Moore's Law states that transistor density will double every two years, which is sustained until today due to continuous multidirectional innovations (such as extreme ultraviolet lithography, novel patterning techniques etc.), leading the semiconductor industry towards 3 nm node (N3) and beyond. For any patterning scheme, the most important metric to evaluate the quality of printed patterns is edge placement error, with overlay being its largest contribution. Overlay errors can lead to fatal failures of IC devices such as short circuits or broken connections in terms of pattern-to-pattern electrical contacts. Therefore, it is essential to develop effective overlay analysis and control techniques to ensure good functionality of fabricated semiconductor devices. In this work we have used an imec N-14 BEOL process flow using litho-etch-litho-etch (LELE) patterning technique to print metal layers with minimum pitch of 48nm with 193i lithography. Fork-fork structures are decomposed into two mask layers (M1A and M1B) and then the LELE flow is carried out to make the final patterns. Since a single M1 layer is decomposed into two masks, control of overlay between the two masks is critical. The goal of this work is of two-fold as, (1) to quantify the impact of overlay on capacitance and (2) to see if we can predict the final capacitance measurements with selected machine learning models at an early stage. To do so, scatterometry spectra are collected on these electrical test structures at (a) post litho, (b) post TiN hardmask etch, and (c) post Cu plating and CMP. Critical Dimension (CD) and overlay measurements for line/space (L/S) pattern are done with SEM post litho, post etch and post Cu CMP. Various machine learning models are applied to do the capacitance prediction with multiple metrology inputs at different steps of wafer processing. Finally, we demonstrate that by using appropriate machine learning models we are able to do better prediction of electrical results.

No abstract

Background: The chemically amplified resist (CAR) has been the workhorse of lithography for the past few decades. During the evolution of projection lithography to extreme ultraviolet lithography (EUVL), a continuous reduction in feature size is observed. Also, a reduction in resist film thickness (FT) is required to prevent large aspect ratios that lead to pattern collapse. A further reduction in resist FT, into an ultrathin film regime (<30 nm resist FT), is expected when advancing to high NA EUVL. This brings along associated challenges with (1) resist critical dimension scanning electron microscope (CDSEM) metrology and (2) resist patterning performance.Aim: Assessment of metrology challenges and patterning limits of a CAR working in this ultrathin film regime. Deconvoluting the metrology and patterning effect on the determination of the unbiased line width roughness (uLWR).Approach: Patterning a CAR at different nominal resist FTs on two different underlayers to quantify the changes in CDSEM image quality and resist patterning performance with the resulting uLWR changes. Results:The CDSEM image signal-to-noise ratio (SNR) depends on resist FT and the underlayer. The uLWR increases with a reduction in resist FT but scales differently on the two underlayers.Conclusions: A relationship between CDSEM image SNR and uLWR is found. The SNR and uLWR scaling difference on the two underlayers, as well as the uLWR dependency on SNR was determined to be a metrology effect. The general uLWR increase for a reduced resist FT was determined to be a patterning effect.

No abstract

No abstract

Extreme ultraviolet lithography (EUVL) is a leading-edge technology for pattern miniaturization and the production of advanced electronic devices. One of the current critical challenges for further scaling down the technology is reducing the line-edge roughness (LER) of the final patterns while simultaneously maintaining high resolution and sensitivity. As the target sizes of features and LER become closer to the polymer size, polymer chain conformations and their distribution should be considered to understand the primary sources of LER. Here, we proposed a new approach of EUV photoresist modeling with an explicit description of polymer chains using a coarse-grained model. Our new simulation model demonstrated that interface variation represented by width and fluctuation at the edge of the pattern could be caused by characteristic changes of the resist material during the lithography processes. We determined the effect of polymer chain conformation on LER formation and how it finally contributed to LER formation with various resist material parameters (e.g., Flory–Huggins parameter, molecular weight, protected site ratio, and Tg).

Extreme ultra-violet lithography (EUVL) is the leading-edge technology to produce advanced nanoelectronics. The further development of EUVL is heavily based on implementing the so-called high numerical aperture (NA) EUVL, which will enable even smaller pitches up to 8 nm half pitch (HP). In anticipation of this high NA technology, it is crucial to assess the readiness of the current resist materials for the high NA regime to comply with the demanding requirements of resolution, line-edge roughness, and sensitivity (RLS). The achievable tighter pitches require lower film thicknesses for both resist and underlying transfer layers. A concern that is tied to the thinning down is the potential change in resist properties and behavior due to the interaction with the underlayer. To increase the fundamental understanding of ultra-thin films for high NA EUVL, a method to investigate the interplay of reduced film thickness and different patterning-relevant underlayers is developed by looking at the glass transition temperature (Tg) of polymer-based resists. To minimize the ambiguity of the results due to resist additives (i.e., photoacid generator (PAG) and quencher), it was opted to move forward with polymer-only samples, the main component of the resist, at this stage of the investigation. By using dielectric response spectroscopy, the results obtained show that changing the protection group of the polymer, as well as altering the polymer film thickness impacts the dynamics of the polymer mobility, which can be assessed through the Tg of the system. Unexpectedly, changing the underlayer did not result in a clear change in the polymer mobility at the tested film thicknesses.

No abstract