ktr.srmuniv.ac.in

S. D. Pathak

Department of Mechanical Engineering,
SRM University,
Chennai 603203, India
e-mail: sdpa12@gmail.com

1Corresponding author.

Contributed by the Tribology Division of ASME for publication in the JOURNAL OF TRIBOLOGY. Manuscript received December 31, 2016; final manuscript received March 24, 2017; published online June 30, 2017. Assoc. Editor: Ning Ren.

J. Tribol 139(6), 061802 (Jun 30, 2017) (13 pages) Paper No: TRIB-16-1408; doi: 10.1115/1.4036379 History: Received December 31, 2016; Revised March 24, 2017

The present work investigates the tribological properties of castor oil with various carbonaceous friction modifiers (nano and microsize additives) assessed using four-ball tester as per ASTM D 4172 and ASTM D 2783. Castor oil has been chosen because of its high viscosity and ease of availability. Graphite, multiwalled carbon nanotube (MWCNT), and multilayered graphene are used as friction modifiers (FMs) in castor oil on weight percentage basis. Significant enhancements of tribological properties with a certain level of concentration of friction modifiers have been observed. The surface features of the tested balls were analyzed using a three-dimensional noncontact type profilometer, scanning electron microscope (SEM), and energy dispersive system (EDS). Decrease in surface roughness indicated better antiwear properties in case of nanofriction modifiers-based castor oil as compared to micrographite-based and neat castor oil (NCO). In order to assess the suitability of castor oil as a replacement for mineral oil, the results of castor oil samples are also compared with commercially available mineral oil. The tribological properties of castor oil are found to be competitive and generally superior to the mineral gear oil. The data generated are used to develop a neural network model to map the input–output correlation.

Copyright © 2017 by ASME
Your Session has timed out. Please sign back in to continue.


