A method of laser homogenization removal of composite material organization

Abstract

The application discloses a method for removing composite material structure by laser homogenization, which comprises the following steps: selecting two materials with the largest mass proportion in the composite material to be processed, and processing blind pits or blind grooves by using pulsed laser with adjustable pulse energy area density F; measuring the corresponding average pulse removal depth d of the two materials under different pulse energy area density F, and constructing the corresponding ordered pair (F, d) of each material; determining the ordered pair close to or the same between the two materials, determining the value of F, and taking kxF as the pulse energy area density for processing the composite material to be processed, wherein k is a coefficient with a value close to 1. The application starts from the pulse removal depth and the pulse removal width, and realizes the homogenization removal of the composite material structure by the super-short pulse laser through the convergence of the pulse removal depth and the pulse removal width of the two-phase materials in the core of the composite material, so as to provide support for the precise machining of the composite material structure and the composite material structure.

Description

Technical Field

[0001] This invention relates to the technical field of laser processing of composite material structures, and in particular to a method for laser homogenization to remove composite material structures. Background Technology

[0002] Advanced composite materials, as a class of complex materials formed by combining two or more materials with different physical and chemical properties in a complex spatial arrangement at the microscopic or mesoscopic scale, generally far exceed the performance of their elemental components. They are an extremely important class of engineering materials for national economic development. For example, in the aerospace field, typical composite materials such as fiber-reinforced resin-based materials and ceramic-reinforced metal-based materials have become irreplaceable key materials.

[0003] However, the excellent physical and chemical properties and complex material structure (multi-component, heterogeneous, interlaminated, etc.) of composite materials not only contribute to their excellent service performance but also bring technical challenges to their subtractive manufacturing processes. For example, typical two-phase composites such as carbon fiber-resin composites (CFRP), aramid fiber-resin composites (AFRP), and aluminum-based silicon carbide (SiC / Al) (all heterogeneous materials) have vastly different mechanical, thermal, electrical, and optical physical and chemical properties between their matrix and reinforcing phases (corresponding characteristic parameters can differ by several orders of magnitude). This makes it generally difficult to achieve homogenization of the material structure using traditional cutting, electrical discharge machining, or conventional ultrafast lasers.

[0004] The homogenization and removal of material structures in composite materials has significant application value and demand, such as for precision machining of cross-sections / interfaces required for precision cutting / hole making. Therefore, there is an urgent need to propose a laser processing method with a clear mechanism, simple method, and broad applicability to composite materials to meet the precision machining needs of composite materials and their structures. Summary of the Invention

[0005] As mentioned above, the distinct mechanical, thermal, electrical, and optical properties of the two core phases within composite materials make it difficult to homogenize and synergistically remove these different phases. Existing laser precision machining techniques for composite materials result in rough cross-sections with low dimensional accuracy. This invention addresses these problems by providing a laser homogenization method for removing composite material microstructures. This invention focuses on pulse removal depth and pulse removal width, achieving homogenization of the composite material microstructure using ultrashort pulse lasers by bringing the pulse removal depth and pulse removal width of the two core phases into convergence. This provides support for the precision machining of composite material microstructures and structures.

[0006] In a first aspect, a method for laser homogenization to remove composite material tissue is provided, comprising:

[0007] Step 1: Select materials with the same properties as the two components with the largest mass proportion in the composite material to be processed as two sample materials. Use a pulsed laser with a fixed center wavelength of λ, a fixed single pulse duration of τ, and an adjustable pulse energy surface density F to process blind pits or blind grooves on the two sample materials with N equivalent pulses respectively. The laser pulses incident on the same blind pit or blind groove are only the same pulse energy surface density F. The equivalent pulse N is the same for the two materials.

[0008] Step 2: Determine the maximum processing depth of the blind pit or blind groove corresponding to each value of the pulse energy surface density F for the two materials in Step 1 under different values ​​of F, and calculate the corresponding average removal depth per pulse d. The average removal depth per pulse d is the ratio of the maximum depth of the blind pit or blind groove processed in Step 1 to the number of equivalent pulses N applied; thereby constructing multiple ordered pairs (F) corresponding to the first material of the two materials. A ,d A ), and multiple ordered pairs (F) corresponding to the second material in the two materials. B ,d B );

[0009] Step 3, based on the ordered pairs (F) of the two materials in Step 2. A ,d A ), (F B ,d B By defining a finite preset region, we can determine ordered pairs that are close to or the same, and then determine the value of F.

[0010] Step 4: Based on the value of the pulse energy surface density F output in Step 3, take k×F as the value of the pulse energy surface density of the composite material to be processed, while keeping all other process parameters in Step 1 unchanged, and process the selected composite material, where k is the pulse energy surface density coefficient.

[0011] In conjunction with the first aspect, in some implementations of the first aspect, within a limited preset region, under the same pulse energy surface density F, the higher of the average removal depth d per pulse is no more than 20% higher than the lower of the average removal depth d per pulse.

[0012] In conjunction with the first aspect, in some implementations of the first aspect, in step 3, (F) is selected from multiple ordered pairs corresponding to the first material. A (i),d A (i)), select (F) from the multiple ordered pairs corresponding to the second material. B (j),d B (j)), satisfying: (F A (i),d A (i)), (FB (j),d B (j) are all within a limited preset region, (F) A (i),d A (i) represents the closest ordered pair (F) of the first material to the second material among multiple ordered pairs. B ,d B The ordered pairs of the change curve, (F) B (j),d B (j) represents the closest ordered pair (F) of the second material to the first material among multiple ordered pairs. A ,d A The ordered pairs of the change curve; then according to F A (i) and / or F B (j) Determine the value of F.

