For the most advanced nodes, line roughness reaches the same order of magnitude as the CD. It results in a huge impact on power consumptions and leads to some device failures. Hence, the control of this morphological aspect needs an adapted metrology. CD-SEM is considered as an adapted technique for roughness extraction. It is based on the PSD extraction that allows to obtain roughness information in frequency domain. CD-SAXS has been mentioned as one of the highest potential techniques for microelectronics by ITRS with an expected resolution better than one angstrom. The study presented in this article is based on programmed roughness simulations and first experimental measurements. It demonstrates that a complete PSD can also be extracted from a CD-SAXS analysis and that extended information of roughness can be so deduced. Comparison of SEM and SAXS proves the capability of SAXS technique for the PSD extraction of line roughness. Next challenges to improve this extraction are mentioned.
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 (CD-SEM), because it is a very fast, mainly non-destructive method, and enables direct measurements on wafers. To measure CDs, the distance is estimated between the edges of the observed pattern on a SEM image. As the critical dimension becomes smaller and smaller, the needs for more reliable metrology techniques emerge.<p> </p> In order to obtain more meaningful and reproducible CD measurements regardless of the pattern type (line, space, contact, hole . . . ), one needs to perform a CD measurement at a known and constant height thanks to a methodology that determines the topographic shape of the pattern from SEM images. A SEM capable of bending the electron beam (up to 12° in our case) allows to catch images at different angles, giving access to more information. From the analysis of such images, pattern height and sidewall angles can be consequently determined using geometric considerations.<sup>1 </sup><p> </p>Understanding interactions between 3D shapes, pattern's material 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 NIST. <p> </p>Thanks to this analysis, it is possible to determine theoretical trends for different topographies and beam tilt conditions. Thanks 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 compare to reference measurements.<p> </p> The overall flow used to process images is presented. First, images are transformed into grayscale profiles in order to process them. 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 calibrated thanks to JMONSEL simulations and then re-calibrated on real silicon patterns. <p> </p>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 3D 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 3-sigma standard deviation of 13% on the estimated height. <p> </p>We also show, thanks to simulations, that we are able to reconstruct the corners rounding (CR) from SEM images. However, because our wafer do not present a variability, the CR measurements still need to be assessed.
Currently, Line Edge Roughness (LER) and Line Width Roughness (LWR) control presents a huge challenge for the lithography step in microelectronic industries. For advanced nodes, this morphological aspect reaches the same order of magnitude than the Critical Dimension, which leads to an increased power consumption by transistors and devices. Hence, the control of roughness needs an adapted metrology. This study proposes to manufacture roughness standard samples and their validation. These samples can be used as standards to evaluate the capabilities of several tools. The preliminary part of this study has been carried out with periodical roughness sample to demonstrate the metrology approach. Further, programming of roughness based on Power Spectral Density (PSD) with Auto-Correlation Function (ACF) model is used to achieve roughness close to the real roughness case. A description of how design programmed roughness has been made and its exposition in the real conditions are detailed in this study. Moreover, a specific methodology of control has been developed, the results obtained have been compared with design inputs and mostly validated by experimental processes. This work represents the first step of manufacturing roughness standard samples based on PSD model design.
At modern manufacturing geometries, roughness control presents a huge challenge for the lithography step. For advanced nodes, this morphological aspect reaches the same order of magnitude as the critical dimension (CD). Hence, the control of roughness needs an adapted metrology. Specific samples with designed roughness have been manufactured using e-beam lithography. These samples have been characterized with three different methodologies: CD-scanning electron microscopy, optical critical dimension, and small angle x-ray scattering. The main goal is to compare the capability of each of these techniques in terms of reliability, type of information obtained, time to obtain the measurements, and level of maturity for the industry. The next step will be to develop a hybrid metrology approach for roughness determination with these techniques.
From the first digital cameras which appeared during the 70s to cameras of current smartphones, image sensors have undergone significant technological development in the last decades. The development of CMOS image sensor technologies in the 90s has been the main driver of the recent progresses. The main component of an image sensor is the pixel. A pixel contains a photodiode connected to transistors but only the photodiode area is light sensitive. This results in a significant loss of efficiency. To solve this issue, microlenses are used to focus the incident light on the photodiode. A microlens array is made out of a transparent material and has a spherical cap shape. To obtain this spherical shape, a lithography process is performed to generate resist blocks which are then annealed above their glass transition temperature (reflow). <p> </p>Even if the dimensions to consider are higher than in advanced IC nodes, microlenses are sensitive to process variability during lithography and reflow. A good control of the microlens dimensions is key to optimize the process and thus the performance of the final product. <p> </p>The purpose of this paper is to apply SEM contour metrology [1, 2, 3, 4] to microlenses in order to develop a relevant monitoring methodology and to propose new metrics to engineers to evaluate their process or optimize the design of the microlens arrays.
