A comparative study for surface texture evaluation of TiAlN coatings

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ScienceDirect Materials Today: Proceedings 3 (2016) 2766–2771 www.elsevier.com/locate/procedia

6th International conference on Advanced Nano Materials Title

A comparative study for surface texture evaluation of TiAlN coatings Natalija Bulahaa, , Guna Civcisaa* a

Institute of Mechanical Engineering, Riga Technical University, Ezermalas str. 6k, Lab 513, Riga, LV-1006, Latvia

Abstract This paper explores the relevant 3D roughness parameters used to characterize surface texture of titanium (Ti) based coatings. The main objective of this study was to compare the surface texture parameters, and to obtain 3D topographies of surface roughness. The applied surface analysis in areal manner allows a more complete evaluation of the component part surface and coating properties. This comparative study identified the areas for further consideration. © 2014 Elsevier Ltd. All rights reserved. Selection and Peer-review under responsibility of the Conference Committee of 6th International Conference on Advanced Nano Materials. Keywords: TiAlN coatings; surface texture; roughness;

1. Introduction Industrial usage of titanium can be roughly dated back to the late forties of the past century. Aerospace industry has been the driving sector behind titanium exploitation from since on. An approach when a durable coating is applied on the material surface is becoming more used. Application of coatings could improve operation of equipment and their constructive parts, and thus protect them from the negative environmental influence (e.g., extreme high temperatures). Titanium finds wide usage as a coating component due to its characteristic property of combining into hard compounds [1]. Research into surface texture measurement and characterization has been carried out for over a century and is still very active [2].

*

Corresponding author. Tel.: +371-67089701; fax: +371-67089739. E-mail address: [email protected]

2214-7853 © 2014 Elsevier Ltd. All rights reserved. Selection and Peer-review under responsibility of the Conference Committee of 6th International Conference on Advanced Nano Materials.

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2. Experimental Study In this experimental study, the surface texture of two titanium aluminum nitride (TiAlN) coatings for aerospace industry applications were compared. The substrate materials were different for each sample, but the chemical composition of both evaluated coatings was the same. The TiAlN coating was deposited on a glass surface for sample C1 while the coating of sample C2 was deposited on a blade that made of titanium alloy and used in gas turbine engine. A deposition method and technological mode was equal for both sample types. In order to obtain the information on possible functional properties of the surface it is important to conduct the metrological analysis which includes the taking of surface roughness topography and its filtering, and the determination of roughness parameters. For the task execution there was used measuring equipment – profilometer “Taylor-Hobson Talysurf Intra 50”, which provides an accurate measurement of surface roughness parameters. The given profilometer is equipped with a block of electronic system for data receiving, drive, measuring table and measuring arm with a diamond stylus. Information from the measuring equipment is transferred to the computer, which performs all the necessary processing of data. In this work the measuring experiment was carried out for two samples C1 and C2. The specimens after cleansing with cleansing agent from grease and dirt were placed on the measuring table. To begin an experiment, at first it was necessary to set the parameters, which characterize the measurement area of the samples, the number of points and the rate of movement of stylus (Table 1). Table 1. The settings of experiment. Parameter

Unit

Stylus

Standard Stylus Arm 112/2009

Number of points (Y)

500

Data length (Y)

1,5 mm

Number of points (X)

500

Data length (X)

1,5 mm

Measurement Speed

0,5mm/s

While the measuring experiment was running, the stylus was moving in X and Y directions thus forming a threedimensional image of the surface. The measuring process is shown in Figure1. a

b

Fig. 1. (a) the sample C1; (b) the sample C2.

The next step in this experiment was to obtain 3D image of roughness. For the purpose to get a real roughness values, the obtained images were processed using “μultra” software, because, as is known [2,3], the primary surface topography comprises form errors and waviness. Within the experiment it was performed the surface levelling, form

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and waviness separation. The samples C1 and C2 surface 3D simulations before the filtering operation are visible in Fig.2.

Fig. 2. 3D photo simulation (a) of surface C1; (b) and surface C2.

