/Thin films and patterning response in EUV device scaling

Thin films and patterning response in EUV device scaling

Leuven | More than two weeks ago

Explore the impact of material parameters of the thin films stack on EUV lithography patterning response

 

Extreme Ultraviolet (EUV) lithography stands as a pivotal advancement in semiconductor manufacturing, crucial for sustaining the industry's relentless pursuit of smaller and more powerful chips [1]. EUV lithography utilizes extremely short wavelengths of light, allowing for much finer feature sizes than conventional optical lithography. EUV technology has already enabled the production of cutting-edge processors and memory chips [2]. However, to push the boundaries even further, the industry is transitioning to High-NA EUV lithography [3]. This shift involves increasing the numerical aperture, which effectively enhances the resolution and precision of the lithographic process.
 
EUV lithography patterning and subsequent etching steps rely on the thin films stack that is used for pattern transfer into the final layer of interest. This stack has been engineered for both lithographic needs, as well as an optimized etch process in terms of selectivity and profile. However, the impact of the properties of this film stack on the patterning outcome are not well characterized or understood. The role of individual film material properties and interactions between layers need to be understood in relation to the outcomes of EUV patterning post lithography and post etch transfer (i.e., critical dimension (CD) control and its uniformity across the wafer, the line-edge roughness (LER) and line-width roughness (LWR), and the defectivity). The fundamental understanding of material properties and their relationship to EUV patterning outcomes will help drive advancements in High-NA innovation.
 
As part of this PhD work, you will work to define and systematically study the material properties that induce a change in the patterning outcome. You will quantify the impact of surface and bulk material properties on the resulting patterning metrics at lithography and etch levels. You will use advanced semiconductor processing tools in imec’s 300mm clean room, as well as characterization techniques such as Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), X-ray reflectivity (XRR), Time-of-Flight Secondary Ion Mass Spectrometry (TOFSIMS), and Atomic force microscopy (AFM). You will formulate directions on material design toward device scaling and material patterning strategy from a thin films perspective. You will also have the opportunity to work with  a team of researchers with vast experience on these topics that will be able to offer guidance and feedback. 
 
[1] M. van de Kerkhof et al., Solid State Electron 155, p20 (2019)
[2] Moore et al, IEEE Spectrum 55-1, p46 (2018)
[3] Levinson et al, Jpn. J. Appl. Phys. 61, SD0803-1 (2022)

.

Required background: chemical engineering; materials science and engineering; chemistry; nanoscience & nanotechnology; physics

Type of work: 10% modeling/simulation, 80% experimental, 10% literature

Supervisor: Annelies Delabie

Co-supervisor: Danilo De Simone

Daily advisor: Maria Chistiakova

The reference code for this position is 2024-044. Mention this reference code on your application form.

Who we are
Accept marketing-cookies to view this content.
Cookie settings
imec's cleanroom
Accept marketing-cookies to view this content.
Cookie settings

Related jobs

Unraveling Photoresist Exposure Mechanisms in Extreme Ultraviolet Lithography

Leverage advanced processing and materials characterization techniques to elucidate the mechanism responsible for printing the nanosized patterns of integrated circuits. 

Exposure dose control in Extreme Ultraviolet Lithography (EUVL)

Using the fundamentals of light-matter interaction to tackle a technological challenge for high volume semiconductor manufacturing.

Magnetic materials: atomic layer etching and passivation

You will be involved in state-of-the-art spin-logic CMOS research and benefit from our extensive know-how on material processing for nanoelectronics applications

Stripping polymers in semiconductor FAB processes: Impact of rheology and substrate-polymer interactions

You will actively participate in cutting-edge chip manufacturing research and development, acquiring hands-on expertise with state-of-the-art equipment, both at IMEC and within the Softmatter Rheology and Technology group at KU Leuven

Application of Continual Machine Learning and Causal Inference in Semiconductor Process Optimization: Towards Artificial General Intelligence

The goal of this research is to investigate continual learning adaptability in semiconductor process optimization and to establish the causal relationships (causal inference) in a data-centric approach.

Machine-Learning Enabled Extreme Ultraviolet Lenless Imaging of Semiconductor Structures and Devices

Leverage the power of machine learning to enable non-destructive imaging of advanced nano-sized structures and devices at the forefront of semiconductor technology.
Job opportunities

Send this job to your email