TRANSFERRING ALIGNMENT INFORMATION IN 3D TOMOGRAPHY FROM A FIRST SET OF IMAGES TO A SECOND SET OF IMAGES

Abstract

The present disclosure provides a method of transferring alignment information from a first set of images to a second set of images, a respective computer program product and a respective inspection device. A first set of cross-section images in a first imaging mode is obtained, the first cross-section images being taken at times Tai. A second set of cross-section images in a second imaging mode is obtained, the second cross-section images being taken at times Tbj, the times Tbj differing from the times Tai. Obtaining the first and second sets of cross-section images comprises subsequently removing a cross-section surface layer of a sample to make a new cross-section accessible for imaging, and imaging the new cross-section of the sample in the first imaging mode or in the second imaging mode. Switching is performed between the first and second imaging modes while obtaining the first and second sets of cross-section images.

Claims

1. A method of transferring alignment information in 3D tomography from a first set of images to a second set of images, the method comprising: obtaining a first set of cross-section images in a first imaging mode, the first cross-section images being taken at times Tai; switching from the first imaging mode to a second imaging mode; obtaining a second set of cross-section images in the second imaging mode, the second cross-section images being taken at times Tbj which are different from the times Tai; determining alignment information included in the cross-section images of the first set; and using time-dependent interpolation of the alignment information in the cross-section image of the first set to transfer the alignment information from the cross-section images of the first set to the cross-section images of the second set, wherein obtaining the first and second sets of cross-section images comprises subsequently removing a cross-section surface layer of a sample to make a new cross-section accessible for imaging, and imaging the new cross-section of the sample in the first imaging mode or in the second imaging mode.

2. The method of claim 1, wherein the cross-section images of the first set have a first imaging pixel size, and the cross-section images of the second set have a second imaging pixel size different from the first imaging pixel size.

3. The method of claim 2, wherein the first imaging pixel size is at least twice the second imaging pixel size.

4. The method of claim 1, comprising alternating between the first and second imaging modes after obtaining each cross-section image.

5. The method of claim 1, wherein determining the alignment information comprises determining positions of fiducials.

6. The method of claim 5, wherein obtaining the first and second sets of cross-section images is performed in a continuous milling mode.

7. The method of claim 6, wherein transferring the alignment information comprises a time-dependent interpolation of positions of the fiducials for the points of time Tbj when the cross-section images of the second set are obtained based on the points of time Tai when the cross-section images of the first set are obtained.

8. The method of claim 7, wherein the time-dependent interpolation is a linear interpolation.

9. The method of claim 8, wherein time intervals between taking two cross-section images are constant.

10. The method of claim 8, wherein the alignment information comprises a member selected from the group consisting of lateral alignment information and depth alignment information.

11. The method of claim 5, wherein obtaining the first and second sets of cross-section images is performed in a mill-stop-image mode.

12. The method of claim 11, wherein transferring the alignment information comprises a time-dependent interpolation of positions of the fiducials for the points of time Tbj when the cross-section images of the second set are obtained based on the points of time Tai when the cross-section images of the first set are obtained.

13. The method of claim 12, wherein the time-dependent interpolation comprises a linear interpolation.

14. The method of claim 13, wherein the time intervals between taking two cross-section images are constant.

15. The method of claim 13, wherein the time-dependent interpolation of the alignment information is a time-dependent interpolation of lateral alignment information.

16. The method of claim 15, wherein depth alignment information is not interpolated.

17. The method of claim 16, wherein the depth alignment information of the cross-section images of the first set is identically transferred to the corresponding cross-section images of the second set.

18. The method of claim 5, wherein the fiducials comprise a set of parallel fiducials elongating in a depth direction and a set of non-parallel fiducials elongating obliquely to the depth direction.

19. The method of claim 1, further comprising: image registering obtained cross-section images; and obtaining a 3D data set.

20. One or more machine-readable hardware storage devices comprising instructions that are executable by one or more processing devices to perform operations comprising the method of claim 1.

21. A system comprising: one or more processing devices; and one or more machine-readable hardware storage devices comprising instructions that are executable by the one or more processing devices to perform operations comprising the method of claim 1.

22. The system of claim 21, further comprising: a focused ion beam device; and a charged particle device configured to provide charged particles to image the new cross-section of the sample.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The disclosure will be even more fully understood by reference to the following drawings.

[0044] FIG. 1 is an illustration of the cross-section imaging technique.

[0045] FIG. 2 is an illustration of cross-section images and two examples of intersection images through the 3D volume image.

[0046] FIGS. 3A-3B are illustrations of the fiducial alignment process as described in prior art.

[0047] FIGS. 4A-4B are illustrations of an alignment information transfer in continuous milling mode.

[0048] FIGS. 5A-5B are illustrations of an alignment information transfer in a mill-stop-image mode.