Nowadays, roughness control presents a huge challenge for the lithography step. For advanced nodes, this morphological aspect reaches the same order of magnitude than the Critical Dimension. Hence, the control of roughness needs an adapted metrology. In this study, specific samples with designed roughness have been manufactured using e-beam lithography. These samples have been characterized with three different methodologies: CD-SEM, OCD and SAXS. The main goal of the project is to compare the capability of each of these techniques in terms of reliability, type of information obtained, time to obtain the measurements and level of maturity for the industry.
Today’s technology nodes contain more and more complex designs bringing increasing challenges to chip manufacturing process steps. It is necessary to have an efficient metrology to assess process variability of these complex patterns and thus extract relevant data to generate process aware design rules and to improve OPC models. Today process variability is mostly addressed through the analysis of in-line monitoring features which are often designed to support robust measurements and as a consequence are not always very representative of critical design rules. CD-SEM is the main CD metrology technique used in chip manufacturing process but it is challenged when it comes to measure metrics like tip to tip, tip to line, areas or necking in high quantity and with robustness. CD-SEM images contain a lot of information that is not always used in metrology. Suppliers have provided tools that allow engineers to extract the SEM contours of their features and to convert them into a GDS. Contours can be seen as the signature of the shape as it contains all the dimensional data. Thus the methodology is to use the CD-SEM to take high quality images then generate SEM contours and create a data base out of them. Contours are used to feed an offline metrology tool that will process them to extract different metrics. It was shown in two previous papers that it is possible to perform complex measurements on hotspots at different process steps (lithography, etch, copper CMP) by using SEM contours with an in-house offline metrology tool. In the current paper, the methodology presented previously will be expanded to improve its robustness and combined with the use of phylogeny to classify the SEM images according to their geometrical proximities.
Today’s CD-SEM metrology is challenged when it comes to measuring complex features found in patterning hotspots (like tip to tip, tip to side, necking and bridging). Metrology analysis tools allow us to extract SEM contours of a feature and convert them into a GDS format from which dimensional data can be extracted. While the CD-SEM is being used to take images, the actual measurement and the choice of what needs to be measured is done offline. Most of the time this method is used for OPC model creation but barely for process variability analysis at nominal process conditions. We showed in a previous paper  that it is possible to study lithography to etch transfer behavior of a hotspot using SEM contours. The goal of the current paper is to go extend this methodology to quantify process variability of 2D features using a new tooling to measure contour data.
Critical dimension and overlay measurements have become a key challenge in microelectronics process control, and the weight of metrology in the success of a patterning technique is increasing. For the 14 nm node, the limit of scanner resolution can be overcome by double patterning, which requires a maximum overlay variability of 3 nm between the two reticles of the first metal level. In the double patterning case of metal layers, critical dimension of line spaces and overlay are no longer independent. In this paper, the possibility of a common measurement after the second lithography is studied. Scatterometry has been used to fit successfully the critical dimension of the two sublevels. As sensitivity to overlay is too low in device-like target, a strategy has been implemented from diffraction-based overlay measurement. So it becomes possible to provide information on the lithography step quality before the second etch process to enable rework if necessary. Finally a scatterometry target has been designed to fit simultaneously the two critical dimensions and overlay. This target, which is designed to maximize overlay sensitivity, has been placed in the next 14 nm CMOS product and is expected to make this scatterometry method even more attractive.
In microelectronics the two crucial parameters for the lithography step are the critical dimension, which is the width of the smallest printable pattern, and the misalignment error of the reticle, called overlay. For the 14 nm node, the limit of scanner resolution can be overcome by the double patterning technique, which requires a maximum overlay error between the two reticles of 3 nm <sup></sup>. The current approach in the measurements of critical dimension and overlay is to treat them separately, but it has become much more complex in the double patterning context, since they are no longer independent. In this paper, a strategy of a common measurement is developed. The aim of the strategy is to measure simultaneously overlay and critical dimension in the metal level double patterning grating before the second etch process. The scatterometry technique is well known for critical dimension measurement. This study demonstrates that the overlay between the two gratings can also be deduced. Thanks to this original scatterometry-based method, it becomes possible to provide information on the lithography step quality before the second etch process; therefore the lithography can be reworked if it is necessary.
