Critical Dimension Scanning Electron Microscope Research Articles

Application of a machine learning method to model-based library approach for critical dimension measurements using CD-SEM

A model-based library (MBL) method has already been established for the accurate measurement of the critical dimension (CD) of semiconductor linewidth using critical dimension scanning electron microscope (CD-SEM) images. In this work, the MBL method is further investigated by combining CD-SEM image simulation and a neural network algorithm. The secondary electron linescan profiles were first calculated using a Monte Carlo simulation method, enabling us to obtain the dependence of linescan profiles on the selected values of various geometrical parameters (e.g. top CD, sidewall angle and height) for Si and Au trapezoidal line structures. Machine learning methods have then been applied to predict the linescan profiles from a randomly selected training set of the calculated profiles. The predicted results agree very well with the calculated profiles with the standard deviations of 0.1% and 6% for the relative error distributions of Si and Au line structures, respectively. The findings show that the machine learning methods can be practically applied to the MBL method for reducing the library size, accelerating the construction of the MBL database and enriching the content of the available MBL database.

Modeling and algorithm of three-dimensional metrology with critical dimension scanning electron microscope

To address the challenges of accurate metrology of height and sidewall angle (SWA) of three-dimensional structures with critical dimension scanning electron microscopy, general modeling and algorithms based on tilted electron beam technology and the corresponding application skills are proposed, and the validity and error accuracy are evaluated as well. Three typical structures, the trapezoid, inverted trapezoid, and step, are investigated with Monte Carlo simulation. The maximum derivative method is used to extract key parameters from the secondary electron linescan. The efficiency of the proposed modeling, algorithms, and the accuracy of the calculated height and SWA are improved further with the application of wavelet transform.

Uncertainty evaluation of Monte Carlo simulated line scan profiles of a critical dimension scanning electron microscope (CD-SEM)

In recent years, precision and accuracy for a more precise critical dimension (CD) control have been required in CD measurement technology. CD distortion between the measurement by a critical dimension scanning electron microscope (CD-SEM) and a reference tool is the most important factor for a more accurate CD measurement. CD bias varies by a CD-SEM and a pattern condition. Therefore, it is urgently needed to identify, characterize, and quantify those parameters that may or may not affect the CD measurement by a CD-SEM. The sensitivity of the Monte Carlo simulated CD-SEM images with multiple physical modeling components has been studied previously. In this study, we demonstrate that the work function and elastic scattering potential models have a significant impact on secondary electron emission intensity, but their influence on the shape of the linescan profile is small, and other factors like the optical energy loss function and dielectric function models have even smaller effects. We have evaluated the uncertainty in the linescan profiles of Si line structures with different sidewall angles due to several different physical factors. It is found that when the CD is evaluated by a peak/valley method, the uncertainty of the CD is negligible. Therefore, it is concluded that the CD value and its related uncertainty are not critically related to the physical factors of the present Monte Carlo simulation model but rely dominantly on the line structure and electron beam parameters.

Quantification of three-dimensional pattern-shape variation with CD-SEM top-down image

The shrinkage of circuit patterns for improvement of the semiconductor device performance has reduced the tolerances in production. To fit in the tolerances, technologies for improving the uniformity of three-dimensional (3D) shapes of circuit patterns inter- or intra- wafers has been developed. Then, we developed a method for quantifying variations in 3D shapes by critical-dimension scanning electron microscopy (CD-SEM), which can measure widths of circuit patterns with high sensitivity. Since variations in the SEM-image signal are caused by 3D-shape variations, in the method, multiple feature values representing the signal detect shape variations. To compare the effect of the variation in each feature value on the shape variation, the amount of variation in the feature values was normalized by local variations in a reference image. Evaluation on etched wafers showed that several features exhibited independent variation trends that were larger than the local fluctuation. Cross-sectional verification confirmed that one of the feature values correlated with the width at the middle height that cannot be seen in top-view, and variations of 0.24 nm can be detected. It is expected that adjusting processing conditions based on this variation trend will efficiently improve the uniformity of the 3D shape.

Canny Algorithm Enabling Precise Offline Line Edge Roughness Acquisition in High-Resolution Lithography.

