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Abstract
Laser-induced breakdown spectroscopy system based on high-repetition-rate microchip laser (HR-LIBS) has been widely used in elemental analysis due to its high energy stability, good portability and fast spectral acquisition speed. However, repeated ablation on powder pellets like soil and coal using HR-LIBS system encounters the problem of serious decline in measurement accuracy. In this work, the relationship between laser ablation and scanning parameters, their correlation with spectral intensity, as well as the optimization approach were fundamentally studied. The correlations among the crater overlapping rate, crater depth and spectral intensity were obtained. An HR-LIBS system with microchip laser (4 kHz repetition rate, 100 µJ laser pulse energy) to perform repeated scanning ablation was established. A theoretical model of the ablation crater morphology for repeated scanning ablation was developed. By taking soil pellets as the experimental samples, the linear fitting curves of crater depth and the spectral intensity ratio were established with the R2 of 0.90∼0.99. The experimental results showed that as the crater depth developed during repeated ablation, the Si-normalized spectral intensity decreased, and thus the spectral repeatability decreased. It was found that by optimizing the overlapping rate to form a flat crater bottom, the confinement effect of the crater on the plasma could be avoided. As a result, the spectral repeatability was significantly improved. The relative standard deviation (RSD) of Si-normalized spectral intensity was improved from 5% to 0.6%. Finally, repeated ablation was performed with the optimized overlapping rate on soil pellets. The R2 of calibration curves of Fe, Mg, Ca, and Al were all above 0.993, and the average RSDs were between 0.5% and 1%. This study provides a fast, accurate, and stable method for the analysis of the samples consisting of various materials with high heterogeneity.
© 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
1. Introduction
There is a great demand for accurate analysis and determination of element content in modern agriculture and industrial production. Examples include but are not limited to nutrient element analysis in soil [1], coal composition analysis [2], ore grade identification [3], and drug analysis [4]. Therefore, it is necessary to develop a portable and high-throughput quantitative analysis technology. Laser-induced breakdown spectroscopy (LIBS) is a promising elemental analysis method with the advantages of micro-destructive, no sample pretreatment, and in-situ [5,6]. It has been applied in the fields of geochemistry [7], Mars explorations [8], and metals industry [9], etc. However, the unsatisfactory precision yielded by LIBS measurements is the bottleneck restricting its application [10]. Especially in the field that the compositions of the sample to be measured are highly heterogeneous like soil and coal, the relative standard deviation (RSD) of single spectrum acquired by LIBS is higher than 30%∼50% [11], which is completely incomparable to other traditional methods (e.g., ICP). In order to improve the measurement accuracy, in previous studies, on the one hand, the samples with loose structure and uneven distribution such as soil and coal were pressed into compact pellets to reduce the error caused by voids [12]; on the other hand, many studies have used scanning and repeated ablation to increase the number of laser sampling points to overcome the spectral changes caused by uneven distribution and reduce the spectral random error caused by plasma instability [13–16].
LIBS system based on high-repetition-rate microchip laser (HR-LIBS) has been widely used in alloy analysis due to its high energy stability, good portability and fast spectral acquisition speed [17–19]. This approach is also used to determine phosphorus in soil [20]. However, repeated ablation using HR-LIBS system inevitably encounters the problem of measurement accuracy degradation caused by ablation craters, that is, continuous laser pulses produce deep craters, which confine the plasma and affect plasma parameters, and thus reducing the accuracy and repeatability of the spectrum [21–24]. For example, X. B. Xu et al. observed that when ablating the same location of soil pellet with 5 successive laser pulses, the intensities of the spectra decrease, and the RSD of the spectral intensities increase with increasing crater depth [25]. K. H. Li et al. ablated the surface of micro alloyed steel with successive pulses and showed that the intensity of ion lines decreases while the intensity of atomic lines increases with crater development. In this case, the spectral intensity was not only related to the element concentration, but also related to the crater depth. Therefore, the trend of the spectral intensity cannot reflect the trend of the element concentration [26]. Many researchers have found that the crater depth and overlap rate significantly affect the spectral intensity or intensity ratio when using HR-LIBS ablation. K. Amponsah-Manager et al. analyzed the alloy samples by using a microchip laser and found that the spectral intensity ratio of Zn-Cu decreased as the crater depth increased [17]. Z. Y. Xu et al. studied the fiber laser ablation (FL-LIBS) on aluminum alloy and demonstrated a linear function correlation between the intensity and non-overlapping ablation area [27]. W. Wang et al. investigated the effect of the laser-ablated craters on the spectral repeatability of low-alloy steel under different overlapping rates. They found that when the overlapping rate was 75%, the repeatability and Signal-to-Noise Ratio (SNR) of a single spectrum were the best. This result indicated that it is feasible to improve the repeatability of the spectra by changing the overlapping rate of the ablation crater [28].
