Insight into the surface behavior and dynamic absorptivity of laser removal of multilayer materials

Guiyang Yang; Le Liu; Qiaodan Chen; Wei Xiong; Leimin Deng

doi:10.1364/OE.501972

1. Introduction

Laser micro/nano processing is widely applied in various specialized manufacturing fields due to its excellent processing quality, resolution and material applicability [1–3], such as regular/irregular structures [4,5], general/special performances [6,7], heterogeneous/ homogeneous materials [8,9]. Among them, precision microfabrication and three-dimensional orientation properties are exactly what is needed for the directional removal of multilayer heterogeneous materials [10,11]. Thus, exploring the interaction process between laser and materials is of great significance for analyzing laser processing. However, the manufacturing process and physical phenomena of laser processing multilayer heterogeneous materials are different from that of single-layer isotropic materials [12]. Therefore, it is essential to investigate the surface behavior and dynamic reaction for the laser interaction with multilayer heterogeneous materials.

As for the physical mechanism of laser interaction with materials, there is extensive literature involving theoretical and experimental studies, most of them have revealed some qualitative laws of the interaction process from different aspects [13,14], and it can be described in terms of three types of reaction mechanisms as follows: 1) Photothermal effect: it is generally reported that in the accumulation process of multiple pulses, subsequent pulses continue to act on the thermal radiation area of the previous pulse, and the surface temperature will gradually rise, then reducing the material ablation threshold and making the material melt, vaporize and splash [15]. 2) Photoionization effect: when the laser single/multiphoton energy is greater than the bond energy or ionization energy of the material, electronic transition with the absorption of laser energy, photolysis or photoionization will be induced to directly break the chemical bonds and then results in the formation of new specific substances [16–18]. 3) Photoforce effect: after photon energy is absorbed on the surface of the material, the local temperature rises sharply and then generates a vapor-induced recoil pressure shockwave (light pressure), it will change the entanglement network configuration of the submicroscopic structure in the radiation region and form dislocations [19], such as laser shock strengthening [20]. Among them, the photothermal effect is commonly easily induced at the nanosecond pulse width scale [21]. Laser microprocessing has outstanding processing efficiency due to the continuous heat accumulation, it is widely used in fields such as material modification, laser cleaning, micro/nano manufacturing, etc. [22,23]. Therefore, it is of great significance to analyze the formation mechanism and evolution behavior of the photothermal effect for guiding the laser processing.

The high-energy laser pulse interacts with the material, the sample surface is heated and rapidly warms up, and the high temperature plasma region is rapidly expanded along the normal line of the sample surface, and then the atomic spectral lines are radiated outward due to the energy level transition during the cooling [24,25]. Furthermore, the jet particles are formed by the violent interaction of the subsequent pulse and the previous pulse. The incident energy of laser pulse is reflected, scattered and absorbed by the plasma plume generated by ablated material, and then the plasma shielding effect occurs, which causes the laser focus to diverge and diminishes the radiation energy [26]. However, the absorptivity of materials to laser ablation exhibits dynamic variations rather than remaining constant during actual laser processing. It is influenced by the coupling effect of multiple physical factors including surface morphology, radiation temperature, plasma excitation and evolution. Therefore, it is indispensable to investigate the influence mechanism and impact degree of each physical parameter on laser absorptivity.

In this paper, an integrated system of pulsed laser scanning processing with plasma spectrum in-situ monitoring was proposed for multilayer heterogeneous materials. The evolution tendency of spectral signals, the distribution of plasma temperature and electron density were investigated during repeated scanning processing. At the same time, an equivalent roughness model was developed to quantitatively analyze the influence of surface morphology changes on laser absorptivity, and the influence of substrate temperature changes on the material's electrical conductivity and laser absorptivity were analyzed by high-speed infrared imaging. This work reveals the physical mechanism of dynamic variations in laser absorptivity caused by changes in plasma characteristics, surface roughness, and substrate temperature, and it provides a valuable guideline for exploring the dynamic interfacial reaction between laser and materials.

