Dynamic water film assisted laser micromachining of micro-array structured surfaces for inducing hydrophobicity: analysis model and experimental study

Jinda Yang a, Zhongxu Lian *ab, Haonan Jin a, Jiaqi Wang *a, Jinkai Xu a and Yanling Tian b
aMinistry of Education Key Laboratory for Cross-Scale Micro and Nano Manufacturing, College of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130022, China. E-mail: lianzhongxu@cust.edu.cn; jqwang@cust.edu.cn
bSchool of Engineering, University of Warwick, Coventry CV4 7AL, UK

Received 11th March 2026 , Accepted 19th April 2026

First published on 24th April 2026


Abstract

With the advantages of non-contact processing and high precision, laser micromachining technology has shown great potential for applications in functional surface fabrication. However, thermal damage issues inevitably arise during the machining process. This study takes Ti6Al4V titanium alloy as the research object and compares the processing effects of laser direct processing (LDP) and dynamic water film assisted laser machining (DWFALM). The effects of varying laser processing spacing on surface morphology and wetting properties were investigated. The results indicate that, compared with the conventional LDP technique, DWFALM reduces the extent of the heat-affected zone (HAZ), suppresses molten layer formation, and mitigates microcrack defects. By adjusting the scanning spacing, a superhydrophobic surface with a contact angle (CA) of up to 167.6° and a rolling angle (RA) as low as 2.2° was fabricated. In addition, the CA prediction model established in this study was consistent with the experimental measurements, with an average error below 2%. This research achievement not only provides theoretical guidance for the controllable preparation of superhydrophobic surfaces but also offers new approaches for achieving efficient and low damage surface processing. The micro-array-structured superhydrophobic Ti6Al4V surface fabricated by DWFALM shows potential for applications in anti-fouling, anti-icing, seawater desalination, and related fields.


1. Introduction

Titanium alloys are widely used in the aerospace industry for critical components such as aircraft engine parts, airframe structures, and landing gear because of their high strength-to-weight ratio, thermal stability, fatigue resistance, and environmental resistance.1–5 However, low-temperature environments inevitably occur with increasing altitude. In severe cases, ice accretion on wings may result in reduced altitude and airspeed, thereby increasing the risk of aviation accidents.6,7 Therefore, developing an efficient and cost-effective method for fabricating superhydrophobic surfaces is of utmost importance.

The wettability of a material surface is primarily determined by its microscale geometric features and interfacial energy characteristics.8,9 Inspired by natural surfaces such as lotus leaves,10,11 rice leaves,12,13 and water striders,14,15 superhydrophobicity has attracted increasing attention in both fundamental research and practical applications. Representative applications include self-cleaning,16,17 antibacterial properties,18,19 oil–water separation,20,21 corrosion resistance,22–24 anti-icing,25–28 and seawater desalination,29–31 among others.

Researchers have employed various methods to fabricate superhydrophobic surfaces, including conventional machining,32–35 wire electrical discharge machining (WEDM),36–39 3D printing technology,40–43 coating methods,44–47 anodic oxidation,48–51 and laser etching.52–56 Prasad et al.32 fabricated a superhydrophobic surface with hierarchical micro–nano structures on brass alloy using diamond turning process, achieving a CA of approximately 152°. The study also established a predictive model for the relationship between structural dimensions and surface static CA. Wang et al.36 employed WEDM combined with hydrochloric acid electrochemical etching to create micro–nano structures on beryllium copper alloy surfaces. After stearic acid modification, a superhydrophobic surface with a CA of 167.1° and a RA as low as 2.4° was achieved, demonstrating excellent corrosion resistance. In another study, Wang et al.41 fabricated degradable polylactide acid porous membranes using 3D printing technology. Following superhydrophobic nano-SiO2 spray modification, the membranes exhibited a CA of 154.64° and outstanding oil–water separation performance, with a separation flux as high as 81.89 mL cm−2 min−1. Zhu et al.46 successfully developed a superhydrophobic coating with photothermal self-healing functionality. By incorporating hydrophobic SiO2 nanoparticles and perfluorodecyltrimethoxysilane nanospheres, the coating achieved a CA of 155.5° and a RA of 1.9°, and its anti-icing performance was improved. Li et al.48 fabricated a stearic acid-modified CeO2 composite coating on AZ31B magnesium alloy surfaces via low-pressure anodic oxidation combined with hydrothermal method, exhibiting superhydrophobicity with a CA of 164.7°, along with self-cleaning and self-healing properties.

In addition to the above methods, laser etching, as a flexible and controllable micro/nano fabrication technique, has also been widely employed to construct superhydrophobic surfaces. Xu et al.52 fabricated bionic mastoid micro/nano structures on LPBF–NiTi alloy using nanosecond laser processing combined with ultrasonic fluorination treatment, achieving a superhydrophobic surface with a CA of 157° and excellent corrosion resistance. Li et al.53 employed a femtosecond laser to fabricate periodic micro/nano structures on a stainless-steel surface via single-line array etching. After fluoroalkylsilane modification, the surface achieved a contact angle of 154° and a RA of only 4°, demonstrating excellent anti-icing performance, with a 122% extension in freezing time and an ice adhesion strength of 19.4 kPa. Sun et al.54 employed a nanosecond laser to construct honeycomb microcavity arrays on a copper substrate, which were subsequently filled with SiO2 nanoparticle/fluorinated epoxy composites. The resulting surface achieved a CA of 160° and a sliding angle of 4°. After abrasion testing with 200 m of sandpaper under a load of 2.5 kPa, the contact angle remained above 150°, demonstrating excellent mechanical durability. Xie et al.55 employed a direct laser etching technique to construct hierarchical nanosphere structures on the surface of silicone rubber. The modified surface achieved a contact angle of 154° and a sliding angle of 5°. It maintained superhydrophobic stability under a dynamic pressure of 1960.2 Pa and exhibited excellent self-cleaning and anti-icing properties.

Although the aforementioned processing methods can successfully fabricate superhydrophobic surfaces, each approach still faces critical challenges that need urgent resolution. Mechanical machining is often accompanied by tool wear and residual stress, while WEDM is subject to electrode wear and thermal damage. Three-dimensional printing is limited by weak interlayer bonding and low processing efficiency, and anodic oxidation is constrained by the use of strongly acidic or alkaline electrolytes. Coating-based methods may also raise reliability concerns because of limited interfacial bonding strength. Nanosecond laser processing offers flexibility and efficiency, but it tends to generate a HAZ, recast layers, and microcracks. Femtosecond laser processing can reduce thermal damage,57–60 although its photon and equipment costs remain a barrier to large-scale industrial application.