In order to improve the spectral repeatability and measurement accuracy, it is necessary to fundamentally study the relationship between laser ablation and scanning parameters (crater size and crater overlapping rate), their correlation with spectral intensity, and the parameter optimization approach. As far as we know, there was no existing research on the correlations between crater depth, overlap rate and spectral intensity or intensity ratio in HR-LIBS yet.
In this paper, a high-repetition-rate microchip laser LIBS system was established, and soil particles were taken as an example for repeated scanning ablation. The relationship between crater overlap rate, crater depth and spectral intensity under laser ablation and scanning parameters was discussed in detail. A theoretical model of crater morphology for repeated scanning ablation was established. Experiments were designed to verify the theoretical model. Through the model and experiment, the optimal overlap rate was found, which avoided the confinement effect caused by the development of craters, and significantly improved the spectral repeatability of repeated scanning ablation. It realized a rapid, accurate and stable measurement of the samples consisting of various materials with high heterogeneity.
2. Method and ablation model
In order to reveal the relationship between laser ablation and scanning parameters, as well as their correlation with spectral intensity, we developed a theoretical model to simulate the crater profile so as to investigate the evolution of the shape of the crater generated by high-repetition-rate laser pulses. We assume that the spatial irradiance distribution of the laser is approximated as a Gaussian distribution,
where I(r) is the irradiance at distance r from the spot center, and ${I_0}$ is the maximum irradiance at the spot center, and ${w_0}$ is the characteristic length [29].The local ablated depth $\Delta d(r )$ on the sample surface is proportional to I(r):
where k is a constant, depending on the properties of the material and laser [21], and $\alpha (r )$ is the local angle between the normal line of the sample surface and the laser beam. $\cos ({\alpha (r )} )\; $ is approximated by the local derivative of the sample surface [29].Then two coordinate axes are established. An X-axis represents the horizontal position of the sample and a Y-axis represents the sample depth. The local ablated depth $\Delta d({x,{x_c}} )$ produced by a laser pulse of which the center at ${x_c}$ is simulated by the following:
The laser spots keep moving forward during the measurement. The distance between two neighboring spot centers is denoted as d. The sample surface depth $D({x,N} )$ ablated by N laser pulses can be calculated as follows:
The overlapping rate of the craters δ is calculated as follows: where R is the radius of a single crater. Figure 1 showed the schematic diagram of the overlapping craters and the simulated crater profile.We set N = 20, means that one scanning ablation is simulated by 20 laser pulses. Then the same 20 laser pulses were repeated at the same start point of the sample as repeated ablation. Each repeated ablation forms a new layer of sample surface. The number of the layer is denoted as l. With the formula (3), (4) and (5), the sample surface profiles under different δ and l can be simulated. Figure 2 shows the simulated crater profile under l = 1∼6 and the typical $\delta $ of 21.7%, 50%, 65%, and 80%.
Fig. 2. The simulated crater profile formed by repeated ablation under ${\boldsymbol \delta }$=21.7% (a), 50% (b), 65% (c) and 80% (d).
