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Abstract
An approach to characterize laser-induced bulk damage in optical crystal materials was demonstrated. With a homemade swept-source optical coherence tomography (SS-OCT) system, we obtained three-dimensional images of the bulk damage produced by laser pulses with wavelength of 351 nm, pulse width of 5 ns, beam diameter of 5.5 mm and fluences from 4.56 J/cm2 to 9.95 J/cm2 in Potassium Dihydrogen Phosphate (KDP) crystal. Algorithms based on three-dimensional OCT images were specially designed to count and locate bulk damage pinpoints in KDP crystal, obtaining their equivalent diameter distribution and pinpoint density caused by different fluences. It is demonstrated that the characteristics of bulk damage detected by SS-OCT are similar to those obtained by available approaches. The rapid three-dimensional imaging by SS-OCT provides a new approach of detecting laser-induced bulk damage.
© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
Optical crystals, especially nonlinear crystals, such as Potassium Dihydrogen Phosphate (KDP) and its deuterated analog DKDP used in high power laser systems, and Zinc (tris) thiourea sulfate (ZTS), are easily subject to laser-induced bulk damage at simultaneous high fluence and intensity [1,2]. Damage in these optical components will affect the operation in many applications [3], so it is of significant importance to detect and characterize the bulk damage in these crystals. Researchers have proposed several methods to examine the damages including microscopies [4–7], scattering techniques [8–10], photoacoustic [11], Raman spectroscopy and scanning electron microscopy [12]. Some parameters, such as laser-induced damage threshold, damage pinpoint density (PPD), damage size distribution were proposed to characterize the damage onset conditions or features of the damage itself. The laser-induced bulk damage was thought to be micro-cavities and fractures caused by thermal explosion of plasma fireball initiated by enhanced absorption of precursors [13,14]. The density and size distribution of pinpoints are correlated to the fluence, wavelength, and durations of laser pulses [5,9,15,16]. The influence of crystal orientation on damages [17] and the morphology of damages were also studied [12,18]. The observation and characterization of the damage pinpoints are difficult because of their enormous quantity, complex morphology and the obscuration among them. Most available methods obtained two dimensional (2D) images of the interesting regions by projecting all the damage pinpoints on a single plane for image processing or data analysis. However, the obscuration among damage pinpoints of different planes may make these methods count or estimate inaccurately.
Undoubtedly, three-dimensional imaging with rapid imaging speed will help us detect and understand the damage better. Based on low-coherence interferometry, optical coherence tomography (OCT) performs high-resolution, cross-sectional and three-dimensional imaging of internal microstructures in transparent and scattering medium by measuring echoes of backscattering light [19]. Since been proposed in 1991, OCT has been rapidly developed and mostly been used in biomedical imaging for structure detection and disease diagnosis [20]. The ability of imaging the interior of scattering materials makes OCT also useful for detecting inner structures and geometries of materials such as ITO glass [21] and LCD devices [22]. S. G. Demos et al. used time-domain OCT (TD-OCT) to observe the laser-induced damage site in fused silica [23,24]. Y. Zheng et al. observed the lateral morphology of damage sites of fused silica by 2D OCT images [25]. However, they all focused on surface damage of the materials and did not make quantitative characterization of the damage. X. Wu et al. conducted quantitative measurement of machining-induced subsurface damage in BK7 glass by self-reference spectral-domain OCT (SD-OCT) in 2017 [26], in which they evaluated the size and density of sub-surface damage in different depths from reconstructed en-face images. In this paper, we conducted a preliminary study of detecting laser-induced bulk damage in KDP crystals based on 3D images obtained by swept source OCT (SS-OCT). We performed fast detection of a large range within the crystal sample and calculated the size and distribution density of the damages.
2. Materials and methods
2.1 Materials
The KDP crystal sample was cut in the prismatic sector taken from a conventionally grown boule oriented for type I doubling at 1ω (1053 nm), and was cut to 50 × 50 × 10 mm3 in size and polished and uncoated on all sides. The laser pulses used for damage tests were delivered from a medium aperture tripled Nd: glass laser called MODSS (Multipurpose Optical Damage Science System) facility constructed in 2011 [27]. The laser pulse has a Gaussian temporal profile with a pulse width (FWHM) of ~5.0 ns at 3ω (351 nm) and the spatial distribution of the pulse is nearly flat top. The 3ω laser pulse used for damage tests is linearly polarized along the ordinary axis of the sample. The diameter of the beam is 5.5 mm. Twelve separated positions of the sample were irradiated with single shot pulses with fluence from 4.56 J/cm2 to 9.95 J/cm2, respectively.