2. Experimental system and characterization

2.1 Experimental system

Based on the spectral differences from the heterogeneous composition of multilayer materials, we have developed an integrated system of laser scanning processing with coaxial spectrum online monitoring, by which the in-situ spectrogram during laser scanning was reconstructed, and optimized the dynamic alternation influence of signal uniformity and stability across the entire sweep field, as shown in Fig. 1.

Fig. 1. Schematic diagram of laser scanning processing with coaxial spectrum monitoring.

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In Fig. 1, the integrated system was equipped with a nanosecond fiber laser (@1064 nm, 2.48 W, 30 ns, 40 kHz). In the processing unit, a system control card (USC-3, SCAPS, Germany) was used. The laser beam was deflected by the scanning galvanometer in the two-dimensional plane and then focused on the sample surface by the F-θ lens. The galvanometer scanner was customized to reflect laser@1064 nm and broadband spectrum@200-800 nm with high efficiency. An F-θ lens of fused silica telecentric field lens was used with an effective focal length (EFL) of 100 mm and it could coaxially reverse transmitting the induced plasma spectra. In the signal monitoring unit, the reflected light and the atomic emission spectra were separated using a notch filter (86-128, Edmund, USA). The characteristic spectrum was coupled by fiber and then online monitored by the fiber optic spectrometer (Fx∼, Ocean Optics, USA), by which the characteristic plasma spectrum can be collected and analyzed to identify the elemental composition of the ablated materials. And then the pulse control timing and Transistor-Transistor Logic (TTL) signals of the laser would be adjusted according to the analysis results. Hence, it can be used to identify and control the manufacturing stages of processing multilayer materials.

2.2 Characterizations and measurements

The elemental spectral lines of multilayer materials were analyzed online by a fiber optic spectrometer (Fx∼, Ocean Optics, USA). The total reflectance spectra of the sample surfaces were measured using a spectrophotometer (SolidSpec-3700, SHIMADZU, Japan) in the ultraviolet, visible, and near-infrared regions (200-1200 nm). The scanning electron microscopy (SEM EVO 18, ZEISS, Japan) was used to characterize the surface morphology of multilayer materials. The three-dimensional morphology and surface roughness of the multilayer materials were obtained with a laser scanning confocal microscope (VK-X 1000, KEYENCE, Japan). The temperature field distribution during the removal process was monitored online by a high-speed infrared thermal imager (348C+, FOTRIC, China).

3. Results and discussion

3.1 Multilayer heterogeneous materials and multilayer spectra

A multilayer heterogeneous material of copper clad laminate (CCL) with thickness of 1 mm was tested, it consists of four layers and three types of heterogeneous materials from top to bottom, such as (I): Copper layer (12 µm). (II): Epoxy resin layer (1 µm) and it is composed of (C₁₁H₁₂O₃)n. (III): Fiberglass layer (986 µm), it is composed of Al₂O₃ and SiO₂. The material composition and microscopic images of each layer are shown in Fig. 2(a):

Fig. 2. The material composition and characteristic spectrum of CCL. (a) Material composition and microscopic image of each layer. (b) Multilayer characteristic spectra.

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The laser with a pulse width of 30 ns, single pulse energy of 62 µJ, repetition rate of 40 KHz. And the laser beam moved rapidly in 7 mm × 7 mm with scanning speed of 700 mm/s driven by a galvanometer, the line spacing was 0.008 mm. The coaxial spectral signals were tested using a fiber spectrometer (Fx∼, Ocean Optics, USA), the delay and gate width was 4µs and10µs. From the atomic spectral line database of the National Institute of Standards and Technology (NIST) [27], it can be found that the multilayer characteristic spectra during the repeated scanning removal are shown in Fig. 2(b). (I) The characteristic spectrum of copper layer is Cu I (324.754 nm, 327.396 nm, 330.795 nm, 427.511 nm, 510.554 nm, 515.324 nm, 521.820 nm), and the Cu I 521.820 nm is relatively strong and ranges from 11053.5-13814.3 (a.u.). (II) the characteristic spectrum of epoxy resin layer is Cu I (510.554 nm, 515.324 nm, 521.820 nm) and Al I (394.401 nm, 396.152 nm), it is attributed to the fact that plasma excitation of metals is easier than nonmetals, so there are no obvious excitation spectral lines of (C₁₁H₁₂O₃)n. (III) the characteristic spectrum of fiberglass layer is Al I (308.215 nm, 309.284 nm, 394.401 nm, 396.152 nm), and the Al I 394.401 nm is stronger and ranges from 7612.8-9612.7 (a.u.). Thus, adjacent interfaces of multilayer CCL can be distinguished by the wavelength and intensity of spectral lines Cu I 521.820 nm and Al I 394.401 nm.

