Abstract: A simulated wafer image of a physical mask and a defect-free reference image are used to generate a severity score for each defect, thereby giving a customer meaningful information to accurately assess the consequences of using a mask or repairing that mask. The defect severity score is calculated based on a number of factors relating to the changes in critical dimensions of the neighbor features to the defect. A common process window can also be used to provide objective information regarding defect printability. Certain other aspects of the mask relating to mask quality, such as line edge roughness and contact corner rounding, can also be quantified by using the simulated wafer image of the physical mask.

Abstract: A simulated wafer image of a physical mask and a defect-free reference image are used to generate a severity score for each defect, thereby giving a customer meaningful information to accurately assess the consequences of using a mask or repairing that mask. The defect severity score is calculated based on a number of factors relating to the changes in critical dimensions of the neighbor features to the defect. A common process window can also be used to provide objective information regarding defect printability. Certain other aspects of the mask relating to mask quality, such as line edge roughness and contact corner rounding, can also be quantified by using the simulated wafer image of the physical mask.

Abstract: A simulated wafer image of a physical mask and a defect-free reference image are used to generate a severity score for each defect, thereby giving a customer meaningful information to accurately assess the consequences of using a mask or repairing that mask. The defect severity score is calculated based on a number of factors relating to the changes in critical dimensions of the neighbor features to the defect. A common process window can also be used to provide objective information regarding defect printability. Certain other aspects of the mask relating to mask quality, such as line edge roughness and contact corner rounding, can also be quantified by using the simulated wafer image of the physical mask.

Abstract: A simulated wafer image of a physical mask and a defect-free reference image are used to generate a severity score for each defect, thereby giving a customer meaningful information to accurately assess the consequences of using a mask or repairing that mask. The defect severity score is calculated based on a number of factors relating to the changes in critical dimensions of the neighbor features to the defect. A common process window can also be used to provide objective information regarding defect printability. Certain other aspects of the mask relating to mask quality, such as line edge roughness and contact corner rounding, can also be quantified by using the simulated wafer image of the physical mask.

Abstract: A simulated wafer image of a physical mask and a defect-free reference image are used to generate a severity score for each defect, thereby giving a customer meaningful information to accurately assess the consequences of using a mask or repairing that mask. The defect severity score is calculated based on a number of factors relating to the changes in critical dimensions of the neighbor features to the defect. A common process window can also be used to provide objective information regarding defect printability. Certain other aspects of the mask relating to mask quality, such as line edge roughness and contact corner rounding, can also be quantified by using the simulated wafer image of the physical mask.

Abstract: A simulated wafer image of a physical mask and a defect-free reference image are used to generate a severity score for each defect, thereby giving a customer meaningful information to accurately assess the consequences of using a mask or repairing that mask. The defect severity score is calculated based on a number of factors relating to the changes in critical dimensions of the neighbor features to the defect. A common process window can also be used to provide objective information regarding defect printability. Certain other aspects of the mask relating to mask quality, such as line edge roughness and contact corner rounding, can also be quantified by using the simulated wafer image of the physical mask.

Abstract: A simulated wafer image of a physical mask and a defect-free reference image are used to generate a severity score for each defect, thereby giving a customer meaningful information to accurately assess the consequences of using a mask or repairing that mask. The defect severity score is calculated based on a number of factors relating to the changes in critical dimensions of the neighbor features to the defect. A common process window can also be used to provide objective information regarding defect printability. Certain other aspects of the mask relating to mask quality, such as line edge roughness and contact corner rounding, can also be quantified by using the simulated wafer image of the physical mask.

Abstract: A system and method of analyzing defects on a mask used in lithography are provided. A defect area image is provided as a first input, a set of lithography parameters is provided as a second input, and a set of metrology data is provided as a third input. The defect area image comprises an image of a portion of the mask. A simulated image can be generated in response to the first input. The simulated image comprises a simulation of an image that would be printed on a wafer if the wafer were exposed to a radiation source directed at the portion of the mask. The characteristics of the radiation source comprise the set of lithography parameters and the characteristics of the mask comprise the set of metrology data.

Abstract: A simulated wafer image of a physical mask and a defect-free reference image are used to generate a severity score for each defect, thereby giving a customer meaningful information to accurately assess the consequences of using a mask or repairing that mask. The defect severity score is calculated based on a number of factors relating to the changes in critical dimensions of the neighbor features to the defect. A common process window can also be used to provide objective information regarding defect printability. Certain other aspects of the mask relating to mask quality, such as line edge roughness and contact corner rounding, can also be quantified by using the simulated wafer image of the physical mask.

