The stringent and conflicting requirements imposed on optomechanical instruments and the ever-increasing need for higher resolution and quality imagery demands a tightly integrated system design approach. Our aim is to drive the thermomechanical design of multiple components through the optical performance of the complete system. To this end, we propose a new method combining structural-thermal-optical performance analysis and topology optimization while taking into account both component and system level constraints. A 2D two-mirror example demonstrates that the proposed approach is able to improve the system’s spot size error by 95% compared to uncoupled system optimization while satisfying equivalent constraints.

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Digital micromirror device (DMD)-based grayscale lithography is a promising tool for 3-D photolithography of thick photoresists, because this technique provides a patterning solution for free-form 3-D microstructures. Among the numerous process parameters in DMD-based grayscale lithography, the exposure dose pattern corresponding to the grayscale mask pattern, the focal position in the photoresist, and the development time most strongly influence the final profile of the 3-D microstructure. However, finding the best combination of the three process parameters is a difficult and time-consuming task. In this paper, we propose a process optimization method for DMD-based grayscale lithography that is based on the 3-D photolithography simulation and sensitivity analysis. This optimization tool provides not only automatic process optimization for all three process parameters, i.e., the exposure dose pattern, the focal position, and the development time, but also a solution to improve fabrication accuracy for critical features by adopting a variable weight factor. Through a series of experiments, using a 20-μm-thick positive photoresist, the validity and effectiveness of the proposed optimization method and the improvement of the fabrication accuracy were successfully demonstrated. [2015-0055]

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We report a multiple patterning approach utilizing digital-micromirror-device (DMD)-based grayscale lithography, providing a solution to improve fabrication accuracy for entire target three-dimensional structure. Because DMD-based lithography system consists a projection lens system, better resolution can be obtained around focal position comparing to the outer region of depth of focus. Thus, for thick-film resist micro structuring, exposing with multiple focal positions with separate grayscale masks leads to improvement of fabrication accuracy. In order to find the best combination of the multiple focal positions and their grayscale masks, the computational optimization is combined to the multiple patterning approach. Through a several experiments, effectiveness of the proposed approach was successfully demonstrated.

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Digital Micromirror Device (DMD)-based grayscale lithography is a promising tool for three dimensional (3D) microstructuring of thick-film photoresist since it is a maskless process, provides possibility for the free-form of 3D microstructures, and therefore rapid and cost-effective microfabrication. However, process parameter determination lacks efficient optimization tool, and thus conventional look-up table (indicating the relationship between development depth and exposure dose value under a fixed development time) approach with manual try-and-error adjustment is still gold standard. In this paper, we firstly present a complete “input target-output parameters” single exposure optimization method for 3D microstructuring utilizing DMD-based grayscale lithography. This numerical optimization based on lithography simulation and sensitivity analysis can automatically optimize a combination of three process parameters for target microstructure; exposure dose pattern, a focal position, and development time. Through a series of experiments using a 20 μm thick positive photoresist, validity of the proposed optimization approach has been successfully verified. Secondly, with the purpose of further advancing accuracy and improve the uniformity of precision for the target area, a multiple exposure optimization method is proposed. The simulated results proved that the multiple exposure optimization method is a promising strategy to further improve precision for thicker photoresist structure.@en

A novel process optimization tool for grayscale lithography is developed and demonstrated to fabricate three-dimensional (3D) microstructures using thick-film photoresists. For the first time, the two process parameters in grayscale lithography: exposure dose profile and development time are determined automatically for a user-specified target 3D profile. This provides an inexpensive and effective alternative to conventional trialand-error based process design. The optimized parameters were verified by fabricating various 3D microstructures and the experiments revealed good quantitative agreement with the target profile . KEYWORDS Grayscale Photolithography, 3D Microstructuring, Design Optimization, Automatic Process Design@en

With the ongoing development of thick photoresists, promising possibilities have emerged to use these transparent and flexible layers for micro-structures and micropatterns directly and not exclusively as a sacrificial layer in the processing. These 3D polymer microstructures have many potential applications in the field of MEMS: including micro-sensors and actuators, micro-optics and micro-fluidics. Using modern 3D exposure techniques, it is possible to vary the dissolution rate of thick photo resists locally and create complex relief-type three-dimensional structures in just one exposure and development cycle. Unfortunately, realizing the proper exposure conditions needed for a specific 3D micro pattern is complicated, because of the non-linear and smoothing nature of the physical processes. Nowadays, the most widely used approach is based on trial-and-error designed exposure conditions. In this research a systematic approach is developed, based on computational process simulation, associated adjoint sensitivity analysis and optimization techniques.@en