Introducton

AISI 316L austenitic low carbon stainless steel (316L SS) is a widely used stainless steel that is employed in many industries such as automotive, aerospace, marine, energetic, petrol-chemical, biomedical and others. This is due to its high corrosion resistance, good temperature resistance, acceptable biocompatibility, nonmagnetic and excellent mechanical properties (strength and ductility) [1,2,3]. This stainless steel nevertheless possesses a poor wear and friction resistance that restricts its use in the number of applications [3]. Surface texturing in combination with lubricants can be the solution to these latter problems. This is due to the fact that the textures can increase the lubricant lifetime because of their lubricant reservoir function. The wear can also be reduced by the textures as these have a wear debris trap function [4,5,6]. In the case of the liquid lubricant, the textures can furthermore decrease the coefficient of friction, and as a result of this can alter the hydrodynamics of the fluid [5, 7, 8].

Surface texturing is a powerful tool to functionalise the surface of a material. It can be carried out using several methods, such as ion beam, mechanical, etching, sand blasting, laser, plasma deposition and discharge electro machining. Laser Surface Texturing (LST) offers significant opportunities as a result of its exceptional properties such as environmentally friendly, precise, automation, and low cost of processing [7,8,9]. This technique can be conducted with several types of lasers that range from continuous wave lasers to femtosecond pulsed lasers, and from ultraviolet wavelengths to the mid-infrared. Near-infrared nanosecond pulsed lasers are widely employed for LST on metallic materials because of their small Heat Affected Zone (HAZ) in comparison to milli and microsecond pulsed lasers. They can offer, high peak power, good laser absorption and relatively low cost [9,10,11].

The traditional development field of LST is in the tribology of mechanical parts such as, gears, pistons, bearings, cylinders and others [12]. Eighteen years ago, Etsion [12] reviewed the application of LST on mechanical parts and associated basic research of LST in universities. The high reproducibility and precision of this technique is identified compared to other surface texturing methods. Subsequently, several researchers [13, 14] have investigated the influence of texture features (e.g. aspect ratio, shape, organisation and texture density) in the improvement of the wear and friction resistance, and the lasers (e.g. carbon dioxide, solid state, excimer and fibre) that can carry out these textures in a more efficient way. One of the challenges for LST in the 2010´s was the generation of the textures at a few micrometres or nanometres [14]. The creation of the laser induced periodic surface structures using polarised laser radiation was shown to produce the nano-textures, commonly produced with pico and femtosecond pulsed laser [7, 15]. Micro-textures remain the main textures to improve the wear and friction resistance of the materials owing to their lubricant reservoir function. LST is carried out with a wide variety of lasers, from continuous wave through nanosecond pulsed laser to ultrashort pulsed (pico and femtosecond) [7, 16]. In the last decade, LST has also been employed in the biomedical industry to increase the biocompatibility of implants [15, 17,18,19]. The texturing at micro scale can improve the osseointegration of the implant while the laser induced periodic surface structures produce an antibacterial effect. For these reasons, lasers (e.g. polarised laser) that can create these nano-textures have become the focus of the biomedical industry. In the last few years, direct laser interference patterning is being developed in the biomedical field because of the generation of the patterns at varying scales in only one step [20].

The improvement of process efficiency is an important requirement for industrial applications. Efficiency of an industrial process is commonly defined by the power consumption, processing time and material requirements. Reducing these factor values increase the process performance [21,22,23,24,25]. In the case of the LST process, the efficiency can be defined by means of the laser beam-material interactions; energy fluence threshold and energy depth penetration. Energy fluence threshold is the minimum energy fluence necessary to carry out laser processing on the material (e.g. heating, melting, evaporation and ablation) [26]. Laser ablation is the principal process in laser surface texturing [27]. Low energy fluence thresholds allow texture creation at lower energy fluence values. This reduces power consumption. The energy fluence threshold can be classified as a surface parameter (energy fluence threshold to carry out a laser processing on surface). The energy depth penetration parameter mainly influences the laser processing into the material [28, 29]. The depth of textures is proportional to the energy depth penetration [29, 30]. High energy depth penetrations allow the generation of deeper textures using less energy fluence and pulse number [28, 29]. This provides a reduction in the power consumption (energy fluence) and process time (pulse number). It should be noted that an increase of the energy depth penetration relates to an increase in the energy fluence threshold, the energy fluence threshold being proportional to the energy depth penetration [31]. So, the efficiency of LST is higher at low energy fluence thresholds and at larger energy depth penetrations. Properties of LST are defined by the shape and size of the textures [7, 27, 32]. The laser processing and the texture features are defined by the laser parameters and the materials’ properties [9, 33].

