Zinc sulfide (ZnS) exhibits unique properties that make it highly suitable for applications as a multi-wavelength optical element. Its transmittance shows significant improvements in the visible light and near-infrared regions when subjected to high-temperature and high-pressure processes. However, the mechanical cutting of ZnS is limited due to its brittleness and polycrystalline properties. In this study, we propose the feasibility of employing ultrasonic vibration cutting to enable the mechanical cutting of polycrystalline zinc sulfide. The objectives are to analyze both the ductile mode machining and brittle fracture behavior while addressing the issue of spring back encountered during the diamond turning process. Analysis is conducted on cutting parameters, including vibration amplitude, spindle speed, cutting depth, and feed rate, to evaluate their impact on the cutting process. The results showed that we establish ultrasonic vibration cutting can indeed lead to improved cutting quality under specific conditions. We demonstrated the potential of ultrasonic vibration cutting as a promising alternative technique for the precision machining of polycrystalline zinc sulfide. The resolution of the spring back problem represents a significant advancement, potentially enabling the manufacturing of high-quality optical elements using polycrystalline material.
In this study, our aim is to improve the efficiency of the optical manufacturing process employing magnetorheological finishing (MRF) by quantitatively analyzing the MRF response characteristics that vary according to the type and size of low-spatial frequency. Dimension-variable patterns were devised based on the dimension of the tool influence function (TIF), consisting of two types: a width-variable pattern and a height-variable pattern. These dimension-variable patterns were utilized as input data for the MRF corrective polishing system. The resulting residual figure error of the patterns generated through the MRF corrective polishing system was calculated and expressed as output data. Furthermore, to quantify the MRF response characteristics for low-spatial frequency, the relative error is presented by comparing the input data and output data. The results indicate that the MRF polishing performance for low-spatial frequency is influenced by both the type and size of the frequency, and these trends can assist in devising sophisticated and efficient MRF strategies for manufacturing ultra-precision optical surfaces.
Polycrystalline zinc sulfide (ZnS) is a widely used optical material especially for infrared applications. After ultra-precision diamond turning (DT) machining of the material in ductile regime, surface roughness of a few nanometers is achievable. However, the traces of crystal structure were not only visible on the DT machined surface but it also showed the steep ups and downs on the surface profile, although the same depth-of-cut was applied to the whole surface. In this study, it was hypothesized that the ups and downs on the surface profile might be affected by the crystallographic orientation and elastic recovery of each grain on the surface of ultra-precision DT machined ZnS. The relationship between the crystallographic orientation and elastic recovery of the material was investigated using electron microscopy with electron back-scattered diffraction (EBSD) and nanoscale scratch tester. The results showed certain grain orientations exhibit higher levels of elastic recovery, leading to increased surface roughness. These results highlight the importance of considering crystallographic effects in the machining process of ZnS to achieve desired surface quality.
Optics for accelerators require extremely low surface roughness (SR) to achieve high reflectivity due to the very short wavelengths of light used. Diamond turning (DT) is one of the leading machining processes for manufacturing optical components, and is widely used because of its high material removal rate and the ability to obtain optical surfaces with a SR of a few nm or less. There have been many studies on the prediction of SR in the DT process, and many SR prediction models have been proposed for the expression of it. However, when the SR is nm or less, the proposed SR prediction models show different results from the actual results. Aluminum has been used as a material for optical components used in the DT process due to its excellent machinability and high reflectivity, and it is a material that has been used as an actual processing material when proposing the SR prediction model. In order to use aluminum mirrors as optical components for accelerators, their SR must be generated to nm or less. In this study, we have compared and analyzed the nanometer SR of two aluminum materials to fabricate Al mirrors used in infrared optical systems for accelerators.
The initial testing of prototype multiple-order-diffraction engineered (MODE) lens telescope is essential process before the sky test to evaluate the optical imaging performance of a space object. Prototype MODE lens telescope consists of MODE primary lens which is a core component to correct secondary spectrum, a field lens and a double Gauss type color corrector and achieves a diffraction limited performance. The performance is tested on the diffraction efficiency with respect to supercontinuum laser wavelength on an optical testbed and evaluated on the polychromatic performance for prototype molded ring segment.
In this paper, we propose a fabrication process based on Magneto-Rheological Finishing (MRF) for a reflective Spiral Phase Plate (SPP) with a continuous surface. The front surface of a nickel-plated aluminum disk is machined by diamond turning as a plane mirror, and spiral structure with low topological charge is generated by sub-aperture polishing tools, i.e., MRF. Interferometers are used to analyze the smoothness of the spiral structure, steepness of the center step and surface roughness of the random areas for the fabricated SPP. The results indicate that the direct-polishing approach can be a promising technique to fabricate high-precision SPPs.
In this paper, we propose a compensation method for the nanometer level of thermal drift by adopting long-short term memory (LSTM) algorithm. The precision of a machining process is highly affected by environmental factors. Especially in case of a single-point diamond turning (SPDT), the temperature fluctuation directly causes the unexpected displacement at nanometer scale between a diamond tool and a workpiece, even in the well-controlled environment. LSTM is one of the artificial recurrent neural network algorithms, and we figure out that it is quite suitable to predict the temperature variation based on the history of thermal fluctuation trends. We monitor the temperatures at 8 spots nearby a SPDT machine, and the neural network based on LSTM algorithm is trained to construct the thermal drift model from the time series data. Results of thermal drift prediction showed that the proposed method gives an effective model upon the well-controlled laboratory environment, and by which the thermal drift can be compensated to improve the precision of SPDT process.
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