The line edge roughness (LER) is one of the most critical indicators of photoresist imaging performance, and its measurement using a reliable method is of great significance for lithography. However, most studies only investigate photoresist resolution and sensitivity because LER measurements require an expensive and not widely available critical dimension scanning electron microscopy (SEM) technology; thus, the imaging performance of photoresist has not been adequately evaluated. Here, we report an image processing software developed for offline calculation of LER that can analyze lithographic patterns with resolutions up to ∼15 nm. This software can effectively process all graphic files obtained from commonly used SEM machines by utilizing the adjustable double threshold. To realize the effective detection of high-resolution patterns in advanced lithography, we used SEM images generated from extreme ultraviolet and electron beam lithography to develop and validate the software's graphic recognition algorithm. This image processing software can process typical SEM images and produce reliable LER in an efficient and user-friendly manner, constituting a powerful tool for promoting the development of high-performance photoresist materials.

Depth estimation from a single SEM image using pixel-wise fine-tuning with multimodal data

To support the ongoing size reduction in integrated circuits, the need for accurate depth measurements of on-chip structures becomes increasingly important. Unfortunately, present metrology tools do not offer a practical solution. In the semiconductor industry, critical dimension scanning electron microscopes (CD-SEMs) are predominantly used for 2D imaging at a local scale. The main objective of this work is to investigate whether sufficient 3D information is present in a single SEM image for accurate surface reconstruction of the device topology. In this work, we present a method that is able to produce depth maps from synthetic and experimental SEM images. We demonstrate that the proposed neural network architecture, together with a tailored training procedure, leads to accurate depth predictions. The training procedure includes a weakly supervised domain adaptation step, which is further referred to as pixel-wise fine-tuning. This step employs scatterometry data to address the ground-truth scarcity problem. We have tested this method first on a synthetic contact hole dataset, where a mean relative error smaller than 6.2% is achieved at realistic noise levels. Additionally, it is shown that this method is well suited for other important semiconductor metrics, such as top critical dimension (CD), bottom CD and sidewall angle. To the extent of our knowledge, we are the first to achieve accurate depth estimation results on real experimental data, by combining data from SEM and scatterometry measurements. An experiment on a dense line space dataset yields a mean relative error smaller than 1%.

Deep learning model for 3D profiling of high-aspect-ratio features using high-voltage CD-SEM

High-aspect-ratio (HAR) channel holes were developed for competitive cost-per-bit 3D-NAND memory. High-throughput and in-line monitoring solutions for 3D profiling of the HAR features are the key to improving yields. We previously proposed an exponential model to identify the cross-sectional profile of the HAR features using backscattered electron (BSE) images of a high-voltage critical dimension scanning electron microscopy (CD-SEM). However, the 3D profiling accuracy was insufficient when the depth of the HAR features was far greater than the focus depth of the electron beam. To address this issue, we developed a deep learning (DL) model, which takes account of the aperture angle and the aberration of the electron beam, to predict the 3D profile from BSE images. The predicted cross-sections of the HAR holes with different bowing geometries were compared with field-emission SEM measurements. The results show that the DL model provides higher sensitivity than the exponential model does.

Extreme contact shrink for back end of line connectivity

For the past 50 years, Moore’s law has been well followed by the semiconductor industry. The scaling of transistors and interconnects has been enabled not only by various technological advancements but also by novel patterning approaches. However, in order to keep up with Moore’s law, further shrinking at all levels of the integrated circuit is needed. Among them is the back end of line (BEOL), where increasingly smaller metal pitches require tight specifications for vias connecting metal lines. In this paper, BEOL via shrink options is investigated, targeting the bottom critical dimension (CD) 10.5 nm in order to land on metal pitch 21 nm lines below, while maintaining low defectivity, as well as low global and local CD uniformity (CDU and LCDU, respectively). Approaches to this shrink consist of modifications to the etch chemistry at different levels of the mask etch and liner-assisted shrink, either organic or inorganic. Numerical analysis of CD-scanning electron microscopy (CDSEM) images quantitatively shows the efficiency of different approaches via shrink, together with associated CDU, LCDU, and defectivity values. CDSEM results are supplemented by large-area voltage contrast defectivity and transmission electron microscopy data sets.

