Effect of Different Laser Parameters on Surface Physical Characteristics and Corrosion Resistance of 20 Steel in Laser Cleaning

Abstract

The rusting of metals brings huge losses to the industry every year, and post-treatment of rusted metals to restore their properties to the initial state is a hot topic of current research. In particular, 20 steel, which is widely used in various structural components such as ships, is prone to oxidation in atmospheric environment. Therefore, in this study, a nanosecond pulsed laser was used to remove the rust layer on the surface of 20 steel. The effects of different energy densities and spot overlap rates on the roughness, surface morphology, chemical composition, microhardness and corrosion resistance of the rust layer were analyzed. The results showed that the best cleaning effect was achieved at an energy density of 4.26 J/cm² and a spot overlap rate of 75%. Under these conditions, the rust layer was completely removed without damage to the substrate, and it even improved the corrosion resistance of 20 steel. At energy densities of 1.42 J/cm² and 2.84 J/cm², the rust layer was not completely removed, while at 5.68 J/cm², the rust layer was removed but the substrate was damaged. In addition, the mechanism of rust removal and substrate damage is discussed.

1. Introduction

Low-cost carbon steels, extensively utilized in marine engineering for components like ship decks, pipelines, and drilling platforms, face significant longevity challenges due to corrosion and rust. The economic impact of metal rusting is substantial with an estimated annual cost of approximately 2.4 trillion dollars [1]. This issue is particularly acute for 20 steel, which is commonly used in marine environments. Its low carbon and alloy content makes its surface more susceptible to rust-based contaminants [2], potentially leading to a drastic reduction in the lifespan of ship hulls and creating safety hazards. Consequently, developing low-cost methods for treating rusted metal surfaces to restore their original performance has become a focal point of current research.

Presently, the most commonly adopted methods for cleaning metal surfaces include physical cleaning, chemical cleaning, and high-pressure water jet cleaning [3,4]. However, these techniques often suffer from drawbacks such as low efficiency, imprecision, severe damage to material surfaces, environmental pollution, and potential health risks for personnel [5,6,7,8]. In contrast, laser-cleaning technology offers substantial benefits over traditional processes in terms of flexibility, consumable costs, and environmental impact. It has gained widespread application in diverse fields, including pre-soldering cleaning, metal decontamination, and the restoration of cultural artefacts [9,10,11]. Zhang et al. [12] identified that at low energy densities, the primary mechanism of laser cleaning of metal oxides is ablation, where high-energy pulsed lasers not only cause phase explosion but also facilitate oxide layer removal through pressure-induced shock effects. Ma et al. [13] employed a fiber laser to remove rust oxides from Q345 steel commonly used in the mining industry and explored the surface integrity at different laser powers to determine the optimum cleaning parameters and confirm the feasibility of laser cleaning. Xing et al. [9] investigated rusty steel using a combination of molten salt pretreatment and laser cleaning, noting an enhanced ease of rust layer removal at lower laser irradiation intensities. Guo et al. [5] reported that laser descaling could reduce the annual corrosion rate of steel surfaces more effectively than acid descaling. Additionally, Lu et al. [14] utilized a nanosecond ultraviolet laser for the removal of microorganisms and contaminants from the rust layer on AH36 steel surfaces. At an energy density of 5.30 J/cm², the corrosion resistance of the laser-cleaned surface was found to be threefold higher than that of the microbiologically contaminated surface post-recovery. For the shipbuilding field where steel is in high demand, the cost-effective 20 steel has a natural advantage. The above report shows that the corrosion resistance of the material after laser cleaning has been improved while reducing the cost, providing new ideas for the application of laser cleaning in the shipbuilding field.

Despite numerous studies conducted in the field, the primary goal of laser cleaning remains the effective removal of corrosion layers without inflicting damage to the substrate material. Furthermore, understanding how laser treatment can enhance the corrosion resistance of metals by altering the surface structure, composition, and grain size during the corrosion layer removal process is of paramount importance for practical applications. Chen et al. [15] explored how the laser processing speed influences the roughness and hardness of the steel surface, examining the effects of various parameters on surface properties post-laser treatment. Similarly, Ouyang et al. [16] applied Taguchi’s method in experimental design for laser cleaning, discovering that adjustments in laser pulse frequency and scanning speed can significantly enhance the cleaning efficiency while concurrently reducing the system’s specific energy. These investigations have contributed valuable insights into the laws governing surface structure modifications of materials subjected to laser cleaning.