DWFALM is an efficient, low-damage micromachining technique in which the cooling and flushing effects of the dynamic water film during processing help suppress defects commonly found in conventional laser processing, such as recast layers, an enlarged HAZ, and microcracks. This has supported the application of DWFALM in the fabrication of macro-/microstructures.61–68 Tangwarodomnukun et al.62 used DWFALM to form a flowing water layer on Ti6Al4V surfaces, thereby reducing the HAZ and material redeposition. This method also enabled the fabrication of precision grooves with reduced thermal damage, and the groove morphology could be tuned by adjusting the waterjet velocity to produce narrower and deeper microstructures. Feng et al.65 compared the effects of LDP and DWFALM on the surface quality of monocrystalline 4H-SiC. Their results showed that the microgrooves produced by LDP had M-shaped cross-sectional profiles, with material accumulation at the edges, as well as a 50–100 µm wide HAZ and scaly recast layers. In contrast, DWFALM-processed samples exhibited relatively smooth sidewalls with no obvious defects, and recast layers and the HAZ were scarcely observed, indicating improved machining precision. Zhou et al.67 investigated water film behavior during DWFALM of monocrystalline silicon, with particular attention to the effects of water layer geometry and thickness on laser propagation and the influence of water flow velocity and pressure on microgroove morphology. Their experimental and simulation results showed a negative correlation between microgroove depth and water flow velocity. Together, these studies suggest that DWFALM is a feasible approach for fabricating high-quality, low-damage microstructures. However, its use in superhydrophobic surface fabrication remains relatively underexplored, and the associated theoretical framework has not developed as rapidly as the experimental work.

This study presents an experimental investigation on the fabrication of superhydrophobic micro-array structures on Ti6Al4V substrates using DWFALM. The remainder of this paper is organized as follows. Section 2 establishes a predictive model for the CA of water droplets on microgroove array surfaces based on force balance, taking into account the effects of gravity, structural support, and surface tension. Section 3 describes the experimental setup, design methodology, materials, and characterization techniques. Section 4 first provides a comparative analysis of the effects of LDP and DWFALM on the surface and cross-sectional morphologies of microgrooves, as well as their thermal damage behavior. Subsequently, micro-array structures were fabricated by DWFALM to evaluate their wettability, and the experimentally measured contact angles were compared with the model predictions. Section 5 summarizes the main findings and conclusions of this study. This work provides a feasible approach for fabricating low-damage, large-area micro-array structures on difficult-to-machine materials, with potential applications in self-cleaning, oil–water separation, antibacterial surfaces, and droplet manipulation.

2. Mathematical model for surface wettability of microarray groove structure

Numerous plant and animal surfaces in nature exhibit excellent superhydrophobic properties, and these surfaces generally have rough and complex morphologies and low surface free energies. To develop surfaces possessing exceptional superhydrophobicity, constructing precise geometric models is of paramount importance.

When a spherical water droplet, as it exists naturally in air, lands on the surface of a workpiece within an atmospheric environment, its morphology undergoes alterations due to the combined influences of gravity, surface tension, and additional gravitational forces. Fig. 1 illustrates the differences between the 3D and 2D views of a liquid droplet on a microstructured surface, along with the parameters that affect CA.


image file: d6sm00212a-f1.tif
Fig. 1 The 3D and 2D views of liquid droplets on a microstructured surface. (a) Isometric view of a water droplet placed on a microstructured surface. (b) Parameters affecting CA.

To facilitate the calculations, the following assumptions are applied to the model.

(i) The microstructures are uniformly dispersed, with each possessing identical dimensions and shapes.

(ii) Neglect the gravitational load inside the droplet along the radial direction.

(iii) Droplets on microstructured surfaces are considered to satisfy the Cassie–Baxter state.

(iv) The size and shape of droplets remain consistent when they fall onto microstructured surfaces.

(v) The microstructured surface starts out hydrophobic (i.e., the CA is >90°).

(vi) The projected area of the droplet on the microstructured surface is considered to be circular.

(vii) The weight of the liquid droplets is evenly distribution over the surface contact area.

(viii) The portion of the droplet in contact with air between the gaps of microstructures is circular.

(ix) The air inside the microstructures is at atmospheric pressure.

2.1. Water droplet equilibrium force system

To preserve the shape of the droplet, it is crucial to maintain an equilibrium between the gravitational force acting on the droplet and the other forces present. This force equilibrium in the Z-direction is graphically demonstrated in the schematic diagram shown in Fig. 1b. The weight of a water droplet in mechanical equilibrium can be expressed using eqn (1). Additionally, the weight of a water droplet based on the relationship between gravity, mass, density, and volume can be expressed through eqn (2).
 
G = Ft + Fp + Fn(1)
and
 
image file: d6sm00212a-t1.tif(2)

2.2. Microstructure support for water droplets (Fn)

Due to droplet weight, the support force generated on the surface of the microstructure is expressed in eqn (3).
image file: d6sm00212a-t2.tif
 
image file: d6sm00212a-t3.tif(3)
based on Fig. 1b, the uncertain parameters in eqn (3) can be expanded to eqn (4a)–(4c).
 
R1 = R[thin space (1/6-em)]cos[thin space (1/6-em)]θ(4a)
 
h = R[thin space (1/6-em)]sin[thin space (1/6-em)]θ(4b)
 
H = h + ȳ.(4c)

Based on the assumption that the droplet model exhibits symmetry, it follows that the droplet itself displays quarter symmetry in its microstructures. Fig. 2a and b illustrate the upper curved portion of a water droplet integrated with microstructures. Fig. 2c provides a magnified view of a droplet in contact with a microstructured surface.


image file: d6sm00212a-f2.tif
Fig. 2 Quarter symmetry of droplet. (a) Top view. (b) Front view. (c) Schematic diagram of a water droplet forming a sag between microstructures.

According to the generalized equation of a circular arc, the height of any point on the semicircular diameter line is shown in eqn (5).

 
image file: d6sm00212a-t4.tif(5)

Eqn (6a)–(6d) depicts where the center of the droplet is located (i.e. if x = 0, z = R). Thus, as x changes y changes as well, [z with combining macron] is calculated as follows where n is denoted as the number of columns in any radial direction.

 
image file: d6sm00212a-t5.tif(6a)
 
image file: d6sm00212a-t6.tif(6b)
 
image file: d6sm00212a-t7.tif(6c)
 
image file: d6sm00212a-t8.tif(6d)
 
image file: d6sm00212a-t9.tif(6e)

Similarly, when x changes and y changes.

 
image file: d6sm00212a-t10.tif(6f)

Extending eqn (6e) by the binomial expansion theorem (i.e., neglecting second-order and higher order terms) the sum of the mean heights of the columns is based on eqn (7a)–(7e).

 
image file: d6sm00212a-t11.tif(7a)
 
image file: d6sm00212a-t12.tif(7b)
 
image file: d6sm00212a-t13.tif(7c)
 
image file: d6sm00212a-t14.tif(7d)
 
image file: d6sm00212a-t15.tif(7e)