2.2 Imaging system
The schematic of our experimental system is shown in Fig. 1. It is a home-made SS-OCT system based on Mach-Zehnder interferometry. The output of the swept source (Santec, HSL-20-100-B) is about 20 mW, and its turning range is 87 nm with the center wavelength of 1310 nm and the swept rate of 100 kHz. The field of view of the system is 9.3 × 9.3 mm2 and the imaging depth in air is 5.69 mm. The longitudinal resolution is about 14.6 μm in air and the transverse resolution is 17 μm. The sensitivity of the system is 124 dB.
Fig. 1 Schematic of the experimental system. C, circulator; PC, polarization controller; COL, collimating lens; ND, neutral density filter; CP, compensation prisms; M, mirror; AF, analog filter.
The sample was placed on a translation stage below the scanning module of the OCT system, making it possible to detect different positions of the damages. The polarization controllers (PC) were employed to maximize the interference contrast and eliminate possible confusing signal caused by birefringence. A 130 MHz low-pass analog filter was used after the dual-balanced detector to eliminate the aliasing signal. OCT images were displayed in real-time while adjusting the height and position of the sample.
2.3 Counting and locating algorithm
The pinpoints density was analyzed by counting damage pinpoints within a cubic volume of 1 × 1 × 1 mm3 near the region of focus of OCT scan lens. Both of the position and volume of each damage pinpoint were measured. The equivalent diameter of damage pinpoints was calculated, as a measure of the pinpoint size. An automatic algorithm based on divide-and-conquer algorithm [28] was designed to calculate the total pixels that every damage pinpoint contains correctly and count the total damage pinpoints non-repeatedly. Figure 2 shows the flowchart of the algorithm and Fig. 3 is the schematic diagram of the counting procedure for two adjacent layers.
Fig. 3 Schematic diagram of the counting procedure for two adjacent layers. D1-D5: Number of damage pinpoints, the same color means those connected domains belong to the same damage point.
A blank damage data set was firstly initialized to record number, position, and volume of damage pinpoints in the following procedure. The position was recorded in three-dimensional coordinates and volume was recorded by total pixels the damage pinpoint contains. After loading 3D data and preprocessing all 2D images, the 1000 normalized 2D OCT images in a volume were labeled from Layer1 to Layer1000. Since the gray levels of the damage pinpoints are brighter than those of the background and the undamaged region of the crystal, all the layers were binarized using Otsu's method.
Secondly, count all the connected domains in Layeri and Layeri+1. Update damage data set with damage number, position and area of connected domains in Layeri. Then, perform AND operator computing between Layeri+1 and Layeri, getting an intermediate layer, as shown in Fig. 3. The role of the intermediate layer is to confirm whether the connected domains in Layeri+1 are connected to ones in Layeri or whether they belong to the same damage pinpoint. For those connected domains in Layeri+1 who are not connected to existed damages in Layeri, record them as new damage pinpoints in the damage data set.
Finally, check if there are multiple damage pinpoints coalesced into a single one, unify their damage number, then calculate the barycenter position and total pixel numbers every damage point contains, and record them in the damage data set.
3. Experimental results
3.1 Phantom imaging
To test the accuracy of our approach, phantoms were made by dispersing silica microspheres (produced by Baseline company, Tianjin, China, whose refractive index n is 1.53) in index-matching fluid (produced by Yongji company, Shenzhen, China, n = 1.47). Microspheres were used to simulate the damaged points and observed by the SS-OCT system. Three kinds of microspheres, whose diameters (given by Baseline) are 10~20 μm, 20~30 μm, and 30~40 μm, respectively, are tested. Their diameters are further confirmed under the microscope before OCT scanning. Through analyzing 3D OCT images by the above algorithm, the equivalent diameters of the spheres all fall in the range of their actual sizes. Three typical en-face OCT images of these phantoms were shown in Fig. 4, in which we can distinguish different sizes of these microspheres clearly.
