This paper introduces Firefly, an optical lithography origination system that has been developed to produce holographic masters of high quality. This mask-less lithography system has a resolution of 418 nm half-pitch, and generates holographic masters with the optical characteristics required for security applications of level 1 (visual verification), level 2 (pocket reader verification) and level 3 (forensic verification). The holographic master constitutes the main core of the manufacturing process of security holographic labels used for the authentication of products and documents worldwide. Additionally, the Firefly is equipped with a software tool that allows for the hologram design from graphic formats stored in bitmaps. The software is capable of generating and configuring basic optical effects such as animation and color, as well as effects of high complexity such as Fresnel lenses, engraves and encrypted images, among others. The Firefly technology gathers together optical lithography, digital image processing and the most advanced control systems, making possible a competitive equipment that challenges the best technologies in the industry of holographic generation around the world. In this paper, a general description of the origination system is provided as well as some examples of its capabilities.
Compact mask models provide an alternative to speed up rigorous mask diffraction computation based on electromagnetic field modeling. The high time expense of the rigorous mask models in the simulation process challenges the exploration of innovative modeling techniques to compromise accuracy and speed in the computation of the diffracted field and vectorial imaging in optical lithographic systems. The artificial neural network (ANN) approach is presented as an alternative to retrieve the spectrum of the mask layout in an accurate yet efficient way. The validity of the ANN for different illuminations, feature sizes, pitches, and shapes is investigated. The evaluation of the performance of this approach is performed by a process windows analysis, comparison of the spectra, best focus, and critical dimension through pitch. The application of various layouts demonstrates that the ANN can also be trained with different patterns to reproduce various effects such as shift of the line position, different linewidths, and line ends. Comparisons of the ANN approach with other compact models such as boundary layer model, pulses modification, spectrum correction, and pupil filtering techniques are presented.
Compact mask models provide an alternative to speed up rigorous mask diffraction computation based on electromagnetic field (EMF) modeling. The high time expense of the rigorous mask models in the simulation process challenges the exploration of innovative modeling techniques to compromise accuracy and speed in the computation of the diffracted field and vectorial imaging in optical lithographic systems. The Artificial Neural Network (ANN) approach is presented as an alternative to retrieve the spectrum of the mask layout in an accurate yet efficient way. The validity of the ANN for different illuminations, feature sizes, pitches and shapes is investigated. The evaluation of the performance of this approach is performed by a process windows analysis, comparison of the spectra, best focus and critical dimension (CD) through pitch. The application of various layouts demonstrated that the ANN can also be trained with different patterns to reproduce various effects such as: shift of the line position, different linewidths and line ends. Comparisons of the ANN approach with other compact models such as boundary layer model, pulses modification, spectrum correction and pupil filtering techniques are presented.
In this work, correction techniques in the spatial and frequency domains are applied to improve the accuracy of
less rigorous but more efficient mask models. This allows to reproduce the electromagnetic field (EMF) effects
predicted by the rigorous model preserving the simplicity of the Kirchhoff model.
In the frequency domain, two approaches are considered. First, a Jones pupil function is introduced in the
projector pupil plane to describe amplitude, phase and polarization effects which are introduced by the mask.
Second, a correction process performed directly on the scalar spectrum is used to tune the diffraction orders that
get into the pupil of the optical projection system. Since a vector imaging description is needed to include the
polarization phenomena, the spectra of the different polarization components are constructed from the scalar
spectrum using correspondingly calibrated filters. In the spatial domain the well-known boundary layer model is
considered.1 The bright features of the thin mask are surrounded with a semi-transparent region with a certain
width, transmission and phase. Alternatively, the bright mask features of the Kirchhoff model are modified
by adding delta functions to the edges of the absorber. All correction functions for spatial and frequency are
obtained by a calibration with a rigorous model. The validity of these filtering techniques for different feature
sizes and pitches is investigated.
Spatial filtering techniques are used in the analysis of interferograms and off-axis digital holograms to obtain the
phase information from an optical field. The masks applied for the selection of the virtual image order in the
frequency space usually have regular shapes and are located by hand. Therefore, they create artifacts that hide
some details in the obtained phase, especially when holograms from objects with sharp edges are reconstructed.
In this work, a novel algorithm that automatically calculates and locates the mask separating the spectral orders
is presented. This new method uses a distance criterion between the maximum values in the amplitude spectrum
as a clustering parameter. The values for the distance parameter are changed and the results are analyzed for a
simulated image-plane hologram. As an example of the algorithm application, a digital hologram obtained from
one USAF-1951 test target is reconstructed and the phase of the test target element is obtained.
Different mask models have been compared: rigorous electromagnetic field (EMF) modeling, rigorous EMF
modeling with decomposition techniques and the thin mask approach (Kirchhoff approach) to simulate optical
diffraction from different mask patterns in projection systems for lithography. In addition, each rigorous model
was tested for two different formulations for partially coherent imaging: The Hopkins assumption and rigorous
simulation of mask diffraction orders for multiple illumination angles. The aim of this work is to closely approximate
results of the rigorous EMF method by the thin mask model enhanced with pupil filtering techniques. The
validity of this approach for different feature sizes, shapes and illumination conditions is investigated.
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