Therefore, the average height of the column in the z-direction can be found from eqn (8a) and (8b).

 
image file: d6sm00212a-t16.tif(8a)
 
image file: d6sm00212a-t17.tif(8b)

Similarly, the average length of the droplet in the y-direction can be found from eqn (9a) and (9b).

 
image file: d6sm00212a-t18.tif(9a)
 
image file: d6sm00212a-t19.tif(9b)

Therefore, Fn can be calculated from eqn (10).

 
image file: d6sm00212a-t20.tif(10)

2.3. Support provided to droplets by surface tension at the gap of the microstructure (Ft)

As shown in Fig. 2c, without taking into account the influence of the horizontal component, the expression solely accounts for the vertical component of the peripheral surface tension is expressed as:
Ft = (total length of the contact line between the microstructure and the water droplet) × T × sin[thin space (1/6-em)]φ
 
Ft = 4(Ls + Lp) × T × sin[thin space (1/6-em)]φ(11)

The expression 4(Ls + Lp) represents the total length of the contact line that interfaces between the microstructure and the droplet, while T denotes the surface tension of the water. During subsequent calculations, the distance separating the array microstructure from the droplet's center along the x-direction is incrementally increased by a length equivalent to one period (w + p). The relevant calculation equations are displayed in eqn (12a)–(12c).

 
image file: d6sm00212a-t21.tif(12a)
 
image file: d6sm00212a-t22.tif(12b)
 
image file: d6sm00212a-t23.tif(12c)

Hence, to streamline the calculation process, we can approximate the length of the contact line by summing two times the length of the midpoint between the microgrooves of each microstructure and the cumulative arc lengths of all the microstructured segments. This approximation is represented by Ls + Lp and can be computed using the formula outlined in eqn (13a)–(13e).

 
image file: d6sm00212a-t24.tif(13a)
 
image file: d6sm00212a-t25.tif(13b)
 
image file: d6sm00212a-t26.tif(13c)
 
image file: d6sm00212a-t27.tif(13d)
 
image file: d6sm00212a-t28.tif(13e)

To ascertain the value of Ft, it is necessary to evaluate φ. The determination of φ further relies on the radius r of the sagging droplet, as illustrated in Fig. 2c. From the figure, it is evident that A marks the center of the sagging droplet's circle, while B (0, 0), C (p, 0), and D (0.5p, −v) are points located on its periphery. Here, v signifies the distance separating the lowest point of the permeability gap's cross-section from the material plane,69 which is given by eqn (14a). Consequently, the equation for the sagging circle is expressed in eqn (14a)–(14d).

 
image file: d6sm00212a-t29.tif(14a)
 
h12 + k2 = r2(14b)
 
image file: d6sm00212a-t30.tif(14c)
 
(ph1)2 + k2 = r2(14d)

The radius of the sagging arc, denoted as r, is provided in eqn (15).

 
image file: d6sm00212a-t31.tif(15)

The magnitude of the angle at the center of the circle corresponding to the pendant arc is presented in eqn (16a)–(16c).

 
image file: d6sm00212a-t32.tif(16a)
 
image file: d6sm00212a-t33.tif(16b)
 
image file: d6sm00212a-t34.tif(16c)

The values of Ls and φ are substituted into eqn (11), and the resulting expression for Ft is displayed in eqn (17).

 
image file: d6sm00212a-t35.tif(17)

2.4. Surface tension around a water droplet (Fp)

As shown in Fig. 1b, only the effect of the vertical component of the peripheral surface tension is considered since the horizontal component of the surface tension is canceled out, as shown in eqn (18).
 
image file: d6sm00212a-t36.tif(18)

2.5. Development of mathematical models

A mathematical model for water droplet CA on a microstructured surface was developed using a force balance method in the vertical direction. By incorporating eqn (1), (2), (10), (17), and (18), they were modified and combined to form eqn (19). This equation encapsulates the relationship between the geometrical parameters of the microgroove structure surface and the CA, as derived from the mathematical model.
 
image file: d6sm00212a-t37.tif(19)

The mathematical model established above reveals the theoretical relationship between the microgroove geometry and the contact angle. To validate this model and evaluate the practical machining capability of the DWFALM technique for fabricating such microstructures, an experimental investigation using DWFALM was subsequently conducted in this study.

3. Experimental setup and methodology

This section describes the experimental setup, material selection, and characterization methods employed in DWFALM. First, the working principles of DWFALM are introduced, followed by the selection of materials and fabrication procedures. Finally, the characterization methods are described, including the morphological analysis of the surface and cross-sectional profiles of samples processed by LDP and DWFALM, as well as the assessment of their surface wettability.

3.1. Experimental setup and materials

To achieve high efficiency, precision, and processing stability in titanium alloy DWFALM, our research team independently designed and developed the machining system shown in Fig. 3a. The laser employed was a nanosecond pulsed fiber laser with a wavelength of 1064 nm, a pulse width of 100 ns, a maximum average power of 30 W, and a repetition frequency of 20 kHz. The system is equipped with three-axis (XYZ) positioning capability, offering a movement precision of 0.5 µm and a maximum traverse speed of 20 mm s−1. Ti6Al4V alloy specimens measuring 5 mm × 5 mm × 2 mm were employed in the experiments (detailed elemental composition is presented in Table 1).
image file: d6sm00212a-f3.tif
Fig. 3 DWFALM schematic and process parameter diagram. (a) Photograph of the DWFALM system. As shown in the inset at the lower right corner, a thin water film forms during the machining process. (b) Relative position of the laser beam and waterjet beam.
Table 1 The main chemical compositions of Ti6Al4V surface (wt%)
Ti Al V Fe O C Other
88.42 6.92 4.3 0.16 0.13 0.06 ≤0.01


Prior to formal machining, the specimens were mechanically polished to remove the surface oxide layers. To observe thermal damage in the microgroove cross-section, the samples were immersed in an etching solution (HNO3[thin space (1/6-em)]:[thin space (1/6-em)]HF[thin space (1/6-em)]:[thin space (1/6-em)]H2O = 1[thin space (1/6-em)]:[thin space (1/6-em)]2[thin space (1/6-em)]:[thin space (1/6-em)]17) for 20 s, followed by ultrasonic cleaning in deionized water for 10 min, and then dried with clean compressed air.

3.2. Experimental design

During the DWFALM machining process, the laser can move either leftward or rightward, while the water flow is consistently maintained from left to right, thereby resulting in two distinct processing modes. Previous studies have demonstrated that a stable water film is established when the laser scanning direction is opposite to the water flow direction, thereby enhancing machining quality.70 Based on this, the present study employs a processing method in which the laser moves in the direction opposite to the water flow to fabricate arrayed microgrooves.