Chemically amplified resist CDSEM metrology exploration for high NA EUV lithography

Background: The chemically amplified resist (CAR) has been the workhorse of lithography for the past few decades. During the evolution of projection lithography to extreme ultraviolet lithography (EUVL), a continuous reduction in feature size is observed. Also, a reduction in resist film thickness (FT) is required to prevent large aspect ratios that lead to pattern collapse. A further reduction in resist FT, into an ultrathin film regime (<30 nm resist FT), is expected when advancing to high NA EUVL. This brings along associated challenges with (1) resist critical dimension scanning electron microscope (CDSEM) metrology and (2) resist patterning performance. Aim: Assessment of metrology challenges and patterning limits of a CAR working in this ultrathin film regime. Deconvoluting the metrology and patterning effect on the determination of the unbiased line width roughness (uLWR). Approach: Patterning a CAR at different nominal resist FTs on two different underlayers to quantify the changes in CDSEM image quality and resist patterning performance with the resulting uLWR changes. Results: The CDSEM image signal-to-noise ratio (SNR) depends on resist FT and the underlayer. The uLWR increases with a reduction in resist FT but scales differently on the two underlayers. Conclusions: A relationship between CDSEM image SNR and uLWR is found. The SNR and uLWR scaling difference on the two underlayers, as well as the uLWR dependency on SNR was determined to be a metrology effect. The general uLWR increase for a reduced resist FT was determined to be a patterning effect.

Novel XPS Technique for Fluorocarbon Layer Evaluation on Nano-Scale Sicoh Sidewalls

Motivation: The Back End of Line (BEoL) in semiconductor industry uses carbon doped silicon oxides (SiCOH), also called ultra-low-k (ULK) or low-k dielectrics as insulating materials. During reactive ion etching (RIE) of those materials, fluorocarbon passivation layer is formed which controls the etch profile and the plasma induced damage of the material. The etch front of the dielectric is dynamically removed during etching. Due to anisotropic plasma the FC layer builds up differently on the trench sidewalls. Therefore the FC layer on trench sidewalls and the trench bottom should be quantified [i]. It is challenging to study the vertical sidewalls in a patterned film. This work aims to implement X-Ray Photoelectron Spectroscopy (XPS) technique to analyze the sidewalls of the etched film and quantify the buildup of passivating FC layer on the sidewalls in different etch recipes. Methodology: Dense SiCOH (k=2.75, open porosity=7%) with initial thickness of 160nm was deposited on 300mm Si wafers. The wafers were patterned using E-beam lithography. The pattern consists of parallel trench arrays of varying trench widths (50nm to 1500nm) and line widths (75nm to 125nm). Wafers were etched with C4F8/CF4/N2/Ar (Recipe_1) and CHF3/CF4 (Recipe_2) plasma in a Dual Frequency Capacitive Coupled Plasma (CCP) etch chamber. Post etch trench depth and critical dimension (CD) bias of the etched structures were measured using spectroscopic ellipsometry and critical dimension scanning electron microscopy (CDSEM) respectively. Each structures were then measured under XPS for the surface chemical composition.The XPS methodology is based on the mathematical separation of the photoelectron signal intensities of the three different surfaces of a trench, namely the Line Top, Trench Sidewalls and Trench Bottom[ii]. In a model-based approach, electron shadowing by the opposite trench sidewall is calculated using the measured geometry from ellipsometry and CDSEM. It assumes that every point surface on the sidewall emits electrons and only the electrons falling in the acceptance cone of XPS electron detector are counted which limits the conical opening to 60º inclined at 50º to sample surface normal (Fig.1a). Analysis depth of the sidewall varies with the trench width and the trench angle. A physical model is developed to calculate the sidewall analysis depth which is not shadowed by the opposite sidewall (Fig.1b).The layout contains various pitch size which constitute different area ratios of Line Top, Trench Sidewalls and Trench Bottom. In order to find the chemical composition of each surfaces independent of their visible areas, the system of linear equations is solved using Multiple Linear Regression method to find out the signal intensity per unit area from all three surfaces, assuming that each surface composition remains constant across every pitch size. Comparison of the signal intensity per unit area indicates amount of sidewall passivation w.r.t trench bottom. As an additional verification to the methodology and electron shadowing, parallel angle resolved XPS (pAR-XPS) have been carried out at the same structure to find out the variation in sidewall contributions with different angles. Observation: Recipe_1 is highly passivating (C4F8 presence) but directional (high Ar content), therefore shows less deposition of FC layer on the sidewalls compared to line top and trench bottom, shown by the least F1s F-C and C1s C-Fx (x=1:3) intensity but high FC layer deposition on flat surfaces with remaining photoresist adding more carbon and nitrogen to line top than trench bottom (Fig.1c).Recipe_2 shows lower passivation (CHF3 presence) and anisotropy (No Ar) than Recipe_1, therefore lower carbon is seen on line top and trench bottom compared to Recipe_1, but a thicker FC layer on sidewalls. In both the recipes sidewalls and trench bottom shows similar level of Si2p Si-O and O1s O-Si signal intensities but only differ in their FC layer buildup due to different plasma chemistry. Line top with higher carbon content has lesser intensity of Si2p Si-O and O1s O-Si than the other with thinner FC layer buildup. Conclusion: The results confirm that the physical model is capable of separating the signal intensities from the three surfaces through which the FC layer on each surfaces have been accurately predicted. Therefore the normal mode XPS technique can be utilized to gain insight into the chemical composition of sidewalls. Acknowledgement: This work was funded via subcontract from Globalfoundries Dresden within the framework Important Project of Common European Interest (IPCEI) by the Federal Ministry for Economics and Energy and by the State of Saxony.

