Evolution mechanism of subsurface damage during laser machining process of fused silica.

The machining-induced subsurface damage (SSD) on fused silica optics would incur damage when irradiated by intense lasers, which severely restricts the service life of fused silica optics. The high absorption of fused silica to 10.6 µm makes it possible to utilize pulsed CO2 laser to remove and characterize SSD by layer-by-layer ablation, which improves its laser-induced damage threshold. However, thermal stress during the laser ablation process may have an impact on SSD, leading to extension. Still, the law of SSD morphology evolution mechanism has not been clearly revealed. In this work, a multi-physics simulated model considering light field modulation is established to reveal the evolution law of radial SSD during the laser layer-by-layer ablation process. Based on the simulation of different characteristic structural parameters, two evolution mechanisms of radial SSD are revealed, and the influence of characteristic structural parameters on SSD is also elaborated. By prefabricating the SSD by femtosecond laser, the measurements of SSD during CO2 laser layer-by-layer ablation experiments are consistent with the simulated results, and three stages of SSD depth variation under two evolution processes are further proposed. The findings of this study provide theoretical guidance for effectively characterizing SSD based on laser layer-by-layer ablation strategies on fused silica optics.

Data-based systematic error extraction and compensation methods based on wavelet transform in ultra-precision optical polishing.

Sub-aperture polishing is a key technique for fabricating ultra-precision optics. However, the existence of the polishing errors that are difficult to be compensated by physical modeling seriously affects the manufacturing accuracy and efficiency of optical components. To address this problem, a data-based systematic error extraction and compensation (DSEC) method was proposed to enhance the polishing accuracy on optics. To maximize the extraction quality in a small dataset condition, the wavelet transform is introduced into the extraction process, and the uncertainty of the piston term in the interferometer measurement is improved by L1-norm optimization. Furthermore, two typical error sources (loss of polishing fluid in the edge and the robot trajectory error) are used to verify the effectiveness of the proposed method; in experimental verification, the root mean square (RMS) of the surface figure of a ϕ85-mm mirror was decreased from 0.069λ to 0.017λ, and the RMS of the 610 × 440 mm mirrors was achieved at 0.019λ after the edge compensation, where the polishing accuracy can be improved by more than 4 times; additionally, the RMS of the surface figure with an effective aperture of 480 × 360 mm mirror was reached at 0.011λ after the trajectory error compensation, where the polishing accuracy can be improved by more than 2 times. The proposed DSEC model offers insights that will help achieve advancement in the sub-aperture polishing process.

Theoretical and experimental investigations in thermo-mechanical properties of fused silica with pulsed CO2 laser ablation.

Laser ablation is widely used as a flexible and non-contact processing technology for the fabrication of fused silica. However, the introduction of thermal stress inevitably leads to crack growth and reduces the lifetime of fused silica. Due to the complicated coupling interaction and properties of fused silica, the unclear thermal stress formation is the bottleneck restricting further development of laser ablation. In this article, a three-dimensional multi-physics thermo-mechanical model was developed to reveal the evolution mechanism, and experiments were performed to validate the simulated results. The surface morphology evolution was elaborated during process cycles, with recoil pressure identified as the key factor in determining surface morphology. Moreover, thermal stress was quantified utilizing optical retardance and stress birefringence, effectively distinguishing between non-thermal and thermal stress induced by laser ablation. The theoretical simulations fit well with experimental measurements. Meanwhile, stress distribution and evolution behaviors were revealed under different processing parameters by this model. This work not only contributes to a profound understanding of the laser ablation process but also establishes a theoretical foundation for achieving high surface quality and non-thermal stress laser ablation.

Statistical perception of the chaotic fabrication error and the self-adaptive processing decision in ultra-precision optical polishing.

