Laser Cutting of Titanium Alloy Plates: A Review of Processing, Microstructure, and Mechanical Properties

Abstract

The growing use of titanium alloys has led to the gradual replacement of traditional processing methods by laser cutting technology, making it the preferred method for processing titanium alloy plates due to its high efficiency, precision, and adaptability. In this review, the characteristics of laser cutting technology and its application in titanium alloy plate processing are summarized, outlining several aspects of the cutting process, microstructure, and mechanical properties of the material after cutting, along with simulation predictions. Previous research categorized laser-cutting input parameters into beam parameters and process parameters, with the commonly used parameters being the laser power, cutting speed, and gas pressure. Various parameter combinations can achieve different cutting qualities, and seven indices can be used to evaluate the cutting process, with the surface roughness and slit width serving as the most common indices. Different auxiliary gases have shown a significant impact on the laser cutting quality, with commonly used gases consisting of nitrogen, argon, and air. Argon-assisted cutting generally results in better surface quality. Due to the rapid temperature change, the titanium alloy microstructure will undergo a non-diffusive martensitic phase transformation during laser cutting, producing a heat-affected zone. Experimental studies and simulations of the mechanical properties have shown that the occurrence of a martensitic phase transformation increases the hardness and residual tensile stress of the material, which reduces the fatigue strength and static tensile properties. In addition, studies have found that the more streaks appear on the cut surface, the lower the fatigue strength is, with fatigue cracks arising from the stripes. Hence, the established analytical solution model and three-dimensional finite element model can effectively predict the temperature distribution and residual stress during the cutting process. This can provide a better understanding of the high residual stress characteristics of the cutting edge and the stripe formation mechanism, allowing researchers to better explore the mechanism of laser cutting.

1. Introduction

Titanium and titanium alloys are important metallic materials that were developed in the 20th century. Titanium alloys have been extensively utilized in the automotive, chemical, and aerospace industries due to their high specific strengths, low densities, and high fatigue strengths [1,2]. Research on titanium alloys originated from the development of the aviation industry, with the demand in the aerospace sector constituting approximately 40% of the global demand. These alloys are used in applications including engine components, fasteners, and landing gear [3,4]. In the chemical industry, titanium alloys serve as excellent corrosion-resistant materials and are employed as structural materials in petroleum refining, including reactors. In the automotive sector, the use of titanium alloys contributes to weight reductions in vehicles, thereby reducing fuel consumption and diminishing engine noise and vibration. In the medical field, titanium and its alloys are highly desirable biomaterials due to their non-toxicity, high strength, low weight, and excellent biocompatibility, commonly used for medical implants and surgical instruments. With the advancement of technology, the annual production of titanium alloys has increased year by year, and widespread applications across various industries have been found. However, the low thermal conductivities and the tendency for adhesion of titanium alloys result in relatively poor mechanical cutting performances, leading to high application costs that have significantly impeded the widespread use of titanium alloys [5]. Laser cutting involves using a laser beam to cut materials by directing a high-energy-density laser beam onto the surface of a workpiece. The material absorbs energy, causing a rapid temperature increase at the focal point, resulting in melting and vaporization. High-pressure airflow is then utilized to remove the molten material from the cutting seam, thereby achieving cutting [6,7].

In 2008, Dubey and Yadava reviewed the experimental studies on the effect of process parameters on the machining performance of Nd:YAG lasers and summarized the influence of process parameters on cutting pure titanium and Ti–6Al–4V titanium alloys [8]. In 2014, Pedram et al. reviewed the modeling and simulation of laser beam machining processes, discussing the three stages of material removal during laser beam machining: melting, evaporation, and chemical degradation, and the effect of these processes on the quality of the process [9]. In 2022, Naresh and Khatak reviewed the application of CO₂ laser cutting technology in metal plates, thermoplastic polymers, polypropylene (PP), etc., mainly focusing on laser cutting parameters, which can obtain better cutting quality and improve material removal rates [10]. In 2023, Pramanik et al. reviewed the laser beam processing mechanism, surface formation mechanism, heat affected zone, taper formation, and dimensional deviations of titanium alloys, and noted that laser beam machining can initiate non-diffusive phase transitions in titanium alloys, slightly altering the mechanical properties of their surfaces, in addition to optimizing the parameters [11]. In 2024, Elaziem et al. comprehensively reviewed the application of titanium-based biomaterials in the field of orthopedic implants and summarized the application of laser technology in the surface modification of titanium alloys, including laser surface alloying and laser cladding, which have improved the thermal stability, corrosion resistance, and hardness of titanium alloys [12]. In 2024, Alsaadawy et al. reviewed the effects of laser cutting parameters on the surface and kerf quality of metals (titanium alloys, steel alloys, and aluminum alloys), described the advantages of laser cutting compared to other processing methods, summarized the cutting performance parameters in detail through charts, and discussed the effects of parameters on cutting quality [13]. This study not only included the analysis and prediction of process parameters and modeling, but also placed special emphasis on the relationship between the microstructure and mechanical properties of materials during laser cutting, systematically describing the research findings on laser cutting titanium alloys.

This review was conducted from three perspectives: experiments, result analysis, and numerical simulation. As an emerging technology, laser cutting is widely utilized, and its advantages and classifications need to be clarified. When cutting titanium alloys, the selection of suitable process parameters can yield better cutting quality. Additionally, due to the influence of the laser, the microstructure of titanium alloys changes, which simultaneously affects mechanical properties such as strength, hardness, and stress. Therefore, the effects of laser cutting on alloys were summarized from the perspectives of microstructure and mechanical properties. Finally, the review summarized the analytical solution models and finite element models established by researchers, including the temperature distribution and residual stresses during the cutting process, as well as the cutting results. These contents are summarized as a comprehensive roadmap, as shown in Figure 1. This review aims to present readers with a more comprehensive research perspective.