[0013] In conjunction with the first aspect, in some implementations of the first aspect, when the ordered pairs (F) of the two materials are respectively A ,d A ), (F B ,d B When intersections exist, determine the value of F, including:

[0014] The value of the pulse energy surface density F is determined based on the intersection point.

[0015] In conjunction with the first aspect, in some implementations of the first aspect, when the ordered pairs (F) of the two materials are respectively A ,d A ), (F B ,d B When there are cases where the values ​​are close to but not identical, determine the value of F, including:

[0016] Fit the average per-pulse removal depth d of the first material A The relationship between the pulse energy surface density F and the numerical fitting model d is obtained. A (F);

[0017] Fit the average per-pulse removal depth d of the second material B The relationship between the pulse energy surface density F and the numerical fitting model d is obtained. B (F);

[0018] Let d A (F)=d B (F) is used to determine the value of F.

[0019] In conjunction with the first aspect, in some implementations of the first aspect, the first material is a linear absorbing material, the second material is a nonlinear absorbing material, and the numerical fitting model d A (F)=A×ln(F / F th_ANumerical fitting model A is the removal depth coefficient of the first material, F th_A F is the processing threshold for the first material. th_B B is the processing threshold for the second material, and B is the removal depth coefficient of the second material.

[0020] In conjunction with the first aspect, in some implementations of the first aspect, when the numerical fitting model d A (F) and numerical fitting model d B (F) In the case of non-intersection, under the same pulse energy surface density F, d A (F) and d B (F) The higher value should be reduced by no more than 20%, and d should be recalculated. A (F)=d B (F) is used to determine the value of F.

[0021] In conjunction with the first aspect, in some implementations of the first aspect, when the ordered pairs (F) of the two materials are respectively A ,d A ), (F B ,d B When there are cases where the values ​​are close to but not identical, determine the value of F, including:

[0022] In the same coordinate system, connect the multiple ordered pairs (F) corresponding to the first material with lines in sequence. A ,d A This forms the first piecewise linear function graph, and then connects the multiple ordered pairs (F) corresponding to the second material with lines in sequence. B ,d B This forms a second piecewise linear function graph. The intersection of the first and second piecewise linear function graphs is used to determine the value of F.

[0023] In conjunction with the first aspect, in some implementations of the first aspect, when the first piecewise linear function graph and the second piecewise linear function graph are close but not identical, for the same pulse energy surface density F, the higher of the average removal depth d per pulse is reduced by no more than 20% to adjust a certain piecewise linear function graph, and then the intersection point is re-determined based on the adjusted function graph.

[0024] In conjunction with the first aspect, in certain implementations of the first aspect, the method satisfies at least one of the following:

[0025] The first material is a linear absorbing material, and the second material is a nonlinear absorbing material;

[0026] Both materials must have band gaps within the range of [0, 15], with units of electron volts (eV).

[0027] The radial energy distribution of the laser pulse used is Gaussian.

[0028] For the two material components with the largest mass proportion in the composite material to be processed, the sum of the mass proportions of the two material components is greater than or equal to 90%;

[0029] The duration of a single pulse τ ≤ 50 ps;

[0030] The equivalent pulse number N takes a fixed value in the interval [1, 100], and the unit is pulses;

[0031] Ordered pairs (F) A ,d A ) or (F B ,d B The number is 3 to 5;

[0032] k is a dimensionless number with a value range of [0.8, 1.2].

[0033] Compared with the prior art, the solution provided by the present invention has at least the following beneficial technical effects:

[0034] (1) The laser homogenization method for removing composite material structures provided by this invention is a simple and effective method based on the principle of "seeking common ground while reserving differences" and utilizing relevant physical effects. It leverages the characteristic that the pulse removal depth of nonlinear light-absorbing materials first increases rapidly with the laser pulse energy surface density and then approaches saturation, and that the rate of increase is less than that of linear light-absorbing materials when the pulse energy surface density is high. This achieves the effect of convergence of pulse removal depth between linear and nonlinear light-absorbing components in composite materials composed of nonlinear light-absorbing materials at higher pulse energy surface densities. Simultaneously, since the laser used is a Gaussian beam, its pulse removal width is almost independent of the material type at higher pulse energy surface densities. This achieves the convergence of removal characteristics of materials with different processing properties in the composite material in the pulse removal width direction. In summary, the simultaneous convergence of the laser pulse removal depth and width of the two main components in the composite material ensures quasi-homogeneous removal of non-homogeneous materials such as composite materials from a processing effect perspective. Therefore, this invention provides a precision processing method for composite materials.

[0035] (2) The laser homogenization method for removing composite material tissue provided by this invention is a simple and economical method. At the operational level, only the pulse energy needs to be adjusted to control the pulse energy surface density, which is a key parameter. Compared with those methods that require additional optoelectronic devices to homogenize and remove composite material tissue through pulse energy distribution time shapers, spatial shapers, or dual-band laser sources, this method takes advantage of the natural state of conventional ultrashort pulse laser source energy time distribution as a single pulse sequence and spatial energy distribution as a radial Gaussian distribution. The required laser processing equipment is existing conventional ultrashort pulse laser processing equipment. Therefore, the method provided by this invention is simple, economical, and suitable for a wide range of composite material processing applications.

