Study on laser prepared reinforcement unit distribution of large scale non-uniform hardness surface of gray cast iron against wear

By mimicking the ‘non-smooth structural unit’ of the dung beetle’s cuticle layer through laser, a large-scale striped surface structure with alternating hard and soft areas was fabricated on gray cast iron, which effectively enhanced various properties. This work investigated the impact of different distributions of the striped reinforcement units on wear resistance by introducing distinct local reinforcement areas on the surface. By integrating finite element analysis, an in-depth study of the wear resistance mechanism of the striped bionic samples was conducted. The findings highlight that different distributions of the striped reinforcement units significantly influence the surface stress distribution. In this work, the increase in wear resistance is directly proportional to the uniformity of the reinforcement units’ distribution. Notably, the wear resistance is optimized when the reinforcement units are uniformly dispersed at a spacing of 4.2 mm.


Introduction
Surface texturing stands as a pivotal method in enhancing the tribological properties of engineering materials [1,2].A diverse range of texturing strategies have been developed, while laser surface texturing [3] (LST) distinguishing itself due to its remarkable flexibility, high precision, and excellent controllability.Geometry and parameters of the texture are critical factors in wear resistance [4].Inspired by biomimetics, texture designs that mimic the intricate surface patterns observed in biological entities have been explored, such as leaf vein [5] and lotus leaf [6].Li et al [7] investigated the dry friction and wear behavior of sol-gel ZrO 2 /WS 2 coatings with biomimetic sharkskin textured surfaces.Long et al [8] found the use of biomimetic leaf vein textures can effectively reduce wear and friction coefficients.However most of the works were on micron scales.A large-scale 'non-smooth structural unit' was prepared by LST on the surface of cast iron by mimicking the cuticle morphology of soil animals such as dung beetles [9].The laser-treated reinforcement units (RUs) will act as a hard phase due to its superior hardness and strength, and on the contrary, the untreated area is a soft phase, and the two form a non-smooth structure with alternating hard and soft, which can effectively improve the overall performance of the material, such as wear resistance, mechanical properties [10], and fatigue resistance [11].The reinforcement unit, characterized by increased strength and hardness, interacts with the non-smooth biomimetic structure to transmute continuous wear into a discontinuous form during the abrasion process.This feature significantly augments the wear resistance of the biomimetic specimens.By preparing regularly arranged localized reinforcement regions on the surface through laser processing, this type of process can impart specific functionality to the surface of the part while retaining the original mechanical properties of the core.Zhao et al [12] prepared mesh-like RUs with different density distribution on the surface of 6082 aluminum alloy, and the study showed that the wear resistance was strongest when the density of mesh-like RUs was 0.4.This indicates that the non-uniform surface with a combination of soft and hard has superior wear resistance than a single hard surface.Yuan et al [13] prepared non-uniform surfaces of dots, strips, nets, and their different combinations on the surface of 6082 aluminum alloy and found that the non-uniform specimens with dot-net distribution had the best wear resistance.Wei et al [14] prepared strip-reinforced units with different orientations from 0°-90°on the surface of H13 steel and found that the 45°strip units were the most wearresistant.Cao et al [15] found that when the surface texture direction angle was 30°, the average friction coefficient was the smallest, the supporting performance and wear resistance of parts were the best.Zhangwei et al [16] analyzed the wear performance of the textured surface using finite element software and found that the wear was minimized when the texture angle was 45°.Zhao et al [17] used finite element analysis (FEA) to investigate the wear and rolling contact fatigue behavior of U71Mn rail with laser dispersed quenching (LDQ) spots.And LDQ treatment can significantly improve the wear resistance of U71Mn rail.
Notwithstanding the plethora of studies that have illuminated the distinctive wear properties of surfaces with heterogeneous soft-hard combinations, the specific manner in which the distribution of RUs influences the stress and wear resistance of such surfaces remains uncharted.Consequently, this study, building upon the foundation of 0°striated RUs, employs laser fabrication to create RUs with varying distribution patterns and inter-unit distances.The objective is to investigate the ramifications of the specific distribution of RUs on largescale soft-hard non-uniform surfaces.In conjunction with FEA, this study provides a comprehensive description and analysis of the wear resistance mechanisms of striated biomimetic specimens.