1.1. Advantages and Classification of Laser Cutting

Compared to traditional methods such as machining [14], wire-cut electric discharge machining (WEDM; 5-axis ePULSE-40, Electronica Machine Tool Ltd., Kolkata, India) [15,16], and short electric arc milling (SEAM, DHX33A3000/28FS SEAM, Sun Hung, Taiwan) [17], laser cutting technology offers several advantages, including a small heat-affected zone in the processed material, minimal thermal deformation of the workpiece, easy laser beam guiding, and high processing productivity [18]. Nevertheless, the high costs of machines and their operation, coupled with the significant impact of input factors on the cutting quality, necessitate the optimization of the process parameters and the monitoring of the material surface microstructural changes to achieve high-quality cuts [19]. Additionally, laser cutting offers faster cutting speeds and smoother cutting surfaces [20], eliminating the need for metal hardening before cutting [21]; this is in contrast to non-traditional methods such as laser machining (LM, MFSC-4000W laser, Dechuan Laser Technology Co., Ltd., Dongguan, China) [10], abrasive water jet machining (AWJM, OMAX2626, OMAX Corporation, Kent, WA, USA) [22], ultrasonic machining (USM, 5e-axis DMU 50 evo linear, Deckel Maho Gildemeister, Bielefeld, Germany) [23,24], and abrasive water-jet-assisted laser machining (AWJALM, YLR-300-MM-WC-Y11, IPG, Su Zhou, China) [25].

Laser cutting can be divided into fusion cutting, oxidative cutting, vaporization cutting, and controlled fracture techniques. When the high-power laser is focused on the material through a lens, it can be instantaneously injected into the material, causing the material to change through melting, chemical bond breaking, and evaporation. The high-pressure auxiliary gas will then eject the evaporated and melted material from the cutting zone to complete the precise cutting of the material [26].

(1)

Laser fusion cutting

Fusion cutting refers to the action of a laser beam on a metal material during the laser cutting process, which raises the temperature to the fusion point of the metal and causes it to melt, releasing gases that cannot easily burn with high energy, such as Ar, N₂, and He. High-energy compressed air is then pushed to the metal surface as a promoter to achieve efficient cutting. Laser fusion technology can be used to cut hard metals that are difficult to oxidize. For example, the precise cutting of stainless steel, titanium, aluminum, and their alloys only consumes one-tenth of the original laser energy.

(2)

Laser oxidative cutting

Laser oxidative cutting is a special melting cutting method that uses oxygen as the auxiliary gas type. During the cutting process, the high-energy laser beam heats the material to the ignition temperature without melting it. After the ignition point is reached, oxygen will violently react with the material, releasing a significant amount of oxidation reaction heat. Subsequently, the material will begin to melt to form a molten metal accompanied by a large number of oxides. These melts will be expelled from the kerf surface via auxiliary gas flow, completing the cutting process.

(3)

Laser vaporization cutting

When intense laser radiation hits a workpiece, it rapidly heats the material to the boiling state, turning some of the material into a liquid, while the other portion is discharged from the cutting slit with the flow of hot gas, producing 10 times more laser energy than the effect of fusion cutting. Laser vaporization cutting is a specialized cutting method for materials that cannot be fused, such as wood, rubber, or certain metals. The laser emits laser light on the surface of an object, during which one part is refracted and the other part is absorbed. As the temperature of an object increases, its refractive index decreases. When the energy of a laser beam is released, it heats the material until the surface temperature reaches the boiling point, causing steam to be ejected from the workpiece at the speed of sound.

(4)

Laser cutting through controlled fracture

In laser-controlled fracture cutting, cracking results from the material absorbing laser energy upon heating, and the stress near the laser focus will change due to the high temperature. As the laser beam passes through, the relaxation of compressive stress creates localized residual tensile stress [27]. Under the action of stress, the crack will continue to extend in the direction of laser movement, and the material will break and separate in the path of the laser beam. This cutting method is often used for brittle materials such as ceramics [28].

1.2. Classification of Lasers

A laser, as a laser-generating device, is mainly composed of the pumping source, gain media, and optical resonant cavity, as shown in Figure 2. The pumping source supplies energy to the laser. The gain medium absorbs the energy from the pumping source, causing population inversion and providing the medium with laser amplification through stimulated emission. The optical resonant cavity can provide the space required for energy excitation, with light repeatedly reflected, enhancing the stimulated emission and ultimately releasing coherent laser light [29].

Laser cutting can be divided into three categories based on the different types of lasers, namely CO₂ laser cutting, pulsed Nd:YAG laser cutting, and fiber laser cutting, as shown in Figure 3. Lasers can be divided into solid-state lasers, semiconductor lasers, gas lasers, and fiber lasers.

Solid-state lasers are based on crystals or glass as the matrix material and doped with rare-earth metal ions, transition metal ions, and other activating ions. These systems offer advantages such as high laser powers, stable energy outputs, and compact sizes. Currently, Nd:YAG lasers are the most commonly used. Semiconductor lasers mainly use semiconductor materials as the working medium, providing high energy efficiency and long service life. Another laser type is gas lasers, such as CO₂ lasers and argon lasers. CO₂ lasers have the characteristics of large power ranges, high energy conversion rates, and good beam quality. Commonly used argon laser wavelengths include 458 nm and 488 nm for blue light and 514.5 nm for green light. Argon lasers are frequently applied in the medical field, such as using blue light for dental restoration [30] and the treatment of infant jaundice [31], and for ophthalmic procedures utilizing blue-green light [32]. In the industrial manufacturing sector, blue and green lasers are used for processing highly reflective metals, resulting in a smaller heat-affected zone and reduced deformation. However, compared to fiber lasers and CO₂ lasers, argon lasers have lower output power, lower conversion efficiency, and higher operating and maintenance costs, making them less common in industrial applications [33]. Fiber lasers are a type of laser based on optical fibers, utilizing fibers infused with various rare-earth metal ions as the working medium. According to their time-domain characteristics, these systems can be divided into continuous wave fiber lasers and pulsed fiber lasers. Due to their advantages of high efficiencies, low thresholds, excellent beam quality, and cost-effectiveness, lasers have gradually become the mainstream choice in fields such as industrial processing, medical treatment, military defense, aerospace, automobile manufacturing, shipbuilding, and scientific research [34].