3.3. Characterization

The water film thickness was measured using a laser displacement sensor (TS-P25EA, TronSight), as shown in SI Fig. S1. To systematically characterize the surface morphology, machining-induced damage, and wetting performance of the microgroove arrays, scanning electron microscopy (SEM, EVO 25, ZEISS) was used to examine the surface and cross-sectional morphologies, whereas an ultra-depth-of-field optical microscope (smart zoom 5) was employed to assess thermal damage. Subsequently, confocal laser scanning microscopy (CLSM, LSM 700, ZEISS) was employed to characterize the microstructures by acquiring three-dimensional morphologies and cross-sectional profiles, while energy-dispersive spectroscopy (EDS, X-Max, Oxford) was used for chemical composition analysis and elemental mapping of the sample cross-sections. Surface wettability was assessed using an SL200L contact angle meter for static CA measurements. A 5 µL droplet of deionized water was deposited at three different locations on each sample surface, and the average CA was calculated based on the ellipse-fitting method. The RA was determined as the critical inclination angle at which a 10 µL water droplet started to roll off the surface.

4. Experimental results and discussion

This section presents and discusses the results of the study. First, a comparison of the microgroove morphologies and elemental compositions produced by LDP and DWFALM confirmed that DWFALM significantly mitigates thermal damage. Second, by adjusting the laser scanning spacing (150–350 µm), controllable preparation of large-area micro-array structures on the Ti6Al4V surface was achieved. Finally, the relationship between microstructural dimensions and wettability was elucidated, and the established CA prediction model exhibited high agreement with the experimental results, with an error of less than 2%, thus providing theoretical guidance for the design of superhydrophobic surfaces.

4.1. Effects of DWFALM on the micro-surface morphology of microgrooves

In the field of microstructure fabrication, LDP technology has been widely employed owing to its high flexibility and non-contact processing capability.71,72 However, the inherent thermal accumulation associated with this process tends to generate defects such as a HAZ, recast material accumulation, and microcracks.73–75 In this study, DWFALM technology is employed to exploit the active cooling and continuous scouring effects of a dynamic water film, thereby effectively suppressing HAZ formation and removing molten material and redeposited particles, which ultimately enhances machining quality. To further investigate the influence of DWFALM processing on microgroove surface quality, comparative experiments on microgrooves fabricated by LDP and DWFALM were carried out, as summarized in Table 2.
Table 2 Operational specifications of the DWFALM in Ti6Al4V alloy processing
Processing parameters Value
Single pulse energy (mJ) 1.2
Scanning speed (mm s−1) 0.02
Defocusing amount (mm) 0
Laser beam diameter (µm) 50
Laser pulse repetition rate (kHz) 20
Nozzle diameter (mm) 0.4
Waterjet offset distance X (mm) 6.0
Waterjet inclination angle θ (°) 45
Nozzle stand-off distance W (mm) 6
Water pressure (MPa) 0.4


Fig. 4 shows the surface morphologies of the titanium alloy after processing by LDP and DWFALM. Fig. 4a–c show SEM images of the LDP-processed surface, where pronounced molten layer accumulation and microcracks can be observed at the microgroove edges. In contrast, the DWFALM-processed surface exhibited a substantial reduction in these defects, as shown in Fig. 4d–f. Fig. 4g and h show ultra-depth-of-field optical microscopy images, further confirming that LDP processing leads to the formation of a pronounced HAZ at the microgroove edges as a result of localized energy accumulation. In contrast, the water film in DWFALM exerts combined convective cooling and mechanical scouring effects, which together reduce the signatures of thermal damage.


image file: d6sm00212a-f4.tif
Fig. 4 Effects of LDP and DWFALM on surface micro-morphology of the microgroove. (a)–(c) SEM images of the surface processed by LDP. Pronounced molten layer accumulation can be observed on both sides of the microgroove, along with surface defects including thermal damage and microcracks. (d)–(f) SEM images of the DWFALM-processed surface. A significant reduction in molten layer accumulation is observed at the microgroove edges, while defects such as thermal damage and microcracks are effectively suppressed. (g) and (h) Ultra-depth-of-field optical microscopy observations. Pronounced heat-affected discoloration zones are observed at the microgroove edges after LDP processing because of localized surface energy accumulation, whereas DWFALM significantly reduces thermal damage. (i) and (j) 3D topography images from LCSM. LDP results in molten layer protrusions at the microgroove edges, whereas DWFALM exhibits clearer contours and superior surface quality.

To further elucidate the effects of the two processing methods on microgroove morphology, LCSM characterization was performed, as shown in Fig. 4i and j. The results showed that the LDP-processed microgrooves exhibited edge protrusions of molten material with a height of approximately 30 µm. In contrast, DWFALM processing not only significantly improved the surface smoothness but also markedly enhanced the contour definition of the microgrooves. These results clearly demonstrate the advantages of DWFALM technology for precision machining.

4.2. Impact of DWFALM on the microgroove cross-section

To assess the impact of DWFALM on the cross-sectional morphology of microgrooves, this study analyzed three aspects: remelted layer characteristics, elemental distribution, and the evolution of the HAZ. Fig. 5 shows SEM images of LDP-processed samples, revealing pronounced remelted layers at the groove edges and protruding molten layers on the microgroove surface, measuring approximately 30 µm. This phenomenon may be attributed to the recoil pressure generated during material vaporization, which radially propels molten material toward the solidification front.
image file: d6sm00212a-f5.tif
Fig. 5 Cross-sectional morphology and chemical composition of the microgrooves processed by LDP and DWFALM. (a) and (b) SEM images of microgroove cross-sections for LDP and DWFALM, LDP formed a 30 µm thick remelted layer, while DWFALM significantly reduced molten layer accumulation and exhibited a more regular surface contour. (c)–(f) EDS images of microgroove cross-sections for LDP and DWFALM. Notable oxygen enrichment is observed in LDP-processed regions. (g) and (h) Ultra-depth-of-field optical images of microgroove cross-sections after chemical etching for LDP and DWFALM. Chemical etching reveals a ∼200 µm wide HAZ with irregular etch pits in LDP, while DWFALM exhibits essentially no observable HAZ formation.

In contrast, DWFALM processing not only remelted layer accumulation but also produced microgroove cross-sections with a higher aspect ratio (Fig. 5b). EDS analysis (Fig. 5c–f) revealed significant oxygen enrichment and reduced titanium content in LDP-processed regions, indicating pronounced oxidation during processing. Conversely, DWFALM-processed samples showed lower oxygen content and higher titanium content, further confirming the effectiveness of dynamic water film-assisted cooling.