Fig. 4 En face OCT images of silica microspheres dispersed in index-matching fluid. (a), (b) and (c) are OCT images of microspheres with diameters of 10~20 μm, 20~30 μm, and 30~40 μm, respectively.
3.2 Damage detection
In damage detection experiments, OCT data of 12 damage sites were acquired, each damage site was scanned in two perpendicular directions and one data volume was saved for one scanning. Each image volume consists of 1000 2D OCT images with 1024 × 1000 pixels, whose acquisition time is 10 seconds.
Figure 5 shows a 2D cross-sectional image of a damage site produced by a single-shot laser pulse with fluence 9.62 J/cm2 and a 3D OCT image of the site produced by fluence of 7.56 J/cm2. It must be noted that it is the optical length difference between the sample and reference mirror in the longitudinal direction that OCT measured. By observing the OCT images, we found the total optical length from the top surface to its bottom surface keep nearly the same for all A-line in the sample, including damaged and the undamaged regions. For its simplicity, the physical length in the longitudinal direction is obtained as 3.8 mm by the optical length difference dividing by the uniform refractive index of KDP crystal n = 1.51, just as shown in Fig. 5.
Fig. 5 A typical 2D Cross-sectional and 3D OCT image of the damage site in the bulk of KDP crystal. (a) The 2D cross-sectional image of a damage site resulting from a laser pulse with fluence 9.62 J/cm2, the sub-image at the left-bottom corner is the enlarged image in the red-dotted box. (b) The 3D OCT image of the whole detection region of one OCT scan of a damage site resulting from a laser pulse with fluence 7.56 J/cm2, the 3D sub-image at the left-bottom corner is the enlarged image of the small cuboid.
From Fig. 5, we can see the laser-induced damage appears as bright points with complex shape and different brightness, which coincides with previous microscopy images and scattering images [8,29,30]. The bright line in the top of Fig. 5(a) is the top surface of the crystal sample. Figure 5(b) shows the whole detection region of an OCT 3D scan. Obviously, the positions of damage pinpoints can be easily located, and the damage pinpoints can be counted accurately in 3D images.
The pinpoint density and size distribution of damage pinpoints induced by different fluences were calculated from the damage data set and were shown in Figs. 6 and 7, respectively. The pinpoint densities of the two scans and their average values are all shown in Fig. 6. Blue and pink triangular signs represent the statistic results of two scans, respectively, and red square signs are their average results. The difference of counting between two perpendicular scanning is less than 10%, which proves our method has good repeatability. As shown in Fig. 6, the relationship between pinpoints density ρ(ϕ) and the fluence ϕ are fitted to power function, referring to the nanoabsorber model proposed by M. D. Feit et al. at 2004 [14]. The fitted curve shows the evolution of the distribution density of damage pinpoints over fluences. From Fig. 6, we find the curve agrees well with the results of 3ω laser irradiation in Ref [31], in which they only gave the results of fluence 4~7 J/cm2. The power exponent 2.7449 is close to the result in Ref [32].
Fig. 6 The distribution density of damage pinpoints plotted versus fluence of laser pulses with duration of 5ns, and wavelength of 351nm. Three kinds of signs, blue and pink triangular signs, and red square signs, represent the statistic results of two scans and their average values, respectively. The relationship between pinpoint density ρ(ϕ) and fluence ϕ is fitted to power function using the average values.
Fig. 7 Size distribution of two damage sites irradiated by fluence of 9.61 J/cm2 and 8.63 J/cm2. (a) Number of damage pinpoints versus the size of damage pinpoints (equivalent diameter); (b) average equivalent diameters of damage pinpoints at 12 damage sites by different fluences. Three kinds of signs, red and purple triangular signs, and blue square signs, represent the statistic results of two scans and their average values, respectively. Linear fits of the data using the average values are shown as a dotted line.