[0036] (3) The laser homogenization method for removing composite material structures provided by this invention is a highly applicable and flexible method. Depending on the manufacturing target and specific process, pulsed laser processing involves various processes, including precision laser cutting, precision hole making, and the precision machining of cross-sections and surfaces / interfaces required for polishing. The common basic unit involved in the material removal process of these subtractive processes is the micro-etching of materials by the pulsed laser. The method provided by this invention starts from the characteristics of this common basic unit, namely the pulse removal depth and pulse removal width in the micro-etching of materials by the pulsed laser. It utilizes the relevant processing saturation effect to facilitate the "intersection" of the material micro-etching characteristic curves, achieving quasi-homogeneous removal of heterogeneous materials at the microscopic level. This provides crucial support for various precision machining needs driven by homogenization removal at a more macroscopic level, thus giving the method strong applicability. Furthermore, for the "intersection" method of the micro-etching characteristic curves, different data analysis methods are provided, such as the analytical function solution method and the discrete point broken line connection graphical method, offering the advantage of flexibility. Attached Figure Description

[0037] Figure 1 This invention provides a flowchart of a method for laser homogenization to remove composite material tissue.

[0038] Figure 2 This is a graph showing the pulse removal rate depth-pulse energy surface density calculation for two core components in carbon fiber reinforced resin materials.

[0039] Figure 3 These are typical scanning electron microscope results of carbon fiber reinforced resin materials processed using the present invention.

[0040] Figure 4 The images show typical scanning electron microscope results of carbon fiber reinforced resin materials processed before the application of this invention.

[0041] Figure 5This is a graph showing the pulse removal rate depth-pulse energy surface density calculation for two components in an aluminum-based silicon carbide material.

[0042] Figure 6 This is a topographic image of the pinhole edge of an aluminum-based silicon carbide material processed using the method provided in this invention. Detailed Implementation

[0043] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0044] like Figure 1 As shown, the present invention provides a method for laser homogenization to remove composite material tissue, and the specific steps are as follows.

[0045] Step 1: Select materials with the same isomorphic properties as the two components with the largest mass proportion in the composite material to be processed as two sample materials. Use a pulsed laser with a fixed center wavelength of λ, a fixed single pulse duration of τ, and an adjustable pulse energy surface density F to process blind pits or blind grooves on the two sample materials by in-situ tapping or single-track scanning with N equivalent pulses respectively. The laser pulses incident on the same blind pit or blind groove are only the same pulse energy surface density F, and the equivalent pulse N is the same for the two materials.

[0046] To clarify the pulse removal characteristics of the main components of the processed composite material, it is necessary to select materials with the same properties as the two components with the largest mass proportion in the composite material as two sample materials. On the sample, by adjusting the shutter time of the processing optical path, or by comprehensively controlling other processing parameters such as the scanning processing speed and pulse repetition frequency, it is possible to achieve in-situ tapping processing of blind pits or single-track scanning processing of blind grooves, and control the number N of equivalent pulses irradiated to the same position of each sample material.

[0047] In this application, materials with the same physical and chemical properties as the components refer to materials that are completely identical, including the selection of raw materials, material composition, preparation method, grade, physical and chemical properties, which are kept as highly consistent as possible.

[0048] In some embodiments, the duration of a single pulse τ is ≤50 ps.

[0049] In some embodiments, the radial energy distribution of the laser pulse used is Gaussian, which is the most common natural state of lasers used in manufacturing. The pulse energy distribution can be a circular Gaussian distribution or an elliptical Gaussian distribution.

[0050] In some embodiments, the equivalent number of pulses N takes a fixed value in the range [1, 100], and the unit is pulses.

[0051] The constraint of the equivalent pulse number N to a value within the range of [1, 100] fully considers that when the equivalent pulse number N does not exceed 100, the total depth of the processed blind pit or blind groove changes almost proportionally with N. This is beneficial for achieving accurate and reliable calculation of the average removal depth d per pulse in step 2.

[0052] In some embodiments, for the two material components with the largest mass percentage in the composite material to be processed, the sum of the mass percentages of the two material components is greater than or equal to 90%.

[0053] The composite material to be processed should be at least a two-phase composite material, and the sum of the mass percentages of the two material components with the largest mass percentage in the composite material should be greater than or equal to 90%. In other words, other material components in the composite material with a mass percentage of less than 10%, such as a small amount of material that plays a bonding or other role at the interface of the two-phase materials, can be regarded as impurity components in the composite material due to their low proportion.

[0054] In some embodiments, the band gap of each of the two sample materials must satisfy the range of [0, 15], with the unit being electron volts (eV). The two sample materials must satisfy the following conditions: one material has an optical absorption order m = 1, i.e., linear absorption, and the other material has an optical absorption order m ≥ 2, i.e., nonlinear absorption. Here, the optical absorption order m is the round-rounded integer of the ratio of the band gap of the material to the laser photon energy h × c / λ used, h is Planck's constant, c is the speed of light in vacuum, and λ is the center wavelength of the laser in step 1.

[0055] Since the method provided by this invention addresses two fundamental key characteristics of the micro-etching process of materials using pulsed lasers—pulse removal depth and pulse removal width—it needs to utilize the saturation effect of related etching processes to facilitate the intersection of the micro-etching characteristic curves of the two materials. In one implementation scenario, when the two main components of the composite material to be processed correspond to materials that are linear and nonlinear light-absorbing, it facilitates the intersection of the micro-etching characteristic curves of the two materials.