Figure 3. Laser diagram: (a) CO₂ laser cutting [35], (b) fiber laser cutting [36], and (c) pulsed Nd:YAG laser cutting [37].

Figure 3. Laser diagram: (a) CO₂ laser cutting [35], (b) fiber laser cutting [36], and (c) pulsed Nd:YAG laser cutting [37].

2. Laser Cutting Parameters

The laser cutting process involves changes in energy, temperature fields, thermochemical reactions, and fluid mechanics, including aerodynamics. The input parameters of laser cutting can be divided into two parts, namely beam parameters and process parameters, as shown in Figure 4 and

Table 1. Classification of laser cutting parameters.

Beam Parameter	Process Parameter
Laser power (Pu)	Auxiliary gas and pressure (p)
Wavelength (λ)	Cutting speed (v)
Spot size (r)	Cutting distance (D)
Types of beams	Nozzle diameter (R)
Pulse width (PW) Pulse frequency (Pf) Pulse energy (Q)	Defocusing quantity (f)

. In actual processing, the relevant properties and parameters of the material and equipment are definitive. To improve the cutting quality and efficiency, the effects of different processing parameters on the results should be considered.

The use of different laser parameters results in different cutting qualities. Currently, there is no uniform standard for determining laser cutting quality, with differences in evaluation criteria among different laser equipment manufacturers worldwide. According to the international standards for thermally cut products and various studies, commonly used criteria for cutting quality can be divided into seven types: surface roughness (Ra) [38], kerf width (KW) [39], kerf taper (KT) [36], heat-affected zone (HAZ) [40], kerf deviation (KD) [41], material removal rate (MRR) [42], and hanging slag (S) [39], as shown in Figure 5.

The formulas for three parameters, KT, KD, and MRR, are as follows:

$$\mathrm{KT}={\displaystyle \frac{\mathrm{UKW}-\mathrm{LKW}}{2\pi T}}\cdot 180,$$

(1)

$$\mathrm{KD}=\mathrm{Avg}.\mathrm{Max}.\mathrm{TKW}-\mathrm{Avg}.\mathrm{Min}.\mathrm{TKW},$$

(2)

$$\mathrm{MRR}(\mathrm{kg}/\min )={\displaystyle \frac{\mathrm{W}1-\mathrm{W}2}{\mathrm{t}}},$$

(3)

where UKW is the upper kerf width, LKW is the lower kerf width, T is the thickness of the workpiece, Avg. Max. TKW is the average maximum taper kerf width, Avg. Min. TKW is the average minimum taper kerf width, W1 is the mass of the workpiece before cutting, W2 is the mass of the workpiece after cutting, and t is the cutting time. Based on several previous studies, Ra and KW are the most commonly used parameters [13].

Understanding the effect of machining parameters on the cutting quality helps to achieve accurate cuts. Some researchers have used different test methods for different evaluation quality parameters, including the Taguchi method (TM), full factorial design (FFD), responsive design (RD), the multiple regression method (MRM), single-factor experiments (SFEs), neural network models (NNMs), and a genetic algorithm (GA). The influences of different cutting parameters have been assessed, and optimal parameter combinations have been identified, as shown in

Table 2. Research on laser cutting process parameters of titanium alloys.

Author	Laser	Material	Method	Process Parameters	Auxiliary Gas	Cutting Quality Evaluation Parameter	Optimal Combination of Parameters
Aoud et al. [43]	CO2 laser cutting	3 mm Ti-6Al-4V	TM	Pu, v, p	N2	Ra	Pu = 3 kW, v = 2400 mm/min, and p = 2 bar
Shrivastava et al. [44]	Pulsed Nd:YAG laser cutting	1.6 mm Ti-6Al-4V	GA and MRM	PW, Pf, v, p	Air	KW, KT	p = 9.959 bar, PW = 1.447 ms, Pf = 6 Hz, v = 5.06 mm/min
Boudjemline et al. [45]	CO2 laser cutting	5 mm Ti-6Al-4V	FFD	Pu = 2000 W, v, p	N2	Ra	v = 2250–2400 mm/min, p = 12–14 bar
Shanjin et al. [46]	pulsed Nd:YAG laser cutting	1 mm TC1	SFE	Q, PW, v, p	air, Ar, N2	HAZ	Medium-Q, high-PW, high-v, and high-p, Ar
Kochergin et al. [47]	fiber laser cutting	2 mm BT1-0	SFE	v, Pf, p, f	Ar	KW, Ra, S	v = 3 mm/min, Pf = 100–200 Hz, p = 1–1.2 MPa, f = 0 mm
Kumar et al. [5]	pulsed Nd:YAG laser cutting	1.4 mm Ti-6Al-4V	TM	p, v, PW, Pf	N2	Ra, KT	Low-PW, low-Pf, high-v, medium-p
Boujelbene et al. [48]	CO2 laser cutting	2 mm pure Ti	TM	v, Pu, p	N2	Ra	v = 2400 mm/min, Pu = 2 kW, p = 14 bar
El Aoud B et al. [49]	CO2 laser cutting	3 mm Ti-6Al-4V and Ti	TM	Pu, v, p	N2	KW	Pu = 2 kW, v = 2400 mm/min, p = 8 bar
Pandey et al. [50]	pulsed Nd:YAG laser cutting	1.4 mm Ti-6Al-4V	NNM and GA	PW, Pf, v, p		Ra	p = 50.04 N/2, v = 0.278 mm/min, Pf = 13.9995 Hz, PW = 1.7 ms
Tamilarasan et al. [41]	pulsed Nd:YAG laser cutting	1 mm Ti-6Al-4V	RD and GA	PW, Q, v, p		KD, MRR	PW = 1.789 ms, Q = 4.574 J, v = 10 mm/min, p = 7.674 kg/cm2

, offering a reference for practical applications of laser cutting.