During the repeated scanning removal of the copper layer, the characteristic signal of Cu I 521.820 nm shows an unsteady tendency, in which the peak intensity of Cu I 521.820 nm increased from 11053.5 (a.u.) to 13814.3 (a.u.) and then decreased to 6222.25 (a.u.). Among them, plasma spectral fluctuations are influenced by multiple physical factors, and the formation mechanism is attributed to the dynamic interaction between laser and materials, which is a complex process that combines thermal ablation, thermal melting and then thermal diffusion on the ns pulse scale. The absorption characteristics of material surface to laser are affected by the shielding effect caused by induced plasma, the roughness of ablated area, and the substrate temperature. Therefore, it is extremely necessary to explore the influence mechanism and degree of each physical parameter on laser removal of multilayer materials.

3.2 Dynamic evolution of plasma characteristics during repeated scanning removal

Since the free electrons are accelerated by the electric field in the focal region and then induced the plasma by the avalanche effect [28]. The air breakdown and shielding effects are caused by continuous aggregation of plasma, resulting in dynamic variations of laser absorptivity. Plasma temperature ${T_e}$ and electron density ${N_e}$ are key parameters to evaluate the degree of plasma shielding effect. The plasma temperature ${T_e}$ can be calculated by the Boltzmann method [29]:

(1)$$\ln (\frac{{{I_{ki}}\lambda }}{{{A_{ki}}{g_k}}}) ={-} \frac{{{E_k}}}{{{k_B}{T_e}}} + \ln (\frac{{hc{N_0}}}{{4\pi Z}})$$

where k, i is the upper-lower levels of the transition, ${I_{ki}}$ is the relative integral intensity of spectral line, $\lambda$ is the excitation wavelength, and ${E_k}$ is the Einstein transition probability. It can be obtained by the National Institute of Standards and Technology (NIST) [27] atomic spectrum database as shown in Table 1. The ${k_B}$ is Boltzmann's constant, h is Planck's constant, c is light speed, ${N_0}$ is the number of particles in the ground state, Z is the atomic partition function. Six spectral lines of Cu I (330.795 nm, 427.511 nm, 510.554 nm, 515.324 nm, 521.820 nm, 578.213 nm) were selected to fitting, and the plasma temperature was calculated based on the regression slope.

Table 1. Main parameters of the Cu atomic spectral lines

View Table

Based on the Stark broadening mechanism [30], the plasma electron density can be calculated by measuring the full width at half maximum (FWHM) of the spectral line, as shown in Eq. (2):

(2)$$\Delta {\lambda _{1/2}} = 2{\omega _e}(\frac{{{N_e}}}{{{{10}^{16}}}}) + 3.5\Lambda {(\frac{{{N_e}}}{{{{10}^{16}}}})^{1/4}}(1 - \frac{3}{4}N_D^{1/3})\omega (\frac{{{N_e}}}{{{{10}^{16}}}})$$

where the Cu I 521.820 nm is selected and $\Delta {\lambda _{1/2}}$ is the FWHM, ${\omega _e}$ is the electron collision parameter, and the $\Lambda $ is ion broadening parameter, ${N_D}$ represents the number of particles in the Debye sphere. The spectrometer was used to measure the intensity of multiple copper atomic spectral lines, as depicted in Fig. 3.

