Design and Manufacturing Method of Fundamental Beam Mode Shaper for Adapted Laser Beam Profile in Laser Material Processing

HoloTile light engine: new digital holographic modalities and applications

HoloTile is a patented computer generated holography approach with the aim of reducing the speckle noise caused by the overlap of the non-trivial physical extent of the point spread function in Fourier holographic systems from adjacent frequency components. By combining tiling of phase-only of rapidly generated sub-holograms with a PSF-shaping phase profile, each frequency component-or output 'pixel'- in the Fourier domain is shaped to a desired non-overlapping profile. In this paper, we show the high-resolution, speckle-reduced reconstructions that can be achieved with HoloTile, as well as present new HoloTile modalities, including an expanded list of PSF options with new key properties. In addition, we discuss numerous applications for which HoloTile, its rapid hologram generation, and the new PSF options may be an ideal fit, including optical trapping and manipulation of particles, volumetric additive printing, information transfer and quantum communication.

High fidelity laser beam shaping using liquid crystal on silicon spatial light modulators as diffractive neural networks

Spatial light modulators (SLMs) based on liquid crystal on silicon (LCoS) are powerful tools for laser beam shaping as they can be used to dynamically create almost arbitrary intensity distributions. However, laser beam shaping with LCoS-SLMs often suffers from beam shaping artifacts in part caused by unconsidered properties of the LCoS devices: astigmatism that stems from the non-normal incidence of the laser beam on the SLM and the effect commonly referred to as the '0-th diffraction order' that is caused by both the crosstalk between neighboring pixels and the direct reflection at the cover glass of the SLM. We here present a method to consider and compensate for these inherent properties of LCoS devices by treating the SLM as a diffractive neural network.

Phase retrieval for the generation of arbitrary intensity distributions using an optofluidic phase shifter

An optofluidic phase shifter can be used to generate virtually arbitrary intensity patterns, but only if the phase shift generated by the controllably deformed fluidic surface can be appropriately defined. To enable this functionality, we present two phase retrieval algorithms based on neural networks and least-squares optimization which are used to determine the necessary phase profile to generate a desired target intensity pattern with high accuracy. We demonstrate the utility of the algorithms by showing experimentally the ability of an optofluidic phase shifter to generate arbitrary complex intensity distributions.

Utilizing a Diffractive Focus Beam Shaper to Enhance Pattern Uniformity and Process Throughput during Direct Laser Interference Patterning

Uniform periodic microstructure formation over large areas is generally challenging in Direct Laser Interference Patterning (DLIP) due to the Gaussian laser beam intensity distribution inherent to most commercial laser sources. In this work, a diffractive fundamental beam-mode shaper (FBS) element is implemented in a four-beam DLIP optical setup to generate a square-shaped top-hat intensity distribution in the interference volume. The interference patterns produced by a standard configuration and the developed setup are measured and compared. In particular, the impact of both laser intensity distributions on process throughput as well as fill-factor is investigated by measuring the resulting microstructure height with height error over the structured surface. It is demonstrated that by utilizing top-hat-shaped interference patterns, it is possible to produce on average 44.8% deeper structures with up to 60% higher homogeneity at the same throughput. Moreover, the presented approach allows the production of microstructures with comparable height and homogeneity compared to the Gaussian intensity distribution with increased throughput of 53%.