[0056] On the one hand, for nonlinear light-absorbing materials, when the pulse energy surface density F reaches a high value within a certain range, the pulse removal depth almost no longer increases with increasing F. However, the pulse removal depth of linear light-absorbing materials increases with increasing F more rapidly than that of nonlinear light-absorbing materials. By limiting such material composition conditions, the pulse removal depths of the two components in the composite material to be processed are more likely to be the same or similar at higher pulse energy surface densities F. On the other hand, the above constraints generally do not significantly restrict the range of composite materials to which the method provided by this invention is applicable: this is because composite materials are generally organically fused together from two materials with very different physicochemical properties. Therefore, the band gaps of the two phases in the composite material are generally different, or even significantly different. In fact, a considerable number of composite materials, such as carbon fiber-resin composites (CFRP) and aluminum-based silicon carbide (SiC / Al), which are widely used typical two-phase composites, satisfy this constraint for common laser bands, such as λ = 1030 nm to 1064 nm, 800 nm, and 532 nm.

[0057] Step 2: Determine the maximum processing depth of the blind pit or blind groove corresponding to each value of the pulse energy surface density F for the two materials in Step 1 under different values, and calculate the corresponding average removal depth d per pulse. This allows the construction of multiple ordered pairs (F) corresponding to the first material in the two materials. A ,d A ), and multiple ordered pairs (F) corresponding to the second material in the two materials. B ,d B ).

[0058] The average depth removed per pulse, d, is the ratio of the maximum depth of the blind pit or blind groove processed in step 1 to the number of equivalent pulses N applied. Higher precision requirements for composite material processing necessitate a greater number of ordered pairs.

[0059] This mainly involves measuring the maximum depth of blind pits or trenches. The equivalent pulse number N takes a fixed value within the range [1, 100]. The depth of the blind pits or trenches processed in step 1 should be distributed in the range of 10 nm to 100 μm. Furthermore, the larger the value of the pulse number N, the greater the average depth removed per pulse, within the constraints of the laser pulse width used, in the range of 10 nm to 1 μm. Therefore, when the equivalent pulse number N is N∈[1, 100], the total depth of the blind pits or trenches should be in the range of 10 nm to 100 μm. Measurement tools such as white light interferometers, laser confocal microscopes, optical ultra-depth-of-field microscopes, and atomic force microscopes should be selected according to the equivalent pulse number N used. However, the measurement tool should be selected based on the total depth of the blind pits or trenches to meet the corresponding resolution and range.

[0060] This invention requires at least two ordered pairs for both materials. This is the minimum requirement for fitting the function curve relationship. A larger number of ordered pairs leads to greater accuracy, whether in step 3 using the model-based solution to derive the analytical expression of the d(F) function or using the discrete point-polyline graph method. However, too many ordered pairs increase unnecessary workload: especially for the model-based solution method for deriving the analytical expression of the d(F) function, generally 3-5 ordered pairs are sufficient. The purpose is simply to derive the two unknown constants of the model through fitting, and then use the model to predict the values ​​of more ordered pairs. For the discrete point-polyline graph method, the number of ordered pairs can be selected according to requirements.

[0061] Step 3: Based on the ordered pairs (F) of the two materials in Step 2... A ,d A ), (F B ,d B By defining a finite preset region, we can determine ordered pairs that are close to or the same, and then determine the value of F.

[0062] In step 3, a limited preset area is defined, which can circle the ordered pairs of the two materials that are close in distance or even directly intersect, thus forming two types of cases: ordered pairs that are the same and ordered pairs that are different but close in distance.

[0063] In some embodiments, within a limited preset region, at the same pulse energy surface density F(F) A =F B Under the action of F, the average removal depth d per pulse of the material with the higher value is no more than 0-20% higher than that of the material with the lower value. The value of 0 represents that the average removal depth d per pulse of the two materials is equal under the action of the same pulse energy surface density F.

[0064] In some embodiments, in step 3, (F) is selected from the plurality of ordered pairs corresponding to the first material. A (i),d A (i)), select (F) from the multiple ordered pairs corresponding to the second material. B (j),d B (j)), satisfying: (F A (i),d A (i)), (F B (j),d B (j) are all within a limited preset region, (F) A (i),d A (i) represents the closest ordered pair (F) of the first material to the second material among multiple ordered pairs. B ,d B The ordered pairs of the change curve, (F) B(j),d B (j) represents the closest ordered pair (F) of the second material to the first material among multiple ordered pairs. A ,d A The ordered pairs of the change curve; then according to F A (i) and / or F B (j) Determine the value of F.

[0065] When the ordered pairs (F) of the two materials A ,d A ), (F B ,d B When there is an intersection, the value of the pulse energy surface density F can be determined directly based on the intersection.

[0066] When the ordered pairs (F) of the two materials A ,d A ), (F B ,d B When there are values ​​that are close to but not identical, methods for determining the value of F include the analytical method of solving by function and the graphical method of connecting discrete points with broken lines.

[0067] For the analytical solution method, in the first possible case, let F... A =F B =F, let The ideal value of the pulse energy surface density F required to make the average removal depth per pulse of the two components with the largest proportions in the specified composite material approach the same can be determined. th_A F is the processing threshold for the first material. th_B Let A be the processing threshold of the second material, B be the removal depth coefficient of the first material, and C be the removal depth coefficient of the second material.

[0068] Taking one of the aforementioned implementation scenarios as an example, the first material is a linear light-absorbing material with an absorption order m = 1, and the second material is a nonlinear light-absorbing material with an absorption order m ≥ 2.