Adhvaryu, A. , and Erhan, S. Z. , 2002, “ Epoxidized Soybean Oil as a Potential Source of High-Temperature Lubricants,” Ind. Crops Prod., 15(3), pp. 247–254. [CrossRef]
Lawate, S. , 2006, “ Environmentally Friendly Hydraulic Fluids,” Synthetics, Mineral Oils, and Bio-Based Lubricants: Chemistry and Technology, Rudnick, L. R. , ed., CRC Press, Boca Raton, FL, pp. 20–34.
Fox, N. J. , and Stachowiak, G. W. , 2007, “ Vegetable Oil-Based Lubricants—A Review of Oxidation,” Tribol. Int., 40(7), pp. 1035–1046. [CrossRef]
Adhvaryu, A. , Erhan, S. Z. , and Perez, J. M., 2004, “ Tribological Studies of Thermally and Chemically Modified Vegetable Oils for Use as Environmentally Friendly Lubricants,” Wear, 257(3–4), pp. 359–367. [CrossRef]
Bekal, S. , and Bhat, N. R. , 2012, “ Bio-Lubricant as an Alternative to Mineral Oil for a CI Engine—An Experimental Investigation With Pongamia Oil as a Lubricant,” Energy Sources, 34(11), pp. 1016–1026. [CrossRef]
Biresaw, G. , 2006, “ Elastohydrodynamic Properties of Seed Oils,” J. Am. Oil Chem. Soc., 83(6), pp. 559–566. [CrossRef]
Bhaumik, S. , and Pathak, S. D. , 2016, “ A Comparative Experimental Analysis of Tribological Properties Between Commercial Mineral Oil and Neat Castor Oil Using Taguchi Method in Boundary Lubrication Regime,” Tribol. Ind., 38(1), pp. 33–44.
Imran, A. , Masjuki, H. H. , Kalam, M. A. , Varman, M. , Hasmelidin, M. , Al Mahmud, K. A. H. , Shahir, S. A. , and Habibullah, M. , 2013, “ Study of Friction and Wear Characteristic of Jatropha Oil Blended Lube Oil,” Proc. Eng., 68, pp. 178–185. [CrossRef]
Ossia, C. V. , Han, H. G. , and Kong, H. , 2008, “ Additive Properties of Saturated Very Long Chain Fatty Acids in Castor and Jojoba Oils,” J. Mech. Sci. Technol., 22(8), pp. 1527–1536. [CrossRef]
Saad Elmunafi, M. H. , Kurniawan, D. , and Noordin, M. Y. , 2015, “ Use of Castor Oil as Cutting Fluid in Machining of Hardened Stainless Steel With Minimum Quantity of Lubricant,” Proc. CIRP, 26, pp. 408–411. [CrossRef]
Shashidhara, Y. M. , and Jayaram, S. R. , 2010, “ Vegetable Oils as a Potential Cutting Fluid—An Evolution,” Tribol. Int., 43(5–6), pp. 1073–1081. [CrossRef]
Syahrullail, S. , Kamitanib, S. , and Shakirin, A. , 2013, “ Performance of Vegetable Oil as Lubricant in Extreme Pressure Condition,” Proc. Eng., 68, pp. 172–177. [CrossRef]
Yu, H. L. , Xu, Y. , Shi, P. J. , Wang, H. M. , Zhao, Y. , Xu, B. S. , and Bai, Z. M., 2010, “ Tribological Behaviors of Surface-Coated Serpentine Ultrafine Powders as Lubricant Additive,” Tribol. Int., 43(3), pp. 677–685.
Choi, Y. , Lee, C. , Hwang, Y. , Park, M. , Lee, J. , Choi, C. , and Jung, M., 2009, “ Tribological Behavior of Copper Nanoparticles as Additives in Oil,” Curr. Appl. Phys., 9(2), pp. 124–127. [CrossRef]
Ginzburg, B. M. , Shibaev, L. A. , Kireenko, O. F. , Shepelevskii, A. A. , Baidakova, M. V. , and Sitnikova, A. A. , 2002, “ Antiwear Effect of Fullerene C60 Additives to Lubricating Oils,” Russ. J. Appl. Chem., 75(8), pp. 1330–1335. [CrossRef]
Xiaodong, Z. , Xun, F. , Huaqiang, S. , and Zhengshui, H. , 2007, “ Lubricating Properties of Cyanex 302-Modified MoS2 Microspheres in Base Oil 500SN,” Lubr. Sci., 19(1), pp. 71–79. [CrossRef]
Zhou, J. , Yang, J. , Zhang, Z. , Liu, W. , and Xue, Q. , 1999, “ Study on the Structure and Tribological Properties of Surface-Modified Cu Nanoparticles,” Mater. Res. Bull., 34(9), pp. 1361–1367. [CrossRef]
Zhou, J. , Wu, Z. , Zhang, Z. , Liu, W. , and Dang, H. , 2001, “ Study on an Antiwear and Extreme Pressure Additive of Surface Coated LaF3 Nanoparticles in Liquid Paraffin,” Wear, 249(5–6), pp. 333–337. [CrossRef]
