WO2014088409A2

WO2014088409A2 - A nano liquid lubrication composition and its preparation method

Info

Publication number: WO2014088409A2
Application number: PCT/MY2014/000003
Authority: WO
Inventors: Aly Diaa Mohammed Sarhan Ahmed; Sayuti Bin Ab Karim Mohd; Hamdi Abd Shukor Mohd
Original assignee: University Malaya
Priority date: 2012-12-04
Filing date: 2014-01-08
Publication date: 2014-06-12
Also published as: MY166526A; WO2014088409A3

Abstract

A lubricating composition comprises a liquid lubricant oil and silica of nano-size dispersed homogeneously within the lubricant oil.

Description

A NANO LIQUID LUBRICATION COMPOSITION AND ITS PREPARATION

METHOD

Field Of Invention

The present invention relates to a liquid lubricant with improved properties for reducing energy consumption in machining process. More specifically, the disclosed composition contains nano-particles of silica to carry out the improved lubricating function in metal cutting operation. Background Of The Invention

Considering rapid depletion of fossil energy and the looming energy crisis, moving current society towards a more sustainable model has been a constant topic in recent years. Significant efforts have been put into research for developing the energy sustainable society especially aiming to discover new renewable energy source and better approach in harvesting such energy. Apart from that, energy sustenance can be improved as well through consuming available energy in a much efficient practice. Owing to the fact that industry is the major user of energy which accounts for roughly 40% of total energy use in present society, improving various industrial activities particularly in the field of machining and metal cutting can result in saving of considerable amount of energy. It is known friction between the rake face of a tool and the working surface determines the ease of the metal cutting process and, thus, the energy used thereof. In machining or metal cutting operation, existence of clean surfaces and high hydrostatic stresses favors the formation of strong adhesive friction junctions that influence of such factors can be greatly reduced by the provision of a suitable lubricant. Although the significance of lubrication in machine is widely recognized, the usage of conventional approach flooding the working surfaces with lubricant is far from efficient. Not only is the used lubricant considered as hazardous waste, but the excessive amount of lubricant applies in the flooding method incurs unnecessary cost to the process too. Hence, many efforts are being undertaken to develop advanced machining processes aiming to reduce the use of lubrications that it advances into application named as minimum quality lubrication (MQL). Besides developing machining process demanding less power and less lubrication, attention has been given to produce improved lubricant which capable of decreasing further the friction generated in the machining process. For example United States patent publication no. 20060247139 describes a method to apply supercritical carbon dioxide to the workpiece to carry out lubrication thereof. Moreover, commercial available nano-particles are resorted to develop new formulation of lubricant as well. Specifically, both United States patent publication no. 20100204072 and 201 10046027 disclose lubricant containing nano-particles of graphite. The former employs exfoliated graphite nanoparticles while the later mixes nano grapheme platelets into a fluid to acquire the lubricant.

Summary Of The Invention

The present invention aims to offer a liquid lubricant suitable to be used in machining and/or cutting processes. Particularly, the mentioned lubricant contains nano-particles to improve its lubricating property.

Another object of the present invention is to provide a liquid lubricant containing homogeneously suspended nano-particles of silica that the homogeneous mixture is attained through sonification. Silica (Si0₂), being hard and brittle material, is ideal to be incorporated into conventional liquid lubricant oil to significantly improve lubricating property of the lubricant composition.

Further object of the present invention is to offer a method of preparing the liquid lubricant preferably subjecting the mixture to sonification to achieve a homogeneously mixed composition.

At least one of the preceding objects is met, in whole or in part, by the present invention, in which one of the embodiments of the present invention involves a lubricating composition comprising a liquid lubricant oil and silica of nano-size dispersed homogeneously within the lubricant oil. Preferably, surfactants maybe used in another embodiment to facilitate suspension of the dispersed nanoparticles. In another aspect, the silica is in an amount of 0.05 to 5 by weight percentage of the total composition. More preferably, the amount is 0.1 to 0.5 by weight percentage of total composition. In another aspect, the silica added into the liquid lubricant oil is in amorphous form having particles size ranged from 3 to 50nm.