[0069] first, For composite material components with light absorption order m≥2, the average removal depth d per pulse B The relationship between the pulse energy surface density F and the pulse energy surface density F is generally taken as (F B ,d B The purpose is simply to fit 3 to 5 ordered pairs of numbers to the model to deduce the two unknown constants, namely B and F. th_B Thus, d is obtained. B The analytical expression of (F). It is readily known mathematically that d B (F) The curve shows a characteristic of first increasing rapidly and then tending to saturate;

[0070] Secondly, dA (F)=A×ln(F / F th_A ) represents the average removal depth d per pulse for the composite material component with an absorption order m = 1. A The relationship between the pulse energy surface density F and the pulse energy surface density F is generally taken as (F A ,d A The purpose is simply to fit 3 to 5 ordered pairs of numbers to the model, with the goal of deriving the two unknown constants, A and F, through fitting. th_A It is easy to see mathematically that, relative to d B (F) curve, as F increases, d A The rate of increase of curve (F) gradually accelerates, thus d increases when F takes a larger value. A (F) The growth rate is also relatively fast.

[0071] Then let d A (F)=d B (F), that is, it was passed. The method for solving the equation to obtain F. This includes constants A and B, and the processing threshold F. th_A Processing threshold F th_B For the four unknowns, only 2 to 4 pairs of ordered pairs from each of the two materials are needed to numerically fit the model d. A (F)=A×ln(F / F th_A ),Model Therefore, the equation can be solved. The only remaining unknown is F. The F obtained at this point is the ideal value.

[0072] In the second possible case, when d is obtained by fitting using the analytical method of function expression... A (F) curve and d B When the (F) curves are close but cannot intersect in practice, under the same pulse energy surface density F, the curve corresponding to the higher average removal depth d per pulse will be... The value of B, or d A (F)=A×ln(F / F th_A Adjust the value of A in the calculation by no more than 20%, and then recalculate. The only remaining unknown in the equation is F. Because a certain error tolerance is artificially introduced, the subsequent processing result corresponding to the solved F will be an approximation that deviates from the ideal value to a certain extent.

[0073] For the discrete point piecewise line graphical method:

[0074] First, simply connect the composite material components with light absorption order m=1 sequentially using broken lines in the same coordinate system (F... A ,d A Scatter plot, forming function d A(F) is plotted as a broken line function, and the same method is used to obtain the function d of the composite material component with light absorption order m≥2. B The broken line graph of (F). Finally, using d A (F) and d B (F) Find the intersection or near-intersection of the function graph and solve for the F required in step 3.

[0075] For the discrete point piecewise linear graphical method, when the function d A The broken line graph of (F) and function d B When the piecewise linear function graphs of (F) are close to but not identical, under the same pulse energy surface density F, the higher of the two average removal depths d per pulse is allowed to be up to 20% higher than the lower of the two average removal depths d per pulse. By adjusting the higher of the average removal depths d per pulse by no more than 20% under the same pulse energy surface density F, a certain piecewise linear function graph can be adjusted, and then the intersection point or proximity region can be re-determined based on the adjusted function graph. The subsequent processing result corresponding to F obtained at this time will be an approximation that deviates from the ideal value to a certain extent.

[0076] Step 4: Referring to the value of the pulse energy surface density F output in Step 3, take k×F as the value of the pulse energy surface density of the composite material selected in Step 1, while keeping all other process parameters in Step 1 unchanged, and process the selected composite material, where k is the pulse energy surface density coefficient.

[0077] In some embodiments, k is a dimensionless number with a value range of [0.8, 1.2].

[0078] The following description, in conjunction with specific embodiments, provides further details.

[0079] Specific Example 1: Precision Cutting and Machining of Typical Non-metallic Composite Materials

[0080] First, following step 1, prepare the laser source for processing and its processing state for the sample material.

[0081] The laser used can emit a center wavelength of 532 nm, a single pulse duration of τ≈12 ps, and a pulse energy surface density F of 0–50 J / cm². 2 The tunable pulsed laser has a maximum usable pulse repetition frequency of 2.0 MHz. According to basic physics, the photon energy of the laser used is E = h × c / λ ≈ 2.33 eV. The radial energy distribution of the laser pulse is a near-circular Gaussian distribution, which is the most common natural state for manufacturing lasers. The diameter of the resulting focused spot for processing is (1 / e... 2The thickness (defined by type) is 30 μm. The processing head is a scanning galvanometer type scanning processing head. By coordinating the scanning processing speed v and the pulse repetition frequency, it can generate processing capability covering the value range of [1, 100] for the equivalent pulse number N. For the processed material, consider the case where the equivalent pulse number N = 50.

[0082] Consider a carbon fiber reinforced resin (CFRP) composite material, specifically a multidirectional plate made of a certain grade of epoxy resin reinforced with M55 carbon fiber with a thickness of 1.5 mm. The carbon fiber volume fraction is approximately 70%, and the combined mass of carbon fiber and epoxy resin in this CFRP material accounts for over 95% of the total mass. The band gaps of the carbon fiber and epoxy resin used are <0.5 eV and 2.9 eV, respectively. The photon energy of the laser used is approximately 2.33 eV, and the optical absorption order m is m = 1 (i.e., linear absorption) and m = 2 (i.e., nonlinear absorption), respectively.

[0083] In the sample material processing stage, pulse energy surface density F = 1.0, 2.0, 3.0, 5.0, 10, 20 J / cm³ is considered. 2 Six energy density values ​​were obtained and used to process carbon fiber tow specimens and epoxy resin specimens clamped on a processing table. Each energy density F was processed at least five times to ensure repeatability and subsequent data acquisition. During processing, it was ensured that the laser pulses incident on the same blind pit or blind groove had the same pulse energy density F, and that the equivalent pulse N for the carbon fiber tow specimen and the epoxy resin specimen in the same blind pit or blind groove was the same.

