As the rapid expansion of artificial intelligence (AI) drives demand forhigher-capacity memory solutions, the semiconductor industry is exploring novelmemory architectures beyond conventional DRAM. The most promising approach is 3D-DRAM,where memory cells are vertically stacked to substantially increase storagedensity [1]. A key building block of these architectures is the fabrication ofthick multilayer structures, consisting of repeated ONO (SiO₂/SiNx) [2] or Si/SiGe [3] layer pairs. Asthese stacks grow from tens to nearly one hundred bilayers and thus reach a totalthickness of several micrometers, precisely controlling layer thickness andinterface quality becomes challenging due to strain [3]. Thickness and interface variations may propagate throughout the stack and ultimately leadto nonuniform devices.
This internship focuses on the development of advanced X-raytechniques to characterize the thick multilayer structures occurring in future3D-DRAM technologies [4,5]. In particular, the work will employ X-rayreflectivity (XRR) and High-resolution X-ray diffraction (HR-XRD) toquantify multilayer periodicity, individual layer thicknesses, and interfacequality throughout the stack. In addition, synchrotron-basedgrazing-incidence small-angle X-ray scattering (GISAXS) and diffusescattering measurements will be used to investigate interface waviness andcorrelations between buried interfaces [4]. These techniques provide uniquenon-destructive access to deeply buried layers, overcoming limitations ofconventional optical and electron microscopy methods [2,5]. The X-ray resultswill be benchmarked against established reference techniques such as transmissionelectron microscopy (TEM).
The student will join imec's team of experts in metrology and materialscharacterization for advanced semiconductor technologies. The internship willstart with exploring X-ray characterization techniques and the material systems.Then, the student will focus on the analysis and interpretation of lab-scale X-rayspectra acquired from ONO and Si/SiGe samples with varying layer thickness, stackheights and interfaces. Finally, complementary spectra are collected with highcounting statistics during a synchrotron beamtime. The precise content of theproject will be aligned with the interests of the student.
We seek a candidate with a background in physics, materials science,nanotechnology, or a related field, and a strong interest in experimental work, data analysis and theoretical interpretation. The ideal candidate is analytical,meticulous, and comfortable with mathematical concepts. Basic familiaritywith X-ray techniques, data analysis, statistics, or scientific programming isappreciated but not required. This internship offers hands-on experience withstate-of-the-art metrology, exposure to cutting-edge semiconductor memoryresearch, and insight into the relationship between multilayer growth,interface morphology, and the future scaling of 3D-integrated memorytechnologies.
References:
[1] Belmonte, A., & Kar, G. S. (2025). Disrupting the DRAM roadmapwith capacitor-less IGZO-DRAM technology. Nature Reviews ElectricalEngineering, 2(4), 220-221. https://doi.org/10.1038/s44287-025-00162-w
[2] Kwak, H., et al. (2021).Non-destructive thickness characterisation of 3D multilayer semiconductordevices using optical spectral measurements and machine learning. Light:Advanced Manufacturing, 2(1), 9-19. 10.37188/lam.2021.001
[3] Loo, R., et al. (2025).Epitaxial growth of up to 120×{Si0. 8Ge0. 2/Si} bilayers in view of three-dimensionaldynamic random access memory applications. Jour of App Phys, 138(5).https://doi.org/10.1063/5.0260979
[4] Siffalovic, P., Jergel, M., &Majkova, E. (2011). GISAXS-probe of buried interfaces in multilayered thinfilms. X-ray Scattering, 1-54.
[5] Ming, Z. H., etal. (1993). Microscopic structure of interfaces in Si1− xGex/Si heterostructuresand superlattices studied by x-ray scattering and fluorescence yield. PhysRev B, 47(24), 16373. https://doi.org/10.1103/PhysRevB.47.16373
Type of internship: Master internship
Duration: Minimally 6 months
Required educational background: Physics, Nanoscience & Nanotechnology, Materials Engineering
University promotor: Claudia Fleischmann (KU Leuven)
Supervising scientist(s): For further information or for application, please contact Ruben Van der Borght (< correo electrónico eliminado por razones de seguridad >) and Mohamed Saib (< correo electrónico eliminado por razones de seguridad >) and Janusz Bogdanowicz (< correo electrónico eliminado por razones de seguridad >)
The reference code for this position is 2026-INT-328. Mention this reference code in your application.