Zhang, B.-S. , Xu, B.-S. , Yi, X. , Gao, F. , Shi, P.-J. , and Wu, Y.-X. , 2011, “ CU Nanoparticles Effect on the Tribological Properties of Hydrosilicate Powders as Lubricant Additive for Steel–Steel Contacts,” Tribol. Int., 44(7–8), pp. 878–886. [CrossRef]
Tarasov, S. , Kolubaev, A. , Belyaev, S. , Lerner, M. , and Tepper, F. , 2002, “ Study of Friction Reduction by Nanocopper Additives to Motor Oil,” Wear, 252(1–2), pp. 63–69. [CrossRef]
Wu, Y. Y. , Tsui, W. C. , and Liu, T. C. , 2007, “ Experimental Analysis of Tribological Properties of Lubricating Oils With Nanoparticle Additives,” Wear, 262(7–8), pp. 819–825. [CrossRef]
Xiang, L. , Gao, C. , Wang, Y. , Pan, Z. , and Hu, D. , 2014, “ Tribological and Tribochemical Properties of Magnetite Nanoflakes as Additives in Oil Lubricants,” Particuology, 17, pp. 136–144. [CrossRef]
Padgurskas, J. , Rukuiza, R. , Prosyčevas, I. , and Kreivaitis, R. , 2013, “ Tribological Properties of Lubricant Additives of Fe, Cu and Co Nanoparticles,” Tribol. Int., 60, pp. 224–232. [CrossRef]
Mohamed, K. A. A. , Xianjun, H. , Mai, L. , Qingping, C. , Turksona, R. F. , and Bicheng, C. , 2016, “ Improving the Tribological Characteristics of Piston Ring Assembly in Automotive Engines Using Al2O3 and TiO2 Nanomaterials as Nano-Lubricant Additives,” Tribol. Int., 103, pp. 540–554. [CrossRef]
Kimura, Y. , Wakabayashi, T. , Okada, K. , Wada, T. , and Nishikawa, H. , 1999, “ Boron Nitride as a Lubricant Additive,” Wear, 232(2), pp. 199–206. [CrossRef]
Pawlak, Z. , Kaldonski, T. , Pai, R. , Bayraktar, E. , and Oloyede, A. , 2009, “ A Comparative Study on the Tribological Behaviour of Hexagonal Boron Nitride (H-BN) as Lubricating Micro-Particles—An Additive in Porous Sliding Bearings for a Car Clutch,” Wear, 267(5–8), pp. 1198–1202. [CrossRef]
Demas, N. G. , Timofeeva, E. V. , Routbort, J. L. , and Fenske, G. R. , 2012, “ Tribological Effects of BN and MoS2 Nanoparticles Added to Polyalphaolefin Oil in Piston Skirt/Cylinder Liner Tests,” Tribol. Lett., 47(1), pp. 91–102. [CrossRef]
Elisa, R. , and Brune, H. , 2003, “ Young Modulus Dependence of Nanoscopic Friction Coefficient in Hard Coatings,” Appl. Phys. Lett., 83(10), pp. 1986–1988. [CrossRef]
Yu, B. , Liu, Z. , Ma, C. , Sun, J. , Liu, W. , and Zhou, F. , 2015, “ Ionic Liquid Modified Multi-Walled Carbon Nanotubes as Lubricant Additive,” Tribol. Int., 81, pp. 38–42. [CrossRef]
Nunn, N. , Mahbooba, Z. , Ivanov, M. G. , Ivanov, D. M. , Brenner, D. W. , and Shenderova, O. , 2015, “ Tribological Properties of Polyalphaolefin Oil Modified With Nanocarbon Additives,” Diamond Relat. Mater., 54, pp. 97–102. [CrossRef]
Bhushan, B. , Gupta, B. K. , Van Cleef, G. W., Capp, C. , and Coe, J. V. , 1993, “ Fullerene (C60) Films for Solid Lubrication,” Tribol. Trans., 36(4), pp. 573–580. [CrossRef]
Bose, N. K. , and Liang, P. , 1996, Neural Network Fundamentals With Graphs, Algorithms and Applications, McGraw-Hill, Hightstown, NJ.
Datta, S. , 2016, Materials Design Using Computational Intelligence Techniques, CRC Press, Boca Raton, FL. [CrossRef]
Datta, S. , and Chattopadhyay, P. P. , 2013, “ Soft Computing Techniques in Advancement of Structural Metals,” Int. Mater. Rev., 58(8), pp. 475–504. [CrossRef]
Ray, M. , Ganguly, S. , Das, M. , Datta, S. , Bandyopadhyay, N. R. , and Hossain, S. M. , 2009, “ Artificial Neural Network (ANN)-Based Model for In Situ Prediction of Porosity of Nanostructured Porous Silicon,” Mater. Manuf. Process., 24(1), pp. 83–87. [CrossRef]