Machine learning virtual SEM metrology and SEM-based OPC model methodology

Background: E-beam metrologies, both critical dimension scanning electron microscope metrology and defect scan metrology, have been playing a very critical role in gating patterning quality. SEM images can provide rich visual information for engineers to do qualitative and quantitative analyses. However, the low e-beam metrology tool throughput makes it impossible to obtain SEM images for larger area. Monte Carlo-based SEM image simulations or other SEM image simulations require postlithography or postetch pattern three-dimensional structures as prerequisite, and the simulation speed is not sufficiently fast for full chip implementation. Aim: We aim to develop machine learning SEM models with sufficient accuracy and speed for full chip application in semiconductor manufacturing environment. Approach: We have proposed a virtual SEM metrology solution based on U-Net neural network with physics-based feature maps as model input. With information in aerial image space encoded properly, SEM images of both postlithography and postetch can be predicted accurately enough for practical applications using our proposed virtual SEM metrology models. Equipped with GPUs, the machine learning-based SEM image models are fast enough to make it possible to realize full chip SEM generation from post-OPC data. Results: Our machine learning SEM image models can predict SEM images with normalized cross correlation around 0.95 in reference to ground truth SEM images, each SEM image (512 × 512 in size) takes about 800 ms using single CPU, and the speed can be accelerated to about 10 ms with single GPU. Conclusions: Using U-Net structure and physics-based feature maps as model inputs, machine learning-based SEM image models can be developed. The models are sufficiently accurate and fast to find their applications in semiconductor manufacturing, and they can be used as independent model for OPC data verification or generate SEM images as reference for SEM defect scan metrology.

Critical-dimension scanning electron microscope characterization of smoothly varying wave structures with a Monte Carlo simulation