For layer number l of a certain $\delta $, its crater local depth $S({l,\delta } )$ and average depth $\bar{D}({l,\delta } )$ can be defined as follows:
Fig. 3. The schematic diagram of crater local depth ${\boldsymbol S}$ and average depth $\bar{{\boldsymbol D}}$.
Fig. 4. The relationship between the local depth of the simulated crater S and ${\boldsymbol \delta }$ (blue curve). The relationship between the average depth $\bar{{\boldsymbol D}}$ and ${\boldsymbol \delta }$ (red curve).
As can be seen from Fig. 4, when $\delta $ is between 20%∼80%, the larger the $\delta $, the smaller the S. When $\delta $ is larger than 80%, the S is down to zero. And the $\bar{D}$ increased as the $\delta $ increases, similar to an exponential relationship. From Fig. 2, we can see the S and $\bar{D}$ are linear to layer number l. For example, $S({6,\,21.7{\%}} )$ is 6 times of $S({1,\,21.7{\%}} )$. That means when $\delta = 21.7{\%}$, the S increased heavily after 6 times repeated ablation. The fast-increasing crater depth may heavily affect the plasma parameters by the confinement effect. The spectra intensity may be affected by the crater depth. Therefore, too small $\delta $ leads to bad repeatability of the plasma and spectra. When the $\delta $ is larger than 80%, the $\bar{D}$ increase sharply. This may cause serious problem, like the low SNR, the confinement effects generated by the sidewall of the deep crater, the defocus of the laser beam and collective lens, and the low representativeness caused by the small ablation area. All of these may reduce the measurement repeatability. Therefore, the $\delta $ must be chosen appropriately. According to the curves in Fig. 4, $\delta $ = 70% may be an optimal choice.
3. Experimental and Instrument
3.1 Sample pretreatment
The sample to be measured in the experiment was the soil collected from our campus. The soil was dried, ground, and sieved through stainless steel sieves (200-mesh), and then pressed into pellets of 1 mm thickness and 10 mm diameter under 8 Mpa pressure, without binder. For elemental quantitative analysis, a new sample set that contained 6 soil samples was prepared as follows: a reference material named GBW(E)070043 was used as a matrix, doped with different masses of Al2O3, CaCO3, Mg(OH)2, and Fe2O3, and then they were mixed evenly. The elemental concentrations of each sample are shown in Table 1.
Table 1. Concentration of elements of interest in the mixed samples
3.2 Instrument setup
The schematic diagram of the HR-LIBS apparatus with scanning function is shown in Fig. 5. The microchip laser was a diode-pumped passively Q-switched Nd: YAG laser, wavelength 1064 nm, repetition rate 4 kHz, single pulse energy 100 µJ, and pulse width 1 ns. This setup of laser pulse generates the ablation crater with approximately 150 µm diameter on the soil pellet. The apparatus contained a rotating stage, an X-Y motorized stage (reset accuracy = 1 µm), and a Z motorized stage. A laser pointer was focused on the sample surface with an oblique incidence. The pixel coordinates of the laser pointer spot in the CCD camera image represent the distance from the sample to the lens, guiding the Z-axis moving stage to move up or down to correct the defocus of the laser. A vacuum cleaner was utilized beside the rotation stage to produce airflow to reduce the dust and the re-deposition of the ablated material. The plasma emission spectra are collected by one self-designed C-T spectrometer covering the wavelength range of 252∼373 nm with a resolution of 0.1∼0.2nm, which is equipped with 2048 pixels linear CCD. A better description of the spectrometer is given elsewhere [30]. The circuit of the spectrometer sent a trigger signal to control the lasers to work synchronously. The integration time of the spectrometer was set as 50ms.
3.3 The setup of scanning ablation, spectra acquisition and preprocess
During the measurement, the soil pellet was placed on the rotating stage. The laser spot moving path is shown in Fig. 6(a). After one round rotation, the sample stage moves a certain distance in the radial direction, denoted by dr. The linear velocity V is defined as the angular velocity multiplied by the rotation radius Rs. The Rs was an average rotation radius of 4 mm. Although the radial displacement changes the Rs as well as the V, the average of V is constant, so the changes in Rs can be ignored. The image of a soil pellet after 6 times repeated scanning ablation is shown in Fig. 6(b).