Alsaadawy et al. [51] studied the laser cutting of a Ti-6Al-4V (TC4) titanium alloy sheet with a 4 mm thickness and investigated the effects of the laser cutting power, cutting speed, and gas pressure on the surface roughness, kerf width, kerf taper, and slag hanging height. In the laser cutting process, commonly used auxiliary gases include air, oxygen (O₂), nitrogen (N₂), and argon (Ar). O₂-assisted cutting will generate hard and brittle oxides on the cutting surface, and even an uncontrollable burning phenomenon. If the cutting plate is thicker and the quality of the cutting surface is not considered, O₂ can be used to assist [46]. Air- and N₂-assisted laser cutting produces a thin layer of hard, brittle oxides and nitrides on the surface, leading to the formation of micro-cracks and a reduction in surface quality. In comparing nitrogen- and argon-assisted laser cutting of commercially pure titanium and Ti-6Al-4V titanium alloys, the results show that the surface is pale yellow and TiN is formed during nitrogen cutting. Compared with the substrate, the Vickers microhardness of the remelted zone is increased by about two times on the surface of pure titanium and three times on the surface of TC4 titanium alloy. In argon cutting, the surface is usually a bright white metallic color, and the cut edges are more regular and flatter [52,53]. By diluting nitrogen with argon, the properties of the nitride layer in surface roughness and crack can be improved, while the more argon content, the lower the microhardness of the titanium alloys [54]. In contrast, Ar-assisted cutting can produce a better cutting quality, a smaller HAZ, and minimal slag hanging [46], and the use of Ar-assisted cutting can produce a smaller HAZ and low slag hanging [53,55].

3. Microstructural Evolution Induced by Laser Cutting of Titanium Alloys

Titanium has two crystal structures, a closely packed hexagonal αphase below 882 °C and a body-centered cubic β phase at higher temperatures [56]. These structures serve as the basis for the classification of titanium alloys as α, near-α, α-β, and β [57]. Phase transitions occur in nearly all manufacturing processes involving rapid temperature changes, such as welding, forging, machining, and additive manufacturing [58]. These transitions induce significant microstructural changes and high residual stresses, thereby reducing the mechanical properties of the material [59]. Burgers [60] first obtained a certain orientation relation for the transition of hexagonal close-packed α phase to body-centered cubic β phase in zirconium alloys, which was later confirmed in titanium alloys. Therefore, this relationship is also known as the Burgers orientation relationship, defined as {110} β//{0001} α, <111>β//<11-20>α.

Shanjin et al. [46] used an Nd:YAG pulsed laser to cut TC1 titanium alloy plates with a thickness of 1 mm. The effects of three auxiliary gases—compressed air, N₂, and Ar—on the thickness of the HAZ, surface topography, and corrosion resistance were studied. The researchers found that a non-diffusion phase transition occurred in the HAZ, and the acicular martensite α′ structure formed. The effect of the pulse energy on the thickness of the HAZ is shown in Figure 6. Pulsed energies of 1.5 and 2.5 J produced HAZs with thicknesses of about 10 μm. Correspondingly, thicker HAZs were observed below and above 1.5 and 2.5 J. Due to the narrow kerf width at lower energies, the cleaning ability of the auxiliary gas was limited. This allowed additional molten material to adhere to the cutting surface, thus transferring more heat to the workpiece. Therefore, pulse energies below 1.5 J could produce a thicker HAZ layer. As the pulse energy increased above 2.5 J, more energy accumulated on the material, transferring more energy to the material and producing a thicker HAZ [46]. When the pulse frequency and cutting speed were maintained constant, at lower pulse widths, the kerf taper (KT) decreased with the increase in assist gas pressure. This was primarily due to the inverse relationship between pulse width and peak power, where an increase in peak power led to an increase in the laser penetration depth, resulting in a larger bottom kerf. Consequently, the difference in the kerf widths between the top and bottom decreased, leading to a reduction in KT. At higher pulse widths, KT initially decreased and then increased with the augmentation of assist gas pressure. This was mainly because the decrease in peak power caused the melt zone to approach the top, and the deposition of molten material on the sides and bottom reduced as the gas pressure increased, diminishing the difference in kerf widths. However, as the pulse width continued to increase, the amount of molten material produced at the top increased, causing the top kerf to widen, which in turn led to an increase in KT [5].

Scintilla et al. [61] used a fiber laser to cut a TC4 titanium alloy sheet with a thickness of 1 mm, employing Ar as the cutting auxiliary gas. They studied the effects of different cutting parameters on the cutting surface quality, and the results showed that different microstructures appeared in the TC4 during laser cutting. The microstructure of the matrix consisted of intergranular β (black) and equiaxed α (white) phases. The microstructure of the HAZ consisted of an acicular α phase, primary α phase, martensitic α′ phase, and β phase. The microstructure of the remelting zone (RL) was dominated by a β-transformation into the martensite α′ phase, as shown in Figure 7. With an increase in the cutting speed, the thicknesses of the HAZ and RL increased, primarily due to reduced heat input and the cooling effect of the auxiliary gas pressure, which led to a decrease in the temperature. However, the increased molten material that adhered to the section acted as an additional heat source, thereby increasing the RL and HAZ widths.