[0084] Secondly, the samples of the two materials in step 1 were measured, and the average removal depth d per pulse was considered under the action of different values ​​of pulse energy surface density F.

[0085] Using a white light interferometer and an optical super-depth-of-field microscope, the values ​​of F were measured sequentially at 1.0, 2.0, 3.0, 5.0, 10, and 20 J / cm². 2 The total processing depth at each pit or groove on the carbon fiber tow specimen and a certain grade of epoxy resin specimen was measured under six numerical conditions. The processing depth data was collected by averaging at least three measurements. Since the effective number of pulses applied to each pit or groove is 50, dividing the collected data by 50 yields the average removal depth d per pulse under different values ​​of pulse energy surface density F.

[0086] Next, we need to find the intersection or near-intersection of the ordered pairs of the two materials, namely carbon fiber and a certain grade of epoxy resin. Here, we consider using the discrete point broken line connection graphical method.

[0087] This graphical method requires a large amount of data, which is why six pulse energy surface densities F were considered in the preceding steps. In practice, the smaller values ​​of pulse energy surface density F can be removed as appropriate, without affecting the subsequent output results. Figure 2 As shown, the pulse removal depth of epoxy resin materials with nonlinear absorption characteristics first increases rapidly with the laser pulse energy surface density and then approaches saturation. Furthermore, when the pulse energy surface density is high, the rate of increase is less than that of carbon fiber materials with linear light absorption characteristics. This achieves the effect of convergence of pulse removal depth between carbon fiber and resin materials in the pulse removal depth direction of the carbon fiber reinforced resin composite material at higher pulse energy surface densities. Simultaneously, from... Figure 2 It can be seen that the pulse energy surface density is approximately F = 12.5 J / cm². 2 At that time, the average pulse removal depth of carbon fiber materials and resin materials reached the same value, which is ≈470nm.

[0088] Finally, in the actual processing of composite materials, a value of (0.8~1.2)×12.5J / cm can be taken. 2 =10~15J / cm 2 The value within the range is used as the processing energy surface density for the selected carbon fiber reinforced resin (CFRP) composite material, while keeping all other process parameters in step 1 constant. Where F = 12.5 J / cm² 2 It is the optimal value for homogenizing and removing CFRP composite materials. Figure 3 The paper presents typical scanning electron microscopy results of carbon fiber reinforced resin materials processed using this invention. It shows that the cut surface of the material remains relatively smooth even at 5000x magnification—a sign that the microstructure of CFRP, as a heterogeneous material, has been homogenized and removed. This is consistent with… Figure 4 The images show typical scanning electron microscope results of processed carbon fiber reinforced resin materials before the application of this invention, providing a stark contrast. Figure 4 In this process, the resin at the same height as the carbon fiber has been removed, but the carbon fiber remains. This is achieved using F = 1–3 J / cm. 2 A common problem during the processing of CFRP is that, as a heterogeneous material composite, the carbon fibers and resin cannot be homogenized and removed synergistically. This directly results in rough processed surfaces and low dimensional accuracy determined by the cross-section.

[0089] Specific Example 2: Precision Milling of Typical Metal Matrix Composites

[0090] First, following step 1, prepare the laser source for processing and its processing state for the sample material.

[0091] The laser used can emit a center wavelength of 1030 nm, a single pulse duration τ≈0.8 ps, and a pulse energy surface density F in the range of 0–200 J / cm². 2 The tunable pulsed laser has an adjustable pulse repetition frequency ranging from 10 kHz to 1.0 MHz. The radial energy distribution of the laser pulse is a near-circular Gaussian distribution, and the resulting focused spot diameter for processing is (1 / e). 2 The diameter (defined as 30 μm) is 30 μm. The machining head is a rotary scanning head, specifically designed for rotary scanning hole making. Depending on the size of the hole to be machined, it can generate scanning speeds ranging from v = 0 to 380 mm / s. For the target hole, by coordinating the scanning speed v and the pulse repetition frequency, it can generate an equivalent pulse number N covering the range [1, 100]. For the material being machined, the case of equivalent pulse number N = 10 is considered.

[0092] Consider an aluminum-based silicon carbide (SiC / Al) composite material, which is an Al-Cu aluminum alloy reinforced with 40% SiC particles by volume and approximately 1.0 mm thick. The combined mass of the silicon carbide particles and the aluminum alloy accounts for over 95% of the total composite material. The band gaps of the silicon carbide and aluminum alloy used are approximately 3.0 eV and <0.2 eV, respectively. Referring to the photon energy of the laser used, E≈1.21 eV, the optical absorption orders m are m=3 (i.e., nonlinear absorption) and m=1 (belonging to linear absorption), respectively.

[0093] In the sample material processing stage, only the pulse energy surface density F is considered. A =F B =F = 1.0, 2.0, 5.0 J / cm 2 Three values ​​are obtained, and using this energy density, specimens with properties identical to those of the aluminum alloy and silicon carbide in the processed aluminum-based silicon carbide (SiC / Al) composite material are processed. Each energy surface density F is processed at least 5 times to ensure data reliability. During processing, it is necessary to ensure that the laser pulses incident on the same blind pit or blind groove have the same pulse energy surface density F, and to ensure that the equivalent pulse N for the aluminum alloy and silicon carbide specimens in the same blind pit or blind groove has the same value.

[0094] Secondly, based on the above steps, for aluminum alloy and silicon carbide specimens, the average removal depth d per pulse under different values ​​of pulse energy surface density F is considered.