Fig. 6. The scanning path (left) and a soil pellet after 6 times repeated scanning ablation (right).
There were two kinds of crater overlapping rates in this scanning method, the radial overlapping rate denoted by ${\delta _r}$ and the circumferential overlapping rate denoted by ${\delta _c}$. Figure 7 showed the schematic diagram of ${\delta _r}$ and ${\delta _c}$. Therefore, the ${\delta _r}$ and ${\delta _c}$ were discussed respectively in the experiment. A grid of experiments was conducted under 3 linear velocities and 7 dr. Under each scanning parameter setup, the unified number of spectra were acquired in each layer of repeated ablation. The repeated ablation layer number l was set as 6. In the quantitative experiment, 80 spectra were acquired in each layer. The spectra of each layer were the accumulation of 200 (per spectrum) ×80 = 16000 laser pulses. For reducing the time cost in the grid experiments, 40 spectra were acquired in each layer, which were the accumulation of 200 × 40 = 8000 laser pulses. The spectra of each layer were averaged into one spectrum. Therefore, one layer generated one averaged spectrum. Wavelet denoising was performed to reduce spectral random noise [31]. The spectral continue background was removed by adaptive iteratively reweighted penalized least squares [32]. The internal standard method was applied by default to enhance the experimental analysis results. The Si I 288.158 nm was selected as the internal standard line.
4. Results and discussion
4.1 Effect of ${{\boldsymbol \delta }_{\boldsymbol c}}$ on the spectral intensity and RSD of single spectrum
We first investigated the effect of linear velocity V (linear to ${\delta _c}$) on the repeatability of single spectrum in the case of laser ablating the fresh sample surface (no repeated ablation). Experiments were conducted under 13 linear velocity setups. 6 spectra were acquired per linear velocity on different position of soil pellet. The range of V is from 3 mm/s to 314 mm/s, related to the ${\delta _c}$ from 99.47% to 47.64%. Due to the limited speed of the step motor, ${\delta _c}$ smaller than 47.64% could not be investigated. The relationship between the raw intensity (without normalized by the Si line of 288.158 nm) of Fe, Ti, Ca, Al, Si, Mg and the linear velocity V is shown in Fig. 8(a), and the normalized intensity is shown in Fig. 8(b). The curve of single spectrum RSD of these spectra (normalized and unnormalized) is shown in Fig. 9. The single spectrum RSD is the average of the RSD of Fe, Ti, Ca, Al, Si, Mg from 6 single spectra.
Fig. 8. (a) The relationship between the raw intensity and the linear velocity V. (b) The relationship between the normalized intensity and the linear velocity V and the overlapping rate ${{\boldsymbol \delta }_{\boldsymbol c}}$. The error bars were calculated from 6 single spectra.
Fig. 9. The relationship between the single spectrum RSD and the linear velocity V and the overlapping rate ${{\boldsymbol \delta }_{\boldsymbol c}}$.
From Fig. 8. (a), the raw intensity first increased and then slightly decreased with the increase of V and the decrease of ${\delta _c}$. When the ${\delta _c}$ is larger than 90%, the raw intensity was weak and the spectral repeatability was poor according to Fig. 9. This phenomenon is caused by many factors, like the confinement effect of deep crater, the dust or the vapor generated by the high-repetition-rate laser pulses and so on. It has been discussed in many previous researches [18,28].