Scanning electron microscopy (SEM) characterization of a smoothly varying nanograting structure (a Pt-coated Cr grid on a Si substrate) with a sinusoidal waveform has been carried out by a Monte Carlo (MC) simulation technique. Previous studies with critical-dimension (CD) SEM (CD-SEM) have mostly concerned line structures with sharp edges so that there is an obvious edge bloom in the linescan profile of secondary electrons. In contrast, the present grating structures prepared by a laser-focused atomic deposition technique have a smoothly varying waveform in the cross-sectional profile, which pose greater difficulty for quantitative structural characterization by SEM. The grating structure, with a fixed pitch of λ/2 as the period of the standing-wave laser light field, where λ is the wavelength of the corresponding laser light, can be used as an ideal nanoscale metrological length tool; therefore, it is important to characterize its structural features over a large deposited area by SEM imaging for quality control, with the aim of mass reproduction. The present work extends the CD characterization of MC simulation methods to more complex structures. Taking into account different experimental factors, i.e. primary electron beam parameters, geometrical parameters and material properties, the unknown geometrical parameters (i.e. base height, peak height, linewidth shrinkage and peak tilt angle) of the grating lines have been successfully extracted from the experimental linescan profiles of SEM images.

Understanding the influence of three-dimensional sidewall roughness on observed line-edge roughness in scanning electron microscopy images

Background: Line-edge roughness (LER) is often measured from top-down critical dimension scanning electron microscope (CD-SEM) images. The true three-dimensional roughness profile of the sidewall is typically ignored in such analyses. Aim: We study the response of a CD-SEM to sidewall roughness (SWR) by simulation. Approach: We generate random rough lines and spaces, where the SWR is modeled by a known power spectral density. We then obtain corresponding CD-SEM images using a Monte Carlo electron scattering simulator. We find the measured LER from these images and compare it to the known input roughness. Results: For isolated lines, the SEM measures the outermost extrusion of the rough sidewall. The result is that the measured LER is up to a factor of 2 less than the true on-wafer roughness. The effect can be modeled by making a top-down projection of the rough edge. Our model for isolated lines works fairly well for a dense grating of lines and spaces as long as the trench width exceeds the line height. Conclusions: In order to obtain and compare accurate LER values, the projection effect of SWR needs to be taken into account.

High-voltage CD-SEM-based application to monitor 3D profile of high-aspect-ratio features

Background: In-line metrology for three-dimensional (3D) profiling high-aspect-ratio (HAR) features is highly important for manufacturing semiconductor devices, particularly for memory devices, such as 3D NAND and DRAM. Aim: Our purpose was to obtain the cross-sectional profiles of the HAR features from top-view critical dimension scanning electron microscopy (CD-SEM) images. Approach: Based on Monte Carlo simulation results, we proposed a method for 3D profiling of HAR features using backscattered electron (BSE) signal intensities. Several kinds of HAR holes with different taper angles and bowing geometries were fabricated. High-voltage CD-SEM was used for experiments to determine the feasibility of our approach. Results: Using the BSE line-profile, we constructed cross sections of the taper holes and estimated sidewall angles (SWAs), which were approximately the same as those observed using field-emission scanning electron microscopy (FE-SEM). The constructed cross sections of the bowing holes and the trends of the geometric variance, which were estimated by the middle CD and its depth, were consistent with the cross sections observed by FE-SEM. Conclusions: The results demonstrate that the variation in the HAR holes, such as SWA and bowing geometry, can be measured and monitored using the BSE images.

Surface effects in simulations of scanning electron microscopy images

Background: Monte Carlo simulations of scanning electron microscopy (SEM) images ignore most surface effects, such as surface plasmons. Previous experiments have shown that surface plasmons play an important role in the emission of secondary electrons (SEs). Aim: We investigate the influence of incorporating surface plasmons into simulations of low-voltage critical dimension SEM (CD-SEM). Approach: We use a modified inelastic scattering model, derived for infinite flat surfaces, and apply it to nonflat, but smooth, geometries. This simplification captures most qualitative effects, including both surface plasmons and a reduced interaction with bulk plasmons near interfaces. Results: We find that the SE signal hardly changes when surface interactions are turned on for a perpendicularly incident beam. When the incident beam is perfectly parallel to a surface, the SE signal does significantly increase. However, the beam must be extremely close to the surface for this effect to be appreciable. An SEM is unable to produce a beam that is both narrow and parallel enough to be noticeably affected. Conclusions: The position of edges may appear shifted under specific circumstances. In realistic situations, it is unlikely to be a large effect.