Figure 7(a) shows size distribution of damage pinpoints of two sites who were irradiated by one-shot pulses whose fluence are 9.61 J/cm2 and 8.63 J/cm2, respectively. Damage pinpoints whose size below 17 μm were absent due to the resolution limitation. The average equivalent diameters of damage pinpoints of all 12 sites calculated from the results of the two scans and their average values, were calculated and depicted in Fig. 7(b). Red and purple triangular signs represent the statistic results of two scans, respectively, and blue square signs are their average results. It can be seen that damage size increased with fluence nearly in linear form. This behavior is similar to the previous research [33].
4. Discussions
Low-coherence interferometry makes OCT possible to extract depth information of the sample with non-destruction and high sensitivity. It has been proven that the sensitivity of the refractive index change detected by OCT is 10−3 [34,35], so OCT is more sensitive to detect inconspicuous damages than available methods. Compared with TD-OCT and SD-OCT used in previous researches, SS-OCT have even higher sensitivity for the reflection or scattering from the damage structure. Besides, the swept light source usually has longer coherence length which makes it easily have a larger detection depth and the improvement of imaging speed of SS-OCT will also help to detect large area of samples.
Considering its large quantity and distribution ranges, complex morphology and obscuration, the laser-induced bulk damage is more complicated to be characterized than that of the surface damage. Through three-dimensional OCT imaging, the damage sites can be observed in 3D view and the quantitative analysis can be performed based on 3D data, in which the depth information was extracted by the frequency encoded in the interference signal from objects in different depth of the sample. That makes it possible to solve the problem of obscuration among damage pinpoints from different depths. Although after reflecting or scattering from the upper damage points, the intensity of the light was somewhat attenuated in the direction of the detecting light beam, the signals of damage within the depth detection range of our OCT system were all collected in our experiments, which indicated the lower damage pinpoints were really not obscured by the upper ones. Besides, based on 3D volume data, the size of the damage pinpoints can be measured from any directions, including parallel or vertical to the direction of light propagation, or by calculating the volume to obtain its equivalent diameter. We think it will be more practical than those of 2D imaging methodology or analysis based on 2D OCT images.
The counting and locating algorithms were specially designed based on 3D OCT data. Firstly, the binarization method is a factor that will affect the accuracy of damage detection. In our study, 16-bit OCT data were converted to 8-bit gray images for binarization and damage recognition. Bright damage pinpoints were superimposed over a dark background in OCT images of the sample crystal. Compared with local binarization methods often used in available references [9], or entropy binarization method, we think when dealing with the OCT data, the Ostu binarization method is more effective in recognizing the damaged area, and can avoid the shot noise, which is the dominant noise in OCT images and can be easily recognized as damage pinpoints mistakenly, especially in dark background areas. Secondly, the connecting status was considered not only within a single layer but also within two or more layers in the counting algorithm. The situations of separated damage points in different layers coalescing into a single one, or a single damage point splitting to multiple points, were all checked by the counting algorithm. It is hard to distinguish mutual occlusion points via traditional microscopy or scattering imaging methods. Based on 3D data, during the counting process, the unconnected damage points in 3D OCT images were given different labels, which can easily solve the counting problems for the mutual occlusion points.
The value of the damage density in our experiment is similar to that in Ref [31], in which they only gave the results of fluence 4~7 J/cm2. However, it is much lower than that in the references [9,36,37]. The behavior of the damage size in Fig. 7(b) acts as linearly growth with the increase of fluence. While the value of equivalent diameter keeps within a small range. The difference may be explained by the following reasons. Firstly, the principle of OCT is different to the traditional imaging method used in this field. It has high sensitivity which may enable it to observe more slight change in materials, and it will lead to different results when identifying the damage points or measuring their dimensions. Secondly, the range of the fluences in our experiment is smaller than that in Ref [33], which may result in the different of the plot of damage sizes. Thirdly, different sample characterization (growing process, preprocessing, etc.) may also affect the results. The distribution density of damage points in the middle region is a little larger than other regions in Fig. 5, which may be caused by the resolution and sensitivity loss due to the Gaussian distribution of detection light. In addition, the non-uniform distribution of the damage points may also be influenced by the inhomogeneity of the crystal sample [38].