From Fig. 8. (b), as the ${\delta _c}$ deceasing, the normalized intensity of Fe, Ti, Ca, Al, Si, Mg increased. In fact, besides Si, the intensity ratio of every two elements changed as the ${\delta _c}$ changing. To verify the point that the plasma emission is affected by crater depth, we investigated the relationship between the average depth and the intensity ratio. The single spectrum was the accumulation of 200 laser pulse. The 200 laser pulses were distributed along one-line direction. The plasmas were confined by the sidewall of the line. The depth of this sidewall could be represented by the average depth in Eqs. (7). Therefore, we calculated the $\bar{D}$ for each ${\delta _c}$ in Fig. 8 and plotted the fitting curves of the sum of normalized intensity of Fe, Ti, Ca, Al, Mg and the calculated $\bar{D}$, shown in Fig. 10(a). And the fitting curves of the intensity ratio of Mg and Al and the calculated $\bar{D}$ was plotted in Fig. 10(b). From Fig. 10, when the calculated $\bar{D}$ is in the range of 5 um∼30 um (${\delta _c} = 50{\%}\sim 90{\%}$), the intensity ratio of different elements is linear to the calculated $\bar{D}$. This verified the point that the intensity ratio is affected by the crater depth. The reason maybe that as the crater depth growing, the confinement effects from sidewall changed the plasma parameters like plasma temperature, electron density and the geometry of the plasma. A detail discussion about the physical mechanism of the effects of sample surface geometry on the spectral intensity was given in Ref. [33].
Fig. 10. (a) The polynomial fitting curves of the sum of normalized intensity of Fe, Ti, Ca, Al, Mg and the calculated $\bar{{\boldsymbol D}}$. (b) The polynomial fitting curves of the intensity ratio of Mg and Al and the calculated $\bar{{\boldsymbol D}}$.
In Fig. 10, when the calculated $\bar{D}$ is larger than 30 µm (${\delta _c} > 90{\%}$), the curve is nonlinear. The reason may be that the model assumed the ablating amount of each laser pulse remain constant as the crater depth growing. In reality, the ablating amount of each laser pulse may decrease as the crater depth growing [21]. Therefore, the actual depth of ${\delta _c} > 90{\%}$ in the experiment may be smaller than the calculation, causing the nonlinearity of the curve.
According to the analysis above, in the application where the measurement repeatability depends on the intensity ratio, the crater overlapping rate $\delta $ have to be keep constant, or the effect of $\delta $ have to be corrected with the fitting curve of intensity ratio and $\delta $.
In Fig. 9, the RSD of single spectrum decrease as the ${\delta _c}$ decrease. In the case of ${\delta _c}$>99%, the RSD = 20%∼40%, and the Si normalization did not improve the RSD. The main reason for these large RSD may be the heterogeneity of the soil pellets. The smaller the ${\delta _c}$, the larger the laser ablation area which enhance the representativeness of the laser sampling spots and resulting in lower RSD of single spectrum. In the case of ${\delta _c}$=47.64% (V = 314 mm/s), the RSD of the normalized single spectrum is the lowest (2.1%), which represented the best precision in the case of 200 laser pulses accumulation and ablating on fresh sample surface on campus soil pellets.
4.2 Effect of ${{\boldsymbol \delta }_{\boldsymbol c}}$ and ${{\boldsymbol \delta }_{\boldsymbol r}}$ on the spectral intensity and repeatability of the averaged spectra of the repeated scanning measurement
To investigate the effect of ${\delta _c}$ and ${\delta _r}$ on the spectral intensity and repeatability of repeated ablation, a series of experiments were conducted under the grid of V = 50, 100, 250 mm/s (${\delta _c}$=91.6%, 83.2%, 58.1%) and dr = 10, 20, 40, 60, 80, 100, 150 µm (${\delta _r}$=0∼93.3%). The setups of V = 50, 100, 250 mm/s (${\delta _c}$=91.6%, 83.2%, 58.1%) were corresponding to the point with the highest SNR, the point with the lowest RSD and the point between the previous two points in Fig. 8, respectively. The amount of the grid nodes is 3 × 7 = 21. The repeated ablation layer number l was set as 6. 40 spectra were acquired in each layer with 200 × 40 = 8000 laser pulses. The spectra of each layer were averaged into one spectrum. One layer generated one averaged spectrum. The repeatability of the averaged spectrum is represented by the RSD of normalized intensity averaged from Fe, Ca, Al, Mg. The averaged spectra of the first layer were dropped out from analysis due to its large difference to the spectra of the other layers. Figure 11 shown the averaged spectra RSD under different ${\delta _c}$ and ${\delta _r}$.