The roughness of the surface to be textured is an important factor that influences the shape and size of the texture and LST efficiency [34]. The optimum surface roughness for LST on metallic materials is the subject of discussion for researchers today. Several studies [26, 35] about LST on various metallic materials confirm that the increasing of surface roughness can improve the LST efficiency as this decreases the reflectivity of the material. High initial reflectivity of metallic alloys means that a significant part of the laser radiation is reflected, reducing the efficiency of the process. The reflectivity can be reduced via painting, coating deposition and surface roughening [35]. Other investigations [33, 36] have observed the opposite effect, where increased surface roughness decreased the efficiency of the laser process. This is owing to scattering effect of the roughened surface on the laser radiation that can enlarge the area exposed by the laser radiation on the samples. This creates a reduction in the effective energy fluence that diminishes the LST efficiency. Another study [34] considers that the surface roughness influence can depend on the roughness level and the type of the metallic material. Currently, no study has given a satisfactory explanation about the roughness influence on the laser beam-material interactions.

For these reasons, a study about the influence of the surface roughness on single shot dimple LST of 316L SS with 1064 nm nanosecond laser pulses is reported in the present paper. Several single pulse shots were performed to produce separate dimples on SS316L surfaces with different average roughness to avoid the influence of the previous laser pulse surface topography on the LST efficiency. Laser beam-material interaction factors (energy depth penetration, melting and ablation, focused beam diameter, melting, surface and in-depth ablation energy fluence thresholds) were calculated and assessed to give a deeper understanding of the average roughness influence on the efficiency of LST.

Experimental Setup

Materials and Pre-treatment

Sample coupons were prepared from stainless steel AISI316L (SS316L) supplied by Columbus Stainless Ltd. The size of the samples was 50 mm by 50 mm by 0.8 mm thick. Chemical composition of the SS316L was provided by supplier and this is summarised in the Table 1. The physicochemical properties of the SS316L [27,28,29] can be observed in the Table 2.

Table 1 SS316L chemical composition in weight percent (wt%)
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Table 2 SS316L Physical–chemical properties. *Value calculated using Eqs. (1), (2)
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Thermal diffusivity (\(\kappa\)) was calculated with Eq. 1 [26, 33, 40, 41].

$$\kappa =\frac{\beta }{\rho {C}_{p}}$$
(1)

Absorption coefficient (\(\alpha\)) was estimated using Eq. 2 [38].

$$\alpha =\frac{4 \pi k}{\lambda }$$
(2)

where, \(\lambda\) is the wavelength (1064 ± 5 nm).

Surfaces of the sample coupons were polished with various methods before laser processing (pre-treatment). This was carried out to get surfaces with dissimilar average roughness (\({S}_{a}\)). The Sa values were measured using a Bruker ContourGT optical profiler. Two measurements were taken on five separate areas within each coupon. Assessment of the roughness was conducted with green light and at 27.5 × magnification. Silicon carbide paper of grit 80P was used to obtain a surface with a \({S}_{a}\) value of 360 ± 40 nm. A second surface was firstly polished with grit 80P abrasive paper and then with 400P silicon carbide paper. \({S}_{a}\) of the second surface was 180 ± 30 nm. Third surface had a \({S}_{a}\) of 100 ± 20 nm, which was achieved via a polishing process with subsequent abrasive papers that were grit 80P, grit 400P and grit 1200P. The next sample was polished with grit 80P, grit 400P and grit 1200P silicon carbide paper and, polycrystalline diamond paste of 3 μm as the last polishing stage. This treatment produced a Sa value of 24 ± 10 nm. The final surface had a \({S}_{a}\) value of 12 ± 8 nm that was generated through successive steps. First step was a grinding process with silicon carbide papers of grit 400P, grit 600P and grit 1200P. The next step was a sequential polishing via polycrystalline diamond pastes of 3 µm. The last step was mirror polishing employing a colloidal silica gel solution that was formed of 50% in volume of silica gel (0.04 µm of grain size) and 50% in volume of distilled water. All polishing consumables and items were provided by Struers. A cleaning process was conducted after each polishing treatment that consisted of first cleaning with commercial detergent and rinsing with fresh water, and then the surface was sprayed with isopropanol and, finally, a fast drying with a hot air dryer. Samples were named according to their \({S}_{a}\) and therefore, these were called as 360 nm, 180 nm, 100 nm, 24 nm and 12 nm as can be seen in Table 3. Note, \({S}_{a}\) was measured on ten areas with optical profilometer whose specifications will be detailed later.