Although EDS can detect variations in oxygen content across the cross-section, it cannot directly characterize the features of the HAZ. Therefore, chemical etching was conducted to characterize the sample cross-sections. Fig. 5g and h show that LDP-processed cross-sections exhibit irregular etch pit morphologies after etching, with a HAZ width of approximately 140 µm, whereas DWFALM samples display uniform etching and an essentially negligible HAZ. These results corroborate the EDS analysis, conclusively demonstrating that DWFALM offers significant advantages in minimizing thermal damage.

4.3. Fabrication of microarray structures

In the processing of titanium alloy surface microgrooves, those produced by the LDP method display pronounced thermal damage and inferior surface quality. Therefore, this study utilizes the DWFALM method to fabricate large-area microgroove array structures on Ti6Al4V alloy surfaces. During processing, surface morphology is controlled by varying the laser scanning spacing (150 µm, 200 µm, 250 µm, 300 µm, and 350 µm).

Fig. 6a displays the surface morphology of the smooth Ti6Al4V substrate, while Fig. 6b–f present SEM and LCSM images of microgroove surfaces fabricated by DWFALM at different scanning spacings. Observations indicate that DWFALM can produce microgrooves with well-defined contours at scanning spacings above 150 µm. As the spacing increases to 350 µm, the rib width of the microgroove array surface exhibits a corresponding increasing trend. This morphological evolution of the periodic structures may affect the material's surface wetting properties. LCSM images further confirm that the microgroove array surfaces processed by DWFALM exhibit excellent surface morphology.


image file: d6sm00212a-f6.tif
Fig. 6 Microstructural analysis of initial Ti6Al4V surface and DWFALM-treated specimens at multiple scanning intervals using SEM and LCSM. (a) Smooth substrate surface. (b) 150 µm. (c) 200 µm. (d) 250 µm. (e) 300 µm. (f) 350 µm.

4.4. Effect of microstructure size on CA

The preparation of superhydrophobic surfaces entails two essential steps: first, creating intricate surface microstructures, and second, lowering the material's surface energy. Building on the previously fabricated microarray structures, this study immersed them in a 0.01 mol L−1 fluorosilane ethanol solution for 3 to 4 hours for surface modification at room temperature. Subsequently, the samples were allowed to air dry naturally at room temperature, resulting in the formation of a superhydrophobic microarray surface. To investigate the impact of varying scanning spacings on the wettability of the microarray surface, CA measurements were performed.

Fig. 7a illustrates the CA measurements of microgroove array surfaces at scanning spacings varying from 150 µm to 350 µm. As shown in (SI Fig. S2), although fluorination treatment enhanced the hydrophobicity of the smooth substrate (with CA reaching 126.2°), it still fell short of achieving superhydrophobicity. In contrast, the fluorinated DWFALM microgroove array surfaces demonstrated exceptional superhydrophobicity, with CA significantly exceeding 162.7°. Additionally, as the laser scanning spacing increased, the CA showed a gradual decrease. However, even when the scanning spacing was increased to 350 µm, the water droplets still maintained a relatively high contact angle.


image file: d6sm00212a-f7.tif
Fig. 7 Influence of different scanning spacings on CA and the verification results of theoretical predictions. (a) Influence of scanning spacing variation within the 150–350 µm range on CA, with experimental data showing a monotonic decreasing trend of CA as spacing increases. (b) A comparison between predicted and experimental results for CA.

4.5. Model validation

By solving eqn (19), the volume of the water droplet used is 5 µL. Calculating based on the volume of a sphere, the radius R = 1.06078 × 103 µm. Therefore, θ is the only unknown variable, found to depend on the variations of w and p. Under scanning spacings ranging from 150 µm to 350 µm, corresponding to different cavity dimensions and spacing values (w = 10 µm, p = 140 µm; w = 160 µm, p = 140 µm; w = 210 µm, p = 140 µm; w = 360 µm, p = 140 µm; w = 510 µm, p = 140 µm), the parameters were substituted into the system of equations and calculated using professional mathematical software, Wolfram Mathematica. The predicted and experimental values of CA are shown in Fig. 7b, with an average error less than 2%. The results indicate that the observed water CA values in all cases are relatively close to those derived from the proposed mathematical model.

4.6. RA test

Superhydrophobic surfaces are characterized not only by a CA exceeding 150° but also by a low RA, typically below 10°. Fig. 8 illustrates the impact of varying scanning spacings on the RA of superhydrophobic surfaces following chemical treatment. As shown in (SI Fig. S3), although the RA value exhibits an increasing trend with larger scanning spacings, it remains below 6.2°. The RA values measured at different scanning spacings all meet the dynamic wetting criteria for superhydrophobic surfaces. Compared with superhydrophobic surfaces fabricated using various laser techniques, DWFALM produces outstanding low-damage superhydrophobic surfaces (Table 3).
image file: d6sm00212a-f8.tif
Fig. 8 Influence of different scanning spacings on RA. (a) 150 µm. (b) 200 µm. (c) 250 µm. (d) 300 µm. (e) 350 µm.
Table 3 Influence of different laser processing techniques on the performance of superhydrophobic surfaces
Method Laser model Post-processing Wettability Ref.
Nanosecond laser ablation Nanosecond laser (240 ns, 1064 nm) Perfluorodecyltrithioxysilane (PFDS) CA ∼ 162.8° and SA ∼ 7.8° 76
Femtosecond laser texturing Femtosecond laser (320 fs, 1035 nm) 1H,1H,2H,2H-Heptadecafluorodecyl CA ∼ 155.03° 77
Picosecond laser texturing Picosecond laser (12 ps, 1064 nm) Annealing treatment CA ∼ 144.58° 78
Laser-induced plasma-assisted ablation Picosecond laser (12 ps, 1064 nm) 1H,1H,2H,2H-Perfluorodecyltriethoxysilane CA ∼ 153° 79
Water jet guided laser texturing Nanosecond laser (240 ns, 1064 nm) Aging treatment CA ∼ 130° 80
Nanosecond laser beam machining under silicone oil Nanosecond laser (18 ns, 355 nm) CA ∼ 150° and RA < 10° 81
Laser-electrolyte jet hybrid machining Nanosecond laser (110 ns, 1064 nm) 1H,1H,2H,2H-Perfluorodecyltriethoxysilane and PFDS CA ∼ 154.8° 82
DWFALM Nanosecond laser (240 ns, 1064 nm) Fluorosilane ethanol solution CA ∼ 167.6° and RA ∼ 2.2°


5. Conclusions

This study demonstrates the fabrication of micro-array superhydrophobic surfaces on Ti6Al4V substrates using DWFALM, achieving both low thermal damage and excellent wettability. The main conclusions are summarized as follows:

(1) A force balance-based mathematical model was established to predict the contact angle of water droplets on microgroove array surfaces. The model incorporates the gravitational force of the droplet, the structural support force, and surface tension effects. The average deviation between the predicted and experimentally measured contact angles is less than 2%, demonstrating excellent agreement.