Aoud et al. [62] used a CO₂ laser to cut a TC4 titanium alloy sheet with a thickness of 3 mm, and N₂ was selected as the auxiliary gas. The microstructure was observed by SEM. The researchers found that the surface of the cut titanium alloy could be divided into three regions, namely the top, middle, and bottom, as shown in Figure 8a. The top area was the initial region of laser cutting where the surface material started to melt at high temperatures. The acicular martensite phase was observed in the middle area. The main reason was that when the laser beam passed through, the surface of the plate rapidly cooled due to the action of the auxiliary gas and heat conduction, resulting in a martensitic transformation, as shown in Figure 8b. These results were consistent with the findings obtained by Shanjin et al. [46] on the pulsed laser cutting of the titanium alloy. As shown in Figure 9, microcracks and voids formed on the TC4 cut surface. Microcracks are mainly due to thermal stresses generated during laser cutting, and increasing the cutting speed reduces the number and size of microcracks [63].

Parmar et al. [64] used argon as an auxiliary gas to cut 3-mm-thick TC4 using a fiber laser and confirmed that the TC4 titanium alloy could be largely converted into oxides after cutting with X-ray photoelectron spectroscopy (XPS, SPECS, Berlin, Germany), X-ray diffraction (XRD, Ultima-IV, Rigaku, Woodlands, TX, USA), and energy-dispersive X-ray spectroscopy (EDX, Swift ED3000, Oxford Instruments Analytical Limited, Wycombe, UK). The XPS analysis shown in Figure 10a indicated that Ti–6Al–4V was transformed into various oxides of its constituent metals, where TiO₂ was enhanced and transformed into Ti₂O₃. The XRD analysis in Figure 10b revealed that Ti, TiN, and TiO₂ were transformed into Ti₂O₃, and the EDX analysis in Figure 10c showed that the O₂ content increased by 19%. Kalyanasundaram et al. [65] proposed that the lattice spacing of the oxides was larger than that of the matrix material and hypothesized that the oxides could expand and help the molten metal penetrate and separate the substrate [66,67].

Electron backscatter diffraction (EBSD) orientation difference analysis serves as an important technical method for plasticity characterization, and it is widely used for the failure analysis of polycrystalline alloys under various operating conditions, such as tension, impulse, creep [68,69], creep-fatigue [70,71], and fatigue crack growth [72]. Accumulated plasticity in polycrystalline alloys can induce dislocation multiplication and lattice curvature within the grains, which can be measured by the EBSD local mismatched angle (e.g., kernel average misorientation (KAM) and grain reference orientation deviation (GROD)) [73]. The KAM method is based on the measurement of the core region, which can be used to explain the local strain distributions of crystalline materials. This method is especially suitable for illustrating the strain distribution at the grain and phase boundaries of crystalline materials after deformation, and it can be used to calculate the geometrically necessary dislocation (GND) density. The GROD method is based on grain measurement, with a higher KAM value indicating a higher geometrically necessary dislocation density inside the material.

Sun et al. established a quasi-in situ EBSD observation method to assess the microstructures and damage evolution of titanium alloys under cyclic loading [74]. The fatigue specimen axis of the Ti–6Al–4V ELI alloy was along the rolling direction, and its microstructure is shown in Figure 11, which consisted of equiaxed α-phase and lamellar β-transformation structures. Figure 11d presents the KAM diagram.

In a word, the microstructure of the cut surface after laser cutting consists of three typical regions: remelting zone, heat-affected zone, and matrix. Combined with the scanning electron microscope (SEM) image in Figure 12, it is evident that the matrix of the TC4 sheet consists of primary equiaxed α phase and intergranular β phase. The remelted zone consists of fine acicular martensite, with no β phase detected. The main reason is that the high-energy-density laser beam makes the temperature of the cutting zone rise rapidly, reaching and exceeding the phase transition temperature of the β phase, and then cools rapidly from above the β-phase transition temperature under the effect of auxiliary gases and heat conduction with the matrix and undergoes a non-diffusive martensitic phase transition into the acicular α’ phase [46]. The typical microstructure in the heat-affected zone includes the primary equiaxed α phase, black β phase, and a small amount of acicular α’ phase. The maximum temperature and cooling rate in this area are smaller than those in the remelting zone, and the martensitic transformation is less; the pinch α’ phase is finer.

4. Mechanical Properties of Cut Titanium Alloy

Laser cutting of titanium alloys can lead to changes in the surface properties of the processing area, mainly due to the high energy density of the laser beam acting on the surface of the workpiece. This causes the temperature to increase, the heat to diffuse along the edge of the kerf under the action of heat conduction, and rapid cooling to occur after the laser beam passes. Due to temperature changes, the microstructure of the titanium alloy changes, resulting in the formation of an HAZ. The emergence of this zone changes the hardness, plasticity, and other mechanical properties of the material.

Wu et al. [75] investigated the effects of laser cutting on the fatigue performance of TC4 titanium alloys by setting up three groups of specimens containing an HAZ, after removing the HAZ, and with no HAZ. The results showed that (1) the HAZ constituted a fatigue source zone, exhibiting brittle fracture characteristics. (2) The fatigue lives of the laser-cut specimens were significantly reduced by the presence of the HAZ, which were an order of magnitude lower than those of specimens without the HAZ. Hou et al. [76] set up three sets of specimens in the same manner and found that the presence of an HAZ affected the fatigue life of the material, and the fatigue life of the laser-cutting aircraft skin material was reduced by 20% to 25%. Germain et al. [77] analyzed the effect of laser-assisted processing on the fatigue lives of TC4 titanium alloys from a microstructural perspective. The researchers found that the fatigue life decreased from 580 to 550 MPa due to the formation of martensite in the HAZ. With increasing laser power, the residual stress increased and tended toward tensile stress or normal stress.