Further embodiment of the disclosed invention is a method of preparing lubricating composition comprising the step of dispersing silica of nano-size in a liquid lubricant oil through sonification, wherein the silica is in an amount of 0.05 to 5 by weight percentage of the total composition. Preferably, the silica is in amorphous form having particles size ranged

Further object of the present invention is, nano base lubrication system is applied in metal cutting operation such as milling and turning to improve the machining performance in term of surface quality, prolong the tool wear, reduce power consumption and less environmental issues.

Brief Description Of The Drawings

Figure 1 is a schematic diagram showing establishment of the apparatus used to test the disclosed lubricating composition;

Figure 2 illustrates the workpiece and tool path in the performed experiments; Figure 3 is a schematic diagram showing one embodiment of the nozzle can be employed to deposit the disclosed composition;

Figure 4 is a graph showing measured surface roughness at 5,000 min^" cutting speed,

100 mm/min feed and 5 mm depth of cut, nanoparticle concentration: 0.2wt%, air pressure: 1 bar and nozzle angle 30°; Figure 5 provides graphs showing TPM and S/N response graphs of cutting force at different control factors (a) nanoparticles suspended concentration, (b) air pressure and (c) nozzle orientation; Figure 6 provides graphs showing TPM and S/N response graphs of cutting temperature at different control factors (a) nanoparticles suspended concentration, (b) air pressure and (c) nozzle orientation; Figure 7 provides graphs showing TPM and S/N response graphs of surface roughness at different control factors (a) nanoparticles suspended concentration, (b) air pressure and (c) nozzle orientation;

Figure 8 provides FESEM on sample (a), (b), (c) and (d) which machined with 0, 0.2,

0.5 and 1.0 wt% of Si0₂ concentration respectively;

Figure 9 provides Energy Dispersive X-Ray Spectroscopy (EDX) on sample (a), (b), (c) and (d) which machined with 0, 0.2, 0.5, 1.0 wt% of Si0₂ concentration respectively; Figure 10 provides surface elemental mapping of sample machined with different Si0₂ nanoparticle concentration (a) 0.2 wt%, (b) 0.5 wt% and (c) 1.0 wt%; and

Figure 11 shows elemental mapping and EDX spectroscopy on machined surface at

8mm depth of cut, 5000 min^"1 cutting speed and lOOmm min feed rate.

Detailed Description Of The Invention

One skilled in the art will readily appreciate that the present invention is well adapted to carry out the objects and obtain the ends and advantages mentioned, as well as those inherent therein. The embodiment describes herein is not intended as limitations on the scope of the invention. The present invention discloses a lubricating composition comprising a liquid lubricant oil and silica of nano-size dispersed homogeneously within the lubricant oil. It is important to be noted herein that any types of oil of either natural or synthetic origin can be used in the disclosed composition. Preferably, the liquid lubricating oil is a fraction of refined mineral oil which likely contains complex mixture of hydrocarbons. The mineral oil can be solvent refined mineral oil, hydrocracked mineral oil, polyalphaolefins, napthenic oil, paraffin oil and the like. While the synthetic lubricant oil can be polybutylenes, polypropylene, chlorinated polybutylenes, polydecenes, dodecybenzenes, tetradecylbenzenes, biphenyl, terphenyl, alkylated polyphenyls or any mixture derived thereof. Apart from that, ester acquired from reaction in between C₅ to Q₂ monocarboxylic acids and polyols can be used as well in the disclosed invention as the liquid lubricating oil; for example neopentyl glycol, trimethylolpropane, pentaerythritol, dipentaerythritol and the like. Ester of dicarboxylic acids may be used to constitute the liquid lubricating oil in other embodiments of the present invention.

As in the foregoing, the silica nano-particles are suspended homogeneously inside the liquid lubricating oil in order to serve best as lubricants. Lubricating properties of the disclosed composition can be negatively affected in the presence of agglomeration or sedimentation of the dispersed silica. Consequently, the disclosed lubricating composition may further comprise surfactants and/or emulsifier to prevent silica nanoparticles agglomeration or sedimentation to prolong both shelf life and service life of the disclosed composition Preferably, the surfactants can be anionic, cationic, nonionic, zwitterionic, amphoteric and ampho lytic. The amount of surfactant used may range from 0.1 to 15 by weight percentage of total composition.

