Direct comparison of line edge roughness measurements by SEM and a metrological tilting-atomic force microscopy for reference metrology

Line edge roughness (LER) measurement of a nanoscale line pattern is a metrology challenge in the inspection of semiconductor devices. Conventional scanning electron microscopy (SEM), a classical LER measurement technique, is a top-view (2D) metrology and incapable of accurately measuring 3D structures. For LER measurements, SEM measurement generates a single line edge profile for the 3D sidewall roughness, although the line edge profile differs at each height in the 3D sidewall. In this study, we used atomic force microscopy (AFM) with the tip-tilting technique to measure the 3D sidewall roughness, as an LER reference metrology. An identical location of a line pattern measured by SEM and AFM was compared to evaluate the SEM’s performance. The line edge profile from the AFM measurement exhibited lower noise than that from SEM. The measured line edge profiles were analyzed using the power spectral density (PSD), height-height correlation function (HHCF), and autocorrelation function. The results demonstrate that the standard deviation (σ) and correlation length (ξ) are overestimated while the roughness exponent (α) is underestimated by SEM, considering the AFM results as reference values.

Line edge roughness (LER) measurement is one of the metrology challenges for 3D device structures, and LER reference metrology is important for reliable LER measurements. We developed an LER measurement technique, which is able to analyze LER distribution along height of a line pattern, with high accuracy, resolution, and reproducibility. Highly accurate atomic force microscopy (AFM) image of a vertical sidewall of a line pattern was obtained using a metrological tilting- AFM, which offers SI-traceable dimensional measurements. The tilting-tip was controlled with an inclined servo axis and scans the vertical sidewall along a line pattern with a high sampling density to enable an analysis of the LER height distribution at the sidewall. A horizontal cross-section of the sidewall shows sidewall roughness with sub-nm resolution. Power spectral density (PSD) analysis of the sidewall profile showed that the PSD noise in the high-frequency region was several orders of magnitude lower than the noise of typical scanning electron microscopy methods. AFM measurements were sequentially repeated three times to evaluate the reproducibility of the sidewall measurement and LER analysis; results indicated a high reproducibility of 0.07 nm evaluated as a standard deviation of LER at each height.

Line edge roughness (LER) measurement is one of the metrology challenges for three-dimensional device structures, and LER reference metrology is important for reliable LER measurements. For the purpose of LER reference metrology, we developed an LER measurement technique that can analyze LER distribution along the height of a line pattern, with high resolution and repeatability. A high-resolution atomic force microscopy (AFM) image of a vertical sidewall of a line pattern was obtained using a metrological tilting-AFM, which offers SI-traceable dimensional measurements. The tilting-tip was controlled with an inclined servo axis, and it scans the vertical sidewall along a line pattern with a high sampling density to enable an analysis of the LER height distribution at the sidewall. A horizontal cross-section of the sidewall shows sidewall roughness with sub-nm resolution. Power spectral density (PSD) analysis of the sidewall profile showed that the PSD noise in the high-frequency region was several orders of magnitude lower than the noise of typical scanning electron microscopy methods. AFM measurements were sequentially repeated three times to evaluate the repeatability of the LER measurement; results indicated a high repeatability of 0.07 nm evaluated as a standard deviation of LER at each height.

Background: Scanning electron microscopy (SEM)-based line edge roughness (LER) measurement suffers from an error due to noise in SEM image. Noise correction methods have been developed to obtain unbiased roughness results, however, there are still concerns in the viewpoint of measurement precision. Aim: To develop an unbiased roughness analysis for highly precise LER measurement. Approach: Combining the conventional unbiased roughness analysis with a profile-averaging method, where a line pattern is repeatedly measured and then the obtained profiles are aligned and averaged. The experimental result measured by SEM was verified using atomic force microscopy (AFM)-based LER metrology, which has higher reliability than SEM. Results: The experimental evaluation showed that the proposed method can obtain roughness parameters more precisely than the conventional method. Conclusions: When the noise in the line edge profile by SEM is too large, it is necessary to reduce the noise beforehand and then perform roughness analysis in order to obtain precise roughness results. The proposed method enables to measure LER with the highest precision using SEM. Additionally, the AFM-based LER metrology was demonstrated as a feasible technique to evaluate the performance of SEM-based LER metrology.