Ullah et al. [78] obtained the static tensile and fatigue properties of 0.5- and 1-mm-thick AA2B06–T4 alloy plates cut with different parameters. The results showed that the plate has higher tensile strength values at a cutting speed of 9 m/min, and the 1.5 MPa auxiliary gas pressure produces a better ultimate tensile strength (UTS), as shown in Figure 13a. For both thicknesses, UTS increases with increasing auxiliary gas pressure and decreasing severance energy (SE), as shown in Figure 13b,c. The combination of low SE (6.67–13.34 J/mm²) and high auxiliary gas pressure (1.5 MPa) results in better static mechanical properties and fatigue strength as shown in Figure 13d.

The failure mode in the fatigue test involved the generation, growth, and catastrophic failure of cracks. Surface irregularities such as indents, notches, stripes, or splines often serve as the sources of fatigue cracks. Figure 14 shows the SEM image of the fracture surface, which shows that a crack originated from the fringe, and the fatigue source area produced a depression structure, which is characteristic of ductile fracture. The V-shaped markings in the direction of fatigue extension indicate that catastrophic failure occurred as a result. Zhang et al. [79] investigated the deformation behavior of the Ti-17 titanium alloy under uniaxial stretching via in situ SEM. The results showed that slip was the main deformation mechanism of the primary α phase in the Ti-17 tensile test.

The hardness of the HAZ produced during laser cutting of the material was significantly higher than that of the base material, and in some instances, it was even twice as hard [80,81], where the final performance of the HAZ was mainly related to the martensite near the edge of the slit. Bursi et al. [82] analyzed the microhardness, residual stress, and high-cycle fatigue performance of laser-cutting metallic materials and found that the hardness of the HAZ was significantly improved. XRD revealed the visible peaks of martensite and the γ phase, as shown in Figure 15. The increase in the number of section stripes was identified as a key feature of the fatigue properties. The residual tensile stress in the material increased the external stress in the structural features, resulting in a decrease in the fatigue strength. Slow quenching of the cutting edge after the thermal cutting operation significantly reduced the residual stress.

Digital image correlation (DIC) technology is a non-contact optical measurement method, based on the principle of human binocular stereo imaging, mainly using the scattering pattern on the object and two camera-type image acquisition instruments. The image is compared before and after object deformation to obtain real-time strain field results [83]. DIC has been widely used to examine the formability and local deformation behavior during tensile testing [84]. Specifically, it has been used to investigate the local tensile properties of welds obtained by friction stir welding [85,86,87] and laser welding [88,89] of different metal materials. This technology has also been applied to the laser welding of Ti–6Al–4V [90,91]. Scintilla et al. [92] investigated the mechanical properties of welded joints using DIC technology after cutting and welding 1-mm-thick TC4 plates. Data acquisition was carried out using a LabVIEW-specific virtual instrument, and the DIC system used the ARAMIS three-dimensional (3D) optical deformation analysis system. The experimental setup is shown in Figure 16, where global strain maps were obtained from two cameras. Before the test, a pattern of scattered black spots was applied to a matte white background to prepare the tensile specimen. This pattern was used to correlate the images at different stages in the tensile process and calculate the strain data for each stage. Specifically, the influence of the weld geometry and microstructural changes on the mechanical properties of the joints could be assessed.

5. Numerical Simulations of Laser Cutting

The theoretical modeling of laser cutting can be used to establish a mathematical model of the relevant characteristics of the material cutting process through the use of physical principles and energy balance equations, such as temperature distribution and residual stresses.

5.1. Heat Source Model

In numerical calculations, the laser is typically represented using a relevant heat source expression, which is why the choice of heat source expression can be directly related to the results of the numerical calculations. Commonly used heat source models include the Gaussian heat source, rotary Gauss body heat source, double-ellipsoidal heat source, and composite heat source models [93].

5.1.1. Gaussian Heat Source Model

The Gaussian heat source model [94] is spatially in the form of a normal distribution, with the laser energy concentrated within the laser-spot diameter, which is in line with the distribution of the laser energy density in actual processing. The mathematical expression of the heat flux shown in Figure 17 is as follows:

$$q=\left(3\eta {\displaystyle \frac{P}{\pi r^2}}\right)\exp \left(-3{\displaystyle \frac{x^2+y^2}{r^2}}\right),$$

(4)

where q is the heat flux, η is the material absorption coefficient of the laser, P is the laser power, r is the laser spot radius, and x and y are the spatial position coordinates of the laser.

5.1.2. Rotary Gaussian Body Heat Source Model

The rotary Gaussian body heat source model [96] assumes that the laser energy density is concentrated in the Gaussian rotating body during laser action, which improves the energy distribution in the depth direction and improves the calculation accuracy of the puddle. As shown in Figure 18, the mathematical expression is given by the following:

$$q={\displaystyle \frac{9P}{\pi h{R}^2\left(1-e^{-3}\right)}}\exp \left[{\displaystyle \frac{-9\left(x^2+y^2\right)}{R^2\log \left(\frac{h}{z}\right)}}\right],$$

(5)

where P is the laser power, R is the radius of the heat source, and h is the height of the heat source.