Fig. 3. Plasma evolution during repeated scanning removal. (a) The plasma spectrum of copper layer at different stages. (b) Plasma temperature and electron density.

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The intensity distribution of the six characteristic spectral lines in the removal process is shown in Fig. 3(a), the results indicate that the evolution trends of the six spectral lines are consistent. In 1st-11th, the intensity of spectral lines Cu I 521.820 nm is between (11053.5, 12186.3, 12581.8, 13028.8, 13077, 13418, 13479, 13754, 13814.3, 12510.3, 6222.3 a.u.). The spectral intensity increases abruptly during the 1st-2nd processing, which is mainly attributed to the material oxide film being removed, the surface roughness and laser absorption rate are increased gradually promoting spectral excitation. Gradually rise and stabilize in the 2nd-9th processing. Along with the copper layer is gradually removed and the copper content decreases synchronously, so the spectral intensity drops sharply after the 9th processing. Based on the spectral line results and Eq. (1), Eq. (2), the distribution of plasma temperature ${T_e}$ and electron density ${N_e}$ is shown in Fig. 3(b). The variation is consistent with the spectrum intensity, showing a gradual increase and stabilization before decreasing. Plasma temperature increased from 9978 K to 10021 K in the 1st-9th, and then decreased to 9793 K in the 10th-11th. However, the variation tendency of electron density ${N_e}$ is opposite of the plasma temperature ${T_e}$, showing an initial decrease, followed by a gradual stabilization and then an increase. The electron density decreased from 1.763 × 10¹⁶cm⁻³ to 1.735 × 10¹⁶cm⁻³ in 1st-9th, and then increased to 1.869 × 10¹⁶cm⁻³ in 10th-11th. This is attributed to the plasma shielding effect caused by reverse bremsstrahlung absorption. The variations in plasma temperature reflect the thermal movement of electrons, atoms and ions in the plasma, higher temperature will cause stronger collisions between ions, atoms and electrons. Furthermore, it is required that the plasma characteristics meet the local thermodynamic equilibrium (LTE) when analyzing the plasma temperature and electron density, and the Mc Whirter criterion [29] is adopted for judgment:

(3)$${N_e} \ge 1.6 \times {10^{12}}T_e^{1/2}{(\Delta E)^3}$$

where $\Delta E$ is the energy difference between upper and lower energy levels transition of spectral line, and the spectral line Cu I 521.820 nm energy level difference is 2.375 eV. The minimum electron density that satisfies the LTE condition is approximately 2.146 × 10¹⁵cm⁻³ according to Eq. (3), which is one order of magnitude smaller than the minimum electron density of 1.735 × 10¹⁶cm⁻³ calculated by Eq. (2). Therefore, the plasma remains in a local thermal equilibrium state during repeated scanning removal.

3.3 Dynamic evolution of the material absorptivity during repeated scanning removal

The optical reflectance curves of the unprocessed original surface and the ablated surface after 1st to 11th in the range of 200-1200 nm were tested by spectrophotometer (SolidSpec-3700, SHIMADZU, Japan), and the dynamic absorptivity for laser@1064 nm was obtained in Fig. 4.

Fig. 4. Surface absorptivity and roughness. (a) The distribution of absorptivity on different ablated surfaces. (b) The absorptivity at 1064 nm and roughness distribution of different ablated surfaces.

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Figure 4(a) shows the dynamic variety of material absorptivity in the range of 200-1200 nm, with the highest absorptivity in the UV band and decreasing successively in the visible and near-infrared bands. The absorptivity of the original unprocessed copper layer surface was only 15.42%@1064 nm, and the absorptivity gradually increased as the material was repeatedly scanning removed, as shown in Fig. 4(b). The absorptivity suddenly increased to 28.30% after the 1st processing, and then stabilized between 28.30%-31.46% during the 1st-7th processing. The absorption rate increased from 33.79% to 75.08% after the 8th-11th. The evolution trend is consistent with the distribution of surface roughness of different ablated surfaces. It is attributed that the surface oxide layer is removed during initial laser ablation, the surface roughness gradually increases and performs extensive microstructures. The optical trap effect is induced by laser multiple reflections in the microstructures [31]. Therefore, dynamic fluctuations in the absorption rate of the material surface will induce a dynamic laser manufacturing process.

