Fast optical and process proximity correction algorithms for integrated circuit manufacturing
Fast optical and process proximity correction algorithms for integrated circuit manufacturing
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发表时间：
1998
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通讯作者：
Nicolas B. Cobb;A. Zakhor
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作者：
Nicolas B. Cobb;A. Zakhor
在这篇论文中，我们首先研究了光学邻近校正（OPC）问题，并定义了目标、约束和可用的技术。然后，一个实用的和一般的OPC框架建立使用的概念，从线性系统，控制理论和计算几何。开发了一种基于模拟或基于模型的OPC算法，该算法模拟了数百万个位置的光刻的光学和处理步骤。本文对OPC领域的主要贡献包括：（1）使用迭代解将OPC公式化为反馈控制问题，（2）具有成本函数准则的OPC期间的边缘移动算法，（3）使用OPC的快速空间图像仿真，其真正实现基于全芯片模型的OPC，（4）基于空间像的可变阈值抗蚀剂（VTR）模型，用于简化CD预测。本论文的一个主要贡献是针对OPC问题开发了一个快速的航空图像模拟器。在OPC应用程序中，最好在稀疏点处计算强度。因此，我们的快速航拍图像模拟器是专门为计算稀疏点的强度而设计的，而不是在一个规则的密集网格上。快速模拟的起点是最初由Gamo（14）提出的霍普金斯部分相干成像方程的已建立分解。在本论文中，这种分解称为相干系统和（SOCS）结构。详细描述了使用奇异值分解（SVD）的这种分解的数值实现。本论文的另一个贡献是发展了一个可变阈值抗蚀剂模型（VTR）。该模型利用空间像峰值强度和沿着切割线的像斜率来推断抗蚀剂的显影点，并且具有两个主要优点：（1）它是快速的，（2）它可以拟合经验数据。我们结合联合收割机的快速航空图像模拟器和VTR模型在一个迭代反馈回路，制定OPC作为一个反馈控制问题。（摘要由UMI缩短。）
In this thesis, we first look at the Optical Proximity Correction (OPC) problem and define the goals, constraints, and techniques available. Then, a practical and general OPC framework is built up using concepts from linear systems, control theory, and computational geometry. A simulation-based, or model-based, OPC algorithm is developed which simulates the optics and processing steps of lithography for millions of locations. The key contributions to the OPC field made in this thesis work include: (1) formulation of OPC as a feedback control problem using an iterative solution, (2) an algorithm for edge movement during OPC with cost function criteria, (3) use of fast aerial image simulation for OPC, which truly enables full chip model-based OPC, and (4) the variable threshold resist (VTR) model for simplified prediction of CD based off aerial image. A major contribution of this thesis is the development of a fast aerial image simulator which is tailored to the problem of OPC. In OPC applications, it is best to compute intensity at sparse points. Therefore, our fast aerial image simulator is tailored to computing intensity at sparse points, rather than on a regular dense grid. The starting point for the fast simulation is an established decomposition of the Hopkins partially coherent imaging equations, originally proposed by Gamo (14). Within this thesis, the decomposition is called the Sum of Coherent Systems (SOCS) structure. The numerical implementation of this decomposition using Singular Value Decomposition (SVD) is described in detail. Another contribution of this thesis is the development of a variable threshold resist model (VTR). The model uses the aerial image peak intensity and image slope along a cutline to deduce the development point of the resist, and has two primary benefits: (1) it is fast, (2) it can be fit to empirical data. We combine the fast aerial image simulator and the VTR model in an iterative feedback loop to formulate OPC as a feedback control problem. (Abstract shortened by UMI.)