5.1.3. Double-Ellipsoidal Heat Source Model

In the actual application process, the laser energy distribution does not consist of a 3D rotating Gaussian body. Some researchers have proposed an ellipsoidal heat source model, as shown in Figure 19. However, based on a large number of experimental observations, studies have found that the ellipsoidal model does not match the actual heat source distribution. As a result of this, some researchers proposed a double-ellipsoid heat source model [98] to model the laser energy density of the surface in different regions. The expressions are given by the following:

$$q_f={\displaystyle \frac{12\sqrt{3}{f}_f}{a_{f}bc\pi \sqrt{\pi }}}Q\exp \left(-{\displaystyle \frac{3x^2}{{a_f}^2}}-{\displaystyle \frac{3y^2}{b^2}}-{\displaystyle \frac{3z^2}{c^2}}\right),$$

(6)

$$q_r={\displaystyle \frac{12\sqrt{3}{f}_r}{a_{r}bc\pi \sqrt{\pi }}}Q\exp \left(-{\displaystyle \frac{3x^2}{{a_r}^2}}-{\displaystyle \frac{3y^2}{b^2}}-{\displaystyle \frac{3z^2}{c^2}}\right),x<0,$$

(7)

where the subscripts f and r denote the front and back of the semi-ellipsoid, respectively; a, b, and c indicate the long, middle, and short semi-axes of the ellipsoid, respectively; and f_f, f_r are the percentages of the front and back of ellipsoid energy scores, f_f + f_r = 2.

5.1.4. Recombination Heat Source Model

The single heat source model cannot accurately represent the actual laser energy. Therefore, a composite heat source model was proposed to establish different heat sources for various regions affected by the laser. This approach can provide a heat distribution that more closely aligns with the actual processing conditions with improved calculation accuracy. However, the selection of a combined heat source and the energy distribution coefficient must be based on empirical results and should be verified and refined in subsequent experiments.

Modest et al. first proposed the finite difference method (FDM) to model the beam machining process in 1988. Subsequent researchers gradually developed various finite element models (FEMs) to describe the characteristics of the temperature distribution, residual stress, and other factors in the material removal process, explaining the formation mechanisms affecting the kerf width and HAZ width. As shown in Figure 20, Yilbas et al. investigated the modeling of laser machining of thicker samples [100]. They developed a numerical model of laser machining using Abaqus software (https://www.3ds.com/products/simulia/abaqus, accessed on 30 September 2024) and analyzed the stresses during laser machining [101,102]. A temperature higher than the melting point indicated the transformation of the solid phase into the fluid phase. The titanium alloy remained in the liquid phase until it reached 3000 °C [103], and the molten metal started to partially vaporize from the fluid phase until it reached the vaporization temperature of 3558 °C. [104] The oxidation temperature of the titanium/titanium alloy was higher than 600 °C [105].

5.2. Laser Cutting Temperature and Stress Field Simulation

The temperature field during laser cutting consists of a nonlinear transient heat transfer problem, accompanied by phase transitions [112,113,114], where the changes in the stress field and the distributions of thermal and residual stress serve as the key parts of the laser cutting process design. Kardas et al. [115] experimented with high-pressure nitrogen-assisted laser cutting and predicted the temperature and thermal stress fields in the cutting zone using Abaqus finite element software. Morphological and elemental changes in the cut sections were analyzed by light microscopy, SEM, and EDX. The study found that the von Mises stress reached high values at the cutting edges, while in the mid-thickness position of the cut section, thermal strain during the cooling cycle was higher, which increased the stress at this location. Gu et al. [116] established a 3D transient FEM of Ni–Ti alloy powders as the raw material, observed the distribution of thermal stresses in the laser-selective melting process, and proposed a method for calculating the distribution of residual stresses to investigate the effect of residual stresses on the workpiece after cooling. Samanta [117] studied the cutting forces and residual stresses in laser-assisted processing and developed a thermo-mechanical coupled heat source model to predict the temperature, cutting forces, and residual stresses. Gaussian heat source models have often been used to predict the temperature field distributions of laser cutting [100,114,118]. Sharmlooei et al. [119] proposed an improved heat source model based on a Gaussian distribution, where the parameters of the model consisted of the laser power, cutting speed, spot size, and specimen thickness. The model was used to simulate the temperature field of the laser cutting in Abaqus, and an infrared thermal imager was used to detect the laser cutting process and the position of trace components during the test. The test results were consistent with the simulated temperature curve, and the distribution of trace components along the depth matched the temperature distribution predicted with the following equation, as shown in Figure 21:

$$Q={\displaystyle \frac{\left[c_1\left(w_i+\frac{w_u - w_i}{h}z\right)+c_2\right]q^{\prime }h}{\pi {\left[w_{i}h+\left(w_u-w_r\right)z\right]}^2}}\exp \left[-K^2{\displaystyle \frac{\left(x^2+y^2\right)h^2}{{\left[w_{i}h+\left(w_u-w_i\right)z\right]}^2}}\right]$$

(8)

where Q is the heat flux, c₂ is a constant, q’ is the effective laser power, h is the thickness of the steel element, x and y denote the coordinates of the Gaussian point from the center of the beam, z is the coordinate of the laser along the beam from the inlet face of the element, w_i and w_u are the beam radii at the inlet and outlet surfaces of the laser beams, respectively, and K₂ is the modulator coefficient.

Through simulation of the stress field of the temperature field in the cutting process, the study found that the temperature rose sharply in the region close to the laser heat source and then rapidly decayed as the laser heat source moved away. During the cutting process, the von Mises stress near the cutting edge achieved a higher value. However, due to changes in the temperature gradient along the cutting direction, the thermal strain generated in the cutting area changed, which reduced the von Mises stress to a local minimum. As the cutting progressed, the initially heated part of the cutting edge cooled to a low temperature, and the stress field transitioned to residual stress. The residual tensile stress at the cutting edge remained high [100], as shown in Figure 22.