Xiao, G. , and Zhu, Z. , 2010, “ Friction Materials Development by Using DOE/RSM and Artificial Neural Network,” Tribol. Int., 43(1–2), pp. 218–227. [CrossRef]
Gyurova, L. A. , and Friedrich, K. , 2011, “ Artificial Neural Networks for Predicting Sliding Friction and Wear Properties of Polyphenylene Sulfide Composites,” Tribol. Int., 44(5), pp. 603–609. [CrossRef]
Jiang, Z. , Gyurova, L. , Zhang, Z. , Friedrich, K. , and Schlarb, A. K. , 2008, “ Neural Network Based Prediction on Mechanical and Wear Properties of Short Fibers Reinforced Polyamide Composites,” Mater. Des., 29(3), pp. 628–637. [CrossRef]
Shahabuddin, M. , Masjuki, H. H. , Kalan, M. A. , Bhuiya, M. M. K. , and Mehat, H. , 2013, “ Comparative Tribological Investigation of Bio-Lubricant Formulated From a Non-Edible Oil Source (Jatropha Oil),” Ind. Crops Prod., 47, pp. 323–330. [CrossRef]
Yan, Z. G. , 2000, Technical Manual for Lubricant Performance Testing, Petroleum Industry Press, Beijing, China.
Wen, S. Z. , and Huang, P. , 2008, Principles of Tribology, 3rd ed., Tsinghua University Press, Beijing, China.
Hernandez Battez, A. , Gonzalez, R. , Fergueroso, D. , Fernandez, J. E. , Fernandez Rocio del, M. , Garcia, M. A. , and Penuelas, I. , 2007, “ Wear Prevention Behavior of Nanoparticle Suspension Under Extreme Pressure Conditions,” Wear, 263(7–12), pp. 1568–1574. [CrossRef]
Dobson, G. R. , 1978, “ A Re-Examination of the Four Ball Test,” Tribol. Int., 11(1), pp. 59–62. [CrossRef]
Guhados, G. , Wan, W. , Sun, X. , and Hutter, J. L. , 2007, “ Simultaneous Measurement of Young's and Shear Moduli of Multiwalled Carbon Nanotubes Using Atomic Force Microscopy,” J. Appl. Phys., 101(3), p. 033514. [CrossRef]
Tsai, J. L. , and Tu, J. F. , 2010, “ Characterizing Mechanical Properties of Graphite Using Molecular Dynamics Simulation,” Mater. Des., 31(1), pp. 194–199. [CrossRef]
Kashyap, K. T. , and Patil, R. G. , 2008, “ On Young's Modulus of Multi-Walled Carbon Nanotubes,” Bull. Mater. Sci., 31(2), pp. 185–187. [CrossRef]
Kharissova, O. V. , and Kharisov, B. I. , 2014, “ Variations of Interlayer Spacing in Carbon Nanotubes,” RSC Adv., 4(58), p. 30807. [CrossRef]
Bhadeshia, H. K. D. H. , 1999, “ Neural Networks in Materials Science,” ISIJ Int., 99(10), pp. 966–979.
Bhadeshia, H. K. D. H. , 2009, “ Neural Networks and Information in Material Science,” Stat. Anal. Data Min.: ASA Data Sci. J., 1(5), pp. 296–305.
Olden, J. D. , Joy, M. K. , and Death, R. G. , 2004, “ An Accurate Comparison of Methods for Quantifying Variable Importance in Artificial Neural Networks Using Simulated Data,” Ecol. Model., 178(3–4), pp. 389–397. [CrossRef]
Ettefaghi, E. , Alimorad, R. , Ahmadi, H. , Mohtasebi, S. S. , and Pourkhalil, M. , 2013, “ Thermal and Rheological Properties of Oil-Based Nano Fluids From Different Carbon Nanostructures,” Int. Commun. Heat Mass Transfer, 48, pp. 178–182. [CrossRef]
Martin, J. M. , Matta, C. , Bouchet, M. , Forest, C. , Mogne, T. , Dubois, T. , and Mazarin, M. , 2013, “ Mechanism of Friction Reduction of Unsaturated Fatty Acids as Additives in Diesel Fuels,” Friction, 1(3), pp. 252–258. [CrossRef]
Ossia, C. V. , Han, H. G. , and Kong, H. , 2008, “ Response Surface Methodology for Eicosanoic Acid Triboproperties in Castor Oil,” Tribol. Int., 42(1), pp. 50–58. [CrossRef]
Reeves, C. J. , Menezes, P. L. , and Lovell, M. R. , 2015, “ The Influence of Surface Roughness and Particulate Size on the Tribological Performance of Bio-Based Multi-Functional Hybrid Lubricants,” Tribol. Int., 88, pp. 40–55. [CrossRef]