Experimental materials
Gray iron possesses some exceptional mechanical properties, such as high machinability, vibration absorption, and castability.It is frequently used in the manufacturing of compressor crankshafts, rails, gears, piston rings, and diesel engine cylinder liners [18,19].Among them, HT250 not only exhibits strength, wear resistance, and heat resistance but also has excellent casting properties.Its outstanding performance in shock absorption makes it the primary material for the fabrication of automobile brake system [20].Therefore, this paper selected HT250 as the research material.The microstructure of HT250 primarily consists of flake graphite and pearlite.The chemical composition of HT250 was analyzed by Glow discharge optical emission spectrometer (GD750, SPECTRO, Germany) and table 1 delineates the chemical composition.

Sample preparation
The main objective of this work is to ascertain the influence of RUs distribution against wear.By applying laser treatment to the surface of gray cast iron, six distinct RUs were generated, forming a non-homogeneous bionic specimen with dimensions of 30 mm * 20 mm * 7 mm.
The specimen was evenly split into three sections(I, II and III), and the six RUs were then separated into three groups.These groups were organized according to the count of RUs they contained.This approach resulted in the generation of fourteen unique combinations: The samples with the uniformly distributed RUs (UD) are the control group.This configuration is presented for elucidation in figure 1.
The laser processing system is depicted in figure 2(a).Oriented strip RUs were created on the surface of the bionic specimens utilizing an Nd:YAG solid-state laser with a wavelength of 1.06 μm and a maximum power of 300 W. Laser processing was performed under an argon protective atmosphere, maintained at a steady argon gas flow rate of 10 l min −1 , and involved parameters such as laser energy density of 360.8 J cm −2 , duration of 5 ms, frequency of 5 Hz, a defocus of 5.5 mm, and a scanning speed of 1 mm s −1 .As illustrated in figure 1(b), the RUs exhibit a uniform distribution across the specimen, PP refers to the untreated area.Detailed values can be found in table 2, where 'a' corresponds to the center-to-center distance between adjacent RUs, and 'b' denotes the distance from the center of the outmost RUs to the edge of the specimen.

Experimental method
The samples were etched with a 4% nitric acid alcohol solution for metallographic corrosion.Microstructural analysis of the samples was conducted using a scanning electron microscope (Zeiss, evo18, Germany).Wear tests were conducted with a multifunctional wear tester (RTEC, USA), setting parameters at 85 N pressure for 2 h and a wear velocity of 10 cm s −1 .An electronic balance of the FA2004 type, with an accuracy of 0.0001 g, was used to measure the weight of the samples before and after the wear test, enabling the calculation of weight loss, .The wear resistance of the bionic coupled specimens was evaluated using Δm, with the Δm value for each specimen being the average derived from three independent tests.The surface hardness was ascertained using a Vickers microhardness tester (model 5104, Buehler Ltd, USA).The microhardness of PP and RUs was measured under a 0.2 kg load for 10 s.The hardness value attributed to each sample is the average derived from three replicated tests.

Numerical simulation
The stress and strain distribution on the sample's surface during linear reciprocating motion was meticulously analyzed through numerical simulation.FEA was conducted utilizing Abaqus/Standard 6.14 with the chosen method being static analysis.The interaction between the friction pair and the sample surface was characterized as face-to-face contact, accompanied by a friction coefficient of 0.2.The selected element type was 3D Stress (C3D8R), and the minimum mesh size was 0.5mm for the bionic sample and 3mm for the wear pair.
Comprehensive details regarding the physical properties of the friction pair, substrate, and unit material are delineated in table 3.

