Evangelos Gogolides

Setting up a proper power spectral density (PSD) and autocorrelation analysis for material and process characterization

Power spectral density (PSD) analysis is playing more and more a critical role in the understanding of line-edge roughness (LER) and linewidth roughness (LWR) in a variety of applications across the industry. It is an essential step to get an unbiased LWR estimate, as well as an extremely useful tool for process and material characterization. However, PSD estimate can be affected by both random to systematic artifacts caused by image acquisition and measurement settings, which could irremediably alter its information content. In this paper, we report on the impact of various setting parameters (smoothing image processing filters, pixel size, and SEM noise levels) on the PSD estimate. We discuss also the use of PSD analysis tool in a variety of cases. Looking beyond the basic roughness estimate, we use PSD and autocorrelation analysis to characterize resist blur[1], as well as low and high frequency roughness contents and we apply this technique to guide the EUV material stack selection. Our results clearly indicate that, if properly used, PSD methodology is a very sensitive tool to investigate material and process variations

Cell Array Fabrication by Plasma Nanotexturing

Cell behavior (i.e. attachment, proliferation, etc.) on nanostructured surfaces is currently a hot topic throughout the scientific community. However, studies often show diverging results due to differences in cells, local surface chemistry, and nanotopography fabrication methods. In this study, we use Oxygen plasma etching to both randomly nanotexture a PMMA surface and change its surface chemistry. We find that 3T3 cells behave quite differently on flat PMMA surfaces as compared to nanotextured ones, showing an on-off attachment behavior. Work is under progress to exploit this effect allowing selective cell capturing, and creation of cell arrays in adjacent plasma-nanotextured/smooth areas using a stencil mask during etching.

Line-width roughness analysis of EUV resists after development in homogenous CO 2 solutions using CO 2 compatible salts (CCS) by a three-parameter model

Line Width Roughness (LWR) of resists constitutes one of the main obstacles in the race of further shrinking the feature dimensions of fabricated devices. Thus, the reduction and control of LWR is one of the biggest challenges of next generation lithographies. In this paper, the LWR output of a new development process of EUV resists which uses homogeneous carbon dioxide (CO2) solutions containing CO2 compatible salts (CCS) has been examined. The measurement and characterization of LWR has been made through the analysis of CD-SEM images and the application of a three-parameter model. The three parameters involved in this model (sigma value σLWR, correlation length ξ, roughness exponent α) determine both the spatial aspects (spectrum) of LWR as well as the interplay between LWR and local CD variations. It is found that wafers developed with CCS process gives substantially lower LWR parameters (σLWR,ξ) than comparable TMAH developed samples. Also, the impact of the preparation of resist wafer (exposure time, PAG and quencher level) and the development conditions (temperature, CCS concentration) on LWR parameters is examined so that we are able to identify trends to lead toward optimized LWR performance.

3D Plasma Nanotextured ® Polymeric Surfaces for Protein or Antibody Arrays, and Biomolecule and Cell Patterning

Plasma micro-nanotexturing is a generic technology for topographical and chemical modification of surfaces and their implementation in microfluidics and microarrays. Nanotextured surfaces with desirable chemical functionality (and wetting behavior) have shown excellent biomolecule immobilization and cell adhesion. Specifically, nanotextured hydrophilic areas show (a) strong binding of biomolecules and (b) strong adhesion of cells, while nanotextured superhydrophobic areas show null adsorption of (a) proteins and (b) cells. Here we describe the protocols for (a) biomolecule adsorption control on nanotextured surfaces for microarray fabrication and (b) cell adhesion on such surfaces. 3D plasma nanotextured® substrates are commercialized through Nanoplasmas private company, a spin-off of the National Centre for Scientific Research Demokritos.

Allowable SEM noise for unbiased LER measurement

Recently, a novel method for the calculation of unbiased Line Edge Roughness based on Power Spectral Density analysis has been proposed. In this paper first an alternative method is discussed and investigated, utilizing the Height-Height Correlation Function (HHCF) of edges. The HHCF-based method enables the unbiased determination of the whole triplet of LER parameters including besides rms the correlation length and roughness exponent. The key of both methods is the sensitivity of PSD and HHCF on noise at high frequencies and short distance respectively. Secondly, we elaborate a testbed of synthesized SEM images with controlled LER and noise to justify the effectiveness of the proposed unbiased methods. Our main objective is to find out the boundaries of the method in respect to noise levels and roughness characteristics, for which the method remains reliable, i.e the maximum amount of noise allowed, for which the output results cope with the controllable known inputs. At the same time, we will also set the extremes of roughness parameters for which the methods hold their accuracy.