The objective of this paper is to extend the ability of a more stable overall process control for the 28 nm Metal layer. A method to better control complex 2D-layout structures for this node is described. Challenges are coming from the fact that the structures, which limit the process window are mainly of 2D routing nature and are difficult to monitor. Within the framework of this study the emphasis is on how to predict these process-window-limiting structures upfront, to identify root causes and to assist in easier monitoring solutions enhancing the process control. To address those challenges, the first step is the construction of a reliable Mask-3D and Resist-3D model. Advanced 3Dmodeling allows better prediction of process variation upfront. Furthermore it allows highlighting critical structures impacted by either best-focus shifts or by low-contrast resist-imaging effects, which then will be transferred non-linearly after etch. This paper has a tight attention on measuring the 3D nature of the resist profiles by multiple experimental techniques such as Cross-section scanning electron microscopy methods (X-SEM) and atomic force microscopy (AFM). Based on these measurements the most reliable data are selected to calibrate full-chip Resist-3D model with. Current results show efficient profile matching among the calibrated R3D model, wafer AFM and X-SEM measurements. In parallel this study enables the application of a new metric as result of the resist profiles behavior in function of exposure dose. In addition it renders the importance on the resist shape. Together these items are reflected to be efficient support on process optimization and improvement on the process control.
S-Genius is a new universal scatterometry platform, which gathers all the LTM-CNRS know-how regarding the rigorous
electromagnetic computation and several inverse problem solver solutions. This software platform is built to be a userfriendly,
light, swift, accurate, user-oriented scatterometry tool, compatible with any ellipsometric measurements to fit
and any types of pattern. It aims to combine a set of inverse problem solver capabilities — via adapted Levenberg-
Marquard optimization, Kriging, Neural Network solutions — that greatly improve the reliability and the velocity of the
solution determination. Furthermore, as the model solution is mainly vulnerable to materials optical properties, S-Genius
may be coupled with an innovative material refractive indices determination. This paper will a little bit more focuses on
the modified Levenberg-Marquardt optimization, one of the indirect method solver built up in parallel with the total SGenius
software coding by yours truly. This modified Levenberg-Marquardt optimization corresponds to a Newton
algorithm with an adapted damping parameter regarding the definition domains of the optimized parameters.
Currently, S-Genius is technically ready for scientific collaboration, python-powered, multi-platform
(windows/linux/macOS), multi-core, ready for 2D- (infinite features along the direction perpendicular to the incident
plane), conical, and 3D-features computation, compatible with all kinds of input data from any possible ellipsometers
(angle or wavelength resolved) or reflectometers, and widely used in our laboratory for resist trimming studies, etching
features characterization (such as complex stack) or nano-imprint lithography measurements for instance. The work
about kriging solver, neural network solver and material refractive indices determination is done (or about to) by other
LTM members and about to be integrated on S-Genius platform.
The aim of this paper is to present a new method of in-line determination of etching tool parameters deviation during the
transistor fabrication. For that, we study the possibility to use an optical metrology technique, the scatterometry, and its
capability to determine quickly and accurately the temporal evolution of geometric dimensions of a periodic pattern. In
this case, this optical tool can be considered as an external monitoring probe. The experiments developed in this article are based on a DOE where 20 different experiments are made, followed both by scatterometric measurements and internal etching tool probes. Comparing the two outputs, we determine the correlations between the evolution of the geometrical parameters of the pattern and the fluctuation of the internal tool parameters. We conclude that the use of a scatterometer following the evolution of the geometrical parameters of a pattern during an etching process is also a good tool to in-line anticipate the drift of the etching parameters.