[0095] Using a white light interferometer and other microscopic measuring equipment, F = 1.0, 2.0, and 5.0 J / cm were measured sequentially. 2The total machining depth at each pit or groove on the aluminum alloy and silicon carbide specimens was determined when three values ​​were applied. The average of at least three measurements was taken when collecting the machining depth data. Since the effective number of pulses applied at each pit or groove is 10, the collected data was divided by 10 to obtain the average removal depth d per pulse under different values ​​of pulse energy surface density F.

[0096] Next, we need to find the intersection or near-intersection of the ordered pairs of the aluminum alloy and silicon carbide materials used. Here, we consider using the analytical function method to solve this problem.

[0097] First, for silicon carbide materials with an absorption order m=3, such as Figure 5 As shown, using the three ordered pairs (F) obtained by measurement B ,d B Fitting the analytical model We obtain B = 103 ± 6 (nm·J) 2 / cm 4 ),F th_B =0.50±0.04J / cm 2 It is easy to see d B (F) The curve shows a rapid increase followed by a tendency to saturate.

[0098] Secondly, for aluminum alloy materials with an absorption order m=1, such as Figure 5 As shown, using the three ordered pairs (F) obtained by measurement A ,d A Fit analytical model d A (F)=A×ln(F / F th_A ), yielding A = 160 ± 9 (nm), F th_A =0.30±0.04J / cm 2 It is easy to see that, compared to the aforementioned silicon carbide d... B (F) curve, for aluminum alloys d A The (F) curve increases faster when F is large, to the point that it exceeds d when F takes a relatively large value. B The value of (F).

[0099] Again, let d A (F)=d B (F), that is, consider 160×ln(F / 0.3)=103×(0.5) -2 -F -2 The solution is easily obtained numerically: F≈3.75J / cm². 2. At this point, the average pulse removal depth of both silicon carbide and aluminum alloy materials reaches the same value, approximately 404 nm.

[0100] Finally, in actual processing, a value of (0.8~1.2)×3.75J / cm can be taken. 2 =3.0~4.5J / cm 2 The values ​​within the range are used as the processing energy surface density for the selected aluminum-based silicon carbide composite material, while keeping all other process parameters in step 1 unchanged.

[0101] Figure 6 Typical optical microscopic results of the processed aluminum-based silicon carbide composite material using the present invention are shown. It can be seen that the processed aluminum-based silicon carbide material exhibits good pore edge morphology. Although there is no excessive removal of silicon carbide or aluminum alloy matrix, this is a sign that the microstructure of the particle-reinforced aluminum-based silicon carbide material, which is a heterogeneous material, has been homogenized and removed.

[0102] It is worth mentioning that, on the one hand, the method provided by this invention elucidates, both mechanistically and methodologically, why different components in composite materials tend to converge or even become equal in the pulse removal depth direction, serving as the primary and key starting point for achieving homogenized removal of heterogeneous materials; on the other hand, although the method provided by this invention does not directly solve the problem of equalizing different components in the pulse removal width direction in a theoretical sense, the surface density F of the processing energy required to ensure that different components are consistent in the depth direction during pulse removal naturally takes into account the convergence of different components in the material removal width direction. For Gaussian lasers, the width of the pulsed material removal (i.e., D) is related to the processing spot radius (ω), the applied pulse energy surface density (F), and the material processing threshold (F). th The relationship between the four is as follows: That is, with the relative threshold multiple F / F th As the threshold increases, the pulse width D for material removal will continue to increase, but its value will tend to saturate. Specifically, in implementation case 2, the processing threshold F for aluminum alloy materials... th_A ≈0.30J / cm 2 The processing threshold F of silicon carbide materials th_B ≈0.50J / cm 2 Compared to the processing threshold F of aluminum alloy materials th_A It is 67% higher. Simultaneously, the applied pulse energy surface density is F = 3.75 J / cm². 2 Top and bottom, and for aluminum alloy materials there is F / F th_A =12.5 times, for silicon carbide there is F / F th_B = 7.5 times. However, due to the pulse removal width for aluminum alloy materials... Only compared to the pulse removal width of silicon carbide materials The difference is approximately 12%. Therefore, the pulse removal widths of the two different materials within the aluminum-based silicon carbide composite material converge. Considering that equal pulse removal depths of the two different materials within the composite material have been previously achieved, this indicates that the proposed method, by controlling an appropriate pulse energy surface density F, can achieve both equal pulse removal depths and simultaneous convergence of removal widths of the two different materials within the composite material in an engineering sense. This advantageously ensures the homogeneous removal of material structures with non-uniform characteristics within the composite material.

[0103] In summary, this invention provides a laser homogenization method for removing microstructures from composite materials. Targeting composite materials composed of nonlinear light-absorbing materials, it utilizes the "seeking common ground while reserving differences" approach. By leveraging the different sensitivities of the pulse removal depth to changes in pulse energy surface density for both nonlinear and linear light-absorbing materials, it achieves equal pulse removal depths within a high pulse energy surface density range. Furthermore, by utilizing the saturation characteristics of a Gaussian beam in the pulse removal material width direction, it achieves convergence in pulse removal widths. The pulse removal depth and width are fundamental and crucial properties in the micro-etching of materials by pulsed lasers. Therefore, achieving quasi-homogeneous synergistic removal of different components within heterogeneous materials at the microscopic level greatly helps to fundamentally solve the problems in existing technologies, such as the difficulty in homogenizing and synergistically removing different phases in the material microstructure due to the vastly different mechanical, thermal, electrical, and optical physicochemical properties of the two phases within the composite material, and the resulting roughness of the processed cross-section. This provides crucial support for achieving various precision machining needs driven by homogenization removal at a more macroscopic level.