Bartz, W. Z. , 1971, “ Solid Lubricant Additives—Effect of Concentration and Other Additives on Anti-Wear Performance,” Wear, 17(5–6), pp. 421–432. [CrossRef]
Zhang, L. , Jibin, P. , Liping, W. , and Qunji, X. , 2014, “ Synergistic Effect of Hybrid Carbon Nanotube–Graphene Oxide as Nanoadditive Enhancing the Frictional Properties of Ionic Liquids in High Vacuum,” Carbon, 80, pp. 734–745. [CrossRef]
Cursaru, D. L. , Andronescu, C. , Pirvu, C. , and Ripeanu, R. , 2012, “ The Efficiency of Co-Based Single-Wall Carbon Nanotubes (SWNTs) as an AW/EP Additive for Mineral Base Oils,” Wear, 290–291, pp. 133–139. [CrossRef]
Zhang, W. , Zhou, M. , Hu, H. , Tian, Y. , Wang, K. , Wei, J. , Ji, F. , Li, X. , Li, Z. , Zhang, P. , and Wu, D. , 2011, “ Tribological Properties of Oleic Acid Modified Graphene as Lubricant Oil Additives,” J. Phys. D: Appl. Phys., 44(20), pp. 205–303.
Cornelio, J. A. C. , Cuervo, P. A. , Palacio, L. M. H. , Romero, J. L. , and Toro, A. , 2016, “ Tribological Properties of Carbon Nanotubes as Lubricant Additive in Oil and Water for a Wheel–Rail System,” J. Mater. Res. Technol., 5(1), pp. 68–76. [CrossRef]
Martin, J. M. , and Ohmae, N. , 2008, Nanolubricants: Carbon-Based Nanolubricants, Wiley, Chichester, UK.
Ni, B. , and Sinnott, S. B. , 2001, “ Tribological Properties of Carbon Nanotube Bundles Predicted From Atomistic Simulations,” Surf. Sci., 487(1–3), pp. 87–96. [CrossRef]
Lin, J. , Wang, L. , and Chen, G. , 2011, “ Modification of Graphene Platelets and Their Tribological Properties as a Lubricant Additive,” Tribol. Lett., 41(1), pp. 209–215. [CrossRef]
Berman, D. , Erdemir, A. , and Sumant, A. V. , 2013, “ Reduced Wear and Friction Enabled by Graphene Layers on Sliding Steel Surfaces in Dry Nitrogen,” Carbon, 59, pp. 167–175. [CrossRef]
Ni, W., Cheng, Y. T., Lukitsch, M. J., Weiner, A. M., and Lev, L. C., 2004, “ Effects of the Ratio of Hardness to Young's Modulus on the Friction and Wear Behavior of Bilayer Coatings,” Appl. Phys. Lett., 85(18), pp. 4028–4030. [CrossRef]
Bowden, F. P. , and Tabor, D. , 1950, Friction and Lubrication of Solids—Part I, Oxford University Press, New York.
Johnson, K. L. , 1987, Contact Mechanics, Cambridge University Press, Cambridge, UK.
Persson, B. N. J. , 2000, Sliding Friction: Physical Principles and Applications, 2nd ed., Springer, Berlin. [CrossRef]
Greenwood, J. A. , 1992, Fundamentals of Friction, Kluwer, Dordrecht, The Netherlands.
Delbé, K. , Mansot, J.-L. , Thomas, Ph. , Baranek, Ph. , Boucher, F. , Vangelisti, R. , and Billaud, D. , 2012, “ Contribution to the Understanding of Tribological Properties of Graphite Intercalation Compounds With Metal Chloride,” Tribol. Lett., 47(3), pp. 367–379. [CrossRef]
Gupta, B. , Kumar, N. , Panda, K. , Melvin, A. A. , Joshi, S. , Dash, S. , and Tyagi, A. K. , 2016, “ An Effective Noncovalent Functionalization of Poly(Ethylene Glycol) to Reduced Graphene Oxide Nanosheets Through γ-Radiolysis for Enhanced Lubrication,” J. Phys. Chem. C, 120(4), pp. 2139–2148. [CrossRef]
Fall, A. , Weber, B. , Pakpour, M. , Lenoir, N. , Shahidzadeh, N. , Fiscina, J. , Wagner, C. , and Bonn, D. , 2014, “ Sliding Friction on Wet and Dry Sand,” Phys. Rev. Lett., 112(17), p. 175502. [CrossRef] [PubMed]
Restuccia, P. , and Clelia Righi, M. , 2016, “ Tribochemistry of Graphene on Iron and Its Possible Role in Lubrication of Steel,” Carbon, 106, pp. 118–124. [CrossRef]


