Applications

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  1. EUV mask feature reconstruction via phase retrieval

    JCMsuite has been used in a simulation study to assess the performance of coherent diffractive imaging (CDI) and related phase retrieval methods for the reconstruction of non-trivially shaped and a–periodic nanostructures from far field intensity data.

    P. Ansuinelli, et al. EUV mask feature reconstruction via phase retrieval. Proc. SPIE 11089, 110892F (2019).

    2019 DOI

    Optical Metrology and Sensing, Optical and EUV Lithography, Light Scattering Computation

  2. Gaussian process regression for efficient parameter reconstruction

    Optical scatterometry is a method to measure the size and shape of periodic micro- or nanostructures on surfaces. For this purpose the geometry parameters of the structures are obtained by reproducing experimental measurement results through numerical simulations. The performance of Bayesian optimization as implemented in JCMsuite's optimization toolbox is compared to different local minimization algorithms for this numerical optimization problem. Bayesian optimization uses Gaussian-process regression to find promising parameter values. The paper examines how pre-computed simulation results can be used to train the Gaussian process and to accelerate the optimization.

    P.-I. Schneider, et al. Using Gaussian process regression for efficient parameter reconstruction. Proc. SPIE 10959, 1095911 (2019).

    2019 DOI

    Optical Metrology and Sensing, Optical and EUV Lithography, Optimization and Parameter Retrieval Methods, software benchmarks

  3. Grazing incidence x-ray fluorescence based profile reconstruction

    Rigorous field simulations obtained from a Maxwell solver (JCMsuite) in combination with Bayesian optimization allow to determine the spatial distribution of elemental species and the geometrical shape with sub-nm resolution.

    A. Andrle, et al. Grazing incidence x-ray fluorescence based characterization of nanostructures for element sensitive profile reconstruction. Proc. SPIE 11057, 110570M (2019).

    2019 DOI

    Optical Metrology and Sensing, Optical and EUV Lithography, Advanced Finite Element Methods, Optimization and Parameter Retrieval Methods

  4. Element sensitive reconstruction of nanostructured surfaces with finite elements and grazing incidence soft X-ray fluorescence

    The geometry of lamellar gratings is investigated experimentally with reference-free grazing-incidence X-ray fluorescence analysis. The demonstrated combination of GIXRF and finite-element simulations paves the way for a versatile characterization of nanoscale-structured surfaces.

    V. Soltwisch, et al. Element sensitive reconstruction of nanostructured surfaces with finite elements and grazing incidence soft X-ray fluorescence. Nanoscale 10, 6177 (2018).

    2018 DOI

    Optical Metrology and Sensing, Optical and EUV Lithography, Light Scattering Computation, Optimization and Parameter Retrieval Methods

  5. Evaluating the effects of modeling errors for isolated finite three-dimensional targets

    Optical three-dimensional (3-D) nanostructure metrology utilizes a model-based metrology approach to determine critical dimensions (CDs) that are well below the inspection wavelength. A project at the National Institute of Standards and Technology is evaluating how to attain key CD and shape parameters from engineered in-die capable metrology targets. The performance of simplified models is validated using highly accurate, fully 3D simulations.

    M. A. Henn, et al. Evaluating the effects of modeling errors for isolated finite three-dimensional targets. J. of Micro/Nanolithography, MEMS, and MOEMS, 16, 044001 (2017).

    2017 DOI

    Optical Metrology and Sensing, Optical and EUV Lithography, Advanced Finite Element Methods, Optimization and Parameter Retrieval Methods

  6. FEM for validation of alternative scattering computation method.

    JCMsuite is used for validation of an integral method for computing scattering response of finite dielectric objects.

    R. J. Dilz, et al. 2D TM scattering problem for finite dielectric objects in a dielectric stratified medium employing Gabor frames in a domain integral equation. J. Opt. Soc. Am. A 34, 1315 (2017).

    2017 DOI

    Optical Metrology and Sensing, Optical and EUV Lithography, other fields, Light Scattering Computation, software benchmarks

  7. Investigating surface structures by EUV scattering

    An exploration of soft X-ray and EUV-scatterometry from grazing to near normal incidence is presented. Measurements are performed on e-beam written silicon gratings. The reconstructed geometrical line shape models are statistically validated by applying a Markov-Chain Monte Carlo sampling technique. Experimental data and simulation results provide insight into the potential of EUV scatterometry.