(2) Compared with conventional LDP, DWFALM significantly suppresses the formation of heat-affected zones, reduces molten layer thickness, and eliminates micro-cracks. EDS analysis reveals that DWFALM decreases oxygen content while increasing titanium content, indirectly evidencing its efficient cooling and dynamic scouring effects, which effectively inhibit thermal damage in the material.

(3) By adjusting the laser scanning spacing, controllable variation in the rib width of the microgroove arrays was realized. Following surface modification, superhydrophobic surfaces with contact angles exceeding 162.7° were achieved under all spacing conditions, and the rolling angle remained below 6.2° even when the spacing was increased to 350 µm.

This study developed a mathematical model for predicting the contact angle of water droplets on microgroove array surfaces, offering strong theoretical support for the efficient preparation of superhydrophobic surfaces.

Author contributions

Jinda Yang: writing – original draft, methodology, data curation. Zhongxu Lian: writing – review & editing, writing – original draft, formal analysis. Haonan Jin: methodology, data curation. Jiaqi Wang: writing – original draft, conceptualization. Jinkai Xu: supervision, investigation. Yanling Tian: supervision, formal analysis.

Conflicts of interest

The authors declare no competing interests.

Abbreviations

G Gravity of a water droplet (N)
F n Microstructure support for water droplets (N)
F p Surface tension on droplets due to microgroove arrays (N)
F t Surface tension at the periphery (N)
T Tension of water (N m−1)
w Microgroove width (µm)
p Spacing between microgrooves (µm)
R Water droplet radius (mm)
h Height from the drop center to the top surface of the microarray microgroove (mm)
θ Angle between OE and EF (degrees)
H Height of the droplet on the microstructure (mm)
y Vertical distance between the highest point of the drop and the center position of the droplet (mm)
R 1 The projected contact radius of the droplet with the surface (mm)
O Water droplet center position
φ Angle between the droplet's sagging tangent and the vertical direction (°)
r Radius of circle formed by droop (mm)
h 1 Distance of the center of the sagging circle from the surface (mm)
k Radius of the pendant circle (mm)
v Droop height (mm)
ρ Density of water (kg m−3)
g Acceleration due gravity (m s−2)

Data availability

Supplementary information (SI) is available. The Supplementary Information contains additional experimental details, surface morphology characterization, wettability measurements, contact angle analysis, and supporting data related to the preparation and performance evaluation of the superhydrophobic surfaces. See DOI: https://doi.org/10.1039/d6sm00212a.

Data will be made available on request.

Acknowledgements

This work was supported by the National Key Research and Development Program of China (No. 2024YFB4607502), the UKRI guarantee funding for Horizon Europe MSCA Postdoctoral Fellowships (No. EP/Z001218/1), and the “111” Project of China (No. D17017).