The low-k1 domain of immersion lithography tends to result in much smaller depths of focus (DoF) compared to prior technology nodes. For 28 nm technology and beyond it is a challenge since (metal) layers have to deal with a wide range of structures. Beside the high variety of features, the reticle induced (mask 3D) effects became non-negligible. These mask 3D effects lead to best focus shift. In order to enhance the overlapping DoF, so called usable DoF (uDoF), alignment of each individual features best focus is required. So means the mitigation of the best focus shift. This study investigates the impact of mask 3D effects and the ability to correct the wavefront in order to extend the uDoF. The generation of the wavefront correction map is possible by using computational lithographic such Tachyon simulations software (from Brion). And inside the scanner the wavefront optimization is feasible by applying a projection lens modulator, FlexWave<sup>TM</sup> (by ASML). This study explores both the computational lithography and scanner wavefront correction capabilities. In the first part of this work, simulations are conducted based on the determination and mitigation of best focus shift (coming from mask 3D effects) so as to improve the uDoF. In order to validate the feasibility of best focus shift decrease by wavefront tuning and mitigation results, the wavefront optimization provided correction maps are introduced into a rigorous simulator. Finally these results on best focus shift and uDoF are compared to wafers exposed using FlexWave then measured by scanning electron microscopy (SEM).
To print sub 22nm node features, current lithography technology faces some tool limitations. One
possible solution to overcome these problems is to use the double patterning technique (DPT). The
principle of the double patterning technique is pitch splitting where two adjacent features must be
assigned opposite masks (colors) corresponding to different exposures if their pitch is less than a
predefined minimum coloring pitch. However, certain design orientations for which pattern features
separated by more than the minimum coloring pitch cannot be imaged with either of the two exposures.
In these directions, the contrast and the process window are degraded because constructive
interferences between diffractive orders in the pupil plane are not sufficient. The 22nm and 16nm nodes
require the use of very coherent sources that will be generated using SMO (source mask cooptimization).
Such pixelized sources while helpful in improving the contrast for selected
configurations, can lead to degrade it for configurations which have not been counted for during the
SMO process. Therefore, we analyze the diffractive orders interactions in the pupil plane in order to
detect these limited orientations in the design and thus propose a new double patterning decomposition
algorithm to enlarge the process window and the contrast of each mask.
In double patterning technology (DPT), two adjacent features must be assigned opposite colors,
corresponding to different exposures if their pitch is less than a predefined minimum coloring pitch.
However, certain design orientations for which pattern features separated by more than the minimum
coloring pitch cannot be imaged with either of the two exposures. In such cases, there are no aerial
images formed because in these directions there are no constructive interferences between diffractive
orders in the pupil plane. The 22nm and 16nm nodes require the use of pixelized sources that will be
generated using SMO (source mask co-optimization). Such pixelized sources while helpful in
improving the contrast for selected configurations can lead to degraded contrast for configurations
which have not been set during the SMO process. Therefore, we analyze the diffractive orders
interactions in the pupil plane in order to detect limited orientations in the design and thus propose a
decomposition to overcome the problem.
The challenge of the Integrated Circuit size reducing leads to the development of new processes for future years. In the
lithography domain, since several years, the EUV Lithography appears as a possible technique to reach the ITRS
roadmap requirements. The EUV interferometry Lithography is still nowadays an efficient way to study and improve the
EUV resist behaviors. Although the interferometer principle seems to be obvious, the optimization of its use is only
reached regarding some huge constraints. In this work accurate numerical models and experimental studies have been
developped. It shows that some undesirable effects can reduce the interference region and disturb the contrast of the
resist printed lines. The EUV light is identified as the first issue. The beam divergence of EUV light affects the contrast
quality of the fringes. The photometry computation, taking into account the optimum angular source light width is then
detailed. The second cause is the Fresnel diffraction of light due to boundaries of the grating windows. Its
superimposition with diffraction orders induces a damage of local printed interferences. This phenomenon leads to an edge disturbance of the interference fringes. The third cause addressed is the decrease of the interference area by the position of the wafer out of the focal distance. Possible shadowing effects are also shown.
Double patterning (DP) is one of the main options to print devices with half pitch less than 45nm. The basis of DP is to
decompose a design into two masks. In this work we focus on the decomposition of the contact pattern layer. Contacts
with pitch less than a split pitch are assigned to opposite masks corresponding to different exposures. However, there
exist contact pattern configurations for which features can not be assigned to opposite masks. Such contacts are flagged
as color conflicts. With the help of design of manufacturing (DFM), the contact conflicts can be reduced through
redesign. However, even the state of the art DFM redesign solution will be limited by area constraints and will introduce
delays to the design flow. In this paper, we propose an optical method for contact conflicts treatment. We study the
impact of the split on imaging by comparing inverse lithography technology (ILT), optical proximity correction (OPC)
and source mask co-optimization (SMO) techniques. The ability of these methods to solve some split contacts conflicts
in double patterning are presented.