In summary, during the laser-cleaning process of steel materials, different laser parameters exert distinct impacts on the surface characteristics of the cleaned material. The interplay of these parameters and their influence on the changes in the material’s surface structure and composition is especially crucial. Understanding the mechanisms behind the removal of the corrosion layer and the subsequent changes in the material’s corrosion resistance is key to enhancing the value of metal applications. Therefore, this study employs an infrared nanosecond pulsed laser to clean the rust layer on the surface of 20 steel. It investigates the effects and improvement mechanisms of laser energy density and spot overlap rate on the micromorphology, mechanical properties, and corrosion resistance of the 20 steel surface, aiming to guide practical industrial applications.

2. Materials and Methods

2.1. Materials

The laser-cleaning experiments were conducted using 20 steel, which is a widely used material in the marine sector. The basic elemental composition of the material is presented in

Table 1. Nominal chemical composition of 20 steel (wt%).

Element	C	Si	Mn	P	Ni	Cr	Cu
Mass faction	0.17	0.17	0.35	0.035	0.30	0.25	0.25

. The steel was cut into small pieces measuring 20 mm × 20 mm × 1 mm (length × width × thickness). Following a 120 h salt spray test using a salt spray machine with a constant temperature of 35 °C [17], relative humidity of 95%, and NaCl solution concentration of 5%, a substantial amount of rust formed on the surface of the sample.

2.2. Laser-Cleaning Experiment

Figure 1a presents a schematic representation of the pulsed laser-cleaning apparatus, comprising a laser source, a galvanometer scanning system, and a control card. During the experimental procedure, the field mirror’s focal length was set at 180 mm with a laser spot diameter of 0.05 mm and a repetition frequency of 60 kHz. The efficiency of the laser-cleaning process is primarily influenced by the laser energy density and the rate of spot overlap. Additionally, the power density of the laser and the diameter of the laser beam spot are critical determinants in the efficacy of the cleaning process [18]. The equation for laser energy density is as follows:

$$\mathsf{\epsilon }=\frac{4\mathrm{{\rm P}}}{\pi D^2ƒ}$$

(1)

The laser energy density ε is a function of the laser spot diameter $D$ and the laser pulse repetition frequency $f$. When $D$ and f are held constant, the laser power $\mathrm{P}$ can be modulated by adjusting the laser’s operating current. This adjustment enables precise control over the laser energy density $\mathsf{\epsilon }$, thereby influencing the outcomes of the laser-cleaning process.

The spot overlap rate equation is as follows [19]:

$$\mathsf{\lambda }=(1-\frac{\mathsf{\nu }}{Dƒ})\times 100\%=(1-\frac{L}{D})\times 100\%$$

(2)

The scanning speed of the galvanometer $\mathsf{\nu }$, the laser spot diameter $D$, the laser pulse repetition frequency $f$, and the distance between adjacent spot centers L were key parameters. The non-energy density and spot overlap rate were regulated by varying the laser’s loading current and scanning speed. For these experiments, the selected spot overlap rates were 25%, 50%, 75%, and 80%. Correspondingly, the laser energy densities were set at 1.42 J/cm², 2.84 J/cm², 4.26 J/cm², and 5.68 J/cm².

2.3. Surface Analysis

The surface morphology of the samples post-laser cleaning was analyzed using Field Emission Ring Scanning Electron Microscopy (SEM) (Carl Zeiss, GeminiSEM300, Oberkochen, Germany). For characterizing the chemical composition of the surfaces before and after the cleaning process, Energy-Dispersive X-ray Spectroscopy (EDS) and X-ray Diffraction (XRD) (SmartLab, Tokyo, Japan) were employed. The SEM and surface roughness of each specimen were determined by averaging the measurements of four different surface points. The XRD measurements encompassed a 2θ diffraction angle range from 10° to 80° with incremental steps of 0.02°. The surface roughness of the cleaned samples was quantified using Laser Scanning Confocal Microscopy (CLSM) (Olympus, OSL5000) with parameters varied to assess their impact. Microhardness evaluations pre- and post-laser cleaning were conducted using a digital micro-Vickers hardness tester, applying a load of 500 g. The microhardness for each specimen was ascertained by averaging measurements from four distinct surface points.