Microstructure and microhardness
The experimental material employed in this study was HT250, a hypo-eutectic cast iron with a carbon content of 3.56%.The microstructure of the untreated area denoted as PP, exhibited coarse, flaky graphite and lamellar pearlite, as illustrated in figure 3(a).In contrast, figure 3(b) shows the distinct structural transformation in the RUs following laser irradiation.Laser irradiation resulted in the complete dissolution of graphite, inducing eutectic transformation in the melt zone.Initially, primary austenite precipitated from the molten pool.As the residual liquid phase persisted in cooling, carbon underwent segregation from the austenite, culminating in a eutectoid transformation.The rapid cooling inherent in the laser processing method limited the complete phase transition of austenite.A significant portion transforms into martensite, while a smaller fraction remains residual austenite due to the constrained transformation time.The overall macrostructure consists of a  composite of modified ledeburite featuring fine carbides, residual austenite, and acicular martensite and cementite.In addition, due to the high carbon content of cast iron itself, a large amount of carbide will precipitate along the austenite grain boundaries during solidification to form reticulated carbides, the appearance of martensite and carbides make RUs hardness significantly higher than PP.
The hardness test and microhardness of the samples are shown in figure 3(c), where microhardness values were measured at a depth of 25 μm below the surface.The microhardness of the PP ranged approximately between 240HV and 290HV.Laser treatment resulted in RUs having a higher microhardness than PP.Due to the compact microstructure of RUs, the hardness was nearly unchanged in the width direction, with only a slight increase observed at the center of the melting pool.
As shown in figure 4, the distribution of the RUs exerts a pronounced influence on the wear resistance, with the uniformly distributed (UD) sample manifesting the most diminutive wear.Moreover, under conditions of analogous distribution, there is a notable attenuation in weight loss when RUs are concentrated in zone II.The specimens exhibiting the minimal wear within Groups A to D, in conjunction with the 2-2-2 and the UD, are collectively designated as Group MIN.The wear morphology of Group MIN is depicted in figure 5.
As shown from the wear morphology, it is evident that when the RUs distributions are configured as 1-5-0, 2-4-0, and 3-3-0, the wear predominantly exhibited by PP is adhesion.Moreover, when the RUs distributions are configured as 1-4-1, 2-2-2, and UD, the wear chiefly exhibited by PP is abrasion, while RUs consistently manifest marginal furrowing attributable to its elevated hardness.As depicted in figures 5(a)-(f), the direction of the abrasion marks in the figure is the same, and an abundance of pits and scratches characterizes the worn surface.The primary mechanism underpinning abrasive wear is the induction of cracks on the graphite wear surface due to plowing, which results in the exfoliation of minute graphite fragments.Simultaneously, the oxide film, engendered by the oxidation of graphite during the frictional process, may also undergo exfoliation: the exfoliated graphite and its oxide film function as wear debris, exacerbating the severity of abrasive wear.As the abrasives transition from PP to RUs, the disparity in hardness between the two parts causes the debris to leap from a relatively softer to a harder surface.This leap impedes the movement of the abrasives, consequently transforming the erstwhile continuous plowing into a discontinuous one.
To further investigate the wear mechanism, finite element analysis of the wear process was performed as follows.The surface von Mises stresses of the specimens were analyzed using the finite element analysis software Abaqus/Standard 6.14 to investigate the variation of surface stresses for different distributions of RUs during the sliding wear process.By utilizing the modeling capabilities of Abaqus, stress analysis models for different distributions of RUs under surface contact conditions were established to investigate the changes in surface stress during sliding wear.The stress distribution of the worn samples under a load of 1.28 MPa was determined.The color map representation showed that brighter colors corresponded to higher stresses, while cooler colors indicated lower stresses.
As shown in figure 6, different distributions of RUs result in significant changes in equivalent stress of softhard non-uniform surface, wherein pronounced stress concentrations are observed in the RUs.To delve into a more granular analysis of the stress magnitude, the von Mises stress line diagram, aligned with the centerline of the surface, is elucidated in figure 7.
Equation (1) was used to calculate the variance of the average stress (x i ) for each RUs and the average stress (x) applied to the entire soft-hard non-uniform surface, resulting in the generation of table 4.This table serves as a metric for evaluating the uniformity of stress distribution of the RUs.A smaller variance value indicates a more homogeneous distribution of stresses exerted on the RUs.
Table 4 reveals notable variations in stress distribution among the three RUs distributions (5-1-0,1-5-0, and 5-0-1) within Group A. Among them, Sample 1-5-0, characterized by RUs mainly settled in zone II, exhibits the smallest variance, indicating a more uniform stress distribution.Notably, this specimen also demonstrates the lowest weight loss in group A, suggesting that the uniformity of RUs distribution impacts the wear resistance of the specimens.Similar results are noted in Group B to E. When RUs are densely distributed in zone II, the specimens exhibit the smallest variance values, indicative of more homogeneous stress distribution and, consequently, the least amount of wear in their respective groups.That is, optimizing the RUs distribution facilitates the preservation of an advantageous equilibrium in stress distribution, thereby augmenting the material's wear resistance.