Only for self-supporting students.
Applications should include the following information:
Incomplete applications will not be considered.
This internship focuses on the development of advanced X-raytechniques to characterize the thick multilayer structures occurring in future3D-DRAM technologies [4,5]. In particular, the work will employ X-rayreflectivity (XRR) and High-resolution X-ray diffraction (HR-XRD) toquantify multilayer periodicity, individual layer thicknesses, and interfacequality throughout the stack. In addition, synchrotron-basedgrazing-incidence small-angle X-ray scattering (GISAXS) and diffusescattering measurements will be used to investigate interface waviness andcorrelations between buried interfaces [4]. These techniques provide uniquenon-destructive access to deeply buried layers, overcoming limitations ofconventional optical and electron microscopy methods [2,5]. The X-ray resultswill be benchmarked against established reference techniques such as transmissionelectron microscopy (TEM).
The student will join imec's team of experts in metrology and materialscharacterization for advanced semiconductor technologies. The internship willstart with exploring X-ray characterization techniques and the material systems.Then, the student will focus on the analysis and interpretation of lab-scale X-rayspectra acquired from ONO and Si/SiGe samples with varying layer thickness, stackheights and interfaces. Finally, complementary spectra are collected with highcounting statistics during a synchrotron beamtime. The precise content of theproject will be aligned with the interests of the student.
We seek a candidate with a background in physics, materials science,nanotechnology, or a related field, and a strong interest in experimental work, data analysis and theoretical interpretation. The ideal candidate is analytical,meticulous, and comfortable with mathematical concepts. Basic familiaritywith X-ray techniques, data analysis, statistics, or scientific programming isappreciated but not required. This internship offers hands-on experience withstate-of-the-art metrology, exposure to cutting-edge semiconductor memoryresearch, and insight into the relationship between multilayer growth,interface morphology, and the future scaling of 3D-integrated memorytechnologies.
References:
[1] Belmonte, A., & Kar, G. S. (2025). Disrupting the DRAM roadmapwith capacitor-less IGZO-DRAM technology. Nature Reviews ElectricalEngineering, 2(4), 220-221. https://doi.org/10.1038/s44287-025-00162-w
[2] Kwak, H., et al. (2021).Non-destructive thickness characterisation of 3D multilayer semiconductordevices using optical spectral measurements and machine learning. Light:Advanced Manufacturing, 2(1), 9-19. 10.37188/lam.2021.001
[3] Loo, R., et al. (2025).Epitaxial growth of up to 120×{Si0. 8Ge0. 2/Si} bilayers in view of three-dimensionaldynamic random access memory applications. Jour of App Phys, 138(5).https://doi.org/10.1063/5.0260979
[4] Siffalovic, P., Jergel, M., &Majkova, E. (2011). GISAXS-probe of buried interfaces in multilayered thinfilms. X-ray Scattering, 1-54.
[5] Ming, Z. H., etal. (1993). Microscopic structure of interfaces in Si1− xGex/Si heterostructuresand superlattices studied by x-ray scattering and fluorescence yield. PhysRev B, 47(24), 16373. https://doi.org/10.1103/PhysRevB.47.16373
Type of internship: Master internship
Duration: Minimally 6 months
Required educational background: Physics, Nanoscience & Nanotechnology, Materials Engineering
University promotor: Claudia Fleischmann (KU Leuven)
Supervising scientist(s): For further information or for application, please contact Ruben Van der Borght (< correo electrónico eliminado por razones de seguridad >) and Mohamed Saib (< correo electrónico eliminado por razones de seguridad >) and Janusz Bogdanowicz (< correo electrónico eliminado por razones de seguridad >)
The reference code for this position is 2026-INT-328. Mention this reference code in your application.
Only for self-supporting students.
Applications should include the following information:
- resume
- motivation
- current study
Incomplete applications will not be considered.
