Abstract:
The present invention relates generally to methods and apparatuses for test pattern selection for computational lithography model calibration. According to some aspects, the pattern selection algorithms of the present invention can be applied to any existing pool of candidate test patterns. According to some aspects, the present invention automatically selects those test patterns that are most effective in determining the optimal model parameter values from an existing pool of candidate test patterns, as opposed to designing optimal patterns. According to additional aspects, the selected set of test patterns according to the invention is able to excite all the known physics and chemistry in the model formulation, making sure that the wafer data for the test patterns can drive the model calibration to the optimal parameter values that realize the upper bound of prediction accuracy imposed by the model formulation.
Abstract:
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.
Abstract:
The present invention relates to lithographic apparatuses and processes, and more particularly to multiple patterning lithography for printing target patterns beyond the limits of resolution of the lithographic apparatus. A method of splitting a pattern to be imaged onto a substrate via a lithographic process into a plurality of sub-patterns is disclosed, wherein the method comprises a splitting step being configured to be aware of requirements of a co-optimization between at least one of the sub-patterns and an optical setting of the lithography apparatus used for the lithographic process. Device characteristic optimization techniques, including intelligent pattern selection based on diffraction signature analysis, may be integrated into the multiple patterning process flow.
Abstract:
The present disclosure relates to lithographic apparatuses and processes, and more particularly to tools for optimizing illumination sources and masks for use in lithographic apparatuses and processes. According to certain aspects, the present disclosure significantly speeds up the convergence of the optimization by allowing direct computation of gradient of the cost function. According to other aspects, the present disclosure allows for simultaneous optimization of both source and mask, thereby significantly speeding the overall convergence. According to still further aspects, the present disclosure allows for free-form optimization, without the constraints required by conventional optimization techniques.
Abstract:
A method of efficient optical and resist parameters calibration based on 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. Systems and methods for calibration of lithographic processes whereby a polynomial fit is calculated for a nominal configuration of the optical system and which can be used to estimate critical dimensions for other configurations.
Abstract:
A three-dimensional mask model of the invention provides a more realistic approximation of the three-dimensional effects of a photolithography mask with sub-wavelength features than a thin-mask model. In one embodiment, the three-dimensional mask model includes a set of filtering kernels in the spatial domain that are configured to be convolved with thin-mask transmission functions to produce a near-field image. In another embodiment, the three-dimensional mask model includes a set of correction factors in the frequency domain that are configured to be multiplied by the Fourier transform of thin-mask transmission functions to produce a near-field image.
Abstract:
Described herein are methods for matching the characteristics of a lithographic projection apparatus to a reference lithographic projection apparatus, where the matching includes optimizing projection optics characteristics. The projection optics can be used to shape wavefront in the lithographic projection apparatus. According to the embodiments herein, the methods can be accelerated by using linear fitting algorithm or using Taylor series expansion using partial derivatives of transmission cross coefficients (TCCs).
Abstract:
A model-based tuning method for tuning a first lithography system utilizing a reference lithography system, each of which has tunable parameters for controlling imaging performance. The method includes the steps of defining a test pattern and an imaging model; imaging the test pattern utilizing the reference lithography system and measuring the imaging results; imaging the test pattern utilizing the first lithography system and measuring the imaging results; calibrating the imaging model utilizing the imaging results corresponding to the reference lithography system, where the calibrated imaging model has a first set of parameter values; tuning the calibrated imaging model utilizing the imaging results corresponding to the first lithography system, where the tuned calibrated model has a second set of parameter values; and adjusting the parameters of the first lithography system based on a difference between the first set of parameter values and the second set of parameter values.
Abstract:
A model-based tuning method for tuning a first lithography system utilizing a reference lithography system, each of which has tunable parameters for controlling imaging performance. The method includes the steps of defining a test pattern and an imaging model; imaging the test pattern utilizing the reference lithography system and measuring the imaging results; imaging the test pattern utilizing the first lithography system and measuring the imaging results; calibrating the imaging model utilizing the imaging results corresponding to the reference lithography system, where the calibrated imaging model has a first set of parameter values; tuning the calibrated imaging model utilizing the imaging results corresponding to the first lithography system, where the tuned calibrated model has a second set of parameter values; and adjusting the parameters of the first lithography system based on a difference between the first set of parameter values and the second set of parameter values.
Abstract:
An efficient OPC method of increasing imaging performance of a lithographic process utilized to image a target design having a plurality of features. The method includes determining a function for generating a simulated image, where the function accounts for process variations associated with the lithographic process; and optimizing target gray level for each evaluation point in each OPC iteration based on this function. In one given embodiment, the function is approximated as a polynomial function of focus and exposure, R(ε,ƒ)=P0+ƒ2·Pb with a threshold of T+Vε for contours, where PO represents image intensity at nominal focus, ƒ represents the defocus value relative to the nominal focus, ε represents the exposure change, V represents the scaling of exposure change, and parameter “Pb” represents second order derivative images. In another given embodiment, the analytical optimal gray level is given for best focus with the assumption that the probability distribution of focus and exposure variation is Gaussian.