Mask Inspection Using Aerial Image Simulation and AIMS Comparison
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Solution Overview
Problem
Current mask inspection methods fail to detect all errors during the design and production phases, leading to high error rates, production delays, and increased costs due to undetected flaws in masks, which are exacerbated by the decreasing size of object structures on wafers and the limitations of existing lithographic systems.
Innovation Solution
The method involves simulating aerial images of mask designs, using an AIMS tool to analyze and compare simulated and real aerial images, identifying critical locations (hot spots), and iteratively improving the design through techniques like OPC to minimize errors, thereby enabling early detection and correction of flaws during the mask design and production process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional mask inspection methods are used, then production costs and time are reduced, but error detection capability is insufficient leading to high error rates
Solution Approach 1:
The patent applies preliminary action by performing aerial image simulation and hot spot identification during the mask design phase, before actual mask production. This allows potential errors to be detected and corrected in advance, preventing defective masks from reaching production and eliminating the need for time-consuming post-production inspection and repair.
Solution Approach 2:
The patent uses aerial image simulation to create a virtual copy of the mask's optical image, which can be analyzed for potential defects without physically producing the mask. This simulated aerial image serves as a precursor for error detection, allowing identification of hot spots and design flaws before committing to actual mask fabrication.
2Reliability
If comprehensive error inspection is performed, then error detection rate is improved, but production delay increases
Solution Approach 1:
By performing aerial image simulation and comprehensive error analysis during the design phase rather than after mask production, the patent enables thorough inspection without delaying the actual manufacturing process. Errors are identified and corrected in the digital design stage, allowing rapid mask production to proceed without interruptions for rework or repairs.
Solution Approach 2:
The patent introduces aerial image simulation as an intermediary step between mask design and physical mask production. This simulation layer acts as a virtual testing environment where comprehensive error detection can occur without affecting the timeline of actual mask fabrication, thus maintaining productivity while improving error detection rate.
3Manufacturing precision
If mask design is iteratively improved, then mask quality is enhanced, but design time increases
Solution Approach 1:
The patent performs aerial image simulation and identifies hot spots during the initial design phase, allowing multiple iterations of design improvement to be conducted in silico before any physical mask production. This preliminary iterative optimization ensures high mask quality from the first production run, eliminating the need for time-consuming post-production adjustments and rework.
Solution Approach 2:
The patent implements a feedback loop where aerial image simulation results and hot spot analysis provide immediate information about potential mask defects. This feedback enables designers to iteratively refine the mask design based on simulated performance, achieving high manufacturing precision through multiple rapid iterations in the digital domain without incurring proportional increases in physical production time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly reduces error rates and production costs by allowing for early recognition and correction of flaws, accelerating mask production and improving mask quality, ensuring masks are suitable for mass production with reduced expenses.
Implementation Method 1
The AIMSTM (Aerial Imaging Measurement System) of Carl Zeiss SMS GmbH has been established in the market for 10 years for analyzing mask defects in terms of printability. It involves illuminating and imaging a small area of the mask (location of a defect and its vicinity) under the same conditions of illumination and imaging (wavelength, NA, type of illumination, degree of coherence of light (Sigma)) as in lithographic scanners.
Implementation Method 2
WO 00/60415 A1 describes a method for correction of imaging errors, wherein a change in an electronic mask layout after exposure of said mask layout causes structures to be imaged on the mask by a mask writer which come as close as possible to the original mask layout or to the desired mask. The process conditions to be taken into consideration are summarized in the form of tables which include, in particular, the parameters that are dependent on the process conditions in the form of correction values.
Data Source
AI summary
The invention relates to a mask inspection method that can be used for the design and production of masks, in order to detect relevant weak points early on and to correct the same. According to said method for mask inspection, an aerial image simulation, preferably an all-over aerial image simulation, is carried out on the basis of the mask design converted into a mask layout, in order to determine a list of hot spots. The mask/test mask is analysed by means of an AIMS tool, whereby real aerial images are produced and compared with the simulated aerial images. The determined differences between the aerial images are used to improve the mask design. The inventive arrangement enables a method to be carried out for mask inspection for mask design and mask production. The use of the AIMS tool directly in the mask production process essentially accelerates the mask production, while reducing the error rate and cost.