Abstract: A simulated wafer image of a physical mask and a defect-free reference image are used to generate a severity score for each defect, thereby giving a customer meaningful information to accurately assess the consequences of using a mask or repairing that mask. The defect severity score is calculated based on a number of factors relating to the changes in critical dimensions of the neighbor features to the defect. A common process window can also be used to provide objective information regarding defect printability. Certain other aspects of the mask relating to mask quality, such as line edge roughness and contact corner rounding, can also be quantified by using the simulated wafer image of the physical mask.

Abstract: A simulated wafer image of a physical mask and a defect-free reference image are used to generate a severity score for each defect, thereby giving a customer meaningful information to accurately assess the consequences of using a mask or repairing that mask. The defect severity score is calculated based on a number of factors relating to the changes in critical dimensions of the neighbor features to the defect. A common process window can also be used to provide objective information regarding defect printability. Certain other aspects of the mask relating to mask quality, such as line edge roughness and contact corner rounding, can also be quantified by using the simulated wafer image of the physical mask.

Abstract: A method for determining device yield of a semiconductor device design, comprises determining statistics of at least one device parameter from at least two device layer patterns; and calculating device yield from the statistics. At least one of the device layer patterns is neither a diffusion layer pattern nor a gate poly layer pattern.

Abstract: Mask simulation tools are typically extremely complicated to learn and to use effectively. Therefore, providing access to a mask simulation tool over a wide area network (WAN) to multiple on-line users can be very cost effective. Specifically, in a network-based simulation server, multiple users can view the same mask image, simulations, and analysis results and provide real-time comments to each other as simulation and analysis are performed, thereby encouraging invaluable problem-solving dialogue among users. The user interface for this mask simulation tool can advantageously facilitate this dialogue. For example, the user interface can include an enter box for a user to enter a message and a talk box for capturing any message sent by any user of the simulation tool using the enter box.

Abstract: A mask defect printability simulation server provides simulations, one-dimensional analysis, and reports to multiple clients over a wide area network, such as the Internet. This network-based simulation server allows a client to leverage a core of highly-trained engineers. Additionally, the network-based simulation server can be easily supported since only a single source for the tools associated with the simulation server is necessary for multiple clients. A client can access the simulation server using a standard personal computer having a browser, thereby eliminating the need for client to maintain an expensive database for the server. Finally, in the network-based simulation server, multiple users can view the same mask defect image and provide real-time comments to each other as simulation and analysis are performed on the defect image, thereby encouraging problem solving and decision-making dialogue among the users.

Abstract: A simulated wafer image of a physical mask and a defect-free reference image are used to generate a severity score for each defect, thereby giving a customer meaningful information to accurately assess the consequences of using a mask or repairing that mask. The defect severity score is calculated based on a number of factors relating to the changes in critical dimensions of the neighbor features to the defect. A common process window can also be used to provide objective information regarding defect printability. Certain other aspects of the mask relating to mask quality, such as line edge roughness and contact corner rounding, can also be quantified by using the simulated wafer image of the physical mask.

Abstract: A simulated wafer image of a physical mask and a defect-free reference image are used to generate a severity score for each defect, thereby giving a customer meaningful information to accurately assess the consequences of using a mask or repairing that mask. The defect severity score is calculated based on a number of factors relating to the changes in critical dimensions of the neighbor features to the defect. A common process window can also be used to provide objective information regarding defect printability. Certain other aspects of the mask relating to mask quality, such as line edge roughness and contact corner rounding, can also be quantified by using the simulated wafer image of the physical mask.

Abstract: A system and method of analyzing defects on a mask used in lithography are provided. A defect area image is provided as a first input, a set of lithography parameters is provided as a second input, and a set of metrology data is provided as a third input. The defect area image comprises an image of a portion of the mask. A simulated image can be generated in response to the first input. The simulated image comprises a simulation of an image that would be printed on a wafer if the wafer were exposed to a radiation source directed at the portion of the mask. The characteristics of the radiation source comprise the set of lithography parameters and the characteristics of the mask comprise the set of metrology data.

Abstract: A method and apparatus for inspecting a photolithography mask for defects is provided. The inspection method comprises providing a defect area image to an image simulator wherein the defect area image is an image of a portion of a photolithography mask, and providing a set of lithography parameters as a second input to the image simulator. The defect area image may be provided by an inspection tool which scans the photolithography mask for defects using a high resolution microscope and captures images of areas of the mask around identified potential defects. The image simulator generates a first simulated image in response to the defect area image and the set of lithography parameters. The first simulated image is a simulation of an image which would be printed on a wafer if the wafer were to be exposed to an illumination source directed through the portion of the mask.