The primary surface of the sample C1 contains small peaks, which are spread evenly over the surface, and a few prominent micro-irregularities, whose placement is chaotic. In contrast, the surface of the sample C2 has peaks, which are significantly larger in size compared with the surface C1, but all of them are densely distributed over the measurement area. Due to the fact that the primary surface does not give the real information about the roughness structure and characteristics in the given work the entire analysis will be based on the filtered surface topography (Fig. 3).

Fig.3. 3D topography (a) of filtered surface C1; (b) and surface C2.

Surface roughness parameters, which will be analyzed in this article, are standardized by ISO 25178-2: 2012 "Geometrical Product Specifications (GPS) - Surface texture: Areal - Part 2: Terms, Definitions and surface texture parameters" [4]. In this standard the roughness parameters are divided into six groups: the height, spatial, hybrid, functional and related and miscellaneous parameters. The height parameters are important, because they give information about the height deviation of the surface. In turn, the spatial parameters are needed to evaluate density of peaks and texture strength, as well as to distinguish the determinate and random structures of surfaces. The hybrid parameters contain the information both about micro-irregularities height and about spatial characteristics. The functional parameters give a notion of the surface material volume in various operational stages. The miscellaneous parameters indicate the texture orientation, but the related parameters gives the information about how the contact stresses will be localized on the surface micro peaks. In the Table 2 there are grouped roughness parameters of the samples C1un C2. move to page 2769

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Table 2. Roughness parameters of samples C1 and C2. Parameter

Sample C1

Sample C2

Unit

Height parameters Sa

0.229

0.829

μm

Sz

4.81

12.1

μm

Ssk

-0.633

0.747

-

Sku

8.54

6.27

-

Sk

0.53

Functional parameters 2.07

μm

Spk

0.261

1.69

μm

Vv

0.00163

0.00656

mm3/mm2

Vm

0.00292

0.00556

mm3/mm2

Vmp

0.000338

0.000784

mm3/mm2

Vmc

0.00308

0.00395

mm3/mm2

Vvc

0.00033

0.00129

mm3/mm2

Vvv

0,0000441

0.000124

mm3/mm2

Spatial parameters Str

0.137

0.67

-

Miscellaneous parameters Spd

1042

802

pks/mm2

Table 2 represents only a part of all the roughness parameters. According to the literature sources [4,5], they are the most accurate for characterizing the surface and its possible applications. 3. Results The both samples have quite different values of the arithmetic average roughness (Sa), for the sample C1 it is in 2.5 times less than for the sample C2. The same situation is with the values of the maximum roughness (Sz), which indicates that the sample C2 has a rougher texture. Conversely, in order to understand, whether the dominant element of the surface are sharp peaks or valleys, it is important to know the value of parameter Ssk (skewness of the scale-limited surface). The sample C1 has a negative Ssk values, but the sample C2 – positive values. The negative values of the given parameter indicate a relatively small number of peaks, which will be very quickly worn out. As a result, it is possible to get relatively deep valleys for lubricant retention. Surfaces with a positive asymmetry have low lubricant retention properties due to the lack of deep valleys. Despite of this, the difference between the parameter Ssk values for the samples C1 and C2 is too small, so to assert that one surface has better lubricating properties than other is not correct. It is also evidenced by quite similar profilograms of both samples (see Fig.4.), in which it is displayed peaks and valleys position relative to the middle line. The sample C2 has a bit better oil retention properties, in turn, sharp peaks of the roughness does not ensure long-term preservation of these qualities during the contacting. According to profilograms, which are shown in Fig.4, the roughness peaks and valleys have sharpened form, what is evidenced also by the large value of the parameter Sku (kurtosis of the scale-limited surface). The sharp peaks may adversely affect the process of friction because due to the small cross-sectional area of micro irregularities the specific pressure on the surface peaks will be higher and, consequently, contact stresses, from which the micro peaks deformation is dependent, also will be more significant. Above the particular limits roughness peaks will be removed. In this case the surface will be worn away. But the process of wear can be affected by the density distribution of peaks (Spd) and the surface isotropy (Str). The parameter Spd represents the number of peaks per unit area; withal peaks have to be arranged above 5% of the Sz, starting from the middle line. For the sample C1 this parameter is a little higher, what indicates that the load will be distributed more evenly. The

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roughness parameter Str identifies whether the surface has the same structure in all directions or there is a specific direction of roughness; its high values (Str> 0.5) indicate that the surface has an isotropic structure. For the sample C2 this parameter value reaches 0.67, what can provide surface strength.

