2D curvilinear patterns are more and more present in the lithography landscape. For the related devices, the line edge roughness (LER) is, as well as for lines and spaces, a critical figure of merit. In this article we propose to use a dedicated edge detection algorithm to measure LER of 2D curvilinear patterns on CD-SEM images. We present an original method to validate the algorithm, in the context of roughness measurement. It is based on the generation of realistic synthetic CD-SEM images with programmed roughness and a precise PSD analysis flow. We show excellent correlation (average R2 = 0.988) between the input roughness parameters and the measured parameters for both 1D and 2D synthetic images. Using synthetic images for different number of frames, the contour extraction sensitivity to noise is also explored. Finally, the methodology is successfully applied to experimental CD-SEM images for two classes of applications : photonic devices and DSA fingerprint patterns.
Directed Self-Assembly (DSA) of Block Copolymers (BCP) by chemo-epitaxial alignment is a promising high resolution lithography technique compatible with CMOS high-volume manufacturing. It allows overcoming limitations in resolution and local stochasticity by conventional, imaging based, lithography. However, for BCP with pitches below 20 nm and guide patterning by immersion lithography (193i), multiplication factors ≥ 4 become necessary, imposing stringent requirements on the guides and defectivity becomes hard to control. The Arkema-CEA (ACE) process flow overcomes this limit by creating the guides by a self-aligned double patterning (SADP) process flow, followed by the deposition of a cross-linkable neutral mat and selective grafting of the guides. This paper reports on the transfer of the process flow to immersion lithography, details challenges encountered in process optimization, notably the dependence of the wetting of the neutral layer on the surface energy and the morphology of the spacers. Last, the paper presents a metrology and defectivity roadmap combined with preliminary, promising results.
This paper introduces line roughness characterization non-straight patterns made of block copolymers (fingerprint patterns). Line Width Roughness have been determined using Power Spectral Density based on a special edge detection developed at CEA-LETI to extract edges contours. We investigated several process parameters impact on LWR such as the degree of polymerization of different BCPs and the impact of UV irradiation on the roughness of the PS block.
Directed Self-Assembly (DSA) of Block Copolymer (BCP) is a promising lithography approach to achieve high resolution pattern dimensions. The current chemo-epitaxy process used to induce block copolymer self-alignment is showing today its limitations. This is due to the resolution limitation of conventional lithography technics needed for the guide formation, used to achieve BCP alignment. This paper introduces a new chemo-epitaxy process, named ACE (Arkema-CEA), which is based on sidewall image transfer (SIT) patterning. This process has the great advantage to offer guides of small critical dimension (CD) and pitch that allows the integration of high χ BCP. In this paper, different parameters of the ACE process are investigated (commensurability, spacer CD …) in order to precisely determine the DSA process window defining the best conditions for BCP alignment. Process window with multiplication factor ranging from 2 to 4 are obtained on BCP under investigation.
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