Moreover, it was found by the inventors of the present invention that silica nanoparticles suspended in the liquid lubricant oil function as rolling elements in the tool chip interface during cutting or machining process to reduce direct contact in between the tool and the working surface. Particularly, silica nanoparticles used in the present invention show good mechanical properties in term of hardness. Vickers hardness test shows silica possesses hardness around lOOkgf/mm. In the presence of disclosed lubricant composition including billions of silica nanoparticles, tool life can be extended and less energy is employed due to less friction generated thereof. According to the preferred embodiment, the silica is in an amount of 0.05 to 5 by weight percentage of the total composition. More preferably, the silica amount ranges from 0.1 to 0.5 by weight percentage of total composition to attain optimal performance. Further, the silica nanoparticles employed in preparing the disclosed composition is in amorphous form with particle size ranged from 3 to 50nm, more preferably 5 to 15nm.

Owing to the liquefied property of the lubricant oil used, the silica nanoparticles used in the present invention can be effectively suspended or dispersed homogeneously through sonification besides conventional mixing the silica nanoparticles physically into the lubricant oil. Sonification not only facilitates homogeneous mixture of the silica nanoparticles and lubricant oil, the applied sound wave also smashes agglomerated silica nanoparticles into smaller fractions to optimize performance of the disclosed composition. It is preferable to subject the mixture of silica nanoparticles and liquid lubricant oil for sonification for a duration of 2 to 100 hours depending upon the volume of the composition prepared.

Preferably, the disclosed invention is suitable to be used in different applications to reduce friction in between two metal surfaces. Typically, the nano-sized particles of silica also allow the disclosed composition to be used in MQL system for milling process.

Pursuant to another preferred embodiment, the present invention involves a method of preparing lubricating composition comprising the step of dispersing silica of nano-size in liquid lubricant oil through sonification, wherein the silica is in an amount of 0.05 to 5 by weight percentage of the total composition. As in the setting forth, the liquid lubricating oil can be a fraction of refined mineral oil such as solvent refined mineral oil, hydrocracked mineral oil, polyalphaolefins, napthenic oil, paraffin oil and the like. In other embodiment, synthetic lubricant oil such aspolybutylenes, polypropylene, chlorinated polybutylenes, polydecenes, dodecybenzenes, tetradecylbenzenes, biphenyl, terphenyl, alkylated polyphenyls or any mixture derived thereof can be used as well. Further, the lubricant oil can be derived from ester acquired from reaction in between C5 to Ci₂ monocarboxylic acids and polyolsor ester of dicarboxylic acids may be used to constitute the liquid lubricating oil in other embodiments of the present invention.

Having the lubricant oil used as the continuous phase, the disclosed method facilitates dispersion of the solid phase through sonification. With the aid of sonification, the solid silica nanoparticles can be easily mixed and dispersed homogeneously within the continuous phase of the liquid lubricant oil while agglomeration of the solid nanoparticles is avoided in the presence of the smashing sound wave produced in the sonification. In another embodiment, the silica used in the disclosed method is in amorphous form with particles size ranged from 3 to 50nm, more preferably 5 to 15nm.

Example 1

The standardized Taguchi based experiment design Lj₆(4³) orthogonal array is used to optimize the machining parameters to minimize cutting force, cutting temperature and surface roughness. The standard orthogonal array consists of sixteen experiments with three control factors and four different experimental condition levels for each factor. The factors and levels as per mentioned are specified in Table 1. The sixteen experiments with the details of combination of the experimental condition levels for each control factor (A-C) are shown in Table 2. The 16 experiments were carried out in a random sequence to eliminate any other invisible factors, which might also contribute to the cutting force, cutting temperature and surface roughness.

Table 1 : Control factors and experimental condition levels

Table 2: Standard Li₆(4)³ Orthogonal array, the sixteen experiments with detail of the combination levels

The most important stage in the design of experiment is the selection of control factors and identifying the orthogonal array (OA) then running the experiment based on that particular OA. To identify the non-significant variables, maximum possible factors should be included in the experiment.