3.4 Dynamic evolution of the surface roughness during repeated scanning removal

Since the laser light field intensity follows a Gaussian distribution, the material surface exhibits an uneven and undulating shape after scanning processing. The influence mechanism of surface roughness on laser absorptivity is shown in Fig. 5.

Fig. 5. Relationship between surface roughness and laser absorptivity. (a) The equivalent contour of linear roughness. (b) The influence of equivalent inclination angle on laser transmission. (c) The relationship between equivalent inclination angle and absorptivity. (d) SEM images of surface micromorphology.

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In Fig. 5(a), there is an ablated surface and all of valleys are continuously folded downward symmetrically, and then the original surface can be equivalent to an inverted triangular contour, as shown. Therefore, the height H of equivalent contour is the sum of all the valleys. In the two-dimensional plane based on the equivalent area and then $H = 2RaN$, $Ra$ is the arithmetic mean deviation of the line contour and N is the number of valleys. Based on the equivalent volume in three-dimensional and then the height of the cone is $H^{\prime} = 3SaN$, $Sa$ is the arithmetic mean deviation of surface contour, the geometric relation can be calculated in Eq. (4).

(4)$$\tan \eta = \frac{{H^{\prime}}}{{L/2}} = \frac{{6SaN}}{L}$$

where $\eta$ is the angle between the equivalent contour and the projection plane, L is the contour length. When the angle $\eta$ changes, the laser-material interaction process is variable as depicted in Fig. 5(b). The relationship between absorptivity ${A_R}$ and equivalent inclination angle $\eta$ can be expressed in Eq. (5).

(5)$${A_R} = \left\{ \begin{array}{ll} \delta &0 <\eta {\le} \pi /6\\ \delta - (1 - \delta )\delta \frac{{\cos 3\eta }}{{\cos \eta }}&\pi /6 <\eta {\le} \pi /4\\ \delta + (1 - \delta )\delta &\pi /4 <\eta {\le} 3\pi /10\\ \delta + (1 - \delta )\delta - {(1 - \delta )^2}\delta \frac{{\cos 5\eta }}{{\cos 3\eta }}&3\pi /10 <\eta {\le} 3\pi /8\\ \delta + (1 - \delta )\delta + {(1 - \delta )^2}\delta &3\pi /8 <\eta {\le} 5\pi /14\\ \delta + (1 - \delta )\delta + {(1 - \delta )^2}\delta - {(1 - \delta )^3}\delta \frac{{\cos 7\eta }}{{\cos 5\eta }}&5\pi /14 <\eta {\le} 5\pi /12 \end{array} \right.$$

In Fig. 4(b), the surface roughness $Sa$ ranges from 0.599-5.835 µm on the original surface and after the 1st to 11th processing. Then, according to the distribution of roughness $Sa$ and Eq. (4), the equivalent inclination angle $\eta$ after repeated scanning processing can be calculated in Fig. 5(c), which is between 0.20-1.11 rad and shows a gradual increase tendency, which is consistent with the distribution of roughness $Sa$. According to Eq. (5), the interaction process of laser with material can be divided into three stages as shown in Fig. 5(c). When the angle $\eta$ is between 0.20-0.49 rad, the laser interacts with material only once, and the absorptivity $A{R_1}$ is approximately 15.42%. When the angle $\eta$ is between 0.60-0.73 rad, the number of laser interactions with material is between the interval of 1-2, and the absorptivity $A{R_2}$ is about 18.68%-40.63%. When the angle $\eta$ is about 1.11 rad, the laser interacts times within the interval of 2-3, and the absorptivity $A{R_3}$ is up to 75.43%, which is close to the test result of 75.08% in Fig. 4(b). The surface morphology during repeated scanning removal is shown in Fig. 5(d), it can be found that the surface morphology changes significantly with the processing, and the surface roughness and absorptivity are also influenced by the variation of surface morphology. It provides excellent guidance for quantitative analysis of the interaction process between laser and material by gradient reflection theory.