In-line process control in microelectronics manufacturing requires real-time and non-invasive monitoring techniques. Among the different metrology techniques, scatterometry, based on the analysis of ellipsometric signatures of the light scattered by a patterned structures, is well adapted. Traditionally, the problem of defining the shape and computing the signature is dealt with modal methods and is called <i>direct problem.</i> On the opposite, the <i>inverse problem</i> allows to find the grating shape thanks to an experimental signature acquisition, and can not be solved as easily. Different classes of algorithms have been introduced (evolutionary, simplex, etc.) to address this problem, but the method of library searching seems to be the most attractive technique for industry. This technique has many advantages that will be presented in this article. However the main limitation in real-time context comes from the short data acquisition time for different wavelengths. Indeed, the lack of data leads to the method failure and several database patterns can match the experimental data.
In this article, a technique for real time reconstruction of grating shape variation using dynamic scatterometry is presented. The different tools to realize this reconstruction, such as Modal Method by Fourier Expansion, regularization technique and specific software and hardware architectures are then introduced. Results issued from dynamic experiments will finally illustrate this paper.
In-line process control in microelectronics manufacturing requires real-time and non-invasive monitoring techniques.
Among the different metrology techniques, scatterometry, based on the analysis of ellipsometric signatures (i.e stokes coefficients vs. wavelength) of the light scattered by a patterned structures, seems to be well adapted.
Traditionally, the problem of defining the shape and computing the signature is dealt with modal methods and is called direct problem. On the opposite, the inverse problem allows to find the grating shape thanks to an experimental signature acquisition, and can not be solved as easily. Different classes of algorithms have been introduced (evolutionary, simplex, etc.) to address this problem, but the method of library searching seems to be the most attractive technique for industry. This technique has many advantages that will be presented in this article, however the main limitation in real-time context comes from the short data acquisition time for
different wavelengths. Indeed, the lack of data leads to the method failure and several database patterns can match the experimental data. In this article, a technique for real time reconstruction of grating shape variation using dynamic scatterometry is presented. The different tools to realize this reconstruction, such as Modal
Method by Fourier Expansion, regularization technique and specific software and hardware architectures are then introduced. Results issued from dynamic experiments will finally illustrate this paper.
In Extreme Ultraviolet Lithography, the electromagnetic modelling of the mask allows determining the influence of the mask structure on the electromagnetic field. That makes it possible to take into account the presence of a defect modifying the multi-layer stack<sup>1,2</sup>. The method used throughout this paper is the MMFE (Modal Method by Fourier Expansion) also known as the RCWA (Rigorous Coupled Wave Analysis). Modal methods allow computing the electromagnetic field just above the EUV mask or the near field. Modal methods are well adapted for EUV mask simulation due to materials and structure size. The previous works performed on 2D simulation with MMFE<sup>3</sup> have shown the influence of a defect inside a EUV mask structure. In this article, the method is extended to address 3D structures. The printability of a spherical shaped defect is analyzed depending on the deposition process used. The influence of a 3D defect position regarding the position of a line absorber is also shown.
In Extreme Ultraviolet Lithography, the electromagnetic modeling of the mask allows to determine the influence of the mask structure on the electromagnetic field. That makes it possible to take into account the presence of a defect modifying the multi-layer stack . This paper presents the results of simulations, performed using a modal method, on the aerial image of the reflected intensity above the resist depending on the position of a defect with respect to an absorber pattern. These simulations allow to consider the influence of a defect not only on top of the structure but also everywhere inside the multilayer. The current method is the MMFE: Modal Method by Fourier Expansion. Modal methods are well adapted for EUV simulation mask due to materials and structure size.
In Extreme Ultraviolet Lithography, the electromagnetic modeling of the mask allows to determine the influence of the mask structure on the electromagnetic field and on the aerial image. It is very useful to study the effect of the shape absorber on the CD shift. This effect, called shadowing effect, is analyzed in this paper. A simple geometrical approach to address this phenomenon is presented first. It is shown that although it can qualitatively be drawn some first orders conclusions, this over simplified view is unable to explain the complex behavior of the reflected light field. A rigorous method is still the more adapted method to assess the influence of the geometrical parameters of the features on the mask to control the CD shift on the printed resist. This study is especially focused on the absorber edges slope. It is demonstrated the choice of edge angles can minimize CD shift or keep a constant CD width.