Grahic Jump Location
Fig. 2

Schematic diagram of four-ball test rig

Grahic Jump Location
Fig. 1

Scanning electron microscope images of (a) graphite microparticles, (b) multiwall carbon nanotubes, and (c) graphene

Grahic Jump Location
Fig. 3

Schematic diagram of perceptron type ANN used in this work

Grahic Jump Location
Fig. 4

Coefficient of friction for various oil samples

Grahic Jump Location
Fig. 5

Variation of (a) coefficient of friction, (b) scar diameter versus contact pressure, and (c) scar diameter with FTP for CMO, NCO, and optimum FM concentrations

Grahic Jump Location
Fig. 6

Three-dimensional images of wear scar on balls before and after the tests: (a) untested ball, (b) CMO, (c) NCO, (d) NCO + 2 wt. % graphite, (e) NCO + 1 wt. % MWCNT, and (f) NCO + 0.5 wt. % graphene

Grahic Jump Location
Fig. 11

SEM images of wear of (a) and (b) graphite-based NCO, (c) and (d) MWCNT-based NCO, and (e) and (f) graphene-based NCO samples

Grahic Jump Location
Fig. 12

EDS spectrum of (a) CMO, (b) NCO, (c) NCO + 2.0 wt. % graphite, (d) NCO + 1.0 wt. % MWCNT, and (e) NCO + 0.5 wt. % graphene

Grahic Jump Location
Fig. 7

Optical microscope images for surfaces of balls at LNSL: (a) and (b) CMO, (c) and (d) NCO, (e) and (f) NCO + 2 wt. % graphite, (g) and (h) NCO + 1 wt. % MWCNT, and (i) and (j) NCO + 0.5 wt. % graphene

Grahic Jump Location
Fig. 8

Optical microscope images for surfaces of balls at ISL: (a) and (b) CMO, (c) and (d) NCO, (e) and (f) NCO + 2 wt. % graphite, (g) and (h) NCO + 1 wt. % MWCNT, and (i) and (j) NCO + 0.5 wt. % graphene

Grahic Jump Location
Fig. 9

Wear scar diameter versus load curve for (a) CMO, (b) NCO, (c) NCO + 2.0 wt. % graphite, (d) NCO + 1.0 wt. % MWCNT, (e) NCO + 0.5 wt. % graphene, and (f) LNSL, ISL, and WL of oil samples

Grahic Jump Location
Fig. 10

(a) LNSL and (b) ISL versus wear scar diameter for different oil samples

Grahic Jump Location
Fig. 13

Scatter plot showing the predictivity and sensitivity analysis of the ANN model

Grahic Jump Location
Fig. 14

Surface views showing the combined effects of (a) E and FMC, (b) SA and FMC, (c) G and SA, and (d) E and ILS on CoF as predicted by the ANN model



Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In