Table 3 Summary of the samples and their pre-treatments
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Laser Equipment and Parameters

The laser system used was formed of an infrared (IR) fibre laser, an optical system and a three axes automatic table. The IR fibre laser model was a SPI Laser (UK) G3 20 W nanosecond pulsed fibre laser. Optical system consisted of a manual 1064 nm beam expander (Linos (Qioptiq) 2-8x), a scanning galvanometer (Nutfield Extreme-15-YAG) controlled using SAMLight v3.05 software (SCAPS Gmbh), a focal length of 100 mm (Linos Ronar F-Theta focal lens) and four silver mirrors (Thorlab). The three axes computer-controlled table was provided by Aerotech Limited (UK). Figure 1 illustrates a schematic drawing of this equipment.

Fig. 1
figure 1

Laser equipment and experimental setup: Schematic drawing a) and photograph b)

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The laser has a wavelength (\(\lambda\)) 1064 ± 5 nm, and a near TEM00 mode with beam quality factor \({M}^{2}\) = 2.1. The laser can work with several pulse lengths (\(\tau\)) varying from 9 to 200 ns and at various Pulse Repetition Frequencies (\(PRF\)) that range from 1 to 500 kHz. The laser has a maximum average power (\({P}_{m}\)) of 22 W and maximum pulse energy (\({E}_{pm}\)) of 880 µJ before the optical system. \({P}_{m}\) was measured after the beam expander with an Ophir laser power meter system, using a 30A-N-SH ROHS head and Nova II display software. The power measurements were taken for 60 s. Maximum pulse energy was estimated with the Eq. 3 [42, 43].

$${E}_{pm}=\frac{{P}_{m}}{PRF}$$
(3)

The beam expander was set to give a raw laser beam diameter (\({D}_{R}\)) of 5.7 mm. Four mirrors guide the laser beam to the scanning galvanometer mirror head fitted with a f-theta focussing lens. This device handled the displacement of the laser beam on the sample surface and the scan rate of the laser beam (\(SR\)) across the surface can vary from 0.01 mm/s to 20,000 mm/s. The lens had a focal length (\(FL\)) of 100 mm. The samples were placed on the three axes automatic table.

In this study, the laser is used in pulsed mode with \(\tau\) = 200 ns, \(PRF\) = 25 kHz and with straight line scanning. The laser beam was focused on the sample surface. Theoretical laser beam diameter (\({d}_{o\left(Theo\right)}\)) was around 51 µm, calculated using Eq. 4 [31, 44,45,46] and the values of in Table 3 for the indicated parameters.

$${d}_{o(Theo)}=\frac{4 FL \lambda {M}^{2}}{\pi {D}_{R}}$$
(4)

The focussed laser beam was scanned across the sample surfaces at a speed to produce single pulse shots. The distance between pulses (\({d}_{t}\)) was set to 200 µm to avoid any possible overlapping of the dimples. \(SR\) was 5000 mm/s using Eq. 5:

$$SR={d}_{t} PRF$$
(5)

Pulse energy (\({E}_{p}\)) was varied from 4 µJ to 614 µJ in this work. \({E}_{p}\) were estimated using Eq. 6 [42] and the average power (\({P}_{ave}\)) measurements after the galvanometer mirror scanner.

$${E}_{p}=\frac{{P}_{ave}}{PRF}$$
(6)

Maximum \({E}_{p}\) is lower than \({E}_{pm}\) because the transmission of the system is 70%. This was measured by comparing an average power measurement of the laser beam after the focussing lens with the measurements after the beam expander outputs. The selected laser parameters for this study are summarised in Table 4.

Table 4 Selected laser parameters
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Characterisation and Analysis of Dimple Dimensions

The dimensions of the dimples were assessed using an Olympus BH2-UMA optical light microscope, equipped with DinoCapture 2.0 software. The topography and geometry of the dimples were evaluated with the Bruker ContourGT optical profiler. Assessment of the optical profilometry was conducted with green light and at 27.5 × magnification. The dimple shape features (e.g. width, diameter and depth) were calculated via the measuring of five dimples. Two measurements were carried out for each dimple and therefore, ten measurements for each experimental condition were conducted. It is noted that Sa measurements were not taken for the dimples, because this is not the object of this work.