Scanning electron microscopy (SEM) is commonly used for line edge roughness (LER) measurement; however, it is difficult to achieve high-precision LER measurement of photoresists because exposure to an electron beam (EB) causes shrinkage of the materials. The differences in the 3D sidewall shape before and after shrinkage have not been investigated in detail. In this study, EB-induced photoresist shrinkage was observed by employing the atomic force microscopy with tip-tilting technique (tilting-AFM), which enables high-precision observation of the vertical sidewall of the pattern. In the experiment, the shrinkage deformation was observed by measuring the same photoresist pattern with the tilting-AFM before and after EB exposure (by SEM observation) on the pattern. The results show that the sidewall was smoothed by EB exposure. Further, the tendency of changes in LER (roughness parameters) was observed. This measurement technique can be used to better understand photoresist materials and to improve the LER measurement by SEM.

Atomic force microscopy (AFM) is an important tool in line edge roughness (LER) measurements, where accuracy for line edge identification is influenced by the shape of the tip. In this article, the effect of tip shape on LER measurement based on AFM is studied theoretically. The formulas for calculating the distance between the measured and actual line edge of the sample are presented. The effects of the three kinds of tips with different shapes are experimentally compared for validation. Suggestions on how to reduce measuring error caused by tip shape are also given.

In this study, we developed a methodology to evaluate scanning electron microscopy (SEM)-based line edge roughness (LER) metrology. In particular, we used a metrological tilting atomic force microscopy (tilting-mAFM) as LER reference metrology. We analyzed the height-height correlation function (HHCF) of SEM line-edge profiles combining averaging and unbiased correction methods. The direct comparison of our method with tilting-mAFM enabled a precise evaluation of the SEM-based LER metrology. We demonstrated that a combination of unbiased HHCF and averaging methods with appropriate condition enabled relatively precise measurement of three roughness parameters. We observed that, for precise roughness evaluation, reducing noise in the line-edge profiles is important before performing the HHCF analysis and unbiased correction.

The measurement of line-edge roughness (LER) has recently become a major topic of concern in the semiconductor industry. This paper proposed a methodology method to measure LER using atomic force microscopy (AFM). Pay attention to the 3-D imaging of AFM, an image analysis algorithm detecting the line edge is presented. The code has been developed using MATLAB, which is able to calculate the amplitude parameters of LER above from measured data. We used this method to deal with the experiment data and analyzed the dependence of the amplitude of LER. After then, a same sample is measured by ordinary probe, ultrasharp probe and carbon nanotube probe. Analysis and comparison of measurement results using established algorithm were made. Then, as the characterization of LER is not only a simple geometry feature, but also is a wide-band including the spatial complexity of the edge, the spatial frequency analysis of the detected edges using the power spectral density function is necessary. For the self-affinity edge roughness, a characterization of LER based on the fractal theory is briefly described. The analysis of experiment data using nanotube probe demonstrated this method can completely characterize LER. Finally, the problem in the study is thoroughly investigated with interesting conclusions.

Measurements of the line edge roughness (LER) and critical dimension (CD) from scanning electron microscope (SEM) images are often required for analyzing circuit patterns transferred onto substrate systems. A common approach is to employ image processing techniques to detect feature boundaries from which the LER and CD are computed. SEM images usually contain a significant level of noise which affects the accuracy of measured LER and CD. This requires reducing the noise level by a certain type of low-pass filter before detecting feature boundaries. However, a low-pass filter also tends to destroy the boundary detail. Therefore, a careful selection of low-pass filter is necessary in order to achieve the high accuracy of LER and CD measurements. In this paper, a practical method to design a Gaussian filter for reducing the noise level in SEM images is proposed. The method utilizes the information extracted from a given SEM image in adaptively determining the sharpness and size of a Gaussian filter. The results from analyzing the effectiveness of the Gaussian filter designed by the proposed method are provided.