2.4. Electrochemical Experiments

The electrochemical behavior of 20 steel post-laser cleaning was studied using an electrochemical workstation [20]. Figure 1c illustrates the schematic setup of this workstation. To enhance the accuracy in measuring corrosion resistance, a hole was opened on the vessel’s exterior, isolating the laser-cleaned area for assessment and thereby mitigating the influence of non-tested surfaces on the results. In these electrochemical experiments, 20 steel served as the working electrode, accompanied by a platinum plate as the auxiliary electrode, and saturated calomel was used as the reference electrode. The workstation facilitated electrochemical testing in a 3.5 wt% NaCl solution.

3. Experimental Results and Analysis

3.1. Microstructure Analysis

Figure S1 (in Supplementary Material) illustrates the surface morphology of 20 steel subjected to laser cleaning at varying laser energy densities and spot overlap rates. Figure 2c–f depict the micromorphology of the surfaces cleaned at a spot overlap rate of 75% with different laser energy densities. The uncleaned original sample displays a non-smooth corrosion layer surface (Figure 2a) characterized by an abundance of protruding oxides (Figure 2b). At a laser energy density of 1.42 J/cm² (Figure 2c), there is a notable reduction in surface roughness, leaving only a few small pits. Increasing the laser energy density to 2.84 J/cm² results in the detachment of parts of the corrosion layer (Figure 2d), although metal oxides remain on the surface. Further escalation of the laser energy density to 4.26 J/cm² (Figure 2e) smoothens the material surface, effectively removing noticeable oxides and demonstrating superior cleaning efficacy. However, at a laser energy density of 5.68 J/cm², the excessive energy inflicts damage to the substrate, which is evidenced by a clear melting phenomenon and the formation of irregular craters on the sample’s surface.

In this study, Energy-Dispersive X-ray Spectroscopy (EDS) was employed to quantify the oxygen content on metal surfaces, serving as an indicator of the extent of corrosion layer removal. As depicted in Figure 3a, the oxygen content of samples subjected to laser cleaning at varying laser energy densities and spot overlap rates was analyzed. The findings demonstrate that an elevation in both laser energy density and spot overlap results in a reduction in oxygen content. This reduction is attributed to the enhanced capability of the laser in removing the corrosion layer due to the increased parameters. However, excessively high energy densities and spot overlap rates can cause laser-induced damage to the substrate. Particularly in an air environment, such damage is further exacerbated by oxidation of the substrate material. Consequently, it is observed that an increase in laser energy density from 4.26 to 5.68 J/cm² paradoxically increases the surface oxygen content. A similar trend is noted when the spot overlap rate is raised from 75% to 80%.

3.2. Surface Composition Analysis after Laser Cleaning

The surface roughness is a critical parameter for assessing the efficacy of laser cleaning. As illustrated in Figure 3b, the surface roughness of materials subjected to laser cleaning exhibits a trend of initial decrease and subsequent increase in response to the escalation of laser energy density and spot overlap rate. Optimal conditions, with a laser energy density of 4.26 J/cm² and a spot overlap rate of 75%, result in the lowest surface roughness, which is measured at 0.95 μm. However, further increments in either the laser energy density or spot overlap rate contribute to surface damage and an increase in roughness.

Figure 3c displays the X-ray diffraction (XRD) patterns of laser-cleaned samples at varying laser energy densities, maintaining a consistent spot coupling ratio of 75%. The surface phases of corroded 20 steel predominantly consist of Fe, α-FeOOH, β-FeOOH, γ-FeOOH, and Fe₃O₄ [21] with each phase exhibiting distinct relative peak intensities. This variation is attributed to the corrosion environment’s NaCl content, where the Cl^- ions induce the formation of β-FeOOH in the rust layer [22]. During the laser-cleaning process, the unstable β-FeOOH phase vanishes, and the intensities of the stable phases α-FeOOH and Fe₃O₄ gradually diminish with increasing laser energy, whereas the Fe-phase peaks intensify. At an energy density of 4.26 J/cm², both the Fe₃O₄ and α-FeOOH phases completely disappear. The reason for this phenomenon is the initial presence of metal oxides on the surface of the 20-gauge steel, which masks the iron phase peaks. As the laser eradicates the corrosion layer, the underlying substrate is progressively revealed, leading to an enhanced intensity of the iron phase. The total absence of oxide spectral lines at a laser energy of 4.26 J/cm² corroborates the thorough removal of the corrosion layer. Furthermore, the emergence of Fe₃O₄ peaks at excessively high energies confirms the oxidative effect of laser-induced damage to the substrate.