Subaperture polishing is a key technique for fabricating ultra-precision optics. However, the error source complexity in the polishing process creates large fabrication errors with chaotic characteristics that are difficult to predict using physical modelling. In this study, we first proved that the chaotic error is statistically predictable and developed a statistical chaotic-error perception (SCP) model. We confirmed that the coupling between the randomness characteristics of chaotic error (expectation and variance) and the polishing results follows an approximately linear relationship. Accordingly, the convolution fabrication formula based on the Preston equation was improved, and the form error evolution in each polishing cycle for various tools was quantitatively predicted. On this basis, a self-adaptive decision model that considers the chaotic-error influence was developed using the proposed mid- and low-spatial-frequency error criteria, which realises the automatic decision of the tool and processing parameters. An ultra-precision surface with equivalent accuracy can be stably realised via proper tool influence function (TIF) selection and modification, even for low-deterministic level tools. Experimental results indicated that the average prediction error in each convergence cycle was reduced to 6.14%. Without manual participation, the root mean square(RMS) of the surface figure of a ϕ100-mm flat mirror was converged to 1.788 nm with only robotic small-tool polishing, and that of a ϕ300-mm high-gradient ellipsoid mirror was converged to 0.008 λ. Additionally, the polishing efficiency was increased by 30% compared with that of manual polishing. The proposed SCP model offers insights that will help achieve advancement in the subaperture polishing process.

Densi-melting effect for ultra-precision laser beam figuring with clustered overlapping technology at full-spatial-frequency.

Laser beam figuring (LBF), as a processing technology for ultra-precision figuring, is expected to be a key technology for further improving optics performance. To the best of our knowledge, we firstly demonstrated CO2 LBF for full-spatial-frequency error convergence at negligible stress. We found that controlling the subsidence and surface smoothing caused by material densification and melt under specific parameters range is an effective way to ensure both form error and roughness. Besides, an innovative "densi-melting" effect is further proposed to reveal the physical mechanism and guide the nano-precision figuring control, and the simulated results at different pulse durations fit well with the experiment results. Plus, to suppress the laser scanning ripples (mid-spatial-frequency (MSF) error) and reduce the control data volume, a clustered overlapping processing technology is proposed, where the laser processing in each sub-region is regarded as tool influence function (TIF). Through the overlapping control of TIF figuring depth, we achieved LBF experiments for the form error root mean square (RMS) reduced from 0.009λ to 0.003λ (λ=632.8 nm) without destroying microscale roughness (0.447 nm to 0.453 nm) and nanoscale roughness (0.290 nm to 0.269 nm). The establishment of the densi-melting effect and the clustered overlapping processing technology prove that LBF provides a new high-precision, low-cost manufacturing method for optics.

Modeling and in-depth analysis of the mid-spatial-frequency error influenced by actual contact pressure distribution in sub-aperture polishing.

In ultra-precision optical processing, the sub-aperture polishing is prone to produce a mid-spatial-frequency (MSF) error. However, the generation mechanism of the MSF error is still not fully clarified, which seriously affects the further improvement of optical component performance. In this paper, it is proved that the actual contact pressure distribution between the workpiece and tool is a crucial source which affects the MSF error characteristics. A rotational periodic convolution (RPC) model is proposed to reveal the quantitative relationship among the contact pressure distribution, speed ratio (spin velocity/feed speed) and MSF error distribution. In-depth analyses show that the MSF error is linearly related to the symmetry level of contact pressure distribution and inversely proportional to the speed ratio, where the symmetry level is effectively evaluated by the proposed method based on Zernike polynomials. In the experiments, according to the actual contact pressure distribution obtained from the pressure-sensitive paper, the error rate of modeling results under different processing conditions is around 15%, which proves the validity of the proposed model. The influence of contact pressure distribution on the MSF error is further clarified through the establishment of RPC model, which can further promote the development of sub-aperture polishing.

Fourier convolution-parallel neural network framework with library matching for multi-tool processing decision-making in optical fabrication.

Intelligent manufacturing of ultra-precision optical surfaces is urgently desired but rather difficult to achieve due to the complex physical interactions involved. The development of data-oriented neural networks provides a new pathway, but existing networks cannot be adapted for optical fabrication with a high number of feature dimensions and a small specific dataset. In this Letter, for the first time to the best of our knowledge, a novel Fourier convolution-parallel neural network (FCPNN) framework with library matching was proposed to realize multi-tool processing decision-making, including basically all combination processing parameters (tool size and material, slurry type and removal rate). The number of feature dimensions required to achieve supervised learning with a hundred-level dataset is reduced by 3-5 orders of magnitude. Under the guidance of the proposed network model, a 260 mm × 260 mm off-axis parabolic (OAP) fused silica mirror successfully achieved error convergence after a multi-process involving grinding, figuring, and smoothing. The peak valley (PV) of the form error for the OAP fused silica mirror decreased from 15.153λ to 0.42λ and the root mean square (RMS) decreased from 2.944λ to 0.064λ in only 25.34 hours. This network framework has the potential to push the intelligence level of optical manufacturing to a new extreme.