Results and Discussion

Surface Morphology

The optical light microscopy pictures of the untextured (Fig. 2.a), d), g), j) and m)) and textured (Fig. 2.b-c), e–f), h-i), k-l) and n–o)) surfaces can be observed in Fig. 2. Laser impacts at ≥ 53 μJ produced textures on all samples. These show a circular shape with micro ripples in the centre and surrounded by crests. The type of textures was classified as dimples. Melting and evaporation of the material are usually the thermodynamic mechanisms that generate dimples on metals for laser irradiation with infrared laser pulses [47]. Material melting commonly creates the ablation mechanism of hydrodynamic expansion for nanosecond pulse lasers. This ablation mechanism is characterised by the displacement of molten material to edge of the laser impacted area. This displacement generates ripples and molten material massing on the edge of the dimples to create the crests [48,49,50,51]. These structures remain after the laser pulse owing to the quick temperature changes of the laser shot area. The temperature of the metallic material is quickly increased during the laser pulse. After the laser pulse impact, the temperature of the laser impacted area of the alloy is rapidly reduced by heat diffusion into the material bulk. This rapid solidification retains the ripples and crest of the dimples [33, 52]. Two dissimilar types of dimples were found, according to \({S}_{a}\) and \({E}_{p}\). The first type of dimple (Fig. 2.b), e), h), k) and n)) are featured by smooth crests while the second dimple kind (Fig. 2.c), f), i), l) and o)) are characterised by an abrupt crest and molten material appearing outside of the laser exposed zone. This indicates that the ablation mechanisms of the textures were different for each type of dimple. The ablation mechanism of the first dimple kind is surface vaporisation that is featured by the conversion of liquid to gas in a liquid–gas interface that is usually named the Knudsen layer. Although the escape speed distribution of the gas material in the liquid layer initially is non-equilibrium, this distribution reaches equilibrium with time [47, 48, 53, 54]. The second type of dimple was produced by the ablation mechanism often called phase explosion, characterised by the creation and subsequent growth of a bubble that is formed of evaporated material surrounded by molten material. Gas material then presses on the molten material that when the pressure is sufficiently high, the bubble can explode. Explosion ejects the liquid material outside of the laser treated area [47, 48, 53,54,55,56,57,58]. The first dimple type was furthermore found at lower \({E}_{p}\) than the second dimple kind as the phase explosion requires higher energy fluence to be produced than surface vaporisation for the nanosecond pulsed lasers [47].

Fig. 2
figure 2

The micrographic pictures of the untextured a), d), g), j) and m) surface and dimples at 53 μJ b), e), h), k) and n) and at 614 μJ c), f), i), l) and o) of the 360 nm a-c), 180 nm d-f), 100 nm g-i), 24 nm j-l) and 12 nm m–o) samples

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Dimple kinds were found at dissimilar \({E}_{p}\) ranges for each sample. 360 nm (Fig. 2.a-c) and 180 nm (Fig. 2.d-f) samples have dimples of the first kind (Fig. 2.b and Fig. 2.e) at Ep ≤ 475 μJ while dimples produced by phase explosion (Fig. 2.b and Fig. 2.e) were created at Ep ≥ 554 μJ for these surfaces. In the case of the 100 nm surface (Fig. 2.g-i), the surface vaporisation dimple (Fig. 2.h) was generated at Ep ≤ 250 μJ and the second dimple kind (Fig. 2.i) was found at Ep ≥ 323 μJ. For the 24 nm (Fig. 2.j-l) and 12 nm (Fig. 2.m–o) samples, the laser shots at Ep ≤ 323 μJ produced dimples by mean of the surface vaporisation whilst phase explosion dimples were produced at Ep ≥ 402 μJ. This showed that the roughness of the original surface has an influence on the laser energy fluence absorbed by surface. The surface with \({S}_{a}\) ≥ 180 nm needed higher \({E}_{p}\) than surfaces with lower roughness because of the scattering effect of the high roughness. This effect enlarges the laser beam effective area, which reduces the energy fluence [36]. Note that the intrinsic laser parameter to determine one or other ablation mechanism is energy fluence. The phase explosion ablation mechanism is therefore produced at higher energy fluence than surface vaporisation. Phase explosion dimples were generated at lower \({E}_{p}\) for 120 nm samples than that for 24 nm and 12 nm samples as a result of the differences in the respective samples’ laser reflectivity. The reflectivity of metallic materials is inversely proportional to the surface roughness because the surface relief can cause the laser radiation to reflect at angles than the nominal incident angle of 90° [33]. The reflected laser radiation away from the normal can impact again within the laser shot area, increasing the laser radiation absorbed by the material. So, a certain roughness can be beneficial to laser absorption by metallic alloys [33]. These results indicate the existence of an optimal roughness surface for LST. An excessive roughness causes a reduction of the energy fluence while a smooth surface provokes a \({E}_{p}\) reduction. The assessments of the laser beam-material interaction factors were carried out to confirm this assertion, this will be discussed later. Dimples on the surface with a Sa of 360 nm (Fig. 2.b-c) and 180 nm (Fig. 2.e–f) have an irregular circular shape due to the high surface roughness. The scattering effect of the roughness on the focussed laser beam causes a laser beam profile deformation that reduces the quality of the dimples [36].