3.3. Microhardness Analysis

Figure 4a illustrates the variations in surface microhardness of samples subjected to laser cleaning at diverse energy densities. To ensure the reliability of the data, the testing methodology depicted in Figure 4b was employed with the final microhardness value representing an average derived from four distinct test points. The findings reveal that laser cleaning at various energy densities consistently enhances the surface hardness of the material. This increase in microhardness can be attributed to the fact that the hardness of the loose metal oxides, initially present on the surface, is lower compared to that of the substrate material. Consequently, as the laser progressively removes the corrosion layer, the material’s microhardness continually increases. The peak microhardness value observed was 142.98 HV, achieved at a laser energy density of 4.26 J/cm². Beyond this point, further increments in laser energy density resulted in negligible changes in the material’s microhardness.

3.4. Corrosion Behavior Analysis

Figure 5 delineates the correlation between corrosion potential (Ecorr) and corrosion current density (Icorr) across varying laser energy densities and spot overlap rates. Ecorr serves as an indicator of a material’s susceptibility to corrosion under electrochemical conditions, while Icorr quantifies the rate of corrosion. Typically, materials exhibiting Icorr values are considered to possess superior corrosion resistance. Concurrently, Figure 6 compares the corrosion potential and current of the material post-laser cleaning against the laser-cleaning parameters, revealing an Ecorr of 752 mV on the rusted 20-gauge steel sample’s surface and an Ecorr of 541 mV on the unrusted sample. The reduction in Icorr following laser cleaning signifies an enhancement in the corrosion resistance of the material’s surface. Remarkably, the sample treated with a laser energy density of 4.26 J/cm² and a 75% spot overlap exhibited the lowest Icorr among all samples, indicating a notable improvement in corrosion resistance relative to the original 20-gauge steel. Conversely, increasing the laser energy density to 5.68 J/cm² diminished the corrosion resistance, suggesting that excessive laser energy can inflict damage on the substrate.

Figure 7 shows the electrochemical impedance spectrum (EIS) of 20 steel. Generally, the diameter of the Nyquist plot curve is indicative of the charge transfer resistance with a larger diameter suggesting enhanced corrosion resistance. Notably, the impedance diameters of the sample surfaces after laser cleaning exceeded those of the unpolarized surfaces, demonstrating that laser cleaning effectively improves corrosion resistance. The maximum curve diameter, indicating optimal corrosion resistance, was observed at a laser energy density of 4.26 J/cm². Furthermore, to provide a more comprehensive understanding of the surface corrosion behavior of rusted 20-gauge steel post-laser cleaning, an equivalent circuit model was employed to fit the EIS data. Figure 8 illustrates this model, where R_s represents the solution resistance, CPE_dl denotes the double-layer capacitance, and R_ct signifies the charge transfer resistance. To enhance the precision of the fitting, a Constant Phase Element (CPE) was utilized in place of traditional capacitance.

$$ZCPE=\left[Q(j\omega )n\right]-1$$

(3)

where $Q$ signifies the magnitude of the CPE, $j$ represents the imaginary unit, $\omega$ stands for the angular frequency, and n denotes the exponent of the CPE index. The specific fitted values are presented in

Table 2. EIS parameters of the equivalent circuit for test samples.

Specimen	Rs (Ω cm2)	CPEdl	Rct (Ω cm2)
Rust	36.98	0.78771	943.4
1.42 J/cm2	37.43	0.78488	1114
2.84 J/cm2	37.78	0.80803	1178
4.26 J/cm2	37.61	0.81421	4116
5.68 J/cm2	37.45	0.81096	1544
Bare	37.46	0.69734	3379

, where it is worth noting that a bigger charge transfer resistance R_ct generally indicates superior corrosion resistance. Upon analyzing the data presented in Table 2, it becomes evident that the corrosion resistance of the laser-cleaned surfaces exhibits a significant improvement when compared to the initial untreated surfaces. Notably, the highest level of corrosion resistance is achieved at an energy density of 4.26 J/cm². Its R_ct is 1.218 times that of the original 20 steel.

