Proc. SPIE. 10959, Metrology, Inspection, and Process Control for Microlithography XXXIII
KEYWORDS: Lithography, Ultraviolet radiation, Scanning electron microscopy, Transmission electron microscopy, Time metrology, Extreme ultraviolet, Line width roughness, Extreme ultraviolet lithography, Line edge roughness, Stochastic processes
We have previously demonstrated our method to obtain unbias dense line’s LER (Line Edge Roughness) processed by EUV (Extreme Ultra-Violet) lithography. No special edge-detection, simulation modeling, beam-scan, nor image processing is required, except optimization of beam-dose parameters. For instance, threshold method that is a conventional edge-detection is used on SEM (Scanning Electron Microscopy) image taken by a conventional beam-scanning with a conventionally used beam-conditions. However, especially for EUV-lithographed features we must determine carefully landing voltage and beam-dose that cause artificial reduction of LER and LWR (Line Width Roughness) due to shrink of photo resist materials.
Note that we made edge-detection interval at every 5 nm, that is as small as probe-beam diameter. For instance, we set the vertical magnification, the pixel-density, and the sum-line-per-point parameter at 52.7k, 1024, and 2, respectively. Although we can make the interval as small as sub-nanometer, it is not reliable to measure the sub-nanometer object that is only one-tenth of the probe-beam diameter.
Then, we verified accuracy of our unbiased LWR by using two independent experimental methods: TEM and FIB-SEM. We obtained spectra of PSD (Power Spectrum Density) from the TEM, the FIB-SEM and our unbiassing CDSEM-method. We found the three PSDs agreed very well to each others. This result strongly implies that three independent methods measured an identical PSD, of true LWR. By our unbiassing CDSEM-method we can measure the true LWR which is calculated from the true PSD.
In this work, by using the similar experimental-methods we verify accuracy of our wiggling measurement. Wiggling is a hot issue in production yield of post dry-etch process. Especially about 20 nm or less in the line-width, wiggling starts appearing due to decreased elastic-stiffness of the line feature.
A reason why we study the accuracy of LER, LWR, and wiggling is inline monitor of stochastic failures. As they increase significantly in EUV lithography process, production yield may not be promising. Bisshop et al.  investigated pitch and/or space-width correlate to incidence of stochastic-failures, such as breaking-line and bridging-line, down to ppm (parts per million). However, the incidence of the stochastic failures should be reduced less to ppb (parts per billion) or ppt (parts per trillion) which is as small as tolerable particle contamination on a wafer.
This implies significance of accurate LWR and/or wiggling monitor because in narrow line or space a-few-nanometer-LWR narrows locally them the more and causes the more stochastic failures.
In this work, in order to control ppb-stochastic failures we figure out a correlation between LWR and the failures’ incidence. We need to measure billions of features, that requires too long measurement time for practical process-monitor. To shorten the measurement time we test an effective method to estimate such very few number of failures.
 Stochastic effects in EUV lithography: random, local CD variability, and printing failures, Peter De Bisschop, J. of Micro/Nanolithography, MEMS, and MOEMS, 16(4), 041013 (2017).
Measurement of line edge roughness (LER) is discussed from four aspects: edge detection, power spectrum densities (PSD) prediction, sampling strategy, and noise mitigation. General guidelines and practical solutions for LER measurement today are introduced. Advanced edge detection algorithms such as the wave-matching method are shown to be effective for robustly detecting edges from low SNR images, whereas a conventional algorithm with weak filtering is still effective in suppressing SEM noise and aliasing. An advanced PSD prediction method such as the multitaper method is effective in suppressing sampling noise within a line edge to analyze, whereas a number of lines are still required for suppressing line-to-line variation. Two types of SEM noise mitigation methods, such as the “apparent noise floor” subtraction method and LER-noise decomposition using regression analysis, are verified to successfully mitigate SEM noise from PSD curves. These results are extended to local critical-dimension uniformity (LCDU) measurement to clarify the impact of SEM noise and sampling noise on LCDU.