5.3. Simulation of Laser Cutting Quality Evaluation Parameter

Zhai et al. [120] conducted a simulation and experimental study on the HAZ during the laser cutting of a TC4 titanium alloy. The results showed that the width of the HAZ was mainly affected by the laser power and cutting speed. Ding et al. [121] analyzed and predicted the effect of the phase transformation on the laser cutting of AISI 1045 steel based on metallo-thermomechanical coupling theory. In the study, a metallo-thermomechanically coupled model was established, and Abaqus software was used to simultaneously solve for the evolution of the phase constituent, cutting temperature, section shape, and cutting force. The experimental data matched well with the predicted values of the model. Fu et al. [122] developed a conical volumetric heat flow model to investigate the effects of each pulse-cutting process parameter on the kerf width, temperature, stress, and HAZ width of an Ni–Ti alloy, as shown in Figure 23. The moving heat flux of the pulsed laser was simulated using the Abaqus DFLUX subroutine. The study found that increasing the cutting speed reduced the kerf width, stress magnitude, and HAZ thickness, while the peak power pulses had the opposite effect. The stress was also mainly affected by the peak pulse power, and the slit was mainly affected by the average power. Yang et al. [114] established a 3D transient finite element model for the laser processing of Ti–6Al–4V alloy plates to predict the depth and width of the HAZ. This model explored the effects of the laser power, spot size, speed, and material properties on the depth and width of the HAZ, which provided a basis for optimizing and improving laser-assisted processing technology.

The formation of stripes has been shown to affect the quality of laser cutting. Laser cutting consists of a surface Fres absorption process, where the laser is converted into heat in the workpiece, melting the material. The molten material is then ejected from the area by an auxiliary gas jet. Wee et al. [123] developed a two-dimensional analytical model that focused on the effects of laser cutting parameters such as power, speed, and spot size on the cutting stripes, which predicted the energy absorption and oxidation processes at the cutting front. Pietro et al. [107] proposed a model to predict surface roughness during laser cutting by analyzing the dynamic phenomena at the cutting front, with the frequency of streak formation and the depth of the periodic structure as the output variables. Tani et al. [124] developed an analytical model of the quality, force, and energy balance, which was used to analyze the 3D geometry of the cutting front, the geometry of the hanging slag, and the temperature field. In addition, a method of interpreting the streak was proposed based on the slag evolution and the effect of the auxiliary gas pressure. Kovalev et al. [125] developed a mathematical model of viscous compressible gas supersonic flow and the experimental results of gas jet visualization in laser cutting by numerically solving the 3D Navier–Stokes equation. As shown in Figure 24, the airflow separation phenomenon at the cutting front was numerically simulated and experimentally verified, providing a model airflow structure of the conical supersonic nozzle. A mechanism was also proposed to control the airflow separation, which indicated that the airflow separation directly affected the changes in the structure of the streak, serving as one of the main reasons for the poor surface quality in laser cutting.

Kar et al. [126] developed a lumped parameter model that combined the width of the incision with various process parameters and obtained an empirical expression similar to the one proposed by Atsuta et al. [127] However, the model contained several constants that were difficult to measure. Based on this model, Li et al. [108] modified and re-established a lumped parameter model for the laser cutting depth, laser cutting parameters, and material properties. The model took into account the threshold power of the incident laser beam and modified earlier cutting models to make them suitable for a range of processes from low to high power and slow to fast cutting. Using ordinary steel as an example, the effects of the laser power, spot size, cutting speed, and other process parameters on the cutting depth were investigated. The model assumed that the temperature of the entire region reached at least the melting temperature and that kerf was generated by the auxiliary gas blowing off the melt. Therefore, this model was suitable for large-nozzle and high-pressure jet cutting. Considering various laser–material–water interaction phenomena, different depletion mechanisms, and the shear forces provided by water jets, Mullick et al. established a lumped parameter model for the water-jet-assisted underwater laser cutting of steel plates [128]. The model predicted the maximum laser cutting speed, notch width, and cutting front under different processing conditions, which were in good agreement with the experimental results.

6. Conclusions

With the increased use of titanium alloys in the aerospace field, laser cutting has gradually become widely used in the processing and manufacturing of metal materials as a non-contact advanced processing technology. In practical applications, this technique can effectively improve work efficiency and achieve a better cutting quality compared to traditional processing methods.

(1)

The quality evaluation factors of laser-cut metal sheets include surface roughness, kerf width, kerf taper, HAZ width, kerf deviation, material removal rate, and slag hanging. The parameters affecting the cutting quality can be categorized into beam parameters and process parameters, and commonly studied process parameters include laser power, cutting speed, and gas pressure. The surface roughness and kerf width have often been used to evaluate the cutting quality.

(2)

In the laser cutting process, the auxiliary gases most commonly used consist of nitrogen, argon, and air, with nitrogen being the most prevalent. Air- and N2-assisted laser cutting can produce a thin layer of hard and brittle oxides and nitrides on the surface, leading to microcracks and reduced surface quality. In contrast, argon-assisted cutting results in a better surface quality and a smaller HAZ.

(3)

Martensite is a pure metal or alloy transformed from one solid phase to another solid phase. The composition of the two phases remains unchanged before and after the transformation, and only the crystal structure changes, which is called non-diffusion martensitic transformation. In the process of laser cutting of titanium alloy, the temperature in the heat-affected zone rises rapidly due to the action of a high-energy-density laser beam, reaching and exceeding the phase transition temperature of the β phase. Then rapidly cooled from above the β-phase transition temperature under the action of heat conduction of the auxiliary gases and the substrate and undergoes a non-diffusive martensitic phase transition to the acicular α’ phase. Non-diffusive martensitic phase transformation can occur in the HAZ during the laser cutting of titanium alloys.

(4)

The modeling and simulation of laser-cut metal sheets can better describe the characteristics of the temperature distribution and residual stress during the material removal process. Simulations have revealed that the temperature will sharply increase in regions close to the laser heat source and rapidly decay as the laser heat source moves away. After the cutting is complete, the temperature will gradually decrease, with the stress field changing to residual stress. At this point, the residual tensile stress at the cutting edge will be very high.

(5)

Analytical models of the quality, force, and energy balance, as well as 3D finite element models of laser cutting with heat flow coupling, have been established. These models can explain the stripe formation mechanism, allowing researchers to explore the overall mechanisms of laser cutting.