Development of standard samples with programmed defects for evaluation of pattern inspection tools for 7-nm and smaller nodes

Background: Continued shrinkage of pattern size has caused difficulties in detecting small defects. Multibeam scanning electron microscopy (SEM) is a potential method for pattern inspection below 7-nm node. Performance of the tool depends on charge control, resolution, and defect detection capability. Aim: The goal of this study is to develop a method for evaluating the performance of multibeam SEM for 7-nm nodes. Approach: By developing various standard samples with programmed defects (PDs) on 12 in. Si wafer, we evaluate the performance of multibeam SEM. Results: The first wafer had line and space (LS) patterns and PDs with varying contrast. A second wafer had various shaped small PDs, ∼5 nm in size in 16- to 12-nm half-pitch LS patterns. A third wafer with extremely small PDs of around 1 nm was fabricated in LS patterns with ultralow line-edge roughness (LER) of less than 1 nm. The first wafer was effective for charge control, whereas second and third wafer confirms resolution and defect detection capability. Conclusions: A set of minimum three standard wafer samples is effective to confirm the performance of multibeam SEM for below 7-nm nodes. Besides, we proposed a method to verify the LER values measured by a critical-dimension SEM.

Tilted beam scanning electron microscopy, 3-D metrology for microelectronics industry

In the microelectronics industry, most of the dimensional metrology relies on critical dimension (CD) estimation. These measurements are mainly performed by critical dimension scanning electron microscopy, because it is a very fast, mainly nondestructive method and enables direct measurements on wafers. To measure CDs, the distance is estimated between the edges of the observed pattern on an SEM image. As the CD becomes smaller and smaller, the needs for more reliable metrology techniques emerge. In order to obtain more meaningful and reproducible CD measurements regardless of the pattern type (line, space, contact, hole, etc.), one needs to perform a CD measurement at a known and constant height due to a methodology that determines the topographic shape of the pattern from SEM images. An SEM capable of bending the electron beam (up to 12 deg in our case) allows images to be caught at different angles, giving access to more information. From the analysis of such images, pattern height and sidewall angles can be determined using geometric considerations. Understanding interaction between three-dimensional (3-D) shapes, pattern materials, and the electron beam becomes essential to correlate topography information. A preliminary work based on Monte–Carlo simulations was conducted using JMONSEL, a software developed by the National Institute of Standards and Technology. With this analysis, it is possible to determine theoretical trends for different topographies and beam tilt conditions. Due to the effects highlighted by simulations, the processing of the tilted beam SEM images will be presented, as well as the method used to create a mathematical model allowing topographic reconstruction from these images. Finally some reconstruction using this model will be shown and compared to reference measurements. The overall flow used to process images is presented. First, images are transformed into grayscale profiles. After a smoothing procedure, positional descriptors are computed for specific profile derivatives values. Then, from these descriptors coming from two images of the same pattern taken at different tilt angles, we use a low-complexity linear model in order to obtain the geometrical parameters of the structure. This model is created and initially calibrated using JMONSEL simulations and then recalibrated on real silicon patterns. We demonstrate that the use of real SEM images coming from real silicon patterns with our model leads to results that are coherent with conventional 3-D measurements techniques taken as reference. Moreover, we are able to make reliable reconstructions on patterns of various heights with a single calibrated model. Our batch of experiment shows a three-sigma standard deviation of 10 nm on the estimated height for heights ranging from 50 nm to more than 200 nm. Based on simulations, we are able to reconstruct the corner rounding (CR) from SEM images. However, because our wafer has no CR variability, measurements still need to be assessed on real wafer.

Review of scanning electron microscope-based overlay measurement beyond 3-nm node device

