Metrology of EUV Masks by EUV-Scatterometry and Finite Element Analysis

Extreme ultraviolet (EUV) lithography is seen as a main candidate for production of future generation computer technology. Due to the short wavelength of EUV light (around 13 nm) novel reflective masks have to be used in the production process. A prerequisite to meet the high quality requirements for these EUV masks is a simple and accurate method for absorber pattern profile characterization. In our previous work we demonstrated that the Finite Element Method (FEM) is very well suited for the simulation of EUV scatterometry and can be used to reconstruct EUV mask profiles from experimental scatterometric data. In this contribution we apply an indirect metrology method to periodic EUV line masks with different critical dimensions (140 nm and 540 nm) over a large range of duty cycles (1:2, ..., 1:20). We quantitatively compare the reconstructed absorber pattern parameters to values obtained from direct AFM and CD-SEM measurements. We analyze the reliability of the reconstruction for the given experimental data. For the CD of the absorber lines, the comparison shows agreement of the order of 1nm. Furthermore we discuss special numerical techniques like domain decomposition algorithms and high order finite elements and their importance for fast and accurate solution of the inverse problem.Comment: Photomask Japan 2008 / Photomask and Next-Generation Lithography Mask Technology X

On Predictability of Revisioning in Corporate Cash Flow Forecasting

Financial services within corporations usually are part of an information system on which many business functions depend. As of the importance of forecast quality for financial services, means of forecast accuracy improvement, such as data-driven statistical prediction techniques and/or forecast support systems, have been subject to IS research since decades. In this paper we consider means of forecast improvement due to regular patterns in forecast revisioning. We analyze how business forecasts are adjusted to exploit possible improvements for the accuracy of forecasts with lower lead time. The empirical part bases on an unique dataset of experts\u27 cash flow forecasts and accountants\u27 actuals realizations of companies in a global corporation. We find that direction and magnitude of the final revision in aggregated forecasts can be related to suggested targets in earnings management, providing the means of improving the accuracy of longer-term cash flow forecasts

Rigorous FEM-Simulation of EUV-Masks: Influence of Shape and Material Parameters

We present rigorous simulations of EUV masks with technological imperfections like side-wall angles and corner roundings. We perform an optimization of two different geometrical parameters in order to fit the numerical results to results obtained from experimental scatterometry measurements. For the numerical simulations we use an adaptive finite element approach on irregular meshes. This gives us the opportunity to model geometrical structures accurately. Moreover we comment on the use of domain decomposition techniques for EUV mask simulations. Geometric mask parameters have a great influence on the diffraction pattern. We show that using accurate simulation tools it is possible to deduce the relevant geometrical parameters of EUV masks from scatterometry measurements. This work results from a collaboration between Advanced Mask Technology Center (AMTC, mask fabrication), Physikalisch-Technische Bundesanstalt (PTB, scatterometry), Zuse Institute Berlin (ZIB), and JCMwave (numerical simulation).Comment: 8 pages, 8 figures (see original publication for images with a better resolution

Reconstructing Detailed Line Profiles of Lamellar Gratings from GISAXS Patterns with a Maxwell Solver

Laterally periodic nanostructures were investigated with grazing incidence small angle X-ray scattering (GISAXS) by using the diffraction patterns to reconstruct the surface shape. To model visible light scattering, rigorous calculations of the near and far field by numerically solving Maxwell's equations with a finite-element method are well established. The application of this technique to X-rays is still challenging, due to the discrepancy between incident wavelength and finite-element size. This drawback vanishes for GISAXS due to the small angles of incidence, the conical scattering geometry and the periodicity of the surface structures, which allows a rigorous computation of the diffraction efficiencies with sufficient numerical precision. To develop dimensional metrology tools based on GISAXS, lamellar gratings with line widths down to 55 nm were produced by state-of-the-art e-beam lithography and then etched into silicon. The high surface sensitivity of GISAXS in conjunction with a Maxwell solver allows a detailed reconstruction of the grating line shape also for thick, non-homogeneous substrates. The reconstructed geometrical line shape models are statistically validated by applying a Markov chain Monte Carlo (MCMC) sampling technique which reveals that GISAXS is able to reconstruct critical parameters like the widths of the lines with sub-nm uncertainty

Road Condition Estimation Based on Heterogeneous Extended Floating Car Data

Road condition estimation based on Extended Floating Car Data (XFCD) from smart devices allows for determining given quality indicators like the international roughness index (IRI). Such approaches currently face the challenge to utilize measurements from heterogeneous sources. This paper investigates how a statistical learning based self-calibration overcomes individual sensor characteristics. We investigate how well the approach handles variations in the sensing frequency. Since the self-calibration approach requires the training of individual models for each participant, it is examined how a reduction of the amount of data sent to the backend system for training purposes affects the model performance. We show that reducing the amount of data by approximately 50 % does not reduce the models’ performance. Likewise, we observe that the approach can handle sensing frequencies up to 25 Hz without a performance reduction compared to the baseline scenario with 50 Hz

Weighted aggregation in the domain of crowd-based road condition monitoring

This paper focuses on crowd-based road condition monitoring using smart devices, such as smartphones and evaluates different strategies for aggregating multiple measurements (arithmetic mean and weighted means using R2 and RMSE) for predicting the longitudinal road roughness. The results confirm that aggregating predictions from single drives leads to a higher model performance. This has been expected and confirms the intuition. The overall R2 could be increased from 0.69 to 0.75 on average and the NRMSE could be decreased from 9% to 8% on average. However, contrary to the intuition, the results show that weighted aggregations of single predictions should be avoided, which is consistent with previous findings in other domains, such as financial forecasting

Ni-Al alloys as alternative EUV mask absorber

Extreme ultraviolet (EUV) lithography is being industrialized as the next candidate printing technique for high-volume manufacturing of scaled down integrated circuits. At mask level, the combination of EUV light at oblique incidence, absorber thickness, and non-uniform mirror reflectance through incidence angle, creates photomask-induced imaging aberrations, known as mask 3D (M3D) effects. A possible mitigation for the M3D effects in the EUV binary intensity mask (BIM), is to use mask absorber materials with high extinction coefficient k and refractive coefficient n close to unity. We propose nickel aluminide alloys as a candidate BIM absorber material, and characterize them versus a set of specifications that a novel EUV mask absorber must meet. The nickel aluminide samples have reduced crystallinity as compared to metallic nickel, and form a passivating surface oxide layer in neutral solutions. Composition and density profile are investigated to estimate the optical constants, which are then validated with EUV reflectometry. An oxidation-induced Al L2 absorption edge shift is observed, which significantly impacts the value of n at 13.5 nm wavelength and moves it closer to unity. The measured optical constants are incorporated in an accurate mask model for rigorous simulations. The M3D imaging impact of the nickel aluminide alloy mask absorbers, which predict significant M3D reduction in comparison to reference absorber materials. In this paper, we present an extensive experimental methodology flow to evaluate candidate mask absorber materials