在數位微影製程中，像差對半導體和微機電系統製造品質的影響至關重要， 因此，有效地校正由數位微影系統產生的畸變是提升製程良率的重大研究議題。 在本篇研究中，我們深入探討數位微影系統的畸變補償問題，並提出一套完整的 畸變校正程序以及影像畸變的演算法，為了準確量化影像畸變的程度，我們提出 一套應用量測不確定度的評估標準，藉此對由成像產生的畸變進行量化與補償目 標圖案的計算。此外，本論文亦提出了兩種主要的演算法:影像畸變量測演算法 和影像畸變校正演算法，藉由該兩種演算法效地應用於修正 DMD 數位微影系統 所產生的成像畸變誤差。在本研究中，我們針對三種不同畸變因子對目標圖案的 影響進行分析。每種畸變因子的影響都在晶圓的不同位置重複量測十次，以降低 隨機量測誤差。根據量測結果和影像畸變校正後的數據，我們發現原始的 RMSE 分別由線性畸變的 24μm、非線性畸變的 6μm 和綜合性畸變的 23μm，降低至 0.998μm、0.966μm、0.934μm。換言之，校正後的影像，其 RMSE 都能被修正至 約 1μm 左右。若比較修正前後的數據，整體的 RMSE 可降低 92.5%。這一結果 證明了我們開發的演算法具有強大的適應性，無論是對線性、非線性畸變，或是 綜合畸變因子，都能有效進行校正。此外，即便在多種畸變因子共同作用的情況 下，該演算法依舊能保持高適應性的校正效能。本實驗室提出的影像畸變校正演 算法亦可直接應用於不同數位微影系統上而不需再額外更改光學架構，對於不同 數位微影系統皆具有極高的適用性。

In digital lithography, aberrations significantly affect the quality of semiconductor and microelectromechanical systems (MEMS). This study explores distortion issues in such systems and proposes a distortion correction procedure and related algorithms. A novel evaluation standard quantifies image distortion, aiding in defining compensation targets. Two main algorithms for measuring and correcting image distortion have been effectively used to rectify errors in DMD digital lithography systems. According to our results, the original Root Mean Square Error (RMSE) from linear distortion of 24μm, nonlinear distortion of 6μm, and comprehensive distortion of 23μm, were significantly reduced to 0.998μm, 0.966μm, and 0.934μm respectively. This drastic reduction translates to an overall RMSE decrease of 92.5%. These results underscore the robust adaptability of our developed algorithms for effectively correcting various types of distortion. One key advantage is that our proposed image distortion correction algorithm can be directly applied to various digital micro-imaging systems without needing additional modifications to the optical structure, demonstrating its broad applicability.

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