Plug-and-play positioning error compensation model for ripple suppressing in industrial robot polishing.

The industrial robot-based polisher has wide applications in the field of optical manufacturing due to the advantages of low cost, high degrees of freedom, and high dynamic performance. However, the large positioning error of the industrial robot can lead to surface ripple and seriously restrict the system performance, but this error can only be inefficiently compensated for by measurement before each processing at present. To address this problem, we discovered the period-phase evolution law of the positioning error and established a double sine function compensation model. In the self-developed robotic polishing platform, the results show that the Z-axis error in the whole workspace after compensation can be reduced to ±0.06m m, which reaches the robot repetitive positioning error level; the Spearman correlation coefficients between the measurement and modeling errors are all above 0.88. In the practical polishing experiments, for both figuring and uniform polishing, the ripple error introduced by the positioning error is significantly suppressed by the proposed model under different conditions. Besides, the power spectral density (PSD) analysis has shown a significant suppression in the corresponding frequency error. This model gives an efficient plug-and-play compensation model for the robotic polisher, which provides possibilities for further improving robotic processing accuracy and efficiency.

Sparse bi-step raster path for suppressing the mid-spatial-frequency error by fluid jet polishing.

The periodic ripple errors (mid-spatial-frequency (MSF) error) produced by computer-controlled sub-aperture polishing severely limit the improvement of high-performance optical systems. At the same time, the fluid jet polishing (FJP) method is non-destructive and non-contact, but it is still hard to widely use it due to the defect of small spot-size and low efficiency. In this paper, we found that FJP has a significant advantage in removing the residual periodic ripples in sub-aperture polishing. The mathematical model developed by complex spectrum optimization verifies the existence of the sparse "bi-step raster path" (BSRP), which can achieve efficient periodic ripple error removal by suppressing the first two-order peaks of the error spectrum. In the experiments, it was observed that the MSF error has been significantly reduced after BSRP processing while the surface form and surface roughness have not been deteriorated, which demonstrates the validity of the proposed method. The proposal of the BSRP provides a new approach for the application of FJP and the suppression of the MSF error.

Iterative space-variant sphere-model deflectometry enabling designation-model-free measurement of the freeform surface.

Freeform optics, offering high degrees of design freeform to control light propagation, have already been widely applied in various photoelectric equipment. The form quality of those optics is crucial to their opto-electronics functionalities, which requires to be measured accurately. The deflectometry is a promising technology to test the complex freeform surfaces. In general, there is a designed surface model for the monoscopic deflectometry to estimate the positions of whole measured points to solve the issue of height-slope ambiguity. However, the unknown or inaccurate surface model can induce errors into the measured normal, thereby decreasing the measurement precision. In this paper, without relying on the known surface model, the proposed method iteratively optimizes a sphere model to describe the measured surface by changing the spherical radius. In order to reduce the global error, the space-variant spheres are optimized, respectively, to estimate the whole-aperture surface coordinate. With the help of the iteration surface reconstruction process, the optimal number of the space-variant spheres is achieved to meantime obtain the final reconstructed surface. Compared to the measurements by using the plane model, the form accuracy can be improved by three times. Experiments demonstrate that the proposed method can successfully reconstruct the complex surfaces without the need of a known surface model, which can greatly improve the measuring flexibility and measurement accuracy.

Modeling and prediction of tool influence function under complex edge in sub-aperture optical polishing.