References

  1. C. G. Ferro, S. Varetti and P. Maggiore, Chin. J. Aeronaut., 2024, 37, 520–532 CrossRef.
  2. Y. M. Wang, X. Wang, C. L. Xu, S. B. Qiu, K. Wang, K. Tian, B. Yu and Y. Yu, Int. J. Fatigue, 2023, 172, 107649 CrossRef CAS.
  3. X. Chen, L. J. Huang, S. Ma, F. B. Sun and L. Geng, J. Mater. Res. Technol., 2025, 206, 1–14 CAS.
  4. Y. Zhang, C. Y. He, Q. Yu, X. Li, X. G. Wang, Y. Zhang, J. Wang, C. Jiang, Y. F. Jia, X. C. Zhang, B. H. Sun, R. O. Ritchie and S. T. Tu, Nat. Commun., 2024, 15, 1 Search PubMed.
  5. S. W. Meng, J. F. Zhang, D. S. Kong, G. F. Shi, X. Wang and H. D. Li, Precis. Eng., 2025, 95, 151–162 CrossRef.
  6. J. J. Zhang, X. C. Liu, H. Liang, L. K. Xie, B. Wei, H. H. Zong, Y. Wu and Y. H. Li, Chin. J. Aeronaut., 2024, 37, 49–62 CrossRef.
  7. V. Vercillo, S. Tonnicchia, J. M. Romano, A. García-Girón, A. I. Aguilar-Morales, S. Alamri, S. S. Dimov, T. Kunze, A. F. Lasagni and E. Bonaccurso, Adv. Funct. Mater., 2020, 30, 1910268 CrossRef CAS.
  8. Y. L. Zhang, H. Xia, E. Kim and H. B. Sun, Soft Matter, 2012, 2012(8), 11217–11231 RSC.
  9. J. J. Yang, G. Liu, K. T. Zhang, P. Li, H. P. Yan, Y. Yan, Y. D. Zheng, Z. H. Zhao, L. W. Zhang, X. L. Liu, G. Yang and H. W. Chen, Small, 2024, 20, 2403420 CrossRef CAS PubMed.
  10. B. Y. Liu, J. W. Wu, C. H. Xue, Y. J. Zeng, J. Liang, S. L. Zhang, M. X. Liu, C. Q. Ma, Z. K. Wang and G. M. Tao, Adv. Mater., 2024, 36, 2400745 CrossRef CAS PubMed.
  11. L. Zhang, Z. L. Zhou, B. Cheng, J. M. Desimone and E. T. Samulski, Langmuir, 2006, 22, 8576–8580 CrossRef CAS PubMed.
  12. G. Lee, S. Lee, D. Kim, S. H. Kim, C. Choi, S. G. Lee and K. Cho, Adv. Funct. Mater., 2024, 34, 2316288 CrossRef CAS.
  13. Z. J. Cheng, D. J. Zhang, T. Lv, H. Lai, E. S. Zhang, H. J. Kang, Y. Z. Wang, P. C. Liu, Y. Y. Liu, Y. Du, S. X. Dou and L. Jiang, Adv. Funct. Mater., 2018, 28, 1705002 CrossRef.
  14. X. D. Wang, L. G. Dai, N. D. Jiao, S. Tung and L. Q. Liu, Chem. Eng. J., 2021, 422, 129394 CrossRef CAS.
  15. X. Yang, Y. H. Chen, X. Zhang, P. Xue, P. F. Lv, Y. Z. Yang, L. Wang and W. Feng, Nano Today, 2022, 43, 101419 CrossRef CAS.
  16. Y. H. Huang, M. J. Wang and T. S. Chung, Nat. Commun., 2025, 15, 1092 CrossRef PubMed.
  17. Y. X. Zhang, X. F. Du, J. W. Huangfu, K. K. Chen, X. T. Han, C. F. Xiao and Q. L. Huang, Chem. Eng. J., 2024, 490, 151831 CrossRef CAS.
  18. Y. L. Zhan, S. R. Yu, A. Amirfazli, A. R. Siddiqui and W. Li, Adv. Eng. Mater., 2022, 24, 2101053 CrossRef CAS.
  19. X. Y. Wang, W. Tian, Y. H. Ye, Y. Chen, W. J. Wu, S. H. Jiang, Y. L. Wang and X. S. Han, Adv. Colloid Interface Sci., 2024, 326, 103142 CrossRef CAS PubMed.
  20. Y. Z. Wang, P. F. Liu, R. X. Luo, B. J. Chen, J. Y. Li, F. W. Yang, H. Zhou, J. X. Zeng, L. L. Xing and J. Guo, Prog. Org. Coat., 2024, 188, 108243 CrossRef CAS.
  21. J. M. He, J. He, M. J. Yuan, M. H. Xue, X. R. Ma, L. G. Hou, T. J. Zhang, X. R. Liu and M. N. Qu, Adv. Eng. Mater., 2018, 20, 1701180 CrossRef.
  22. S. J. Song, H. Yan, M. Cai, Y. Huang, X. Q. Fan and M. H. Zhu, Adv. Mater. Technol., 2022, 7, 2101223 CrossRef CAS.
  23. A. Manoj, R. Ramachandran and P. L. Menezes, Int. J. Adv. Des. Manuf. Technol., 2020, 106, 2119–2131 CrossRef.
  24. X. G. Li, Z. X. Lian, J. K. Xu, Y. L. Tian and H. D. Yu, J. Bionic Eng., 2025, 22, 1834–1849 CrossRef.
  25. Z. X. Lian, J. H. Zhou, Z. M. Liu, Y. L. Wan, R. Liu, J. D. Yang, J. K. Xu, Y. L. Tian and H. D. Yu, Int. J. Mech. Sci., 2024, 275, 109341 CrossRef.
  26. M. L. Zhou, L. Zhang, L. S. Zhong, M. S. Chen, L. M. Zhu, T. C. Zhang, X. F. Han, Y. P. Hou and Y. M. Zheng, Adv. Mater., 2024, 36, 2305322 CrossRef CAS PubMed.
  27. S. Yang, Q. Li, B. Du, Y. Ying, Y. Zeng, Y. Jin, X. Qin, S. Gao, S. Wang, Z. Wang, R. Wen and X. Ma, Int. J. Extreme. Manuf., 2023, 5, 045501 CrossRef CAS.
  28. X. Zhao, P. Wang, Q. L. Zhang, Z. H. Zheng, W. J. An, J. X. Zhang, J. Jia, W. Duan and Y. Yue, Adv. Mater. Technol., 2025, 10, 2401929 CrossRef CAS.
  29. C. M. Tittle, D. Yilman, M. A. Pope and C. J. Backhouse, Adv. Mater. Technol., 2018, 3, 1700207 CrossRef.
  30. W. Z. Wu, M. S. Zhao, S. W. Miao, X. Y. Li, Y. Z. Wu, X. Gong and H. X. Wang, Carbon, 2023, 217, 118593 CrossRef.
  31. Y. Wang, W. N. Zhao, M. Han, J. X. Xu and K. C. Tam, Nat. Water, 2023, 1, 587–601 CrossRef CAS.
  32. K. K. Prasad, T. Roy, M. M. Goud, V. Karar and V. Mishra, Int. J. Mech. Sci., 2021, 193, 106140 CrossRef.
  33. R. J. Sun, B. Hou, J. J. Huang, X. G. Li, C. Liu, M. J. Chen and C. Y. Wu, Sustainable Mater. Technol., 2024, 42, e01136 CrossRef CAS.
  34. Z. P. Zheng, J. F. Zhang, Z. W. Li, J. H. Liu, K. Y. Wu, P. F. Feng and J. J. Wang, J. Manuf. Process., 2025, 133, 734–753 CrossRef.
  35. H. D. Yu, X. R. Zhang, Y. L. Wan, J. K. Xu, Z. J. Yu and Y. Q. Li, Surf. Eng., 2016, 32, 108–113 CrossRef CAS.
  36. H. Wang, G. X. Chi, Y. K. Wang, F. X. Yu and Z. L. Wang, Appl. Surf. Sci., 2019, 478, 110–118 CrossRef CAS.
  37. K. S. Li, C. J. Wang, F. Gong, C. F. Cheung, Z. B. Chen and Z. K. Wang, ACS Appl. Mater. Interfaces, 2024, 16, 15548–15557 CrossRef CAS PubMed.
  38. Z. L. Li, W. W. Li, Y. T. Liu, M. Xun and M. C. Yuan, Int. J. Adv. Des. Manuf. Technol., 2023, 126, 3205–3218 CrossRef.
  39. Y. J. Xiao, Y. J. Zhang, Z. J. Liang, T. M. Yue, Z. N. Guo, J. W. Liu and X. L. Chen, Colloids Surf., A, 2021, 612, 125963 CrossRef CAS.