After the orthogonal array has been selected, the second step in the Taguchi optimization method is to run the experiments based on that particular OA. The experiments are conducted using the experimental set-up shown in Fig. 1. The machine used was a milling vertical type- machining center (Mitsui Seiki VT3A). The spindle has constant position preload bearings with oil-air lubrication while maximum rotational speed and power are 20,000 min^"1 and 15 kW, respectively. To investigate the cutting forces during the cutting process, the slot-milling test was carried out on a cutting process of a rectangular workpiece of Aluminum AL6061-T6 prepared in 50 x 50 x 200 mm³ using the proposed experimental set-up. The mechanical properties of aluminium (AL6061-T6) are shown in Table 3.

Table 3: Mechanical properties of Aluminum (AL6061-T6)

The cutting tool used is high speed steel (HSS) with 2 flute and 10 mm diameter to represent the most common tool selection in milling industry suitable for slot milling process. The tool moves in +X direction to cut a stroke of 200 mm. Figure 2 shows the workpiece and its tool paths. The cutting speed, feed and depth of cut used are 5,000 min^"1, 100 mm/min and 5 mm, respectively and it have been selected based on the tool manufacturer's recommendations. The cutting forces were measured using a Kistler three-axis dynamometer (type 9255B). The measured cutting force signals (X, Y, and Z direction) were captured and filtered with low path filters (10 Hz cut off frequency) while, the cutting temperature is measured by using the thermocouple (K-Type Testo 925 Thermocouple), and each test measurement was repeated three times in order to reduce abrupt readings error. The thermocouple has been installed under the machining surface as can be seen in Fig. 1 and its specification is shown in Table 4. The measured temperature reflects the amount of heat dissipated in the workpiece. This amount of heat should indicate the change of the coefficient of friction between tool and chip in cutting zone. For every machining run, the temperature has been measured at every two minutes while the machined surface roughness has been measured using surface profilometer (MarSurf PS1 Perthometer).

Table 4: -Type Testo 925 Thermocou le s ecification

Example 2

The two different types of lubrication modes used are ordinary lubricant oil and nano lubrication system. The ECOCUT SSN 322 neat lubricant oil type with 40.2 cSt at 40°C from FUCHS was used in the both modes of lubrications. This oil is free from phenol, chlorine and other additive. The nanoparticle-oil is prepared by adding Si0₂ nanoparticles with an average size of 5-15 nm to the mineral oil followed by sonification (240 W, 40 kHz, 500 W) for 48 hours in order to suspend the particle homogeneously in the mixture. The mechanical properties of Si0₂ are presented in Table 5.

Table 5: Mechanical properties of Si0₂

Properties Si0₂

Structure Amorphous

Melting Point (deg C) Approx. 1600

Density (g/cm3) 2.2

Refractive Index 1.46

Dielectric Constant 3.9

Dielectric Strength 10'

Thermal conductivity at 300K (W/cm-deg K) 0.014 To deliver the oil to the tool chip interface area, the MQL system is used. The experimentation is carried out using a thin-pulsed jet nozzle that is developed in laboratory and controlled by a variable speed control drive. In case of using nanoparticle suspended lubrication system, the nozzle has been equipped with additional air nozzle to accelerate the lubricant into the cutting zone and to reduce the oil consumption up to 25%. The nozzle system is attached to a flexible portable fixture fixed on the machining spindle. The flexible design allows the injection nozzle to be located at any desired position without interfering with the tool or workpiece during the machining process. The diameter of the nozzle orifices is 1 mm and the MQL oil pressure is set to be 20 MPa with delivery rate of 2 ml/min. Figure 3 is presenting the schematic drawing of the nozzle.

The slot-milling test is carried out to investigate the machining performance by using the proposed experimental set-up. Table 6 shows the measured values of cutting force, cutting temperature and surface roughness. Figure 4 shows an example of the measured surface roughness in X, Y and Z-axis direction at nanoparticle concentration: 0.2 wt%, air pressure: 1 bar, nozzle angle 30°.