The influences of the pulse energy, \({E}_{p}\), on the dimple width (Fig. 3.a-b) and average surface roughness, \({S}_{a}\), on the laser beam-material factors (Fig. 3.c-d), can be seen in Fig. 3. The width of the dimples (\(W\)), defined as the diameter of all the area processed by the laser pulse (ablation area and crest), was widened with increasing \({E}_{p}\), as can be in the graph of Fig. 3.a. This is due to the energy spatial distribution which is near Gaussian [45]. The dimples were wider on the surfaces with lower \({S}_{a}\) than on the higher \({S}_{a}\). This can indicate that the scattering effect of the roughness is stronger than the reflectivity effect of the smooth surfaces on the LST dimple creation. The increase of laser effective area by the roughness scattering effect decreases the energy fluence. This implies that the laser beam area that can melt the metallic material is reduced [33]. This in turns causes the reduction of the dimple width with the increase of the surface roughness.

Fig. 3
figure 3

Pulse energy influence on width, a) width as function pulse energy and b) width square vs pulse energy natural logarithm according to \({S}_{a}\) and graphs of the \({S}_{a}\) influence on the \({\varphi }_{th\left(melting\right)}\) c) and \({d}_{o\left(Theo\right)}\) d)

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The laser beam-material factors were calculated using Eqs. 7 and 8 [34, 45, 46, 59, 60] and the linear regression method in the graph data of Fig. 3.b.

$${W}^{2}={d}_{o-m}^{2}\mathrm{ln}\left({E}_{p}\right)-{d}_{o-m}^{2}\mathrm{ln}({E}_{th-m})$$
(7)
$${\varphi }_{th-m}=\frac{4 {E}_{th-m}}{\pi {d}_{o}^{2}}$$
(8)

where, \({d}_{o-m}\) is the experimentally determined focused laser beam diameter from the optical light microscopy data, \({E}_{th-m}\) is the experimental energy threshold for melting process and \({\varphi }_{th-m}\) is the fluence energy threshold for the melting process. The smooth surfaces typically showed lower \({\varphi }_{th-m}\) than higher roughness surfaces (Fig. 3.c). This indicates that the polished surface at low roughness has the most efficient laser absorption than the surface with high \({S}_{a}\). This is due to the reduction of the roughness effect on effective laser diameter enlargement [36]. The exception is the surface at 24 nm \({S}_{a}\) that has a higher \({\varphi }_{th-m}\) than that for the samples with \({S}_{a}\) of 100 nm and 180 nm. This \({\varphi }_{th-m}\) increase is due to the reflectivity effect that decreases the laser radiation absorbed by material [61]. This effect is attenuated by hydrodynamic expansion for the 12 nm samples. The low surface roughness can, moreover, result in the low resistance of the surface to the flow of molten material across the surface. This hydrodynamic expansion produces the movement of the liquid material outside of the laser impacted area [47]. This movement on the surface can be limited by surface relief that is proportional to \({S}_{a}\). These results also show that the roughness scattering effect on laser beam-material interactions is the predominant surface parameter at Sa ≥ 100 nm while the laser radiation reflection is the dominant factor for surfaces at Sa ≤ 24 nm. The melting fluence energy, \({\varphi }_{th-m}\), of the samples were slightly higher than the theoretical melting energy fluence (\({\varphi }_{Theo-m}\)) whose value is 2.625 J/cm2, calculated using Table 2 data and Eq. 9 [26, 62, 63]. The slight difference with the samples at high roughness is due the roughness scattering effect [34].

$${\varphi }_{th(Theo-m)}=\frac{\rho \left({C}_{p} \left({T}_{m}-{T}_{o}\right)+{\Delta H}_{m}\right)}{1-R} \left(\sqrt{\kappa \tau }+\frac{1}{\alpha }\right)$$
(9)

\({d}_{o-m}\) of the samples (Fig. 3.c) increased as \({S}_{a}\) is reduced because it is the focused laser beam area that can melt the SS316L. The laser beam has an energy spatial distribution close to Gaussian. Maximum fluence is in the centre of the laser spot and reduces towards the edge of the spot, so the laser spot centre can melt the material while the laser beam edge can only heat the material [30]. The surface roughness enlarges the laser beam diameter by means of laser scattering [36]. This enlargement of the laser beam diameter decreases energy fluence and therefore, the melted surface area is reduced. Although the calculated \({d}_{o-m}\) of the samples varied, all diameters were only a 20% maximum deviation from \({d}_{o\left(Theo\right)}\) (51 µm), which is reasonable.