Proc. SPIE. 10585, Metrology, Inspection, and Process Control for Microlithography XXXII
KEYWORDS: Signal to noise ratio, Edge detection, Metrology, Detection and tracking algorithms, Reliability, Scanning electron microscopy, Process control, Image filtering, Critical dimension metrology, Line edge roughness
Measurement of line edge roughness (LER) is discussed from four aspects: edge detection, PSD prediction, sampling strategy, and noise mitigation, and general guidelines and practical solutions for LER measurement today are introduced. Advanced edge detection algorithms such as wave-matching method are shown effective for robustly detecting edges from low SNR images, while conventional algorithm with weak filtering is still effective in suppressing SEM noise and aliasing. Advanced PSD prediction method such as multi-taper method is effective in suppressing sampling noise within a line edge to analyze, while number of lines is still required for suppressing line to line variation. Two types of SEM noise mitigation methods, "apparent noise floor" subtraction method and LER-noise decomposition using regression analysis are verified to successfully mitigate SEM noise from PSD curves. These results are extended to LCDU measurement to clarify the impact of SEM noise and sampling noise on LCDU.
For EUV lithography features we want to decrease the dose and/or energy of CD-SEM’s probe beam because LER decreases with severe resist-material’s shrink. Under such conditions, however, measured LER increases from true LER, due to LER bias that is fake LER caused by random noise in SEM image. A gap error occurs between the right and the left LERs. In this work we propose new procedures to obtain true LER by excluding the LER bias from the measured LER. To verify it we propose a LER’s reference-metrology using TEM.
Proc. SPIE. 8681, Metrology, Inspection, and Process Control for Microlithography XXVII
KEYWORDS: Metrology, Cadmium, Electron microscopes, Atomic force microscopy, Scanning electron microscopy, 3D metrology, Critical dimension metrology, Line edge roughness, Scanning transmission electron microscopy, 3D image processing
A new method for calculating critical dimension (CDs) at the top and bottom of three-dimensional (3D) pattern profiles from a critical-dimension scanning electron microscope (CD-SEM) image, called as “T-sigma method”, is proposed and evaluated. Without preparing a library of database in advance, T-sigma can estimate a feature of a pattern sidewall. Furthermore, it supplies the optimum edge-definition (i.e., threshold level for determining edge position from a CDSEM signal) to detect the top and bottom of the pattern. This method consists of three steps. First, two components of line-edge roughness (LER); noise-induced bias (i.e., LER bias) and unbiased component (i.e., bias-free LER) are calculated with set threshold level. Second, these components are calculated with various threshold values, and the threshold-dependence of these two components, “T-sigma graph”, is obtained. Finally, the optimum threshold value for the top and the bottom edge detection are given by the analysis of T-sigma graph. T-sigma was applied to CD-SEM images of three kinds of resist-pattern samples. In addition, reference metrology was performed with atomic force microscope (AFM) and scanning transmission electron microscope (STEM). Sensitivity of CD measured by T-sigma to the reference CD was higher than or equal to that measured by the conventional edge definition. Regarding the absolute measurement accuracy, T-sigma showed better results than the conventional definition. Furthermore, T-sigma graphs were calculated from CD-SEM images of two kinds of resist samples and compared with corresponding STEM observation results. Both bias-free LER and LER bias increased as the detected edge point moved from the bottom to the top of the pattern in the case that the pattern had a straight sidewall and a round top. On the other hand, they were almost constant in the case that the pattern had a re-entrant profile. T-sigma will be able to reveal a re-entrant feature. From these results, it is found that T-sigma method can provide rough cross-sectional pattern features and achieve quick, easy and accurate measurements of top and bottom CD.
Metrology of line-edge roughness (LER) or line-width roughness (LWR) reduced less than a few nanometers in recent advanced-process is one of issues because measured LER is strongly dependent on measurement conditions such as magnification and beam dose. It may happen that different organizations measure different LERs on an identical sample. By using an ultra-low LER sample we demonstrate intolerable change of measured LER between with and without necessary key-points in the measurement conditions of critical-dimension secondary electron microscope (CD-SEM).