An experimental study of the line edge roughness (LER) of nine 193 nm photoresist formulations is presented. In these formulations, the same polymer platform is used while the photoacid generator (PAG) properties and base concentration are systematically varied to produce controlled LER in 130 nm dense line/space features. SEM images of each resist are recorded using a KLA 8250 XR inspection tool. The SEM images are post processed using software developed at Shipley to extract frequency dependent LER as well as RMS amplitude LER. We present an investigation of the dependence of frequency limits and sensitivity on the magnification level and image quality. The primary source of noise in the LER measurements is found to be image amplitude noise, which makes determination of the line edge more difficult. The noise introduced by the line edge measurement errors is primarily high frequency noise. The top down resist profiles of the different formulations are used to calculate the LER power spectral density functions. While the absolute amplitude of the spectral density functions is different for each resist, all of the plots show a similar functional form. The resists show a maximum amplitude LER near the low frequency limit with an exponential decay at higher frequencies. The log plot of all of the resists show that the LER follows 1/f noise statistics. The dependence of the amplitude of the LER on the aerial image is also demonstrated.

Atomic force microscopy (AFM) is an important technique for measurement of the surface roughness and surface features of high technology surfaces such as semiconductor chips and micro-optics. One of the key measurands is the linewidth of semiconductor features [1]. A class of AFM instruments often called CD-AFM has been developed for the purpose of measuring linewidth accurately (Fig. 9.1). The smallest linewidth or hole diameter on a semiconductor circuit is called the critical dimension or CD. Recently, a requirement has arisen in the semiconductor industry for control, specification, and measurement of line edge roughness (LER) for functional semiconductor features, such as processor gates [2–5]. As feature dimensions become steadily smaller, the LER of a single gate is becoming a significant fraction of the gate length itself. Hence, the LER is expected to have a significant effect on properties of the gate such as leakage current. The International Technology Roadmap for Semiconductors (ITRS) [6] specifies a physical gate length for 2002 of 75 nm and a maximum LER of 3.9 nm. The effect of LER on the function of an electronic gate has been modeled by several studies and these models have been verified experimentally. This work has led in part to a succinct specification of LER requirements for current and future generations of semiconductor circuits. This specification has been inserted into the International Technology Roadmap for Semiconductors (ITRS) [6].KeywordsAtomic Force MicroscopyLine StructureSpatial WavelengthSidewall RoughnessAtomic Force Microscopy CharacterizationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

As the dimensions of integrated circuit devices continue to shrink, the effect of line edge roughness (LER) of resist patterns on the device performance is becoming a serious problem. Therefore, the desire to measure LER with more accuracy is growing. We have proposed the method for LER measurement by using the wavelet multiresolution analysis. It is still required that a wavelet filter is optimized to reveal line edges from noisy SEM signal profile to achieve more accuracy. In this paper, we try to estimate statistically a wavelet that is matched to measure LER from the scanning electron microscopy (SEM) signal profile. Here we propose a novel mathematical and statistical modeling of the SEM signal profile. The mathematical model has been deduced from a variety of SE signal shapes which have been calculated by Monte Carlo simulations. It is also necessary to consider statistical effects such as the property of the atoms within the nanostructures and the fluctuation of the exposure. We then formulate a model by considering four characteristics of critical dimension (CD) in photolithography: the exponential distribution of the image intensity around the impinging electron beam, the spatial frequency distribution of LER, phase difference between both sides of a line pattern, and shot noise in SEM images. Statistically matched wavelet is estimated from local signal profiles around true edge positions. As a result, it was seen that there was a high degree of similarity between real and model SEM images. We also compared performance in accuracy of CD measurement between the matched wavelet and the first-order derivative Gaussian wavelet, which has selected as the most suitable one for lithography metrology in previous work. CDs measured by both wavelets were almost equal since the matched wavelet has relatively small effect on noise reduction.