Topography

Dimples have different topographies according to the values of \({S}_{a}\) and \({E}_{p}\), as can be seen in Fig. 4 (3D pictures) and Fig. 5 (Profile images). Dimples mainly have a shape that consists of a depression surrounded by a crest. The depression is generated by the ablation of the material through the evaporation of the material and the movement and ejection of the molten material to the outside of the laser shot area [64, 65], as mentioned in 3.1. Surface Morphology. The dimple form has a spherical cap. These dimples are therefore classified as U-type [66,67,68,69]. This geometry arises as the Gaussian peak of the laser beam possesses sufficient energy to ablate the metallic material [31, 69, 70]. Dimples with a different shape were found at Ep = 53 μJ for surfaces with 12 nm of Sa, (Fig. 4.n and Fig. 5.e). These dimples are formed of a peak in the centre of the laser impacted area that was surrounded by a valley that is, in-turn, surrounded by a crest. These dimples are classified according to their shape as “sombrero” type [31, 33, 71]. This kind of dimple is produced by the Marangoni effect that causes the movement of the liquid material to the edge and centre of the laser exposure point. This effect is caused by the thermal gradient differences in the liquid metal pool. The effect is found for the laser treatments where the melting is the dominant thermal process [31, 33]. This indicates that the 12 nm samples absorbed less laser radiation than other surfaces because melting needs less energy fluence than evaporation [47].

Fig. 4.
figure 4

3D images of the untextured a), d), g), j) and m) surface and dimples at 53 μJ b), e), h), k) and n) and at 614 μJ c), f), i), l) and o) of the 360 nm a-c), 180 nm d-f), 100 nm g-i) 24 nm j-l) and 12 nm m–o) samples

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Fig. 5
figure 5

Profile images of the untextured surface and the dimples at 53 μJ and at 614 μJ of the 360 nm a), 180 nm b), 100 nm c), 24 nm d) and 12 nm e) samples

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The crest of the dimples created by the ablation mechanism of phase explosion (Fig. 4.c, f, i, l and o) were wider and higher than the crest caused by surface vaporisation. Evaporated material pressure on the molten metal displaces the liquid material to edge of the dimple [10, 47, 65]. This increases the size of the crest. This pressure is considerable for the phase explosion owing to the confinement of the gas material into the bubble of the phase explosion [47, 72].

The quality of the dimple shape was better for the samples with smooth surface because the low relief (Fig. 5.a higher relief and Fig. 5.d low relief). Peaks and valleys of the non-textured surface cause the absorption of the laser radiation to be heterogeneous. This alters the Gaussian like shape of the laser beam as it is exposed on to the metallic surface [30]. The roughness scattering effect on the laser radiation can also modify the shape of the dimples [36].

The diameter of the dimples (\(d\)) is a texture feature that is defined as the diameter of the laser ablated area (laser exposure area without crest). Figure 6 shows the influence of \({E}_{p}\) on dimple diameter and \({S}_{a}\) on the laser beam-material interaction.

Fig. 6
figure 6

Pulse energy influence on the dimple diameter of the samples, a) diameter as function of pulse energy, b) diameter squared vs pulse energy natural logarithm, c) surface ablation energy fluence threshold vs pulse energy and d) ablation laser beam diameter against \({S}_{a}\)

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The diameter increased with \({E}_{p}\) (Fig. 6.a) as the laser beam has a Gaussian energy spatial distribution [9, 69]. \(d\) was higher on surface with low \({S}_{a}\) because of the laser scattering effect of the surface relief [36]. \({d}_{o-a}\) (focused laser beam diameter) and \({E}_{th-sa}\) (minimum laser energy to ablate the surface) were calculated using Eq. 10 [9, 34, 41, 56, 73] while \({\varphi }_{th-sa}\) (minimum laser energy fluence to ablate the surface) was estimated with Eq. 7 but with do-m and Eth-m replaced by do-a and Eth-sa.

$${d}^{2}={d}_{o-a}^{2}\mathrm{ln}\left({E}_{p}\right)-{d}_{o- a}^{2}\mathrm{ln}({E}_{th-sa})$$
(10)

The linear regression used to estimate \({\varphi }_{th-sa}\) and \({d}_{o-a}\) can be seen in Fig. 6.b. \({\varphi }_{th-sa}\) decreases with the reduction of the surface roughness as can be observed in Fig. 6.c. This seems to show that the laser scattering effect of the roughness is more predominant than the reflectivity effect for this roughness (from 12 to 360 nm). φth-sa of the samples (≈ 7 J/cm2) was lower than the theoretical ablation fluence threshold \({\varphi }_{th\left(Theo-e\right)}\) (11.168 J/cm2) that was calculated using Eq. 11 [26, 31, 58, 62, 74, 75]:

$${\varphi }_{th(Theo-e)}=\frac{\rho \left({C}_{p} \left({T}_{e}-{T}_{m}\right)+{\Delta H}_{e}+{C}_{p} \left({T}_{m}-{T}_{o}\right)+{\Delta H}_{m}\right)}{1-R} \left(\sqrt{\kappa \tau }+\frac{1}{\alpha }\right)$$
(11)