Example 3

The methods for calculating the S/N ratio are classified into three main categories, depending on whether the desired quality characteristics are smaller the better, larger the better or nominal the better. In the case of cutting force, cutting temperature and surface roughness, the smaller values are always preferred. The equation for calculating the S/N ratio for smaller the better characteristics (in dB) is as follows:

Where (j) is the test number from 1 to 16 and >, is the individual measured cutting force, cutting temperature and surface roughness in first, second and third column in Table 6 and n is the number of the individual measured response, in this case n = 3. The S/N values function shown in equation ( 1) is a performance measurement parameter to develop processes insensitive to noise factors. The degree of predictable performance of a process in the presence of noise factors could be defined from S/N ratios in which, for each factor, the 12 higher the S/N ratio the better the result. The calculated S/N ratio and TPM values are summarized in Table 7, where TPM is the target performance measurement, which is equal to the average of the measured cutting forces, cutting temperature and surface roughness at the same level of input parameters (i) in Table 6.

Table 6: The measured values of cutting force, cutting temperature and surface roughness

Table 7: The calculated (S/N) ratio and TPM values.

Calculated TPM Values Calculated S/N Ratio (dB)

Test Cutting Cutting Surface

Cutting Cutting Surface

Levels Force Temperature Roughness

CO Force Temperature Roughness

(N) (Ra)

1 134.16 57.20 3.14 -42.55 -35.15 -9.94

2 197.91 71.20 0.75 -45.93 -37.05 2.48

3 130.78 56.10 1.42 -42.33 -34.98 -3.02

4 184.43 48.80 1.53 -45.32 -33.77 -3.67

5 53.81 43.50 0.74 -34.62 -32.77 2.64

6 150.31 53.50 1.62 -43.54 -34.57 -4.17

7 161.99 73.10 0.88 -44.19 -37.28 1.10

8 157.63 69.70 1.34 -43.95 -36.86 -2.54

9 171.81 67.80 1.07 -44.70 -36.62 -0.60

10 107.70 61.50 0.93 -40.64 -35.78 0.64

11 121.92 51.30 0.80 -41.72 -34.20 1.97

12 188.04 65.00 1.58 -45.49 -36.26 -3.97

13 11 1.43 58.10 0.75 -40.94 -35.28 2.50

14 145.66 56.90 0.68 -43.27 -35.10 3.38

15 186.76 65.50 0.34 -45.43 -36.32 9.47

16 177.31 68.20 0.74 -44.97 -36.68 2.57 Furthermore, the TPM and S/N response data are calculated and summarized in Tables 8 and 9 for cutting force, Tables 10 and 11 for cutting temperature and Table 12 and 13 for surface roughness. As for an example of TPM and S N response calculation, A, is the average of all TPM and S/N values corresponding to the same level of input parameter (z) under A in Table 7. In this case, (/) is equal to 1, 2, 3, or 4. The difference under A, column is equal to the maximum minus the minimum of the S/N or TPM response values. Similarly, the S/N, TPM response values and the differences are calculated for Bi and . The rank is given in order from the highest to the lowest difference values. The significance of each factor is determined based on the value of the difference of both S/N and TPM. The desired "smaller the better" criteria implies that the lowest cutting force, cutting temperature and surface roughness for TPM would be the ideal result, while the largest S/N response would reflect the best response which results in the lowest noise. This is the criteria employed in this study to determine the optimal machining parameters. The S/N and TPM response graphs for selecting the best combination levels for minimum cutting force, cutting temperature and surface roughness are shown in Figs. 5 (a), (b) and (c), Figs. 6 (a), (b) and (c) and Figs. 7 (a), (b) and (c), respectively.

Table 8: The TPM response data for cutting force

Table 9: The S/N response data for cutting force

Level of input S/N Response (dB)

parameters (/) A, B, c,

Level 1 -44.03 -40.70 ^3.20

Level 2 -41.57 ^3.35 -42.86

Level 3 -43.14 ^3.42 -43.56

Level 4 -43.65 -44.93 -42.77

Difference 2.46 4.23 0.79

Rank 2 1 3 From Figs. 5 (a), (b) and (c) and based upon the criteria of smaller TPM and larger S/N ratio, the air pressure (Bl, 1 bar), with the nanoparticle concentration (A2, 0.2 wt %) and highest nozzle angle (C4, 60°), are determined to be the best choices for obtaining the lowest cutting force. While, from Figs. 6 (a), (b) and (c), the air pressure (Bl, 1 bar), with the nanoparticle concentration (Al, 0 wt %) and smallest nozzle angle (CI, 15°), are determined to be the best choices for obtaining the lowest cutting temperature. However and based upon the same TPM and S/N criteria, Figs. 7 (a), (b) and (c), suggests that the highest nanoparticle concentration (A4, 1.0 wt %), with the nozzle angle (C2, 30°) and air pressure (B3, 3 bar), are determined to be the best choices for obtaining the lowest surface roughness. In conclusion, the optimal parameters combination for lower cutting force, lower cutting temperature and lower surface roughness are set as A2 Bl C4, Al Bl CI and A4 B3 C2, respectively.