Overlay control has been one of the most critical issues for manufacturing of leading edge semiconductor devices. Introduction of the double patterning process requires stringent overlay control. Conventional optical overlay (Opt-OL) metrology has technical challenges with measurement robustness, solving overlay discrepancy between overlay mark and device pattern, and measuring smaller marks laid out in large numbers within the die accurately for high-order correction. In contrast, scanning electron microscope-based overlay (SEM-OL) metrology can directly measure both overlay targets and actual devices or device-like structures on processed wafers with high spatial resolution. It can be used for reference metrology and optimization of Opt-OL measurement conditions. SEM-OL uses small structures, including actual device patterns, which allows insertion of many SEM-OL targets across a die. Precise overlay distribution can be measured using dedicated SEM-OL mark, improving measurement accuracy and repeatability. To extend SEM-OL capability, we have been developing SEM-OL techniques that can measure not only surface patterns by critical dimension SEM but also buried patterns for leading edge device processes. There are two techniques to detect buried patterns. One is to use high-acceleration voltage SEM, which detects backscattering electron emphasizing material contrast. It has been adopted for overlay measurements for memory and logic devices at after-etch inspection or even after-develop inspection. The other is to utilize charging effect, which reflects voltage contrast at the surface depending on the material properties of underneath structure. SEM-OL measurement using transient voltage contrast has been developed and its capability of overlay measurement has been proven. An overlay measurement algorithm using template matching method has been developed and was applied to dynamic random access memory (DRAM) process monitor in manufacturing. In order to extend SEM-OL metrology to beyond 3-nm node logic and cutting-edge DRAM devices (half pitch = 14 nm), we are improving measurement precision of detecting buried patterns and measurement throughput by developing optimized SEM-OL mark.

Process optimization of selective wet etching for fabrication of high-aspect-ratio and uniform multilayer grating reference materials

Background: The multilayer gratings are considered as the potential length-standard-traceable lateral scales for calibrating the next-generation critical dimension scanning electron microscope (CD-SEM) magnification. As a key step in the fabrication of multilayer gratings, selective wet etching determines the final grating structure formation. However, the effects of the etching process parameters on the multilayer gratings in several nanometer scales have not been reported in detail. Aim: By optimizing the process of selective wet etching, we should fabricate high-aspect-ratio and uniform multilayer gratings to obtain high-contrast secondary electron signals and stable secondary electron images while also obtaining measurement accuracy from the small line edge roughness. Approach: Based on the analysis of the important factors in the etching process and SEM and TEM measurement results, we evaluate the effects of ultrasonic agitation, HF acid concentration, etch time, and linewidth scale on the aspect-ratio and uniform of multilayer gratings. Results: We recommend to etching the multilayer films with an HF acid concentration of about 2% during the ultrasonic agitation for uniformity. Moreover, selective wet etching reaction is limited by scale when the linewidth is below 20 nm. Despite the fact that the grating structure is fragile and easy to be broken down, for linewidths of about 10 and 5 nm, the aspect ratio of multilayer gratings can reach about 3 and 2, respectively. Conclusions: By focusing on the optimum conditions of ultrasonic agitation, HF acid concentration, and linewidth scale in the selective wet etching, selective wet etching can be used to fabricate high-aspect-ratio and uniform multilayer gratings with linewidth below 20 nm.

Linewidth roughness of advanced semiconductor features using focused ion beam and planar-transmission electron microscope as reference metrology

Line edge roughness (LER) and linewidth roughness (LWR) of a semiconductor device are important measures for evaluating its performance. Conventionally, LER and LWR have been evaluated from critical dimension scanning electron microscope (CD-SEM) images. However, the problem with CD-SEM measurement is that the high-frequency image noise is large, and the resolution is not sufficiently high. In order to overcome the problem of image noise in CD-SEM measurement, some techniques have been proposed. In these methods, it is necessary to set the parameters for the model and processing, and it is required to verify the correctness of these parameters using reference metrology. We have already proposed a reference metrology using the focused ion beam process and planar transmission electron microscope (planar-TEM) method. In this study, we apply the proposed method to three new samples, namely self-aligned quadruple patterning fin-shaped field-effect transistor device, extreme ultraviolet lithography (EUV) conventional resist, and EUV new material resist. The LWR and the power spectral density (PSD) of LWR are calculated from the edge positions on planar-TEM images. We confirm that the LWR and the PSD of LWR can be measured with high accuracy and evaluate the difference between PSD by the proposed method and that by CD-SEM images. Furthermore, from comparisons with the PSD of the same sample obtained using CD-SEM, the validity of measurement of PSD and LWR by CD-SEM is verified.