Various methods and systems for utilizing design data in combination with inspection data are provided. One computer-implemented method for binning defects detected on a wafer includes comparing portions of design data proximate positions of the defects in design data space. The method also includes determining if the design data in the portions is at least similar based on results of the comparing step. In addition, the method includes binning the defects in groups such that the portions of the design data proximate the positions of the defects in each of the groups are at least similar. The method further includes storing results of the binning step in a storage medium.

Methods and systems for utilizing design data in combination with inspection data

Various methods and systems for determining a position of inspection data in design data space are provided. One computer-implemented method includes determining a centroid of an alignment target formed on a wafer using an image of the alignment target acquired by imaging the wafer. The method also includes aligning the centroid to a centroid of a geometrical shape describing the alignment target. In addition, the method includes assigning a design data space position of the centroid of the alignment target as a position of the centroid of the geometrical shape in the design data space. The method further includes determining a position of inspection data acquired for the wafer in the design data space based on the design data space position of the centroid of the alignment target.

Methods and systems for determining a position of inspection data in design data space

A system and a method for creating a focus-exposure model of a lithography process are disclosed The system and the method utilize calibration data along multiple dimensions of parameter variations, in particular within an exposure-defocus process window space The system and the method provide a unified set of model parameter values that result in better accuracy and robustness of simulations at nominal process conditions, as well as the ability to predict lithographic performance at any point continuously throughout a complete process window area without a need for recalibration at different settings With a smaller number of measurements required than the prior-art multiple-model calibration, the focus-exposure model provides more predictive and more robust model parameter values that can be used at any location in the process window

System and method for creating a focus-exposure model of a lithography process

A method of efficient simulating imaging performance of a lithographic process utilized to image a target design having a plurality of features. The method includes the steps of determining a function for generating a simulated image, where the function accounts for process variations associated with the lithographic process; and generating the simulated image utilizing the function, where the simulated image represents the imaging result of the target design for the lithographic process.

Methods and Systems for Lithography Process Window Simulation

Computer-implemented methods and systems for detecting defects in a reticle design pattern are provided. One computer-implemented method includes acquiring images of the reticle design pattern using a sensor disposed on a substrate arranged proximate to an image plane of an exposure system configured to perform a wafer printing process using the reticle design pattern. The images illustrate how the reticle design pattern will be projected on a wafer by the exposure system at different values of one or more parameters of the wafer printing process. The method also includes detecting defects in the reticle design pattern based on a comparison of two or more of the images corresponding to two or more of the different values.

Methods and systems for detecting defects in a reticle design pattern

Methods and systems are disclosed to inspect a manufactured lithographic mask, to extract physical mask data from mask inspection data, to determine systematic mask error data based on differences between the physical mask data and mask layout data, to generate systematic mask error parameters based on the systematic mask error data, to create an individual mask error model with systematic mask error parameters, to predict patterning performance of the lithographic process using a particular mask and/or a particular projection system, and to predict process corrections that optimize patterning performance and thus the final device yield.

System and method for mask verification using an individual mask error model

A method for separately calibrating an optical model and a resist model of lithography process using information derived from in-situ aerial image measurements to improve the calibration of both the optical model and the resist model components of the lithography simulation model Aerial images produced by an exposure tool are measured using an image sensor array loaded into the exposure tool Multiple embodiments of measuring aerial image information and using the measured aerial image information to calibrate the optical model and the resist model are disclosed The method of the invention creates more accurate and separable optical and resist models, leading to better predictability of the pattern transfer process from mask to wafer, more accurate verification of circuit patterns and how they will actually print in production, and more accurate model-based process control in the wafer fabrication facility

Method for lithography model calibration

Methods are disclosed for selecting and optimizing an exposure tool using an individual mask error model. In one embodiment, a method includes selecting a model of a lithography process including an optical model of an exposure tool and a resist model, creating an individual mask error model representing a mask manufactured using mask layout data, simulating the lithography process using the model of the lithography process and the individual mask error model to produce simulated patterns, determining differences between the simulated patterns and a design target, and optimizing settings of the exposure tool based on the differences between the simulated patterns and the design target.

Method for selecting and optimizing exposure tool using an individual mask error model

A method of using an in-situ aerial image sensor array is disclosed to separate and remove the focal plane variations caused by the image sensor array non-flatness and/or by the exposure tool by collecting sensor image data at various nominal focal planes and by determining best focus at each sampling location by analysis of the through-focus data. In various embodiments, the method provides accurate image data at best focus anywhere in the exposure field, image data covering an exposure-dose based process window area, and a map of effective focal plane distortions. The focus map can be separated into contributions from the exposure tool and contributions due to topography of the image sensor array by suitable calibration or self-calibration procedures. The basic method enables a wide range of applications, including for example qualification testing, process monitoring, and process control by deriving optimum process corrections from analysis of the image sensor data.

System and method for measuring and analyzing lithographic parameters and determining optimal process corrections

While a high-resolution 2-dimensional image reconstruction is expected to give the maximum possible amount of information on the aerial image in a projection system, relevant information regarding image quality can be derived from a statistical evaluation of image values. Relevant statistical image data can be derived by sampling at a multitude of non-adjacent locations across a large area, rather than by scanning over many adjacent locations on a small area. Examples of the benefits of the present invention include: (1) it generally does not rely on very precise, repeatable fine alignment of the image sensor array with respect to the mask and/or the projected image; (2) a large number of individual sensor elements are utilized, and image data is generated from a large set of signal values; and (3) it can generate relevant data to assess aerial image quality in a very short data acquisition time.

Jun Ye

Papers

System and method for mask verification using an individual mask error model

Method for lithography model calibration

Method for selecting and optimizing exposure tool using an individual mask error model

System and method for measuring and analyzing lithographic parameters and determining optimal process corrections

System and method for characterizing aerial image quality in a lithography system