Example 4

The analysis of variance using Pareto ANOVA is an alternative method to analyze the data for the optimization process. Pareto ANOVA for cutting force, cutting temperature and surface roughness is constructed using the S/N response data respectively. The summation of squares of differences (S) for each control factor is calculated such that, for example, S_A can be obtained by the following equation:

S_A = (A_l - A₂ ) ² + (A_l - A, )² + (A₂ - A₃ )² + (A₃ - A₄ )² ₍₂)

Similarly, S_B, and Sc are calculated. The contribution ratio for each factor is calculated as the percentage of summation of squares of differences for each factor to the total summation of the squares of differences. A Pareto diagram is plotted using the contribution ratio, and the cumulative contribution. The significant factors are chosen from the left-hand side of the Pareto diagram. It can be seen that the best levels of factor combination for minimum cutting force are found to be; The air pressure (B) 70.44 %, the nanoparticle concentration (A) 26.62 % and finally the nozzle angle (C) 2.94 %. The air pressure and nanoparticle concentration are considered prominent factors, having a cumulative contribution of 95.07 %. The Pareto ANOVA analysis recommends that A2 B 1 C4 is the best parameters combination to obtain the smallest cutting force. Whereas in Table 15, the best levels of factor combination for minimum cutting temperature are; the air pressure (B) 48.44 %, the nanoparticle concentration (A) 27.52% and finally the nozzle angle (C) 24.04 %. In this case all parameters (air pressure, nanoparticle concentration and nozzle angle) are considered as prominent factors, having a cumulative contribution of 100%. The Pareto ANOVA analysis recommends that Al Bl CI is the best parameters combination to obtain the smallest cutting temperature. Finally from Table 16, the best levels of factor combination for minimum surface roughness are found to be: the nanoparticle concentration (A) 57.47 %, the nozzle angle (C) 22.83 %, and finally the air pressure (B) 19.70 %. In this case also all parameters (air pressure, nanoparticle concentration and nozzle angle) are considered as prominent factors, having a cumulative contribution of 100%. The Pareto ANOVA analysis recommends that A4 B3 C2 is the best parameters combination to obtain the smallest surface roughness. In conclusion, the optimal parameters combination for lower cutting force, lower cutting temperature and lower surface roughness obtained using Pareto ANOVA analysis are set as A2 Bl C4, Al Bl CI and A4 B3 C2, respectively. It should be noted that these results are found to be similar to the others obtained using the S/N and TPM analysis.

In this study, two techniques of data analysis have been used and both techniques deliver similar results. Extensive dispersed of Si0₂ nanoparticles in cutting oil facilitate by high pressure stream air in cutting zone shows a good performance in reducing resultant cutting force, temperature and surface roughness. After the optimal levels of all control factors are identified, the last step in the Taguchi optimization method is to conduct a verification test using these optimal parameters combination; A2 Bl C4 for cutting force, Al Bl CI for cutting temperature and A4 B3 C2 for surface roughness to validate the recommendation. This test is repeated sixteen times and the average TPM values of the measured cutting forces, cutting temperature and surface roughness are calculated. The result shows an improvement of 25.02%, 29.34% and 26.28% in cutting force, cutting temperature and surface roughness, respectively, compared to the values obtained from experiments shown in Table 6.

Example 5

For further investigation on machining performance using nanolubrication, the Field Emission Scanning Electron Microscopy (FESEM) and Energy Dispersive X-ray (EDX) were utilized to examine the machined surface morphology. At the beginning, substrate cleaning was required to remove all unwanted surface contamination. Substrate surface finish was achieved by etching in hot solutions of sodium hydroxide to remove minor surface imperfections. To remove surface oxides, which are a combination of inter metallic, metal and metal oxides remaining on the surface after cleaning/etching, an aqueous solution containing an oxidizing inorganic acid, phosphoric and sulfuric acids, simple and complex fluoride ions, organic carboxylic acid, and manganese in its oxidation state was used. The formation and growth of the protective Si0₂ thin film on the machined surface and metal migration during machining were examined through surface elemental mapping analysis.

