Optimization of mask-less lithography conditions for microelectromechanical systems

Abstract

This dissertation focuses on how to optimize the application of maskless lithography in the manufacturing of advanced microelectromechanical systems (MEMS) using digital micromirror devices (DMDs). First, a comprehensive literature review of traditional lithography and emerging maskless lithography technologies is conducted, focusing on the advantages of DMD-based systems in terms of cost-effectiveness and process flexibility. Subsequently, the dissertation describes in detail the key process steps such as pretreatment, spin coating, and prebaking, and designs experimental patterns with multiple specific magnifications. The effects of light intensity, exposure time, and lens magnification on the resolution and fidelity of the developed pattern are systematically studied. Image comparison indicators such as Fourier descriptors, Hu moments, and structural similarity index (SSIM) are introduced to quantitatively analyze the original design image and the developed image. The experimental results show that both short expo sure time and long exposure time can lead to pattern distortion (such as excessive dissolution or edge diffusion), highlighting the importance of balancing exposure parameters. Finally, the dissertation explores future improvements, including quantitative evaluation of developed patterns and integration of machine vision for automated process optimization, so as to develop a predictive model for optimal lithography parameters and further improve process success rate.