Multifractal analysis of line-edge roughness

In this paper, we propose to rethink the issue of LER characterization on the basis of the fundamental concept of symmetries. In LER one can apply two kinds of symmetries: a) the translation symmetry characterized by periodicity and b) the scaling symmetry quantified by the fractal dimension. Up to now, a lot of work has been done on the first symmetry since the Power Spectral Density (PSD), which has been extensively studied recently, is a decomposition of LER signal into periodic edges and quantification of the ‘power’ of each periodicity at the real LER. The aim of this paper is to focus on the second symmetry of scaling invariance. Similarly to PSD, we introduce the multifractal approach in LER analysis which generalizes the scaling analysis of standard (mono)fractal theory and decomposes LER into fractal edges characterized by specific fractal dimensions. The main benefit of multifractal analysis is that it enables the characterization of the multi-scaling contributions of different mechanisms involved in LER formation. In the first part of our work, we present concisely the multifractal theory of line edges and utilize the Box Counting method for its implementation and the extraction of the multifractal spectrum. Special emphasis is given on the explanation of the physical meaning of the obtained multifractal spectrum whose asymmetry quantifies the degree of multifractality. In addition, we propose the distinction between peak-based and valley-based multifractality according to whether the asymmetry of the multifractal spectrum is coming from the sharp line material peaks to space regions or from the cavities of line materis (edge valleys). In the second part, we study systematically the evolution of LER multifractal spectrum during the first successive steps of a multiple (quadruple) patterning lithography technique and find an interesting transition from a peak-based multifractal behavior in the first litho resist LER to a valley-based multifractality caused mainly by the effects of etch pattern transfer steps.

Computational nanometrology of line-edge roughness: noise effects, cross-line correlations and the role of etch transfer

The aim of this paper is to investigate the role of etch transfer in two challenges of LER metrology raised by recent evolutions in lithography: the effects of SEM noise and the cross-line and edge correlations. The first comes from the ongoing scaling down of linewidths, which dictates SEM imaging with less scanning frames to reduce specimen damage and hence with more noise. During the last decade, it has been shown that image noise can be an important budget of the measured LER while systematically affects and alter the PSD curve of LER at high frequencies. A recent method for unbiased LER measurement is based on the systematic Fourier or correlation analysis to decompose the effects of noise from true LER (Fourier-Correlation filtering method). The success of the method depends on the PSD and HHCF curve. Previous experimental and model works have revealed that etch transfer affects the PSD of LER reducing its high frequency values. In this work, we estimate the noise contribution to the biased LER through PSD flat floor at high frequencies and relate it with the differences between the PSDs of lithography and etched LER. Based on this comparison, we propose an improvement of the PSD/HHCF-based method for noise-free LER measurement to include the missed high frequency real LER. The second issue is related with the increased density of lithographic patterns and the special characteristics of DSA and MP lithography patterns exhibits. In a previous work, we presented an enlarged LER characterization methodology for such patterns, which includes updated versions of the old metrics along with new metrics defined and developed to capture cross-edge and cross-line correlations. The fundamental concept has been the Line Center Roughness (LCR), the edge c-factor and the line c-factor correlation function and length quantifying the line fluctuations and the extent of cross-edge and cross-line correlations. In this work, we focus on the role of etch steps on cross-edge and line correlation metrics in SAQP data. We find that the spacer etch steps reduce edge correlations while etch steps with pattern transfer increase these. Furthermore, the density doubling and quadrupling increase edge correlations as well as cross-line correlations.

Noise effects on contact-edge roughness and CD uniformity measurement

The aim of this work is to study the effects of noise on the parameters characterizing the size and roughness of contact edges when they are measured by the analysis of top-down SEM images. The applied methodology is based on the modelling of rough contact edges with controlled roughness parameters and the generation of synthesized top down SEM images with several contact edges and a distribution of Critical Dimension (CD) values (CD nonuniformity). The sources of noise can be the shot noise of SEM electron beam (Poisson-type) and the microscope electronics (Gaussiantype). First, we check out the validity of the model and then we apply it to evaluate the effects of noise in synthesized SEM images with smooth and images with rough contact edges. The results show that in all cases, noise lowers CD and correlation length while it increases the rms value. CD variation is increased with noise in images with smooth and identical contacts whereas it remains almost unaltered in images including rough contacts with CD nonuniformity. Furthermore, we find that the application of a noise smoothing filter before image analysis is able to rectify the values of CD (at small filter parameter) and of rms and correlation length (at larger filter parameters), whereas it leads to larger deviations from the true values of CD variation. Quantitative assessment of the model predictions reveals that the noise induced variations of CD and CER values are inferior to those caused by process stochasticity and material inhomogeneities.