As delineated in figure 7, the surfaces characterized by non-smooth structures reveal a distinct distribution of stress and strain.Specifically, the stress is primarily localized within the RUs, with the stress imparted to the PP consistently lower than that of the control samples.The more rigid RUs absorb most of the stress, thereby mitigating the load on the PP.Owing to the intrinsic characteristics of the RUs, such as elevated hardness and substantial strength, the RUs exhibit enhanced resistance to plastic deformation and superior wear resistance.Moreover, the stress distribution within the samples, as depicted in figure 7, correlates significantly with the spatial arrangement of the RUs.In samples with non-uniform distribution, the von Mises stress experienced by the RUs is reduced compared to uniformly distributed samples (UD), with a corresponding increase in stress on the PP.In UD samples, where the RUs are uniformly distributed, the von Mises stress borne by the RUs reaches a maximum, while the stress on the PP is minimized, resulting in optimal wear resistance.This finding emphasizes the distinct advantage of uniform distribution in wear resistance.A more equitable distribution of RUs leads to a decrease in von Mises stress on the PP, thereby reducing wear.UD's ability to disperse surface stress prevents excessive concentration in specific areas, further reducing wear.Additionally, the uniform distribution of RUs augments the surface stability of the material, further curtailing wear.
Meanwhile, as can be observed from figure 7, Group A, 5-1-0, and 5-0-1, in which the RUs were densely distributed in Zone I, exhibit a distinctly different stress distribution in Zone II.The Mises stress of the PP in Zone II of 5-0-1 is greater than that of 5-1-0, implying that PP is more susceptible to wear during sliding.In contrast, in 1-5-0, the average stress experienced by PP in Zone II is smaller, which is the reason for the excellent wear resistance of 1-5-0.
Comparing 2-4-0 and 1-4-1, they harbor an identical count of RUs in Zone II.The variance between the two is not significant.However, in 1-4-1, the RUs bear a higher von Mises stress.Correspondingly, the PP undergoes a lower one.This culminates in a reduced weight loss for 1-4-1 compared to 2-4-0, thereby suggesting that the stress experienced by the RUs exerts a more substantial influence on wear resistance than the impact of the variance.
By integrating finite element analysis with wear results and employing Ordinary Least Squares (OLS) regression on the experimental data, the following regression equation was derived: Here, Δm represents the wear amount of the sample, σ 2 signifies the variance of the RUs, and S denotes the Mises stress experienced by the RUs.This equation reveals a significant linear relationship between the variance and stress of the RUs and the wear amount of the sample.Specifically, the positive coefficient of the variance indicates that an increase in variance leads to an increase in wear, suggesting that a more extraordinary variance results in a more uneven non-smooth surface, thereby diminishing its wear resistance.Conversely, the negative coefficient of the stress implies that an increase in stress results in a decrease in wear, meaning that the greater the Mises stress endured by the RUs, the better the wear resistance of the non-smooth surface.The impact of the von Mises stress experienced by the RUs in the MIN group on weight loss is illustrated in figure 8.As the stress increases, the weight loss gradually decreases, exhibiting a linear relationship between the two.
The equation (2) correlating wear rate with the applied load was pioneered by Holm [22] in 1940, a reference to which is encapsulated in Archard's paper.This publication is widely regarded as the cornerstone for modeling wear rate within sliding systems.
where w is the weight loss ;K is the wear coefficient, H is the material hardness, m is the pressure index, n is the velocity index, P is the contact pressure, and v rel is the relative sliding speed.The wear equation for t stripes can be obtained as: subject to: x m is a concave function.According to Jensen's inequality concave functions, That is, the wear is minimized when the pressure is uniformly distributed over t strips.From equation (7), it can be seen that the more uniform the stress distribution on RUs, the smaller the wear, which is consistent with our experimental results.9, the stress distribution across the non-uniform surface markedly changes with increasing spacing.According to figure 10, as the spacing expands (from 1 to 5), the stress on the RUs initially increases, then decreases, peaking at a spacing of 4.2 mm.This trend aligns with the wear results, suggesting that the arrangement of the RUs can modulate the stress distribution across the non-uniform surface, thereby influencing its wear resistance.Furthermore, there exists an optimal spacing that minimizes the weight loss, as depicted in figure 11.A closer examination of the average stress values of the RUs and the matrix reveals a clear correlation: an increase in the stress of the RUs corresponds to a decrease in the stress of the matrix, enhancing the protective effect on the matrix and thereby augmenting the wear resistance of the specimen.
Similarly, equation (1) was used to calculate the variance of the average stress (xi) for each RUs and the average stress (x) applied to the entire soft-hard non-uniform surface, resulting in the generation of table 5.A smaller variance is indicative of greater uniformity.With an increase in spacing, the variance initially diminishes and subsequently escalates, attaining its minimum value at a spacing of 4.2 mm.At this point, the specimen is subjected to the most uniform stress distribution.According to equation (6), when spacing of RUs is 4.2 mm, the weight loss should be minimal.
As shown in figure 11, with the increase of RUs spacing, the wear amount and variance showed the same trend, both decreasing first and then increasing and having the minimum value at the spacing of 4.2 mm, as expected by equation (7).That is the more uniform the stress distribution on RUs, the smaller the wear.