[0104] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope defined in the claims of the present invention.

Claims

1. A method for laser homogenization to remove composite material tissue, characterized in that, include: Step 1: Select materials with the same properties as the two components with the largest mass proportion in the composite material to be processed as two sample materials. Use a pulsed laser with a fixed center wavelength of λ, a fixed single pulse duration of τ, and an adjustable pulse energy surface density F to process blind pits or blind grooves on the two sample materials with N equivalent pulses respectively. The laser pulses incident on the same blind pit or blind groove are only the same pulse energy surface density F. The equivalent pulse N is the same for the two materials. Step 2: Determine the maximum processing depth of the blind pit or blind groove corresponding to each value of the pulse energy surface density F for the two materials in Step 1 under different values ​​of F, and calculate the corresponding average removal depth per pulse d. The average removal depth per pulse d is the ratio of the maximum depth of the blind pit or blind groove processed in Step 1 to the number of equivalent pulses N applied; thereby constructing multiple ordered pairs (F) corresponding to the first material of the two materials. A ,d A ), and multiple ordered pairs (F) corresponding to the second material in the two materials. B ,d B ); Step 3, based on the ordered pairs (F) of the two materials in Step 2. A ,d A ), (F B ,d B By defining a finite preset region, we can determine ordered pairs that are close to or the same, and then determine the value of F. Step 4: Based on the value of the pulse energy surface density F output in Step 3, take k×F as the value of the pulse energy surface density of the composite material to be processed, while keeping all other process parameters in Step 1 unchanged, and process the selected composite material, where k is the pulse energy surface density coefficient.

2. The method according to claim 1, characterized in that, Within a limited preset region, under the same pulse energy surface density F, the higher average removal depth d per pulse is no more than 20% higher than the lower average removal depth d per pulse.

3. The method according to claim 1, characterized in that, In step 3, select (F) from the multiple ordered pairs corresponding to the first material. A (i),d A (i)), select (F) from the multiple ordered pairs corresponding to the second material. B (j),d B (j)), satisfying: (F A (i),d A (i)), (F B (j),d B (j) are all within a limited preset region, (F) A (i),d A (i) represents the closest ordered pair (F) of the first material to the second material among multiple ordered pairs. B ,d B The ordered pairs of the change curve, (F) B (j),d B (j) represents the closest ordered pair (F) of the second material to the first material among multiple ordered pairs. A ,d A The ordered pairs of the change curve; then according to F A (i) and / or F B (j) Determine the value of F.

4. The method according to claim 1, characterized in that, When the ordered pairs (F) of the two materials A ,d A ), (F B ,d B When intersections exist, determine the value of F, including: The value of the pulse energy surface density F is determined based on the intersection point.

5. The method according to claim 1, characterized in that, When the ordered pairs (F) of the two materials A ,d A ), (F B ,d B When there are cases where the values ​​are close to but not identical, determine the value of F, including: Fit the average per-pulse removal depth d of the first material A The relationship between the pulse energy surface density F and the numerical fitting model d is obtained. A (F); Fit the average per-pulse removal depth d of the second material B The relationship between the pulse energy surface density F and the numerical fitting model d is obtained. B (F); Let d A (F)=d B (F) is used to determine the value of F.

6. The method according to claim 5, characterized in that, The first material is a linear absorbing material, the second material is a nonlinear absorbing material, and the numerical fitting model d A (F)=A×ln(F / F th_A Numerical fitting model A is the removal depth coefficient of the first material, F th_A F is the processing threshold for the first material. th_B B is the processing threshold for the second material, and B is the removal depth coefficient of the second material.

7. The method according to claim 5 or 6, characterized in that, When numerically fitting model d A (F) and numerical fitting model d B (F) In the case of non-intersection, under the same pulse energy surface density F, d A (F) and d B (F) The higher value should be reduced by no more than 20%, and d should be recalculated. A (F)=d B (F) is used to determine the value of F.

8. The method according to claim 1, characterized in that, When the ordered pairs (F) of the two materials A ,d A ), (F B ,d B When there are cases where the values ​​are close to but not identical, determine the value of F, including: In the same coordinate system, connect the multiple ordered pairs (F) corresponding to the first material with lines in sequence. A ,d A This forms the first piecewise linear function graph, and then connects the multiple ordered pairs (F) corresponding to the second material with lines in sequence. B ,d B This forms a second piecewise linear function graph. The intersection of the first and second piecewise linear function graphs is used to determine the value of F.

9. The method according to claim 8, characterized in that, When the first and second piecewise linear function graphs are close but not identical, for the same pulse energy surface density F, the higher of the average removal depth d per pulse is reduced by no more than 20% to adjust a certain piecewise linear function graph, and then the intersection point is re-determined based on the adjusted function graph.

10. The method according to claim 1, characterized in that, The method satisfies at least one of the following: The first material is a linear absorbing material at the center wavelength λ of the laser used, and the second material is a nonlinear absorbing material at the center wavelength λ of the laser used. Both materials must have band gaps within the range of [0, 15], with units of electron volts (eV). The radial energy distribution of the laser pulse used is Gaussian. For the two material components with the largest mass proportion in the composite material to be processed, the sum of the mass proportions of the two material components is greater than or equal to 90%; The duration of a single pulse τ ≤ 50 ps; The equivalent pulse number N takes a fixed value in the interval [1, 100], and the unit is pulses; Ordered pairs (F) A ,d A ) or (F B ,d B The number is 3 to 5; k is a dimensionless number with a value range of [0.8, 1.2].

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