Because the capabilities for experimental studies are still limited, a predictive simulation of EUV lithography is very important for a better understanding of the technology. One of the most critical issues in EUV lithography modeling is the description of the mask, especially including multilayer defects. A new model for the characterization of defects in the multilayer of an EUV reflective mask is presented. The mask is divided into an absorber part, which defines the features on the mask, and a multilayer part, which determines the reflectivity of the mask without absorber. Since the height of the mask features is large in comparison to the illumination wavelength, the computation of the absorber part is performed by a finite-difference time-domain (FDTD) method. Because of the limited range of illumination angles with a high reflectivity and the limited diffraction efficiency of the multilayer, the computation of the reflectivity of the defective multilayer is performed by the Fresnel-method. The defect topography is taken into account by means of correcting the phase and the angle of incidence. For the complete computation of the reflected light from the EUV mask a coupling of the two methods is realized. Thus, the model can be applied to two and three dimensional defects and masks. The impact of the defects on the mask reflectivity, the near field and the aerial image is analyzed. Typical mask structures, such as 2D-lines and 3D-dots with various defects, are investigated. First comparisons with another simulation model, the MMFE method, are presented.
Lithography modeling is a very attractive way to predict the critical dimensions of patterned features after lithographic processing. In a previous paper, we have presented the assessment of three different simplified resist models (aerial image model, aerial image convolved with fixed gaussian noise and aerial image convolved with variable gaussian noise) by using a systematic comparison between experimental and simulated data. It has been shown that the aerial image convolved with fixed gaussian noise, or "diffused aerial image model" (DAIM), exhibits surprisingly good results of CD prediction for lines @ 193nm. Using these datasets, the DAIM appeared as an accurate model for CD prediction. This approach allows also an easy run, and because it needs only four adjustable parameters, it avoids the difficult task of resist parameters extraction associated to full resist models.
In this paper, we enlarge the datasets used for the assessment of the DAIM by considering both lines and contact holes of various sizes printed at different wavelengths. The reference wafers have been printed at 248nm, 193nm and 157 nm. The procedure used to extract the model parameters has been improved and now needs less data to provide acceptable values. We will show that the validity of the DAIM extends well outside the results presented in Ref. 1. Experimental data printed using various wavelengths, resists and exposure tools can be simulated accurately with CD prediction error ranging within few percents. It is to be noted that the results that will be presented on contact holes data indicate that the model is valid for 2D features. Finally, a comparison with full resist models shows that the accuracy of DAIM is comparable to more sophisticated and heavier models.
In Extreme Ultraviolet lithography, the electromagnetic modeling of the mask allows to determine the influence of the mask structure on the electromagnetic field. That makes it possible for example to analyze the influence of a defect within the multi-layer stack. This paper describes a modeling method of the EUV mask based on the Rayleigh assumptions1. These hypotheses lead to a more restrictive validity domain than rigorous methods like modal methods or Finite Difference Time Domain (FDTD), but is shown in this paper to be usable adapted for EUV mask simulation. Furthermore the simulations are less costly in memory resources and in computing time.
Resist modeling is an attractive way to predict the critical dimensions of patterned features after lithographic processing. Unfortunately, previous works have shown that model parameters are very difficult to determine and have often a poor range of validity outside the dataset that have been used to generate them. The goal of this work is to assess different simplified resist models using a systematic method. We have studied the accuracy of aerial image model and aerial image plus Gaussian noise convolution model. The approach is based on the comparison between simulated and experimental data for periodic lines of various dimensions at various illumination conditions. We also propose a reliable expression for Bossung curves fitting. Using simple physical considerations, the expression has been made very simple and efficient. After a proper setting of the model parameters to the experimental data, mean CD discrepancies between simulation and experiment are as small as 5% and can be 3% for certain feature types. Moreover, we show that simple Gaussian noise convolution models can be predictive with the same accuracy. The method for CD prediction is fully described in this paper. Significant improvements have been made in resists modeling over the last several years, but simplified resist models such as 'aerial image + Gaussian noise' seems to be an effective tool for CD prediction, which remains the major demand of IC manufacturers.