    V. Soltwisch, et al. Investigating surface structures by EUV scattering. Proc. SPIE 10143, 101430P (2017).

    2017 DOI

    Optical Metrology and Sensing, Optical and EUV Lithography, Advanced Finite Element Methods, Optimization and Parameter Retrieval Methods, Uncertainty Quantification Methods

  8. Metrology of nanoscale grating structures by UV scatterometry

    Goniometric scatterometry measurements of gratings with linewidths down to 25 nm on silicon wafers with an inspection wavelength of 266 nm are presented. Data evaluation is performed using FEM based light scattering simulations. As results the reconstruction of the complete cross-section profile is presented.

    M. Wurm, et al. Metrology of nanoscale grating structures by UV scatterometry. Opt. Express 25, 2460 (2017).

    2017 DOI Publication link

    Optical Metrology and Sensing, Light Scattering Computation, Optimization and Parameter Retrieval Methods

  9. Quantifying parameter uncertainties in optical scatterometry using Bayesian inversion

    A Newton-like method is presented to solve inverse problems and to quantify parameter uncertainties. FEM, including direct computation of partial derivatives, is used to solve the forward-problem.

    M. Hammerschmidt, et al. Quantifying parameter uncertainties in optical scatterometry using Bayesian inversion. Proc. SPIE 10330, 1033004 (2017).

    2017 DOI Publication link

    Optical Metrology and Sensing, other fields, Advanced Finite Element Methods, Light Scattering Computation, Optimization and Parameter Retrieval Methods, Uncertainty Quantification Methods

  10. Quantitative optical imaging for in-die-capable critical dimension targets

    FEM simulations are used in a work by U.S. National Institute of Standards and Technology to optimize the design of in-die-capable metrology targets for process control in microlithography.

    B. M. Barnes, et al. Enabling quantitative optical imaging for in-die-capable critical dimension targets. Proc. SPIE 9778, 97780Y (2016).

    2016 DOI

    Optical Metrology and Sensing, Optical and EUV Lithography, Advanced Finite Element Methods, Optimization and Parameter Retrieval Methods

  11. Design of a plasmonic near-field tip for super-resolution IR-imaging

    A metallic near-field probe is designed that relies on plasmonic excitations and adiabatic field compression and allows for subwavelength field confinement.

    F. Ballout. Design of a plasmonic near-field tip for super-resolution IR-imaging. arXiv preprint 1605.04169 (2016).

    2016 Publication link

    Optical Metrology and Sensing, Photonic Waveguides and Fibers, plasmonics, Light Scattering Computation

  12. Modeling of Optical Imaging of Finite Multi-Line Arrays.

    The U.S. National Institute of Standards and Technology provides a dataset which contains MATLAB based scripting files and input files for the software package JCMsuite that enable the modeling of optical imaging of fionite multi-line arrays.

    M. A. Henn and B. M. Barnes. A Library to Enable the Modeling of Optical Imaging of Finite Multi-Line Arrays. DOI: 10.18434/T42C7D (2016).

    2016 DOI

    Optical Metrology and Sensing, Optical and EUV Lithography, Light Scattering Computation, other methods

  13. Efficient Bayesian inversion for shape reconstruction of lithography masks

    In order to quantify the uncertainties of reconstructed geometry parameters, a fast-to-evaluate surrogate for the forward model (a polynomial chaos expansion) is introduced. The surrogate allows, e.g., for determining the probability distribution of the geometry parameters given measurement data, and for a global sensitivity analysis of the measurement process. All methods are implemented in JCMsuite's analysis and optimization toolbox.

    N. Frachmin, et al. Efficient Bayesian inversion for shape reconstruction of lithography masks. Journal of Micro/Nanolithography, MEMS, and MOEMS, 19(2), 024001 (2020).

    2010 DOI Publication link

    Optical Metrology and Sensing, Optical and EUV Lithography, Light Scattering Computation, Optimization and Parameter Retrieval Methods, Uncertainty Quantification Methods

  14. Crescent-Shaped Metal Nanoparticles for Sensing Applications

    Plasmonic resonances of crescent-shaped nanoparticles respond to the attachment of colloidal particles by a shift of the resonance wavelength, as predicted in numerical simulations using FEM.

    A. Unger, et al. Sensitivity of Crescent-Shaped Metal Nanoparticles to Attachment of Dielectric Colloids. Nano Lett. 9, 2311 (2009).

    2009 DOI

    Optical Metrology and Sensing, plasmonics, Light Scattering Computation

  15. Benchmark of computational methods for mask simulation in optical lithography

    Various rigorous methods for simulation of light propagation through optical lithography photomasks are compared.

    S. Burger, et al. Benchmark of FEM, Waveguide and FDTD Algorithms for Rigorous Mask Simulation. Proc. SPIE 5992, 368 (2005).

    2005 DOI Publication link

    Optical Metrology and Sensing, Optical and EUV Lithography, software benchmarks