Diffractive neural networks (DNNs) are an emerging design method for systems of cascaded phase masks, where the optical system is treated as an all-optical neural network. In previous work, we have demonstrated how this method can be used to design highly flexible beam shaping systems. We have also shown that DNNs can be used to correct pixel crosstalk and direct reflection in a spatial light modulator based on liquid crystal on silicon. Here, we extend the correction of these effects to two cascaded spatial light modulators and demonstrate the resulting increase in accuracy of the three-dimensional beam shaping capabilities of DNNs.
Phase-retrieval algorithms are usually limited to the Fourier plane of an optical system. We present a modified iterative Fourier transform algorithm for spatial laser beam shaping in arbitrary optical systems, including systems with optical amplifiers.
Modification of glass with Ultrashort Pulsed (USP) laser radiation with subsequent wet chemical etching is a well-known process, especially for fused silica, and is referred to as Selective Laser induced Etching (SLE). The main advantage of the SLE process is that almost any 3D geometry can be produced, but currently this is mainly limited to the use of fused silica samples with flat surfaces. To extend the SLE process, we have now processed 400 µm thick upward curved borosilicate glass. In the initial studies on planar borosilicate glass, the first process parameters are found and partially transferred to the curved samples. However, it is found that etching of simple structures occurs at different rates when comparing planar and curved material. This presents a challenge for processing curved surfaces, where optical aberrations like spherical aberrations, astigmatism, and coma distort the spot geometry. We are able to spiral cut the curved 400 μm thick borosilicate glass sample as well as drill through it using the SLE process. Difficulties are observed in the structuring of the area with high incident angles at greater radii, since here the influence of optical aberrations becomes dominant. Thus, sufficient modification by the laser radiation is no longer possible. This prevents the subsequent etching process. This allows the limits of the SLE process to be evaluated for thin upward curved borosilicate glass. The spiral created from the curved glass shows high flexibility and therefore the high durability of the material after processing.
The available (average) power of high-power lasers is steadily increasing. This poses the challenge of providing this power dynamically tailored to the respective laser processing application, be it surface structuring, cutting or 3D printing, in order to ensure efficient and high-quality processing. In dynamic high-power laser beam shaping, a compromise usually has to be made between the applicable amount of (average) laser power and the degrees of freedom for the beam shaping device. In general, the higher the damage threshold is, the fewer are the degrees of freedom for available beam shaping devices[1,2]. One way to overcome this deficit is to first shape the beam with a high resolution and low power output and then amplify the beam to the necessary laser power. The subsequent amplification introduces unwanted changes in the desired beam shape, which needs to be compensated. The current method to compensate the amplification induced changes is to exactly simulate the optical system at hand as well as the amplification process. For this purpose, an Iterative-Fourier- Transformation-Algorithm (IFTA) combined with an additional optimization is used. This method requires prior knowledge of all system and amplification defining parameters, which are non-trivial to determine. Another approach, pursued in this paper, is the use of an artificial neural network (ANN). The ANN is trained through the combinations of different phase masks and the resulting beam shape profiles. This training method should allow the ANN to indirectly map any optical system without any regard to its complexity. Through an appropriate choice of training samples and subsequent training the ANN is able to approximate the mapping function of the optical system including the amplification. The fully trained ANN generates phase masks for the beam shaping process in one step and thus allows highly dynamic beam shaping of arbitrary beam shape profiles.
Laser structuring is a powerful tool for functionalizing surfaces, e.g., improving the tribological properties. To achieve small structures in the < 2 μm range, microscope objectives are typically used in laser material processing. There are two main challenges to achieve small structures: On the one hand, the limited working distance between the focusing optics and the workpiece results in a comparatively small processing area of a few square millimeters. On the other hand, the depth of field is limited when structuring with microscope lenses due to their large numerical aperture. As a result, the intensity of the laser beam is strongly dependent on the position in the propagation direction, so that the process window for material removal is only a few μm and small deviations disrupt the process. For highly productive large-area laser structuring in a roll-to-roll (R2R) process, the processing area must be enlarged, and the depth of field must be increased at the same time to enhance process robustness. With a given R2R process speed of the moving material of 2 m/min, and a material width of 0.5 m, we want to structure an area of 1 m²/min. The structuring pattern is a hexagonal arrangement of spots with a spot diameter of 1-2 μm and a spot distance of 2 μm. Additionally, we want to achieve a depth of field of 45-50 μm to enhance the process robustness. Given this background, this paper presents an approach in which a laser beam is split into numerous sub-beams and these sub-beams are subsequently shaped in such a way that the depth of field is increased for each individual beam. For beam shaping, a combination of static optical elements is used to transform a uniform into a Bessel-like intensity distribution to achieve a greater depth of field. By a skillful arrangement of the focusing elements, structure sizes of 1-2 μm as well as structure distances of 2 μm are achieved with the given R2R process speed.
The authors report on experimental and simulative scattering analyses of phase and amplitude defects found in extreme ultraviolet multilayer mirrors, such as mask blanks for EUV lithography. The goal of the analyses is to develop a novel mask blank inspection procedure using one single inspection tool that allows to determine whether a defect is a surface type (amplitude) defect, or a buried type (phase) defect. The experiments were carried out with an actinic dark-field reflection microscope. Programmed defects of both types were fabricated, using different nanostructuring techniques. Analytical and rigorous scattering simulations were carried out to predict and support the experimental results.
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