Researches have been made to study the morphology of the damage itself [12], or factors that influence the morphology of the damage [17], in order to understand the mechanism and the procedure of damage formation. The enlarged sub-images in Fig. 5 clearly presented the shape of damage points, in which the irregular shapes of damage points were observed in OCT images. Limited by the spatial resolution of our SS-OCT system, the OCT images are currently not as effective as those of the high-resolution microscopy to analyze the complex morphology of the damages. Our purpose of the involvement of OCT in this paper is to explore the feasibility of quick and on-line detection of the damage status of the crystal, and obtain as much information as possible within its capability.
In order to do statistical analysis for the damage points, the laser-induced damage experiments were originally designed to irradiate three sites with one-shot laser pulse with the same fluence, but in fact, it is hard to keep the parameter of the laser system exactly the same during the experiment. Therefore, the twelve damage sites were evaluated independently in subsequent analysis. In Fig. 7(b) we can see there are three clusters of points whose fluences are around 6, 7.5 and 10 J/cm2, respectively. They all fall around the fitted line. Whereas in Fig. 6, the three points represent of PPD caused by fluence around 10 J/cm2 have a much bigger deviation, in our opinion, which may be because the PPD is calculated within a selected cubic zone near the center of a damage site, where we attempted to focus the detection light on.
In principle, when doing multiple scanning for fixed samples, OCT can obtain the same results within its resolution range regardless of the noise. It was found that if the sample kept still during the imaging process, the statistics results of damage points were almost the same, so each damage site was scanned two times in two perpendicular directions in our experiments, and their average values were used to fit the curve.
We made a preliminary study to explore the application of SS-OCT in detecting and characterizing laser-induced bulk damage in optical crystals based on 3D images in this paper. Improvements should be further made to optimize the system. Firstly, the longitudinal and transverse resolutions of our current OCT system, ~10 μm (in the sample) and 17 μm, are not enough to distinguish all the damage pinpoints. The pinpoints smaller than the resolution will be recorded larger in size or may be recorded connecting to each other, which may affect the accuracy of the statistics of damage density and damage size. To mitigate the limitation, the longitudinal resolution can be improved to a few micrometers if a light source with a broader tuning range or shorter wavelength is utilized [39,40]. Improving the transverse resolution is a little complicated because of the tradeoff between the transverse resolution and the depth of focus (DOF). Keeping the transverse resolution in a large depth range is extremely important in the application of damage detection in thick optical crystal materials. Some techniques have been proposed to extend the depth of focus while maintaining transverse resolution, such as Bessel beam illumination [41], adaptive optics [42] and digital refocusing [43]. A recently proposed method named multiple aperture synthesis can extend the DOF more than ten times by collecting images based on multiple distinctive apertures and then digitally refocusing them [44–46], which has great potential in this application.
In addition, it needs a larger detection range to characterize laser-induced bulk damage in optical crystals in practical application. The detection depth of SS-OCT is determined by the coherence length of the light source and the sampling rate of the acquisition module. It is also influenced by the scattering and absorption of the medium. Apart from employing light source with boarder coherence length and digitizer with faster sampling rate, it is also possible to expand the imaging depth to the full range of the sample by eliminating the conjugate image based on phase modulation techniques and algorithms [47–49].
In practice, the characterization of damage pinpoints may be more complex because of the difference between optical crystal materials and the possible change of optical properties of those materials during the operation of high-power laser. The inhomogeneity and birefringence of the crystals also need consideration. In future, we will update the OCT system by improving the longitudinal and transverse resolution and its detection depth with suitable devices or techniques mentioned above, making it more practical for detecting bulk damage in optical crystals.
5. Conclusion
To conclude, we demonstrated an approach to detect laser-induced bulk damage in optical crystal materials based on SS-OCT and 3D analysis algorithm. In the preliminary experiment for the KDP crystal sample, the 3D OCT images provided a more visualized exhibition of the damage pinpoints. With the help of automatic damage analysis algorithms, the rapid three-dimensional imaging by OCT was capable of detecting bulk damage pinpoints and helped to analyze their characteristics.
Funding
National Natural Science Foundation of China (NSFC) (61875092, 11374167), State’s Key Project of Research and Development Plan (2016YFC0101002), Science and Technology Support Program of Tianjin (17YFZCSY00740), and Fundamental Research Funds for the Central Universities.
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