Fig. 11. The relationships among the averaged RSD, ${{\boldsymbol \delta }_{\boldsymbol c}}$ and ${{\boldsymbol \delta }_{\boldsymbol r}}$.
From Fig. 11, the lower ${\delta _c}$ caused the lower averaged spectra RSD. The reason may be the same to the case of single spectrum in Section 4.1. In the case of repeated scanning ablation, due to the light-emitting timing jitter of the passive Q-switched microchip laser, the high-repetition rate-laser pulse did not generate local craters like the case in Fig. 2(a). Therefore, in the case of ${\delta _c}$<70%, the repeatability of spectra did not decrease as the model expecting.
In the case of ${\delta _c}$=58.1%, ${\delta _r}$=0% in Fig. 11, the averaged spectra RSD is 2.7%, which is comparable to the single spectrum RSD = 3.2% in the case of ${\delta _c}$=58.1%. Considering an averaged spectrum was the accumulation of 8000 laser pulses while a single spectrum was only the accumulation of 200 laser pulses, the RSD = 2.7% indicated that there were more interferences in the repeated ablation.
In Fig. 12, the relative intensity of Fe, Ca, Al, Mg of layer 2∼6 which normalized by the intensity of layer 2 under ${\delta _c}$=58.1% were plotted. From Fig. 12, the relative intensity decreased as the layer number increasing when ${\delta _r}$<60% and >86.7%. In the case of repeated ablation, the plasma was mainly confined by the sidewall generated by the laser pulses of neighboring scanning line. In this case, the depth of the sidewall could be represented by the local depth S in Eqs. (6). Therefore, we calculated the S corresponding to all ${\delta _r}$ and l setups presented in Fig. 12. And then the fitting curve of the variation percentage of the relative intensity under ${\delta _r}$=0%∼73.3% and the calculated S was developed, as plotted in Fig. 13(a). The R2 of the fitting curve is 0.96. Besides, the fitting curve of the average spectra RSD under ${\delta _r}$=0%∼73.3% and the calculated S under l = 6 was developed, as plotted in Fig. 13(b). The R2 of the fitting curve is 0.90. These two fitting curves indicated that the local depth S was a main factor that affected the normalized intensity of the averaged spectra and so as to the repeatability of the spectra. The mechanism of the S affected on the spectra was probably same to the discussion in Section 4.1. The photos of the sample surface after repeated ablation under ${\delta _r}$=0%, 33.3%, 46.7% and 73.3% taken by the microscope are demonstrated in Fig. 14. In Fig. 14(a), obvious grooves were formed on the sample surface by repeated ablation under ${\delta _r}$=0%. In Fig. 8(d), the sample surface was relatively flat without grooves under ${\delta _r}$=73.3%. This suggested that the spatial confinement effects of the deep grooves caused the decrease of measurement repeatability.
Fig. 12. The relationship between the relative spectral intensity and the scanning layer number under different ${{\boldsymbol \delta }_{\boldsymbol r}}$. The relative spectral intensity was the sum intensity of Fe, Ca, Al, Mg normalized by that of layer 2.
Fig. 13. (a) The linear fit of spectral intensity variation percentage to the calculated local depth S. (b) The linear fit of average spectra RSD to the calculated local depth S.
Fig. 14. The surfaces of soil pellets after repeated ablation under ${{\boldsymbol \delta }_{\boldsymbol r}}$=0% (a), 33.3% (b), 46.7% (c) and 73.3% (d). The grooves in the vertical direction of the figures are the results of repeated scanning ablation. Each groove was generated by a scan line. The edge of the groove is highlighted by two red dash line. And the profile of the sample surface is highlighted by the red solid line.