DETAILED DESCRIPTION

[0049] FIG. 1 shows a schematic view of the cross-section image approach to obtain a 3D volume image of an integrated semiconductor sample. With the cross-section approach, three-dimensional (3D) volume image acquisition is achieved by a “step and repeat” fashion. First, the integrated semiconductor sample is prepared for the subsequent cross-section image approach by methods known in the art. Throughout the disclosure, “cross-section image” and “slice” will be used as synonyms. Either a groove is milled in the top surface of an integrated semiconductor to make a cross-section approximately perpendicular to the top surface accessible, or an integrated semiconductor sample 10 of block shape is cut out and removed from the integrated semiconductor wafer. This process step is sometimes referred to as “lift-out”. In a step, a thin surface layer or “slice” of material is removed. For sake of simplicity, the description is shown at such a block shaped integrated semiconductor sample 10, but the disclosure is not limited to block shaped samples 10. This slice of material may be removed in several ways known in the art, including the use of a focused ion beam milling or polishing at glancing angle, but occasionally closer to normal incidence by focused ion beam (FIB) 50. For example, the focused ion beam 51 is scanned along direction x to form a cross-section 52. As a result, a new cross-section surface 11 is accessible for imaging. In a subsequent step, the newly accessible cross-section surface layer 11 is raster scanned by a charged particle beam (CPB), such as a scanning electron microscope (SEM) or a FIB (not shown). The imaging system optical axis can be arranged to be parallel to the z-direction, or inclined at an angle to the z-direction. CPB systems have been used for imaging small regions of samples at high resolution of below 2 nm. Secondary as well as backscattered electrons are collected by a detector (not shown) to reveal a material contrast inside of the integrated semiconductor sample, and visible in the cross-section image 100 as different grey levels. Metal structures generate brighter measurement results. The surface layer removal and the cross-section image process are repeated through surface 53 and 54 and further surfaces at equal distance, and a sequence of 2D cross-section images 1000 through the sample in different depths is obtained so as to build up a three-dimensional 3D dataset. The representative cross-section image 100 is obtained by measurements of a commercial Intel processor integrated semiconductor chip with 14 nm technology.

[0050] With the method, at least a first and second cross-section images includes subsequently removing a cross-section surface layer of the integrated semiconductor sample, for example with a focused ion beam, to make a new cross-section accessible for imaging, and imaging the new cross-section of the integrated semiconductor sample for example with a charged particle beam. From the sequence of these 2D cross-section images 1000, a 3D image of the integrated semiconductor structure can be reconstructed. The distance dz of the cross-section images 100 can be controlled by the FIB milling or polishing process and can be between 1 nm and 10 nm, for example about 3-5 nm, but other values are also possible depending on the concrete application.

[0051] FIG. 2 shows an example of two x-z-intersection images from the reconstructed 3D volume image or 3D data set obtained from a sequence of N=400 image slices or cross-section images 1000 obtained in x-y-direction, and spaced in z-direction by distance dz. For sake of simplicity, only three cross-section images 100.1, 100.2, 100.3 are illustrated. The random stage or SEM drifts between acquisition of the N=400 image slices lead to artificially enhanced line edge roughness in z-direction, visible in the metal lines 101 extended in z-direction, or large variations of the widths of metal lines 102, oriented perpendicular to the z-direction.

[0052] FIGS. 3A-3B illustrate the alignment with fiducials, according to prior art. Illustrated in FIG. 3A, a marker structure or fiducials are formed on top of the sample perpendicular to the direction of the cross-sections before the FIB cutting of intersections begins. For the marker structure, first a material 20 is deposed on the top surface 55 of the integrated semiconductor sample. In this material, alignment marks such as parallel lines 21 and inclined lines 22 are formed by FIB processing. After slicing and imaging the cross-section 11 by raster scanning along raster scanning lines 82, each cross-section image 100 contains also a cross-section image segment of the fiducials or alignment markers. Illustrated in FIG. 3B is a representative cross-section 100. The central markers 21 are visible via their cross-section image segments 25 and are used to perform the lateral alignment in x-direction and in y-direction amongst the slices; however, the alignment in y-direction is normally less accurate. The distance between the two cross-section image segments 27 of the two outer makers 22 is used to calculate the distance dz between each slice.

[0053] FIGS. 4A-4B illustrate an alignment information transfer in a continuous milling mode: FIG. 4A indicates the continuous milling mode by the plurality of arrows at the bottom of the figure. There is no stop in milling. Furthermore, the corresponding time axis t is depicted. At a plurality of times (time instances), cross-section images 100 are obtained: At times Ta1, Ta2, Ta3 and Ta4 cross-section images 100a.1, 100a.2., 100a.3, and 100a.4 are obtained. These cross-section images 100a.1, 100a.2. 100a.3, and 100a.4 belong to the first set of cross section images and are obtained in a first imaging mode. According to this example, the cross-section images 100a.1, 100a.2. 100a.3, and 100a.4 have a comparatively big pixel size, for example 4 nm, 6 nm, 8 nm or bigger. The imaged area comprises fiducials and alignment information is determined from these cross-section images 100a.1, 100a.2. 100a.3, and 100a.4 of the first set. For example, the position of a fiducial or the positions of a plurality of fiducials 21, 22 is determined in each of the cross-section images 100a.1, 100a.2. 100a.3, and 100a.4. Known image processing methods give the position of the fiducials or positional markers in pixels. Knowing the pixel size in the first imaging mode allows for translating/determining the positions in nanometers.