Figure 8 shows the FESEM image of machined surfaces produced at four different Si0₂ concentrations of 0, 0.2, 0.5 and 1.0wt%. Clearly, many protective thin films were produced on the feed marks of the machined surface containing billions of Si0₂ nanoparticles which provide much less friction and thermal deformation, as shown in Figures 8 (b), (c) and (d). These regular thin film formations grew when the Si0₂ concentration was increased from 0.2%wt to 1.0%wt. It was also observed in the surface layer that small exfoliations, or shedding of the thin film occurred, as is illustrated by Fig. 8 (d). This could be explained by the fact that the increment of nano-oil concentration increases the viscosity of cutting oil. In this case, more nanoparticles exist between the tool-workpiece interface and these nanoparticles will serve as spacers, which eliminate the tool-workpiece contact friction. Moreover, due to the porous nature of spherical Si0₂ nanoparticles, it could impart high elasticity, which augments their resilience in a specific loading range and enhances the gap at the tool-workpiece interface. Therefore, with the extreme pressure of additives in cutting oil and the existence of a gap between tool and workpiece, there is a high contact resistance which induces the formation of film on the workpiece surface through chemical reaction. In addition, the generation of high heat in the cutting zone will change elastohydrodynamic lubrication to boundary lubrication. This results in the formation of thin protective films on the surfaces, as per Figure 8. The increment of nano-oil concentration increases the growth of thin protective film on machined surfaces due to the breaking process. In other words, during machining the high number of nanoparticles rubs with the asperities at the workpiece surface and, thus, the newly created surface is exposed to cutting oil more frequently. In this way, strong chemical interaction is formed between nano-oil and newly created surface and, therefore, a more intensive protective film is formed. This process definitely increases the quality of the machined surface, successfully enhancing the surface properties and reducing its coefficient of friction.

For additional investigation, the substrate surface was analyzed by using Energy Dispersive X-ray (EDX) as shown in Fig. 9 and the results of the elemental composition are summarized in Table 17. As seen in Fig. 9 and Table 17, the contents of Oxygen (O) and Silicon (Si) in the substrate surface increases with increasing Si0₂ concentrations. However, when the Si0₂ concentration is in the range between 0.5 and 1.0wt%, the content of these elements becomes stable. In addition, the Iron (Fe) and Carbon (C), which originated from the cutting tool, were observed when the Si0₂ concentration was more than 0.5wt%.

Surface elemental mapping was employed to investigate the relation between the machined surface quality and the orientation and distribution of Si0₂ nanoparticles on the machined surface. Elemental mapping of samples machined with 0.2, 0.5 and lwt% are shown in Fig. 10(a), (b) and (c), respectively. Figure 10 (a) shows that at 0.2wt% Si0₂ nanoparticles, the polishing track orientation matched the Si0₂ nanoparticle distribution on the machined surface, especially at the exfoliated thin film. By using 0.5wt% Si0₂ nanoparticles, higher amounts of Si0₂ nanoparticles were present compared to the case of using 0.2wt%, as shown in Fig. 10 (b). With 0.5wt% Si0₂ nanoparticles the track of embedded nanoparticles on the machined surface was clearly seen. Eventually the nanoparticles could be ploughed off but left debris nanoparticles behind. When the Si0₂ nanoparticle concentration was increased up to 1.0wt% as illustrated in Fig. 10 (c), higher amounts of Si0₂ nanoparticles were embedded on the machined surface compared to the cases of 0.2 and 0.5wt%. It was clearly seen that the nanoparticles were burnished on the porous alumina. Several Si0₂ nanoparticles were partially embedded into the surface and some showed the tracks from being ploughed off, and more nanoparticle debris was left on it. Following the results of elemental mapping shown in Fig. 1 1 (a), (b) and (c), the mechanism of nanoparticles was found to assist the cutting operation and can be categorized into the three levels. At the first level, the particles were partially embedded on the machined surface when they collided with its asperities due to extremely high pressure in the cutting zone; the particles were sheared and changed shape because of compression. The sheared off debris continues to assist the cutting, but not as well as spherical nanoparticles which exercise rolling with a low coefficient of friction. At the second level, with a higher concentration of nanoparticles, the partially embedded particles were ploughed off by new nanoparticles, and both then continued to polish the surface. The ploughed off particles left a thin exfoliated film on the contact area due to the damage from high loading. Meanwhile, when nanoparticle concentrations continued to increase, those nanoparticles were impregnated into the pore of the surface and were then sheared by other incoming nanoparticles. The rolling of nanoparticles leads to the formation of an easily sheared lubrication film as well as the asperities on the surface, thus the surface is being polished and enhanced in quality. Therefore, as shown in the results, the 1.0wt% concentration provided the best machined surface morphology compared to other concentrations.