Fig. 4. The profilogram (a) of surface C1; (b) and surface C2.

In terms of coatings wear, it is important to note such group of roughness parameter as material volume, which characterizes the coating material amount before contacting with the other surface (Vm), the volume of material that will be removed from the surface after the primary running-in stage (Vmp), and after normal operation phases Vmc. For the samples C1 and C2 the primary material volumes are different, what is explained by the large values of the sample C2 parameter Sa. After the running-in stage the material volume of the second sample remains higher, what provides the greater support area. However, after the normal operating stage it is shown that the volume of material for both samples is decreasing by the similar size. In addition, the coating wear can be predicted by the parameters Spk and Sk, which represent the material nominal height, which can be separated from the surface in the running-in stage, and the core roughness, over which the load can be distributed after the surface running-in. The values of material volume parameter show that the smoother surface will ensure the higher resistance to wear process.

Fig. 5. The Areal Material Ratio Curve (a) of surface C1; (b) and surface C2.

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If the coating works in lubrication conditions, it is important that the surface has valleys, which could retain the lubricants. This property can be characterized by void volume parameters series, which includes the void volume before the running-in stage (Vv), the void volume after the running-in stage (Vvc) and the void volume after the normal operation (Vvv) [6]. For the sample C1, all these parameters are almost in four times less than for the sample C2, what is also explained by the fact, that the second sample has bigger value of arithmetic mean roughness. Analyzing the void volume reduction tendency depending on the surface running stage, then it is evident that void volume of both samples after the running-in stage fell in five times, while, after the normal operating stage sample’s C1 void volume values fell only in seven times, and for the sample C2 – in ten times. Due to the fact that the TiAlN coating was deposited on two surfaces with different roughness, in this paper it was tracked the tendency that coating deposition on the smoother substrate will ensure the smaller roughness of the deposited coating in comparison with the coating C2 which was sprayed on the rougher surface. Therefore, it can be assumed that the roughness of the substrate correlates with the roughness of the coating. 4. Conclusion 3D roughness parameters and topographies of two experimental samples with the TiAlN coatings were analyzed and mutually compared. The selected 3D roughness parameters allow estimating that the TiAlN coating on a glass had a smooth surface compared with the TiAlN coating on a blade. From the study, it can be concluded that the substrate material, on which the coating is deposited, has a strong influence on final surface roughness. If the surface has the enlarged roughness values the void volume and material volume in different stages of running-in process also will be larger, but they will be pretty quickly decreased during the coating exploitation. In contrast, both samples have the expressed sharp form of peaks and valleys, which negatively affects the contact stresses distribution over the surface and respectively accelerates the surface wear mechanism. Further research will be needed for both analyzed coatings to verify changes in parameters, if any, caused by wear-resistance test. Also, it is expected to determine if roughness parameters correlate to the wear resistance properties. Acknowledgements This work has been supported by the European Social Fund within the project “Development of multifunctional nanocoatings for aviation and space techniques constructive parts protection” No.2013/0013/1DP/1.1.1.2.0/13/APIA/VIAA/027. References [1] M. Stueber, et.al, Surf. and Coat. Techn., 257 (2014) 1–2. [2] R. Leach (Ed.), Characterisation of Areal Surface Texture, Springer-Verlag Berlin Heidelberg, 2013. [3] L.Blunt, X.Jiang. Techniques for Assessment Surface Topography: Development of a Basis for 3D Surface Texture Standards "Surfstand", Elsevier, 2003.- 340 p. [4] ISO 25178-2:2012, Geometrical product specifications (GPS) -- Surface texture: Areal - Part 2: Terms, definitions and surface texture parameters. [5] B.Muralikrishnan, J.Raja. Computational Surface and Roundness Metrology, Springer, 2008. - 283 p. [6] Surface Metrology Guide. Internet: http://www.digitalsurf.fr/en/guide.html