  40. R. Jafari, C. Cloutier, A. Allahdini and G. Momen, Int. J. Adv. Des. Manuf. Technol., 2019, 103, 1225–1238 CrossRef.
  41. X. L. Wang, J. J. An, A. Hassan, Q. S. Gao and X. H. Liu, J. Appl. Polym. Sci., 2025, 142, e57217 CrossRef CAS.
  42. Z. Q. Dong, M. Vuckovac, W. J. Cui, Q. Zhou, R. H. A. Ras and P. A. Levkin, Adv. Mater., 2021, 33, 2106068 CrossRef CAS PubMed.
  43. Y. Yang, X. J. Li, X. Zheng, Z. Y. Chen, Q. F. Zhou and Y. Chen, Adv. Mater., 2018, 30, 1704912 CrossRef PubMed.
  44. W. Wang, C. X. Sun, H. X. Zhang, R. R. Fang, L. J. Guo and G. Wang, Adv. Mater. Technol., 2025, 10, 2400555 CrossRef CAS.
  45. Y. Guo, H. B. Zhao, C. S. Zhang and G. Q. Zhao, Chem. Eng. J., 2024, 497, 154383 CrossRef CAS.
  46. J. Zhu, W. Li, T. Wang, H. M. Feng, J. Cheng, C. G. Lin, X. Wang, W. Wang and S. G. Chen, Chem. Eng. J., 2025, 505, 159218 CrossRef.
  47. J. Q. Tao, H. Wu, J. H. Xie, Z. Lu, S. Z. Li, M. Jin, H. X. Zhao, L. Dong, S. H. Chen, Y. Yang and Q. P. Ran, Small, 2025, 21, 2505827 CrossRef CAS PubMed.
  48. F. Z. Li, R. X. Sun and K. Z. Chen, J. Alloys Compd., 2023, 945, 169316 CrossRef CAS.
  49. X. F. Chen and X. Gong, J. Hazard. Mater., 2024, 472, 134465 CrossRef CAS PubMed.
  50. T. Zhu, Y. Yuan, H. Y. Xiang, G. Y. Liu, X. Dai, L. B. Song and R. J. Liao, J. Mater. Res. Technol., 2023, 27, 8151–8163 CrossRef CAS.
  51. C. L. Zhou, H. J. Zhang, X. H. Luo, B. Chen, X. Y. Pan, Y. W. Zhuo, Z. Y. Xiao, Z. Y. Huang, Z. L. Chu, W. R. Dong and Y. L. Liu, Prog. Org. Coat., 2024, 192, 108473 CrossRef CAS.
  52. Z. Z. Xu, C. R. Jiang, R. Y. Liu, P. W. Sha, X. Liu, Z. L. Yu, Z. Z. Mu, Z. H. Zhang, Y. T. Guo and L. Q. Ren, Surf. Coat. Technol., 2024, 490, 131176 CrossRef CAS.
  53. Z. Y. Li, S. Li, X. Su, Z. Y. He, J. Y. Gu, Y. Diao, J. Xu and B. Guo, Adv. Mater. Interfaces, 2025, 12, 2400828 CrossRef CAS.
  54. Z. W. Sun, X. Y. Zhao, J. P. Yuan, G. Kong, D. L. Lai and Y. M. Zheng, Mater. Chem. Phys., 2025, 334, 130480 CrossRef CAS.
  55. H. Xie, W. H. Xu and T. Wu, J. Appl. Polym. Sci., 2020, 138, e49760 CrossRef.
  56. C. Wang, H. Huang, Y. F. Qian, Z. Y. Zhang, W. H. Huang and J. W. Yan, Precis. Eng., 2022, 73, 244–256 CrossRef.
  57. E. Armelin, S. Moradi, S. G. Hatzikiriakos and C. Alemán, Adv. Eng. Mater., 2018, 20, 1700814 CrossRef.
  58. M. J. Cui, W. Yang, Y. C. Guan and Z. Zhang, Precis. Eng., 2022, 78, 60–69 CrossRef.
  59. X. Yang, C. J. Yang, Z. Yang and D. W. Zhang, Opt. Laser Technol., 2024, 169, 110179 CrossRef CAS.
  60. Y. X. Song, C. Wang, X. R. Dong, K. Yin, F. Zhang, Z. Xie, D. K. Chu and J. A. Duan, Opt. Laser Technol., 2018, 102, 25–31 CrossRef CAS.
  61. V. Tangwarodomnukun, J. Wang, C. Z. Huang and H. T. Zhu, Int. J. Mach. Tools Manuf., 2012, 56, 39–49 CrossRef.
  62. V. Tangwarodomnukun, P. Likhitangsuwat, O. Tevinpibanphan and C. Dumkum, Int. J. Mach. Tools Manuf., 2015, 89, 14–28 CrossRef.
  63. V. Tangwarodomnukun, J. Wang, C. Z. Huang and H. T. Zhu, Int. J. Mach. Tools Manuf., 2014, 79, 1–16 CrossRef.
  64. H. Zhu, J. Wang, P. Yao and C. Z. Huang, Int. J. Mach. Tools Manuf., 2017, 116, 25–39 CrossRef.
  65. S. C. Feng, C. Z. Huang, J. Wang and Z. X. Jia, Mater. Sci. Semicond. Process., 2019, 93, 238–251 CrossRef CAS.
  66. V. Tangwarodomnukun and T. Wuttisarn, Int. J. Adv. Des. Manuf. Technol., 2017, 92, 293–302 CrossRef.
  67. J. Zhou, Y. X. Huang, Y. W. Zhao, H. Jiao, Q. Y. Liu and Y. H. Long, Opt. Commun., 2019, 450, 112–121 CrossRef CAS.
  68. J. Q. Wang, J. K. Xu, G. J. Chen, Z. X. Lian, Z. J. Yu, Y. G. Hou, J. D. Wang, Y. Li and H. D. Yu, J. Mater. Res. Technol., 2023, 24, 4986–5006 CrossRef CAS.
  69. Y. K. Cai, W. L. Chang, X. Luo, A. M. L. Sousa, K. H. A. Lau and Y. Qin, Precis. Eng., 2018, 52, 266–275 CrossRef.
  70. Y. Z. Ma, W. Zhao, H. T. Zhang, L. Ma, C. X. Fan, X. Zhang and D. Li, J. Mater. Process. Technol, 2023, 315, 117906 CrossRef CAS.
  71. Z. X. Lian, J. K. Xu, Z. B. Wang, Z. J. Yu, Z. K. Weng and H. D. Yu, Langmuir, 2018, 34, 2981–2988 CrossRef CAS PubMed.
  72. J. R. Li, J. K. Xu, Z. X. Lian, Z. J. Yu and H. D. Yu, Opt. Laser Technol., 2020, 126, 106129 CrossRef CAS.
  73. Y. Z. Mao, J. X. Yang and J. C. Ji, Adv. Manuf., 2021, 9, 538–557 CrossRef CAS.
  74. Q. D. Sun, J. Sun, K. Guo, S. Waqar, J. W. Liu and L. S. Wang, Adv. Manuf., 2022, 10, 520–540 CrossRef CAS.
  75. X. Y. Liu, L. Li, S. Yang, M. Xu, M. Zhong, B. Y. Wang and Y. Jiang, J. Mater. Process. Technol, 2024, 332, 118559 CrossRef CAS.
  76. J. L. Guo, R. Chen, Q. Li and Y. H. Liu, Opt. Laser Technol., 2024, 179, 111361 CrossRef CAS.
  77. S. C. Wang, S. Y. Dong, X. T. Liu and S. X. Yan, Opt. Laser Technol., 2023, 164, 109423 CrossRef CAS.
  78. Z. R. Yang, C. C. Zhu, N. Zheng, D. Z. Le and J. Z. Zhou, Materials, 2018, 11, 2210 CrossRef PubMed.
  79. D. Y. Zhao, H. Zhu, Z. Y. Zhang, K. Xu, W. N. Lei, J. Gao and Y. Liu, J. Mater. Sci., 2022, 57, 15679–15689 CrossRef CAS.
  80. Y. Shi, Z. L. Jiang, J. Cao and K. F. Ehmann, Appl. Surf. Sci., 2020, 500, 144286 CrossRef CAS.
  81. T. H. Dinh and D. M. Chun, Int. J. Pr. Eng. Man-Gt., 2025, 13, 13–28 Search PubMed.
  82. L. Q. Du, C. Zhang, D. Li, X. L. Han, M. X. Yu and P. Sun, Opt. Laser Technol., 2026, 196, 114599 CrossRef CAS.

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