3.5 Dynamic evolution of the substrate temperature during repeated scanning removal

The variation in substrate temperature is caused by material ablation, melting and vaporization, and the material conductivity also changes in the meantime, which also affects the laser absorption characteristics. Based on Fresnel's formula [32], when the laser is incident vertically on the conductor, the reflection coefficient is the ratio of reflected energy flow to incident energy flow, and the absorptivity ${A_T}$ can be expressed as follows:

(6)$${A_T}\textrm{ = 1} - \left[ {{{\left( {1 - \sqrt {\frac{{2\omega {\varepsilon_0}}}{\sigma }} } \right)}^2} + 1} \right] \left/ \left[ {{{\left( {1 + \sqrt {\frac{{2\omega {\varepsilon_0}}}{\sigma }} } \right)}^2} + 1} \right] \approx 2\sqrt {\frac{{2\omega {\varepsilon _0}}}{\sigma }}\right.$$

where $\omega$ is the frequency, ${\varepsilon _0}$ is the vacuum dielectric constant, and $\sigma$ is the material conductivity. Based on the Wiedemann-Franz law [33], the ratio of thermal conductivity to electrical conductivity of metal materials remains approximately constant at a certain temperature. Therefore, the absorptivity ${A_T}$ Eq. (6) can be derived as:

(7)$${A_T} = 2\sqrt {\frac{{2c{\varepsilon _0}LT}}{{\kappa \lambda }}}$$

where L is the Lorenz number, the absorptivity ${A_T}$ and temperature T follow the distribution of one-half order nonlinear. A high-speed infrared thermal imager (348C+, FOTRIC, China) was used to online monitor the temperature field distribution during repeated scanning removal, as depicted in Fig. 6.

Fig. 6. The influence of substrate temperature on absorptivity. (a) The substrate temperature during repeated scanning removal. (b) The relationship between substrate temperature and laser absorptivity.

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Figure 6(a) shows the cloud map and the curve of substrate temperature field, where the substrate temperature gradually increases and it’s attributed to thermal accumulation during repeated scanning processing. The substrate temperature varies periodically with the scanning period. The initial temperature of the material is approximately 298.05 K, and the substrate temperature remains stable between 302.95 K-314.55 K during 1st-8th processing, and then rises sharply from 320.35 K to 360.85 K in 9th-11th. Based on the temperature test results and Eq. (7), the material's absorptivity ${A_T}$ under the influence of temperature can be calculated as shown in Fig. 6(b). The absorptivity ${A_T}$ remains stable between 1.54%-5.38% in 1st-8th processing, and then rises sharply from 7.53% to 19.08% in 9th-11th. Furthermore, it can be found that the impact of substrate temperature on laser absorptivity is less significant compared to surface roughness, and it also provides a guideline for quantitative analyzing the effects of changes in substrate temperature on laser absorptivity.

From the analysis results of evolution behavior in material absorptivity, surface micromorphology and roughness, substrate temperature and plasma characteristics, it is evident that removal of multilayer material is not an invariable process, but it involves mutual influence and restriction. The dynamic removal process is divided into three stages. In stage I, the laser interacts with the dense oxide layer on the material surface, electronic excitation and collisions with less absorption in the substrate. In stage II, the surface oxide layer is removed, and the substrate material is ablated and vaporized by laser interaction, followed by electron ionization and coulomb explosion, which result in heat accumulation and physical interactions that lead to the material being processed. The surface morphology of the material has undergone a dramatically changed. In stage III, when the heat accumulation reaches a certain level, the conductivity of the material changes dramatically. The laser beam will be refracted as it enters the sparse light medium (plasma) from the dense light medium (air). Previous plasma leads to cone radiation of the laser beam and results in plasma shielding effect. Then the laser beam is defocused and the spot size gradually increases, and the single pulse energy density decreases simultaneously. The laser energy interacts with the substrate surface through thermal radiation. The processes of reverse bremsstrahlung and resonance absorption occurred, and thermal diffusion-mechanical force coupling in the homogeneous material. Where the systematic quantitative analysis provides a reference for in-depth understanding of the interaction process between laser and multilayer materials.

