Stochastics defect detection has been a topic of intense study by the extreme ultraviolet (EUV) patterning fraternity [1]. A large part of this initial feasibility work has been performed using electron microscope-based systems [1,2]. A limited sample area is imaged using electron microscopes and images are analyzed using offline analysis techniques [1,2]. However, to accurately quantify the stochastics failure rate, the entire area of interest needs to be inspected. Given such large area inspection requirements, automated and high throughput solutions are the need of the hour to enable stochastics quantification in HVM (high volume manufacturing). This paper demonstrates Broadband Plasma optical wafer inspection capability to capture two key defects on EUV layers a) missing contact in contact hole array patterns b) line breaks in line- space pattern.
Directed self-assembly (DSA) lithography poses challenges in line edge roughness (LER)/line width roughness metrology due to its self-organized and pitch-based nature. To cope with these challenges, a characterization approach with metrics and/or updates of the older ones is required. To this end, we focus on two specific challenges of DSA line patterns: (a) the large correlations between the left and right edges of a line (line wiggling) and (b) the cross-line correlations, i.e., the resemblance of wiggling fluctuations of nearby lines. The first is quantified by the line center roughness whose low-frequency part is related to the local placement errors of device structures. For the second, we introduce the c-factor correlation function, which quantifies the strength of the correlations between lines versus their horizontal distance in pitches. The proposed characterization approach is first illustrated and explained in synthesized scanning electron microscope images with full control of their dimensional and roughness parameters; it is then applied to the analysis of line/space patterns obtained with the Liu–Nealey flow (post-Polymethyl methacrylate removal and pattern transfer), revealing the effects of pattern transfer on roughness and uniformity. Finally, we calculate the c-factor function of various next-generation lithography techniques and show their distinct footprint on the extent of cross-line correlations.
This manuscript first presents a cost model to compare the cost of ownership of DSA and SAQP for a typical front end of line (FEoL) line patterning exercise. Then, we proceed to a feasibility study of using a vertical furnace to batch anneal the block co-polymer for DSA applications. We show that the defect performance of such a batch anneal process is comparable to the process of record anneal methods. This helps in increasing the cost benefit for DSA compared to the conventional multiple patterning approaches.
DSA lithography poses new challenges in LER/LWR metrology due to its self-organized and pitch-based nature. To cope with these challenges, a novel characterization approach with new metrics and updating the older ones is required. To this end, we focus on two specific challenges of DSA line patterns: a) the large correlations between the left and right edges of a line (line wiggling, rms(LWR)<rms(LER)) and b) the cross-line correlations, i.e. the resemblance of wiggling fluctuations of nearby lines. The first is quantified by the Line Center Roughness whose low-frequency part is related to the local placement errors of device structures. For the second, we propose the c-factor correlation function which quantifies the strength of the correlations between lines versus their horizontal distance in pitches. Also, we define roughness and uniformity parameters for the pitch changes along and across lines. The proposed characterization approach is applied to the analysis of line/space patterns obtained with the Liu-Nealey (LiNe) flow (post PMMA removal and pattern transfer) revealing the effects of pattern transfer on roughness and uniformity. Finally, we calculate the cfactor function of various Next-Generation Lithography techniques and reveal their distinct footprint on the extent of cross-line correlations.
This manuscript shows the relationship between defectivity of a typical chemo-epitaxy sequence and the DSA-specific materials, namely the mat, the brush and the block co-polymer. We demonstrate that the density of assembly defects in a line-space DSA flow, namely the dislocations and 1-period bridges have a direct correlation to certain parameters in the synthesis sequence of these materials. The primary focus of this manuscript is on identifying, controlling and reproducing the defects-critical parameters in the block co-polymer synthesis process for a stable and low defect performance of DSA flows.
High-defect density in thermodynamics driven directed self-assembly (DSA) flows has been a major cause of concern for a while and several questions have been raised about the relevance of DSA in high-volume manufacturing. The major questions raised in this regard are: (1) What is the intrinsic level of DSA-induced defects? (2) Can we isolate the DSA-induced defects from the other processes-induced defects? (3) How much do the DSA materials contribute to the final defectivity and can this be controlled? (4) How can we understand the root causes of the DSA-induced defects and their kinetics of annihilation? (5) Can we have block copolymer anneal durations that are compatible with standard CMOS fabrication techniques (in the range of minutes) with low-defect levels? We address these important questions and identify the issues and the level of control needed to achieve a stable DSA defect performance.
The Liu-Nealey (LiNe) chemo-epitaxy Directed Self Assembly flow has been screened thoroughly in the past years in terms of defects. Various types of DSA specific defects have been identified and best known methods have been developed to be able to get sufficient S/N for defect inspection to help understand the root causes for the various defect types and to reduce the defect levels to prepare the process for high volume manufacturing. Within this process development, SEM-review and defect classification play a key role. This paper provides an overview of the challenges that DSA brings also in this metrology aspect and we will provide successful solutions in terms of making the automated defect review. In addition, a new Real Time Automated Defect Classification (RT-ADC) will be introduced that can save up to 90% in the time required for manual defect classification. This will enable a much larger sampling for defect review, resulting in a better understanding of signatures and behaviors of various DSA specific defect types, such as dislocations, 1-period bridges and line wiggling.
High defect density in thermodynamics driven DSA flows has been a major cause of concern for a while and several questions have been raised about the relevance of DSA in high volume manufacturing. The major questions raised in this regard are: 1. What is the intrinsic level of DSA-induced defects, 2. Can we isolate the DSA-induced defects from the other processes-induced defects, 3. How much do the DSA materials contribute to the final defectivity and can this be controlled, 4. How can we understand the root causes of the DSA-induced defects, their kinetics of annihilation and finally, 5. Can we have block co-polymer anneal durations that are compatible with standard CMOS fabrication techniques (in the range of minutes) with low defect levels. This manuscript addresses these important questions and identifies the issues and the level of control needed to achieve a stable DSA defect performance.
Directed Self-Assembly (DSA) of Block Co-Polymers (BCP) has become an intense field of study as a potential patterning solution for future generation devices. The most critical challenges that need to be understood and controlled include pattern placement accuracy, achieving low defectivity in DSA patterns and how to make chip designs DSA-friendly. The DSA program at imec includes efforts on these three major topics. Specifically, in this paper the progress in DSA defectivity within the imec program will be discussed. In previous work, defectivity levels of ~560 defects/cm2 were reported and the root causes for these defects were identified, which included particle sources, material interactions and pre-pattern imperfections. The specific efforts that have been undertaken to reduce defectivity in the line/space chemoepitaxy DSA flow that is used for the imec defectivity studies are discussed. Specifically, control of neutral layer material and improved filtration during the block co-polymer manufacturing have enabled a significant reduction in the defect performance. In parallel, efforts have been ongoing to enhance the defect inspection capabilities and allow a high capture rate of the small defects. It is demonstrated that transfer of the polystyrene patterns into the underlying substrate is critical for detecting the DSA-relevant defect modes including microbridges and small dislocations. Such pattern transfer enhances the inspection sensitivity by ~10x. Further improvement through process optimization allows for substantial defectivity reduction.
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