This is due to the explosive phase producing extra ablation material than the simple vaporising of the material. The explosion of the bubble provokes an increase of the amount of removed material owing to the ejection of the molten material, which is typical of the phase explosion [55]. \({\varphi }_{th-sa}\) was higher than \({\varphi }_{th-m}\) for all samples as the required energy to vaporise the material is larger than that for melting [30, 47].

\({d}_{o-a}\) increases with the decrease of \({S}_{a}\), as can be seen in Fig. 6.d. This is as a result of the reduction of laser effective area with rising \({S}_{a}\) [34]. This in turn causes the energy fluence to be higher for surfaces with low surface roughness and therefore, wider laser beam areas can be evaporated on the material.

\({d}_{o-a}\) of the samples (≈ 30 μm) are smaller than \({d}_{o(Theo)}\) (51 μm) because of the Gaussian like profile. Only the central areas of the laser beam can ablate the material, so, \({d}_{o-a}\) is lower than \({d}_{o-m}\) due to the higher energy fluence required for vaporising process than melting [30].

The influence of \({E}_{p}\) and \({S}_{a}\) on the depth of the dimples and the depth related laser-material interactions can be found in Fig. 7. All U-type dimples were deep while the sombrero-like dimples had raised central point (dimples on 12 nm surface at 53 μJ). These sombrero-like dimples were excluded from the analysis of \({S}_{a}\) and \({E}_{p}\) influence on dimple depth (\(De\)). An increase in \({E}_{p}\) deepens the dimples for all surface roughnesses (Fig. 7.a) as the rate of ablation is proportional to this laser parameter [64]. The samples with lower \({S}_{a}\) commonly have deeper dimples than the samples with high \({S}_{a}\). This is due to the reduction of the roughness scattering effect with decreasing \({S}_{a}\) [36]. The two exceptions were the dimples on \({S}_{a}\) = 360 nm samples that were deeper than that for samples with lower roughness, and \({S}_{a}\) = 12 nm sample dimples that were shallower than the \({S}_{a}\) = 24 nm sample dimples. In the case of the \({S}_{a}\) = 360 nm sample dimples, this can be due to the large relief of the original surface. On such surfaces, the difference of the height between the original surface peaks and valleys can reach 3 μm. This height can be of the same scale as the depth of the dimples for this surface. Thus, the depth of the dimples for the \({S}_{a}\) = 360 nm samples were greater than for those samples with low \({S}_{a}\). For the \({S}_{a}\) = 12 nm sample dimples. The explanation is the high reflectivity of the smooth surfaces [47].

Fig. 7
figure 7

Pulse energy on dimple depth of the samples, a) depth as function pulse energy, b) depth vs pulse energy natural logarithm, c) depth ablation energy fluence threshold against roughness, d) energy depth penetration vs. roughness and e) geometrical factor on function to roughness

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Energy depth penetration (\(l\)) (the depth to which absorbed laser energy is transferred into the material) and pulse energy threshold (\({E}_{th-da}\)) (necessary minimum pulse energy to create a dimple with visible depth) were calculated using the graph of Fig. 7.b. (linear regressions) and Eq. 12 [26, 60, 64, 74].

$$De=l\mathrm{ln}\left({E}_{p}\right)-l\mathrm{ln}({E}_{th-da})$$
(12)