3.5. Rust Removal Mechanisms

Figure 8 illustrates the transformations occurring on the sample surface as the laser energy density is adjusted. Initially, as laser energy is applied to the rust layer, thermal expansion causes the rust particles to break their surface adsorption with the metal substrate via vibrational mechanisms. This initiates the removal of the rust layer, including contaminants. As laser energy further increases and reaches the melting point of the rust layer, an additional ablation mechanism takes effect, leading to some substrate damage. Notably, at a laser energy density of 4.26 J/cm², the sample’s surface exhibits a flat and smooth morphology with clear removal of the rust layer compared to surfaces cleaned at lower energies. However, continued energy escalation results in substrate damage and the formation of a new oxide layer.

Under the influence of higher laser energy, the rust layer on the surface of 20 steel undergoes effective removal with excess energy being directed toward substrate ablation. This process leads to the formation of small craters and protrusions due to the counter-impact pressure caused by evaporation. As the laser beam progresses, thermal energy rapidly dissipates into the substrate or previously solidified layers, which is a phenomenon closely linked to the substrate’s thermal conductivity. Additionally, the thickness of melting and the duration of melting in the substrate are positively associated with laser fluence. Furthermore, different scanning speeds influence the gradient flow of the melt pool. In Equation (2), the laser-scanning speed exhibits a negative correlation with the spot overlap rate, implicating the spot overlap rate in the gradient flow of the melt pool. When laser energy exceeds a certain threshold, a portion of the substrate material melts and disperses in all directions, which is a significant factor in the formation of pits and protrusions.

In Figure 9, the impact of varying spot overlap rates on the material surface is depicted at an energy density of 5.68 J/cm², where the rust layer has been completely removed, and the substrate experiences ablation due to the surplus laser energy. At lower spot overlap rates, the luminous flux per unit area is reduced, resulting in limited material absorption of heat and subsequent melting. The melted material quickly cools, leading to collisions between newly melted and already cooled material in a short timeframe. This collision process gives rise to the formation of numerous dense, wave-like streaks, as evident in Figure S1. When the spot overlap rate reaches 75%, the prominence of the wavy streaks on the sample surface diminishes, and a few pits emerge, rendering an overall smoother surface morphology. At this point, material melting and cooling rates reach a moderate equilibrium. Material that immediately melts upon laser irradiation pushes incompletely melted material to flow in various directions, which is driven by surface curvature gradients, surface tension, and gravity. Consequently, the substrate surface attains a flattened appearance. With further increases in the spot overlap rate, the number of pits on the substrate surface multiplies, indicating a slower cooling rate of the material under laser influence. Additionally, a temperature disparity arises between the surface of the solidifying zone and its front [23]. Concurrently, material flows due to surface tension gradients [24], leading to the gradual formation of numerous pits on the substrate’s surface.

4. Conclusions

Through the laser-cleaning test on the surface of corroded 20 steel, the effect of laser energy density on the surface morphology, surface elemental composition, surface roughness, surface microhardness and surface corrosion resistance of corroded 20 steel was investigated, and the effect of laser descaling mechanism and ablation on the surface of 20 steel was analyzed. The conclusions of this study are as follows:

(1)

Through this study, at the laser energy density of 1.42–4.26 J/cm², the removal of the rust layer on the surface of 20 steel is effective, especially at 4.26 J/cm²: the surface rust layer is basically removed without causing damage to the sample surface.

(2)

Infrared nanosecond pulsed laser can effectively remove the rust layer of 20 steel. The removal mechanism of the rust layer is mainly ablation. When the laser energy is higher than 4.26 J/cm², the substrate absorbs too much laser energy and melts the substrate.

(3)

Compared with the traditional cleaning method, when the laser energy density is 4.26 J/cm², with a spot overlap rate of 75%, laser cleaning not only does not reduce the corrosion resistance of 20-gauge steel but also improves the corrosion resistance of the original 20-gauge steel 1.218 times.

(4)

The morphological evolution of the sample surface after laser ablation at high energy density with different spot overlap rates is discussed; the key lies in the different cooling times of the molten material at different laser-scanning speeds at high energies, which leads to different distributions of the molten material flow around. This evolution provides a reference for the subsequent topographic changes of laser-cleaned substrates.