Wear mechanism
Laser processing imparts an increased hardness to the RUs, thereby bolstering their resistance to wear.Conversely, due to its lower hardness, the PP is more prone to wear.Under vertical loads, stress concentrations are observed on the RUs.As stress bear by the RUs intensifies, their protection of the PP becomes more pronounced, resulting in reduced weight loss of the PP.By adjusting the distribution of RUs, it is possible to manipulate the stress on RUs, thereby influencing the material's wear resistance.Owing to the disparate microstructure of the PP and RU, they exhibit varying elastic deformations.Consequently, when RUs are densely distributed on one side of the specimen, it may induce non-parallelism in the wear surface, increasing weight loss.In other words, the more heterogeneous the distribution of RUs, the more pronounced the non-parallelism of the wear surface, resulting in greater wear.In such scenarios, wear resistance is not solely influenced by stress.However, it is a consequence of the interplay between the nonuniform stress distribution induced by the heterogeneous distribution of RUs and the non-parallelism of the wear surface.Therefore, by optimizing the distribution pattern of RUs to achieve greater uniformity, it is possible to effectively ameliorate the stress distribution, reduce the non-parallelism of the wear surface, and consequently diminish the weight loss.

Conclusion
In this study, non-uniform biomimetic specimens with varying distributions of reinforcement units (RUs) were fabricated on the surface of gray cast iron by laser.The influence of different distributions of RUs on wear resistance was investigated.Based on the findings, the following conclusions can be drawn: 1.A more uniform distribution of RUs is conducive to enhanced wear resistance.The uniformity of RUs' distribution is pivotal in influencing stress and wear.A more homogeneous distribution of RUs results in the untreated area (PP) exhibiting reduced stress and weight loss.
2. A significant linear relationship between the variance and stress and wear.The variance of RUs is positively correlated with the wear; the more significant the variance is, the more inhomogeneous the non-smooth surface is, and the worse the abrasion resistance is; the Mises stress of RUs is negatively correlated with the amount of wear, the larger the stress of RUs subjected to Mises is, the better the abrasion resistance is of the non-smooth surface.
3. The non-uniform distribution of RUs precipitates non-parallelism across the entire wear surface, thereby exacerbating weight loss.By optimizing the distribution pattern of RUs, it is feasible to bolster the wearresistant properties of the material, which holds significant practical value for industrial applications such as brake discs, brake drums and lathe guide rails.
4. Through FEA, by comparing the magnitudes of Mises stress in the RUs and the PP, as well as the variance of Mises stress on the RUs, it can be determined that the optimal distribution form for the RUs is a uniform distribution.
5. RUs distributed at equidistant intervals exhibit an optimal spacing, which in this study was determined to be 4.2 mm.At this spacing, the variance of RUs is minimized, the stress distribution is the most uniform, and the weight loss is the lowest.

Figure 2 .
Figure 2. (a) Sketch of laser processing system (b) Sketch of UD samples with different spacing.

Figure 4 .
Figure 4. Weight loss of samples with different distributions of RUs.

Figure 6 .
Figure 6.Mises stress distribution nephogram of different distributions of RUs.

Figure 7 .
Figure 7. Mises stress of different distributions of RUs on the centerline.

Figure 8 .
Figure 8. Results of mises stress of RUs in Group MIN on Wear.

Figure 11 .
Figure 11.Results of interval of RUs on wear.

Table 1 .
Chemical composition of gray cast iron.

Table 2 .
Equidistant specimens with different spacing of UD.

Table 3 .
Physical properties of materials.

Table 4 .
Variance of different stress distributions of RUs.Wear results and FEA of UD with different spacing of RUs To further elucidate the impact of the distribution of RUs on wear resistance, this study investigated the effect of RUs intervals under equidistant distribution.The spacing of RUs varied from to 5 as shown in table 2. Wear tests and FEA were performed.As shown in figure

Table 5 .
Variance of different intervals of RUs.