Edge mis-figures are regarded as one of the most difficult technical issues in optical fabrication. At present, only the near straight-line edge tool influence function (TIF) can be fitted by a polynomial function, but it is difficult to unify a 2-D analytical model suitable for complex edge workpieces and various tools, due to the lack of the scientific understanding of the edge removal behavior. In this paper, a comprehensive mathematical model is proposed to reveal the mechanism of the edge effect and accurately predict the complex edge TIF. The concept of a nonlinear edge kernel is first proposed and verified that the nonlinear pressure can be characterized by convoluting the kernel with the edge contour, which can be easily adapted to complex edge cases; besides, the edge kernel obtaining algorithm is established. The linear pressure part is verified to be constrained by the moment balance formula, which occurs in universal joint tool. Besides, the basic pressure distribution is presented to compensate the pressure distortion caused by the uneven form of the tool pad. The introducing of these three parts makes the complex edge pressure modeled efficiently and matched perfectly with the FEA results. In addition, a series of TIF experiments were carried out on various complex edge workpieces and different tools, which could be well predicted by the proposed model in 2-D view.

High-efficiency smooth pseudo-random path planning for restraining the path ripple of robotic polishing.

Computer-controlled subaperture polishing technology is limited by its propensity to introduce midspatial frequency (MSF) error (ripple error), which significantly inhibits the performance improvement of optical systems. The pseudo-random polishing path is an important method for suppressing MSF error. However, a pseudo-random path that ensures both path smoothness and planning efficiency is difficult to generate. This paper proposes a novel, to the best of our knowledge, pseudo-random path planning method employing a reconstructive points algorithm that efficiently achieves full coverage of the workpiece under massive sampling points at once. Moreover, the generation time for millions of path points is reduced to less than 3 minutes. Additionally, a path modification method is proposed that achieves smooth processing on a machine tool with few additional path points; the vibration magnitude under the proposed smooth path can be reduced to 0.749 g (gravity acceleration), which is the same as that of a raster path. A precise speed management method is also proposed to ensure precise surface error corrections. Overall, the experimental results show that the peak valley of the form error can be converted to 0.115λ using the proposed algorithm without introducing a periodic MSF error.

Modeling and analysis of the mid-spatial- frequency error characteristics and generation mechanism in sub-aperture optical polishing.

In the field of ultra-precision manufacturing, the mid-spatial-frequency (MSF) error can severely affect the performance of the optical elements, but it is rather difficult to quantitatively predict the MSF error distribution. In this paper, the piecewise-path convolution (PPC) analysis is established to investigate the characteristic and the mechanism of the MSF error. The path type, tool influence function (TIF), feed rate, movement type, etc. are all considered mathematically in the analysis. This method can quantitatively predict the MSF error distribution. The coupling relationship among the path type, TIF and the MSF error are proved through the filtering theory. Besides, the analysis reveals the mathematical relationship between the tool movement type (orbital motion, radial runout) and the MSF error; the results show that the tool motion can also introduce non-negligible MSF error. Based on the research above, two selection formulae of path type, TIF and polishing parameters are provided for low MSF error polishing, which gives the theoretical guidance for the parameter selection in deterministic polishing. Practical experiments demonstrate the validity of the analysis results and conclusions.

Superior Mesenteric Artery Syndrome Improved by Enteral Nutritional Therapy: A Retrospective Case-Series Study in a Single Institution.

INTRODUCTION: Superior mesenteric artery syndrome (SMAS) is a relatively rare cause of chronic duodenal obstruction, owing to the compression of the third portion of the duodenum. OBJECTIVES: This retrospective study aims to discuss the efficacy of enteral nutrition (EN) therapy in nutritional status and symptom improvement at a short-term follow-up for SMAS patients. METHODS: We retrospectively analyzed clinical data of patients diagnosed as SMAS and treated with EN from September 2012 to January 2019. RESULTS: Twenty-six patients were included (16 women; mean age 24.96 ± 11.77 years), none was excluded, and one was lost to follow-up. The patients' mean body weight was 40.94 ± 10.16 kg, mean weight loss 11.73 ± 7.58 kg, and mean body mass index (BMI) 14.82 ± 2.52 kg/m2. The mean duration of EN therapy was 10.10 ± 4.66 months. Serum level of nutritional indicators, BMI and body weight increased after EN therapy. During a median follow-up of 24 months (9-44) after EN therapy, the mean symptom score decreased from 24.28 ± 9.57 to 8.06 ± 8.29 (p < 0.0001), and 65% of patients' symptoms resolved and 15% of patients' symptoms improved. In total, 16 complications occurred, including tube blockage, peristomal wound infections, peristomal leakage, granulomas, and nasopharyngeal pain. CONCLUSION: EN therapy may be an effective option for SMAS patients. While it might not remove all symptoms, it can improve the nutritional status to support subsequent treatments.