Depth ablation energy fluence (\({\varphi }_{th-da}\)) were estimated with Eq. 8 but the \({d}_{o-m}\) and \({E}_{th-m}\) are replaced by \({d}_{o-a}\) and \({E}_{th-da}\). This was carried out to have an intrinsic and comparable value between samples. \({\varphi }_{th-da}\) of all samples (Fig. 7.c) were higher than all \({\varphi }_{th-sa}\) and \({\varphi }_{th-e}\), which can indicate the micro plasma generation at the bottom of the dimple. The evaporated material can interact with the laser radiation, which increases the temperature of the gas. If the material in gas state reaches a certain temperature, this can convert to plasma that can absorb, reflect, and scatter the laser radiation. This can diminish the laser energy absorbed by the material. The plasma effect on the laser radiation is often called the “plasma shielding effect” [48, 72, 76,77,78]. It is noted that plasma can take from 10 ps to a few ns to form [77] and therefore, this can be produced during the laser pulse (200 ns pulse length). Plasma is only created in the centre of the dimple due to the high energy fluence that can be found in the centre of the laser spot [48]. \({\varphi }_{th-da}\) was increased with reducing \({S}_{a}\) until \({S}_{a}\) = 180 nm. This is as a result of the reduction in the roughness laser scattering effect that decreases the laser effective area [34]. This in turns enlarges the effective energy fluence. The temperature of the plasma is proportional to laser energy fluence and the plasma time generation is inversely proportional to this laser parameter. Plasma absorptivity is proportional to the increase in plasma temperature [72]. The smoother surface therefore produces a stronger plasma shielding effect than rougher surfaces up to \({S}_{a}\) = 24 nm. \({\varphi }_{th-da}\) of the \({S}_{a}\) = 24 nm and \({S}_{a}\) = 12 nm samples were lower than that for other samples due to the reflectivity effect. Part of the laser radiation is reflected by the metallic material, which decreases the laser energy absorbed by material [79]. This decreases the amount of the evaporated material that in turns reduces the density of the plasma. The plasma shielding effect is proportional to its density [48, 72, 76, 77]. Thus, the plasma shielding effect is weakened. So, the laser radiation absorbed by the material is increased as a result of the reduction of the plasma shielding effect. Note that the plasma shielding effect was absent in the case of the surface features (melt and ablation widths / diameters) because the plasma was only produced on bottom of the dimple. The \({S}_{a}\) = 24 nm (18 J/cm2) and \({S}_{a}\) = 12 nm (17 J/cm2) sample \({\varphi }_{th-da}\) were higher than \({\varphi }_{th-e}\) (11.168 J/cm2) as the plasma shielding effect still had influence on the laser radiation observed [72].

The influence of \({S}_{a}\) on energy depth penetration,\(l\), is similar to the case of \({\varphi }_{th-da}\) as can be seen in Fig. 7.d. This can indicate that the \(l\) is influenced by the same processes as\({\varphi }_{th-da}\). The value of this factor is lower than theoretical energy depth penetration \({l}_{Theo}\) (858 nm) that is calculated using Eq. 13 [31, 45, 57, 80, 81] and the data in Table 2.

$${l}_{Theo}=\sqrt{\tau \kappa }+\frac{1}{\alpha }$$
(13)

This difference can be quantified through the geometrical factor (\(\zeta\)) that is estimated using the Eq. 14 [31, 45, 80]. It is noted that the influence of \(\alpha\) on \({l}_{Theo}\) is minimum for nanosecond pulsed laser texturing on metallic materials.

$$\zeta =\frac{\sqrt{l-\frac{1}{\alpha }}}{\tau \kappa }$$
(14)

Figure 7e shows that the \({S}_{a}\) = 100 nm samples have the best surface to absorb the laser radiation in depth as this surface has \(\zeta\) nearest to one (≈ 0.7). An excessive roughness can produce a heterogeneous absorption of the laser in depth that decreases the effectiveness of this process [34] while an extremely smooth surface causes a reflectivity effect that diminishes the laser radiation absorbed by the material [61].

Conclusions

The present study shows that the effect of the original surface roughness on laser surface texturing in the form of individual dimples. The dimples are generated via two ablation mechanisms: normal evaporation at low energy and phase explosion at high fluence. Initial surface roughness has differing influences according to the dimple features. The quality of the shape of the dimples is improved with the reduction in the surface roughness while more energetic ablation mechanisms were found at lower pulse energy for the 100 nm samples. Two types of dimples can be created with the correct combination of laser parameter and surface roughness. The U-type dimple is the more common kind, while the sombrero-like type dimple is produced at minimum pulse energy (53 μJ) on \({S}_{a}\) = 12 nm samples. The increase of the dimple width requires less pulse energy for the smooth surfaces (\({S}_{a}\) = 12 nm) than for rough surfaces. Dimples are deepened easier on \({S}_{a}\) = 24 nm samples than other samples. The highest energy depth penetration is found for the \({S}_{a}\) = 100 nm sample. This difference between the surface laser texturing processes with depth is due to the generation of the plasma shielding effect at the bottom of the dimple, which only affects the dimple depth.

According to the outcomes of this study, the following recommendation can be made about the surface for laser surface texturing. The optimum surface to produce wide dimples is the surface at \({S}_{a}\) = 12 nm while the deepest dimples are easier to create on polished surfaces with \({S}_{a}\) = 24 nm. The samples at \({S}_{a}\) = 100 nm are a suitable surface to fabricate phase explosion dimples with large energy depth penetration value.

This information can help to improve the efficiency of laser surface texturing process on SS316L, which can reduce the cost of the process to industry. This study also indicates how to generate different types of dimples and design their features.