Asml Netherlands B.v.

Wenjin Shao

Yu Long Cao

Jun Ye

Antoine Jean Bruguier

James Patrick Koonmen

Ronaldus Johannes Gijsbertus Goossens

Hanying Feng

Luoqi Chen

Ronaldus Johannes Gljsbertus Goossens

Song Lan

Fei Du

Martin Snajdr

Hua Cao

Methods provide computationally efficient techniques for designing gauge patterns for calibrating a model for use in a simulation process. More specifically, the present invention relates to methods of designing gauge patterns that achieve complete coverage of parameter variations with minimum number of gauges and corresponding measurements in the calibration of a lithographic process utilized to image a target design having a plurality of features. According to some aspects, a method according to the invention includes transforming the space of model parametric space (based on CD sensitivity or Delta TCCs), then iteratively identifying the direction that is most orthogonal to existing gauges' CD sensitivities in this new space, and determining most sensitive line width/pitch combination with optimal assist feature placement which leads to most sensitive CD changes along that direction in model parametric space.

Methods and systems for parameter-sensitive and orthogonal gauge design for lithography calibration

Systems and methods for tuning photolithographic processes are described. A model of a target scanner is maintained defining sensitivity of the target scanner with reference to a set of tunable parameters. A differential model represents deviations of the target scanner from the reference. The target scanner may be tuned based on the settings of the reference scanner and the differential model. Performance of a family of related scanners may be characterized relative to the performance of a reference scanner. Differential models may include information such as parametric offsets and other differences that may be used to simulate the difference in imaging behavior.

Model-based scanner tuning systems and methods

Systems and methods for process simulation are described. The methods may use a reference model identifying sensitivity of a reference scanner to a set of tunable parameters. Chip fabrication from a chip design may be simulated using the reference model, wherein the chip design is expressed as one or more masks. An iterative retuning and simulation process may be used to optimize critical dimension in the simulated chip and to obtain convergence of the simulated chip with an expected chip. Additionally, a designer may be provided with a set of results from which an updated chip design is created.

Model-based process simulation systems and methods

Methods according to the present invention provide computationally efficient techniques for designing gauge patterns for calibrating a model for use in a simulation process. More specifically, the present invention relates to methods of designing gauge patterns that achieve complete coverage of parameter variations with minimum number of gauges and corresponding measurements in the calibration of a lithographic process utilized to image a target design having a plurality of features. According to some aspects, a method according to the invention includes transforming the space of model parametric space (based on CD sensitivity or Delta TCCs), then iteratively identifying the direction that is most orthogonal to existing gauges' CD sensitivities in this new space, and determining most sensitive line width/pitch combination with optimal assist feature placement which leads to most sensitive CD changes along that direction in model parametric space.

The present invention generally relates to simulating a lithographic process, and more particularly to methods for smart selection and smart weighting when selecting parameters and/or kernels used in aerial image computation. According to one aspect, advantages in simulation throughput and/or accuracy can be achieved by selecting TCC kernels more intelligently, allowing highly accurate aerial images to be simulated using a relatively fewer number of TCC kernels than in the state of the art. In other words, the present invention allows for aerial images to be simulated with the same or better accuracy using much less simulation throughput than required in the prior art, all else being equal.

Smart selection and/or weighting of parameters for lithographic process simulation

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.

Pattern selection for lithographic model calibration

Embodiments of the present invention describe methods of selecting a subset of test patterns from an initial larger set of test patterns for calibrating a computational lithography model. An example method comprises: generating an information matrix for the initial larger set of test patterns, wherein the terms of the information matrix comprise one or more identified model parameters that represent a lithographic process response; and, executing a selection algorithm using terms of the information matrix to select the subset of test patterns that effectively determines values of the identified model parameters that contribute significantly in the lithographic process response, wherein the subset of test patterns characteristically represents the initial larger set of test patterns. The selection algorithm explores coverage relationships existing in the initial larger set of test patterns.

Information matrix creation and calibration test pattern selection based on computational lithography model parameters

A method for determining an image of a mask pattern in a resist coated on a substrate, the method including determining an aerial image of the mask pattern at substrate level; and convolving the aerial image with at least two orthogonal convolution kernels to determine a resist image that is representative of the mask pattern in the resist.

Harmonic resist model for use in a lithographic apparatus and a device manufacturing method

Methods according to the present invention provide computationally efficient techniques for designing gauge patterns for calibrating a model for use in a simulation process, and which minimize degeneracy between model parameters, and thus maximize pattern coverage for parameter calibration. More specifically, the present invention relates to methods of designing gauge patterns that achieve complete coverage of parameter variations with minimum number of gauges and corresponding measurements in the calibration of a lithographic process utilized to image a target design having a plurality of features. According to some aspects, a method according to the invention includes transforming the space of model parametric space (based on CD sensitivity or Delta TCCs), then iteratively identifying the direction that is most orthogonal to existing gauges' CD sensitivities in this new space, and determining most sensitive line width/pitch combination with optimal assist feature placement which leads to most sensitive CD changes along that direction in model parametric space.

The preset invention provides methods, systems and computer program product for selection of an optimum set of patterns to calibrate a lithography model so that the model can predict imaging performance of a lithography apparatus/system more accurately and reliably without being prohibitively expensive in terms of using computational and metrology resources and time. The method is based on modeling sensitivity of the calibration patterns to measurement noise. In one aspect of the present invention, a method is disclosed, comprising: identifying a model of at least a portion of a lithographic process; identifying a set of patterns for calibrating the model; and, estimating measurement noise associated with the set of patterns.

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Sunnyvale, CA, United States of America

Wenjin Shao