Line-edge roughness (LER) and linewidth roughness (LWR) in semiconductor processing are best characterized by the roughness power spectral density (PSD), or similar measures of roughness frequency and correlation. The PSD is generally thought to be described well by three parameters: standard deviation, correlation length, and PSD(0), the extrapolated zero frequency PSD. The next step toward enabling these metrics for pertinent industrial use is to understand how real metrology errors interact with these metrics and what should be optimized on the critical dimension scanning electron microscopy (CD-SEM) to improve error budgets. In this work, both images from multiple models of commercially-available CD-SEMs and from JMONSEL simulation of modeled roughened lines are used to better understand how various SEM algorithm choices, parameters, beam size/shape, and pixel size/scanning scheme influence SEM line edge uncertainty. Furthermore, how these errors interact with the above-listed PSD metrics will be explored, imparting knowledge for optimizing LER PSD measurement with minimized error. The Analytical Linescan Model (ALM) is a physics-based semi-empirical expression that predicts a SEM linescan given a specified wafer geometry. It can be calibrated to rigorous Monte Carlo simulations. Unlike Monte Carlo simulations, however, the analytical form of the ALM makes computational times very small. Inverting the ALM to produce an inverse linescan model allows wafer geometries to be estimated based on experimental linescan measurements. Thus, an inverse linescan model can be used as an edge detection algorithm for dimensional measurement directly from CD-SEM generated images. Here, an inverse linescan model will be tested as a potential CD, LER, and LWR measurement algorithm and compared to other conventional measurement algorithms.

Model-Based OPC has become a standard practice and centerpiece for 130nm technology node and below. And every model builder is trying to setup a physically realistic model that is adequately calibrated contains the information which can be used for process predictions and analysis of a given process. But there still are some unknown/not-well-understood physics in the process such as line edge roughness (LER). The LER is one of the most worrisome non-tool-related obstacles faced by next-generation lithography. Nowadays, considerable effort is devoted to moderating its effects, as well as understanding its impact on devices. It is a persistent problem for 193 nm micro-lithography and will carry us for at least three generations, culminating with immersion lithography. Some studies showed LER has several sources and forms. It can be quantified by an LER measurement with a top-down CD measurement. However, there are other ways in which LER shows up, such as line breakage results from insufficient resist or mask patterning processes, line-width aspect ratio or just topography. Here we collected huge amount of line-width ADI CD datasets together with LER for each edge. And try to show even using the average value of different datasets will take the inaccuracy of measurement into the modeling fitting process, which makes the fitting process more time consuming and might cause losing convergence and stableness. This work is to weight different wafer data points with a weighting function. The weighting function is dependent on the LER value for each One-dimension feature in the sampling space of the modeling fitting. By this approach, we can filter wrong information of the process and make the OPC model more accurate. Further more, we will introduce this factor (LER) into variable threshold modeling parameters and see its differentiations between other Variable Threshold model forms.

Measurement and control of line edge roughness (LER) is one of the most challenging issues facing patterning technology. As the critical dimensions (CD) of patterned structures decrease, LER of only a few nanometers can negatively impact device performance. Here, Mueller matrix spectroscopic ellipsometry (MMSE) based scatterometry is used to determine LER in periodic line-space structures in 28 nm pitch Si fin samples fabricated by directed selfassembly (DSA) patterning. The optical response of the Mueller matrix (MM) elements is influenced by structural parameters like pitch, CD, height, and side-wall angle (SWA), as well as the optical properties of the materials. Evaluation and decoupling MM element response to LER from other structural parameters requires sensitivity analysis using simulations of optical models that include LER. Here, an approach is developed that quantifies Si fin LER by comparing the optical responses generated by systematically varying the grating shape and measurement conditions. Finally, the validity of this approach is established by comparing the results obtained from top down scanning electron microscope (SEM) images and cross-sectional TEM image of the 28 nm pitch Si fins.