Cases in which defects are analyzed in a manufacturing process stage in which a pattern is not formed or in a manufacturing process in which a pattern formed on a lower layer does not appear in the captured image are increasing. However, in these cases, there is a problem of not being able to synthesize a favorable reference image and failing to detect a defect when a periodic pattern cannot be recognized in the pattern. In the present invention, a defect occupation rate, which is the percentage of an image being inspected occupied by a defect region, is found, it is determined whether the defect occupation rate is higher or lower than a threshold, and, in accordance with the determination results, it is determined whether to create, as the reference image, an image comprising pixels having the average luminance value of the luminance values of a plurality of pixels contained in the image being inspected. In particular, when the defect occupation rate is low, an image comprising pixels having the average luminance value of the luminance values of a plurality of pixels contained in the image being inspected is used as the reference image.

Defect observation method and defect observation device

Provided is a pattern inspection device for accurately simulating an electron beam image of a circuit pattern on a wafer from design data, and implementing high-precision defect detection based on the comparison between the simulated electron beam image and a real image. A pattern inspection device comprises: an image capturing unit for capturing an electron beam image of a pattern formed on a substrate; a simulated electron beam image generation unit for generating a simulated electron beam image using a parameter indicating the characteristics of the electron beam image on the basis of design data; and an inspection unit for comparing the electron beam image of the pattern, which is the image captured by the image capturing unit, and the simulated electron beam image generated by the simulated electron beam image generation unit, and inspecting the pattern on the substrate.

Pattern inspection device and pattern inspection method

We evaluated the accuracy of the simulation based on mask edge extraction for mask pattern quality assurance. Edge extraction data were obtained from SEM images by use of TOPCON UR-6080 in which high resolution (pixel size of 2nm) and fine pixel SEM image (8000 x 8000 pixels) acquisition is possible. The repeatability of the edge extraction and its impact on wafer image simulation were studied for a normal 1D CD prediction and an edge placement error prediction. The reliability of the simulation was studied by comparing with actual experimental exposure results with an ArF scanner. In the normal 1D CD prediction, we successfully obtained good repeatability and reliability. In 65nm node, we can predict a wafer CD with the accuracy of less than 1 nm using the simulation based on mask edge extraction. In the edge placement error prediction mode, the simulation accuracy is ~5 nm including edge extraction repeatability and the uncertainty of lithography simulation model. 
The simulation with edge extraction more accurately predicts the resist pattern at line-end in which the actual mask pattern may be varied from the mask target (CAD) than a conventional simulation in which CAD is used as a mask pattern. This result supports the view that the wafer simulation with edge extraction is useful for mask pattern quality assurance because it can consider actual mask pattern shape.

Mask pattern quality assurance based on lithography simulation with fine pixel SEM image

A pattern verification-test method according to an embodiment of the present invention includes: deriving an illumination condition at a verification-test subject position in a photomask surface of a mask pattern as a verification or a test subject based on the verification-test subject position and illumination condition information about a distribution of an illumination condition in a photomask surface of exposure light incident on the mask pattern, performing lithography simulation on the mask pattern based on the derived illumination condition and the mask pattern, and verifying or testing the mask pattern based on a result of the lithography simulation

Pattern verification-test method, optical image intensity distribution acquisition method, and computer program

Mask topography has effects on important components of optical image formation at 45nm node and beyond, and
therefore, the lithography simulation model required for hotspot-based mask quality assurance has to incorporate mask
topography effects. Since calculation of mask topography effects involves physical phenomena different from those
encountered in resist processes, we propose the concept of the mask & resist dual fitting method that splits the general
experimental model into the experimental resist model and the experimental mask model. To realize mask & resist dual
fitting, we have developed an experimental mask model, namely, the mask topography approximate model. The mask &
resist dual fitting method can improve model fitting accuracy and improve prediction accuracy at hotspots.

Evaluation of lithography simulation model accuracy for hotspot-based mask quality assurance

PROBLEM TO BE SOLVED: To provide a method of examining defects of a photomask, which has less restrictions and uses SEM image data superior in defect extraction precision and to provide a method of generating false SEM image data for use in the same. SOLUTION: With respect to individual pixels of original image data based on a designed shape of a product, a ratio Ra of the number of pixels of a prescribed pattern part to the total number of pixels of a prescribed neighboring area including a pixel being an object and pixels around the pixel is obtained. The obtained ratio Ra is converted to a corresponding luminance value by a prescribed density display function F(Ra) having a ratio Ra preliminarily obtained correspondingly to the density display state of an SEM image, as a parameter. Image data is newly generated where the luminance value obtained by conversion is assigned to each corresponding pixel of original image data as its luminance value, and this image data is taken as false SEM image data. COPYRIGHT: (C)2004,JPO

Method of generating false sem image data and method of examining defect of photomask

We investigated the specifications of scanning electron microscope required for the lithography simulation based on the edge data extracted from an actual reticle pattern in the assurance of reticle pattern in which two-dimensional optical proximity correction is applied. Impacts of field of view, positioning error and image distortion on a lithography simulation were studied experimentally. For the reticle pattern assurance in hp90, the field of view of larger than 16 μm squares, the positioning error within +/- 1 μm and the magnification error of less than 0.3% are needed. Under these conditions, wafer image can be predicted with sufficient accuracy by the simulation.

Reticle SEM specifications required for lithography simulation

Photomasks are currently inspected based on the standard of defect size. A shortcoming of this standard is that the type of defects which do not impact on a wafer, could be detected as impermissible defects. All of them are subject to repair works and some of them require further inspection by AIMS. This is one of the factors that are pushing down the yield and the turnaround time (TAT) of mask manufacturing. An effective way to improve this situation will be to do the repair works selectively on the defects that are predicted to inflict a functional damage on a wafer. In this report, we will propose a defect evaluation system named ADRES (Advanced Photomask Defect Repair Evaluation System), featuring a function to extract edges from a mask SEM image to be passed on to a litho-simulation. A distinctive point of our system is the use of a mask SEM image with a high resolution.

Tsukasa Kawashima

Papers

Mask pattern quality assurance based on lithography simulation with fine pixel SEM image

Method of generating false sem image data and method of examining defect of photomask

Reticle SEM specifications required for lithography simulation

A photomask defect evaluation system