4. Conclusion

In this paper, an integration system of laser scanning processing with coaxial spectrum detection was proposed for monitoring the removal status of multilayer heterogeneous materials. The influence of physical factors including plasma characteristics, surface roughness, and substrate temperature on laser absorptivity (${A_R}, {A_T}$) was systematically analyzed, revealing the dynamic reaction mechanism and surface evolution behavior of repeated scanning removal of multilayer heterogeneous materials. The conclusion can be summarized as follows:

(1) The system exploits the differences in type and intensity of the characteristic spectral signals of adjacent material layers to identify the manufacturing process, by which the interface sensing and material determination via characteristic spectral lines of Cu I 521.820 nm and Al I 394.401 nm in multilayer CCL was completed.
(2) Based on the Boltzmann method and Stark broadening mechanism, the distribution of plasma temperature and electron density during the repeated scanning removal process was calculated, it reflects the thermal movement degree of electrons, atoms and ions in plasma, and demonstrates the dynamic reaction process in theory.
(3) An equivalent approximation model for surface roughness was constructed. The relationship between laser absorptivity and equivalent inclination angle was derived from gradient reflection theory, and the influence of surface roughness evolution on laser absorptivity was quantitatively analyzed from theoretical model and experimental testing.
(4) Based on the relationship between reflected energy flow and incident energy flow, the effects of substrate temperature changes on the material's electrical conductivity and laser absorptivity were analyzed. High-speed infrared imaging test results show a periodic gradient in substrate temperature with the scanning cycle. It is found that repeated scanning removal material is not a constant process, but mutual influence and restriction in dynamic laser absorptivity, which provides a valuable guideline for exploring the dynamic interfacial reaction behavior during the removal of multilayer materials.

Funding

National Natural Science Foundation of China (52105568, 52175405, 61774067, U20A20252).

Acknowledgments

The authors thank the Analytical and Testing Center of HUST, the facility support of the Center for Nanoscale Characterization and Devices at Wuhan National Laboratory for Optoelectronics.

Disclosures

The authors declare no conflicts of interest.

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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Wavelength/nm	Transition form	g_k	A_ki(s⁻¹)	E_k(eV)	Ref.
Cu I 330.795	3d⁹(²D)4s4p(³P°)- 3d⁹4s(³D)4d	12	1.436e + 08	8.819080	NIST [27]
Cu I 427.511	3d⁹(²D)4s4p(³P°)- 3d⁹4s(³D)5s	8	3.45e + 07	7.737027
Cu I 510.554	3d⁹4s²- 3d¹⁰4p	4	2.0e + 06	3.8166920
Cu I 515.324	3d¹⁰4p- 3d¹⁰4d	4	6.0e + 07	6.1911751
Cu I 521.820	3d¹⁰4p- 3d¹⁰4d	6	7.5e + 07	6.1920252
Cu I 578.213	3d⁹4s²-3d¹⁰4p	2	1.65e + 06	3.7858977

Insight into the surface behavior and dynamic absorptivity of laser removal of multilayer materials

Abstract

1. Introduction

2. Experimental system and characterization

2.1 Experimental system

2.2 Characterizations and measurements

3. Results and discussion

3.1 Multilayer heterogeneous materials and multilayer spectra

3.2 Dynamic evolution of plasma characteristics during repeated scanning removal

3.3 Dynamic evolution of the material absorptivity during repeated scanning removal

3.4 Dynamic evolution of the surface roughness during repeated scanning removal

3.5 Dynamic evolution of the substrate temperature during repeated scanning removal

4. Conclusion

Funding

Acknowledgments

Disclosures

Data availability

References

Data availability

Cited By

Figures (6)

Tables (1)

Equations (7)

Optics Express