Risk Factors for Nephrolithiasis in Adults with Short Bowel Syndrome.

INTRODUCTION: Patients with short bowel syndrome (SBS) commonly develop nephrolithiasis. However, the risk factors for nephrolithiasis in patients with SBS remain unclarified. The present study aimed to identify the risk factors for nephrolithiasis in adults with SBS. METHODS: All eligible adults diagnosed with SBS and admitted to a tertiary referral center from December 2008 to 2018 were retrospectively identified from a prospectively maintained database. Patients' demographic and clinical characteristics were analyzed using univariate and multivariate analyses to identify the risk factors for nephrolithiasis. RESULTS: Of 231 adults with SBS, 42 (18.2%) developed nephrolithiasis. The mean age was 46.4 ± 17.8 years, the mean body mass index was 18.2 ± 3.8 kg/m2, and median duration of SBS was 11 months (range 2-324 months). Multivariate binary logistic regression analysis revealed that the independent risk factors for nephrolithiasis in adults with SBS were jejuno-ileal anastomosis and colon-in-continuity (OR 4.335; 95% CI 1.175-16.002; p = 0.028), prolonged duration of SBS (OR 1.008; 95% CI 1.002-1.014; p = 0.010), and increased serum creatinine concentration (OR 1.005; 95% CI 1.001-1.009; p = 0.012). CONCLUSIONS: Nephrolithiasis is common in adults with SBS. As nephrolithiasis can have adverse clinical consequences, patients with SBS should be closely monitored, and prophylactic interventions should be considered.

N-3 polyunsaturated fatty acids ameliorate hepatic steatosis via the PPAR-α/CPT-1α pathway in a mouse model of parenteral nutrition.

Parenteral nutrition (PN) is one of the basic therapies for patients with intestinal failure; however, hepatic steatosis associated with PN limits the long-term use of PN. N-3 polyunsaturated fatty acids (PUFAs) have been used to improve clinical outcomes of patients receiving PN; however, the mechanisms by which n-3 PUFAs ameliorate hepatic steatosis remain unclear. In the present study, C57BL/6J mice were randomly assigned to three treatment groups, namely, enteral nutrition (EN), n-3 PUFAs, and n-6 PUFAs. Additionally, MK 886 was used to inhibit PPAR-α. After 7 days of intervention, mice were sacrificed, and liver tissue and serum samples were collected. Results from liver weight and liver triglyceride measurements and Oil Red O staining showed that n-3 PUFAs significantly reduced the liver triglyceride levels. In addition, treatment with n-3 PUFAs resulted in a greater decrease in serum triglyceride and low-density lipoprotein cholesterol levels compared to n-6 PUFAs. The key enzymes involved in FA oxidation, namely, PPAR-α and CPT-1α, were significantly restored at both the mRNA and protein levels in the n-3 PUFAs group. However, the benefits of n-3 PUFAs in improving serum and liver TG levels were abolished when the PPAR-α/CPT-1α pathway was blocked by MK 886. The results of this study indicated that n-3 PUFAs ameliorated the PN-associated hepatic steatosis by activating the PPAR-α/CPT-1α pathway. The present study provided a reliable scientific basis supporting the potential beneficial effects of n-3 PUFAs for improving hepatic steatosis in patients receiving long-term parenteral nutrition.

Region-adaptive path planning for precision optical polishing with industrial robots.

In the field of ultra-precision manufacturing, industrial robotic polishing has the potential to become a more economical and intelligent method than the conventional polishing machines. But the challenge of the robotic polishing lies in the low control accuracy, which seriously affects the polishing quality. In this paper a new region-adaptive path planning method is proposed, where the path is generated adaptively according to the specific form error. Each time only the regions with form error large enough are processed, thereby improving the polishing stability and efficiency. Smooth paths are generated based on the hexagonal meshing of the processing regions to avoid sharp turning, and then the dwell time is calculated by space-variant deconvolution. The PVr metric of the final form error resulting from the robotic polisher converges down to λ/15. In addition this method can reduce the polishing time by 80%, henceforth the stability and efficiency of robotic polishing can be greatly improved.