[0054] In the presented example, cross-section images 100b.1, 100b.2 and 100b.3 are imaged at times (time instances) Tb1, Tb2 and Tb3. These cross-section images 100b.1, 100b.2, 100b.3 belong to the second set of cross section images and are obtained in a second imaging mode differing from the first imaging mode. According to this example, the cross-section images 100b.1, 100b.2 and 100b.3 have a comparatively small pixel size, for example 2 nm, 1 nm or smaller. No fiducials are imaged in this second imaging mode. Instead, the imaging conditions in the second imaging mode are adapted to imaging a structure of interest in good resolution.

[0055] In the depicted example, the time interval ΔTa=Ta(i+1)−Tai is constant for all i. Furthermore, the time interval ΔTb=Tb(j+1)−Tbj is constant for all j. The cross-section images 100a of the first set are obtained strictly alternatingly with the cross-section images 100b of the second set.

[0056] As already explained above, positional information is determined from positional markers in the cross-section images 100a.1, 100a.2, 100a.3 and 100a.4 of the first set. FIG. 4B indicates the determined positions p at times Ta1, Ta2, Ta3 and Ta4. The position p can be the position of a marker, but this is not necessarily the case. According to an example, p is the position of a structure of interest or of a part of a structure of interest. Since marker structures 21, 22 and the structure of interest are present on the same sample, knowing the positions of the markers also allows for determining the positions of the structure of interest. The position p can be given in full space coordinates, for example px, py, pz. The position p is time dependent and is determined (measured) for times Ta1, Ta2, Ta3 and Ta4.

[0057] What is of interest now, is the position p of the structure of interest at times Tb1, Tb2 and Tb3 in the cross-section images of the second set. This position p varies for the following grounds: First, since imaging is carried out in a continuous milling mode, the depth of the sample is continuously reduced. Therefore, the depth coordinate (z-coordinate) in the slicing direction varies with time. Furthermore, there are also unwanted variations in position because of drifts of for example the stage position and/or the imaging column. Other environmental influences can also occur and can have an influence on the position p. Therefore, according to the disclosure, the position p(Tb1), p(Tb2) and p(Tb3) is determined by interpolation in time: The interpolated values are indicated in FIG. 4B by the crosses without a circle whereas the crosses inside the circles indicate measured values which provide the discrete values for the time-dependent interpolation of position p. The straight line in FIG. 4B is the interpolant which is linear in this example. Therefore, alignment information or positional information p is transferred from the first set of cross-section images 100a.1, 100a.2, 100a.3 and 100a.4 to the second set of cross-section images 100b.1, 100b.2 and 100b.3 by a time-dependent interpolation of the positional information p.

[0058] FIGS. 5A-5B illustrate an alignment information transfer in a mill-stop-image mode. In the following, only the differences between an alignment transfer in a continuous milling mode and an alignment transfer in a mill-stop-image mode will be described. The mill-stop-image mode is indicated by the interrupted plurality of arrows at the bottom of FIG. 5A. A mill-stop-image mode is characterized in that milling is paused when obtaining the cross-section images in both the first imaging mode and the second imaging mode. Furthermore, there is no milling between obtaining a cross-section image of the first set and obtaining a corresponding cross-section image of the second set. In other words, there is no change of any positional marker when comparing its position in slicing direction in a cross-section image of the first set and the corresponding cross-section image of the second set. The depth position (z-coordinate) of the positional marker or position of interest pz stays constant. Therefore, having determined the positional information pz in a cross-section image of the first set, this position pz can be identically transferred to the cross-section image of the second set (still, different pixel sizes in both sets of cross-section images have to be taken into consideration for calculating the transfer).

[0059] Though there is no change in depth direction between corresponding cross-section images, there is still a smooth and slowly varying change of position p with respect to other space coordinates, say in lateral positions px and/or py: Here, drifts of the stage and/or of an imaging column can still occur. Once again, these drift or drifts can be approximated by a smooth function dependent from time, for example by a linear function of time. Therefore, similar to the continuous milling mode, the lateral positions plates in the cross-section images of the second set can be calculated from measured data points in the cross-section images of the first set. FIG. 5B shows an example of an interpolant for illustrating lateral positional deviations: The lateral positions p.sub.lateral at times Tb, Tb2 and Tb3 of a structure of interest in the second set of cross-section images can be determined by time-dependent interpolation.

[0060] In the present examples, a linear interpolation is shown; however, higher-order interpolations are in general also possible.