According to the model and the results of the experiments, the effects of the growing crater on the spectra could be corrected with the fitting curves in Fig. 13. Or we can avoid the effects by choosing the optimal crater overlapping rate. When ${\delta _r}$=73.3% and ${\delta _c}$=58.1%, the average spectra RSD was only 0.6%, which was significantly lower than the RSD of the single spectrum. Therefore, the scanning repeated ablation with optimal ${\delta _r}$ and ${\delta _c}$ could be a useful method for high-throughput and high precision measurement.
4.3 Quantitative analysis of elements with the optimized ${{\boldsymbol \delta }_{\boldsymbol c}}$ and ${{\boldsymbol \delta }_{\boldsymbol r}}$
Using the optimized ${\delta _r}$ and ${\delta _c}$ (${\delta _r}$=73.3% and ${\delta _c}$=58.1%) obtained in Section 4.2, 6 replicate scanning ablations were performed on the quantitative samples described in Section 3.1 and Table 1. 80 spectra were acquired per layer for quantitative analysis. The calibration curves for the Fe, Mg, Ca, and Al elements were obtained, as shown in Fig. 15. Among them, the calibration curves for Fe and Mg were based on univariate linear regressions with Fe I 304.760 nm and Mg I 285.213 nm, respectively. And Ca and Al were based on bivariate linear regressions which add Fe I 304.760 nm with Ca II 317.933 nm and Al I 308.215 nm, respectively. By take the Fe spectral lines into consideration, the calibration models can correct the spectral interference of Fe lines on Ca and Al lines. The experiment showed that this approach was necessary [34].
Fig. 15. Calibration curves for (a) Fe, (b) Mg, (c) Al, (d) Ca. The error bars represent the standard deviation of the averaged spectra.
The fitting results were excellent, with the calculated determination coefficients all above 0.993, and the average RSD around 0.5% to 1%. These results show that the effect of deep craters on the quantitative analysis could be neglected with optimal ${\delta _r}$ and ${\delta _c}$.
5. Conclusion
In this work, we established a microchip LIBS system to perform repeated scanning ablation on soil pellet. The correlation between crater depth generated by different crater overlapping rate ($\delta $) and the spectral intensity was investigated in detail. A theoretical model of the ablation crater morphology for repeated scanning ablation was established. The curves of crater local depth (S), average depth ($\bar{D}$) and $\delta $ were plotted. The results of experiments showed that in the case of single spectrum, the normalized spectral intensities of Fe, Ti, Ca, Al, Mg was related to the $\bar{D}$ calculated by the model. The R2 of the fitting curve was 0.992. In the case of repeated scanning ablation, the normalized spectral intensities of Fe, Ca, Al, Mg were related to the S calculated by the model under ${\delta _r}$=0%∼73.3%. The R2 of the fitting curve was 0.90. And the averaged spectra RSD of repeated scanning ablation was also related to the S with an R2 = 0.96. These correlations proved that the changes in crater depth introduce heavy interference on the normalized spectral intensities, and thus decrease the repeatability of the spectra. The results showed that when ${\delta _r}$=73.3% and ${\delta _c}$=58.1%, the S closely kept constant during repeated scanning ablation, and thus the confinement effects introduced by crater developing were avoided. Therefore, the averaged spectra RSD was improved from 5% to 0.6% compared to other ${\delta _r}$ and ${\delta _c}$ setups. Finally, a set of soil samples were measured under ${\delta _r}$=73.3% and ${\delta _c}$=58.1%, and the quantitative analysis with high precision and high accuracy was obtained. The R2 of calibration curves for Fe, Mg, Ca, and Al elements were all above 0.993. And the average RSD was around 0.5% to 1%. The results are significantly important in the accurate analysis of the samples consisting of various materials with high heterogeneity. It provides a solid foundation for future studies of matrix effects and other issues.
Funding
The Open-Foundation of Key Laboratory of Laser Device Technology, China North Industries Group Corporation Limited (No. KLLDT202109); National Natural Science Foundation of China (No. 62175150); the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University (No. SL2021ZD103).
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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