The accelerated pace of the semiconductor industry in recent years is putting a strain on existing dimensional metrology
equipments (such as CDSEM, AFM, Scatterometry) to keep up with ever-increasing metrology challenges. However, a
revolution appears to be forming with the recent advent of Hybrid Metrology (HM) - a practice of combining
measurements from multiple equipment types in order to enable or improve measurement performance. In this paper we
extend our previous work on HM to measure advanced 1X node layers - EUV and Negative Tone Develop (NTD) resist
as well as 3D etch structures such as FinFETs. We study the issue of data quality and matching between toolsets
involved in hybridization, and propose a unique optimization methodology to overcome these effects. We demonstrate
measurement improvement for these advanced structures using HM by verifying the data with reference tools (AFM,
XSEM, TEM). We also study enhanced OCD models for litho structures by modeling Line-edge roughness (LER) and
validate its impact on profile accuracy. Finally, we investigate hybrid calibration of CDSEM to measure in-die resist line
height by Pattern Top Roughness (PTR) methodology.
Local-distortion of CD-SEM image can be detected and compensated by a unique technique: View-Shift method. As
design rule of semiconductor device is getting shrunk, metrology by critical dimension scanning electron microscope
(CD-SEM) is not only for measuring dimension but also shape, such as 2D contour of hot-spot pattern and OPC
calibration-pattern. Accuracy of the shape metrology is dependent on the local image-distortion that consists of two
components: magnification distortion and shape distortion. The magnification distortion can be measured by pitchcalibration
method, that measures pitch of an identical line pattern at a lot of locations in image. However, this method
cannot measure the shape distortion, that is for instance, bending of a uniform-width line.
To measure accurately and quickly the image-distortion, we invented the View-Shift method, in which images of uniquetexture
sample are taken before and after an image-shift by about 100nm. Between the two images we measure
displacements of the unique-textures found at each grid-point spread over the image. Variation of the local displacements
indicates the local image-distortion. In this work, we demonstrate a method to compensate the image-distortion detected
by the View-Shift method. Due to the image-distortion, edge-points determined in SEM-image have already been
dislocated. Such dislocation can be relocated to compensate the detected local-distortion. Onsite and on-demand
compensation right before CD-SEM measurement for process monitoring is possible because we can quickly apply the
View-Shift method and complete the compensation in a few minutes.
As the design rule for semiconductor device shrinks, metrology for the critical dimension scanning electron microscope
(CD-SEM) is not only for measuring the dimension but also the shape, such as 2D contour of hot-spot pattern and OPC
calibration-pattern. Accuracy of the shape metrology is dependent on distortion of CD-SEM image. The distortion of
magnification in horizontal direction (i.e. x-direction) can be measured by pitch-calibration method, that measures pitch
of identical vertical line patterns while view-shifting the identical pitch in x-direction. However, the number of
measurement point could not be sufficient because this method requires long measurement time. Not only the horizontal
magnification but also vertical magnification (i.e. y-direction) and shear deformation (i.e. distortion of shape) are
necessary to keep highly accurate measurement.
In this paper we introduce the view-shift method for quick and accurate measurement of the image-distortion. From
using this method, both local distortion of magnification and shape can be measured in horizontal and vertical directions
at once. Firstly, two SEM-images of evaluation sample are taken. The sample should have a lot of unique features, e.g.
Textured-Silicon. View-shift about one ninth of the image size should be done by two images, and There are a lot of
unique features in overlapped region between two images. As distribution of the unique features, displacement between
two images indicates the local image-distortion. The dislocation of sample contour from distortion is estimated from the
local-distortion. The image-dislocation on a tool evaluated in this paper is less than 0.5 nm. It is a tolerated size for
current device process. However, it could be increased under the noisy external environment.