Modeling of edge effect in subaperture tool influence functions of computer controlled optical surfacing.

Computer controlled optical surfacing requires an accurate tool influence function (TIF) for reliable path planning and deterministic fabrication. Near the edge of the workpieces, the TIF has a nonlinear removal behavior, which will cause a severe edge-roll phenomenon. In the present paper, a new edge pressure model is developed based on the finite element analysis results. The model is represented as the product of a basic pressure function and a correcting function. The basic pressure distribution is calculated according to the surface shape of the polishing pad, and the correcting function is used to compensate the errors caused by the edge effect. Practical experimental results demonstrate that the new model can accurately predict the edge TIFs with different overhang ratios. The relative error of the new edge model can be reduced to 15%.

Pan-cancer analysis confirms the prognostic and immunological effects of prostate tumor overexpressed-1 in human cancers.

BACKGROUND: Prostate tumor overexpressed-1 (PTOV1) is a conserved oncogenic adaptor protein associated with cancer progression and may be an independent prognostic marker for several malignancies. Consequently, using pan-cancer research to explore the significance of PTOV1 is valuable, and may reveal novel targets for cancer treatment. METHODS: A comprehensive bioinformatics analysis of PTOV1 was performed. The qRT-PCR was utilized to confirm the aberrant PTOV1 expression in several cancer cell lines. RESULTS: We observed that PTOV1 mRNA expression was high in 18 cancer tissues and was thereafter associated with poor survival prognosis in a range of malignancies. The immune subtypes of 14 malignancies and the molecular subtypes of six malignancies were related to PTOV1. A substantial association between PTOV1 and immune checkpoint (ICP) genes was also observed. Tumor mutational burden (TMB), microsatellite instability (MSI), and DNA methylation analyses indicated that PTOV1 acts as a cancer-promoting agent in a series of tumors. In addition, an enrichment study of PTOV1 and related genes revealed that RNA splicing may be responsible for the involvement of PTOV1 in cancers. Lastly, we also verified that PTOV1 expression was elevated in bladder cancer, breast cancer, CESC, LIHC cell lines via qRT-PCR. CONCLUSION: Our bioinformatics research indicated that PTOV1 may be involved in tumor immunity. Furthermore, differentially expressed PTOV1 was found to be related to poor prognosis in cancers, and RNA splicing may be the specific mechanism for this effect. Therefore, PTOV1 mRNA and the corresponding protein may function as potential prognostic indicators and therapeutic targets in various cancers.

Down regulation of NDUFS1 is involved in the progression of parenteral-nutrition-associated liver disease by increasing Oxidative stress.

Parenteral nutrition (PN)-associated liver disease (PNALD) is a common and life-threatening complication of patients receiving PN. However, its definitive pathology remains unclear. Ubiquinone oxidoreductase core subunit S1 (NDUFS1), which is the largest core subunit of mitochondrial complex I, could alter the mitochondrial reactive oxygen species (ROS) formation. The purpose of this study was to investigate the role of NDUFS1 in the pathogenesis of PNALD and its underlying mechanism. We performed hepatic proteomics analysis of PNALD patients, and established a PNALD rat model to verify the role of oxidative stress, NDUFS1, pyrin inflammasome, and IL-1ß in the progression of PNALD. Proteomics analysis revealed the NDUFS1 expression was decreased in PNALD patients, and the differentially espressed proteins were involved in mitochondrial respiratory chain complex Ⅰ. Treatment with MitoQ or overexpression of NDUFS1 can alleviate the progression of PNALD by reducing oxidative stress. The expression of pyrin, caspase-1, and IL-1ß was increased in PN rats. Pharmacological antagonism of pyrin by colchicine can alleviate liver injury and hepatic steatosis. NDUFS1 prevents PNALD pathogenesis by regulating oxidative stress. Pyrin inflammasome and IL-1ß may participate in the process of PNALD development by suppressing the transcription of MTTP and impairing the secretion of VLDL. Oxidative stress reduction may be employed as a strategy in the prevention and treatment of PNALD.