Example 6

To investigate material migration during machining at more extreme conditions, the depth of cut was increased to 8mm while using 0.2wt% nanoparticle concentration. Element mapping on machined surfaces is shown in Fig. 12. This demonstrates intermetallic formations on the machined surface which contained iron (Fe), carbon (C) and copper (Cu) atoms which originated from the HSS M35 cutting tool. Similar observations can be seen in the EDX result shown in Fig. 9. Since aluminum alloys exhibit high adhesive characteristics, the transfer of material between the tool-workpiece interfaces could be easily promoted. The improper feeding of nano-oil in the cutting zone causes the nano-oil to assist the unsuccessful cutting operation, which leads to an increase in cutting temperature and enhances the presence of the adhered layer between tool flank and work surface. This also indicates a high abrasion force between the tool tip and work surface. Therefore, Fe and C were smeared on the surface of the aluminium, since aluminium alloy consisted of Mg-Si-0 element and Fe- Cu adheres only to the areas where Mg-Si-0 binder is exposed. It can also be clearly seen from the elemental mapping that Fe-Cu adheres only to the areas where Mg-Si-0 exists. This material transfer is related to the conditions of high stress and high local temperature developed during machining. Upon inter-diffusion reaction between the tool and workpiece, it tends to form intermetallic particles on the workpiece surface. All these intermetallic particles have a melting point much higher than pure aluminium alloy, then it further tends to form a built-up layer with the existence of thermal-mechanical mechanisms. In consequence, there might be a possibility of forming a built-up layer of aluminium on the cutting tool tip, since HSS M35 consisted of 5% Co binder. However, it can be detrimental to the quality of the machined surface. Meanwhile, Si0₂ hardness is greater than other intermetallic particles formed on the aluminium surface. Thus, the impact of Si0₂ particles encountered on intermetallic particles would increase the cutting force. This would explain the reason why improper feeding of nano-oil would cause the negative effect on the cutting operation.

The present disclosure includes as contained in the appended claims, as well as that of the foregoing description. Although this invention has been described in its preferred form with a degree of particularity, it is understood that the present disclosure of the preferred form has been made only by way of example and that numerous changes in the details of construction and the combination and arrangements of parts may be resorted to without departing from the scope of the invention.

Claims

1. A lubricating composition comprising a liquid lubricant oil and silica of nano-size dispersed homogeneously within the lubricant oil.

2. A lubricating composition of claim 1 further comprising surfactants.

3. A lubricating composition of claim 1 or 2, wherein the silica is in an amount of 0.05 to 5 by weight percentage of the total composition.

4. A lubricating composition of claim 1 or 2, wherein the silica is in amorphous form.

5. A lubricating composition of claim 1 or 2, wherein the silica is dispersed homogeneously within the liquid lubricant oil through sonification.

6. A lubricating composition of claim 1 or 2, wherein the silica has particles size ranged from 3 to 50nm.

7. A method of preparing lubricating composition comprising the step of dispersing silica of nano-size in a liquid lubricant oil through sonification, wherein the silica is in an amount of 0.05 to 5 by weight percentage of the total composition.

8. A method of claim 7, wherein the silica is in amorphous form.

9. A method of claim 7, wherein the silica has particles size ranged from 3 to 50nm.