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/Job opportunities/Achieving high-resolution, quantitative tomography of 3-dimensional nano-scale devices

Achieving high-resolution, quantitative tomography of 3-dimensional nano-scale devices

PhD - Leuven | More than two weeks ago

Unravelling the 3D structure of next generation nano-scale devices

Advanced semiconductor technology heavily relies on 3D concepts such as nanosheets with critical dimensions below 7 nm. The functionality and performance of these devices is a tight interplay between the structure and chemical composition at the atomic level. Clearly, device fabrication and characterization, two processes that must go hand-in-hand, become increasingly complex and call for clever fabrication and 3D metrology solutions with close to atomic precision (“if you can’t see it, you can’t improve it”). Driven by this quest, two important and highly complementary microscopy concepts have emerged over the last years as key players: Transmission Electron Microscopy/Tomography (TEM) and atom probe tomography (APT). While TEM/EDS offers superior spatial resolution and accuracy, elemental sensitivity is a bottleneck in the analysis of advanced nano-devices. On the other end, APT provides high elemental selectivity (from H to U) and sensitivity, but its quantitative and spatial accuracy is strongly degraded in heterogeneous systems. Ultimately, the complementary (hybrid) use of both concepts shows great potential for 3D atomic-scale analysis as it would overcome these limitations. Albeit their analytical power, TEM/APT analysis of complex nanostructures and novel materials suffers from numerous challenges (sample preparation, quantification, reconstruction), particularly for hybrid approaches, that need to be addressed to achieve the analytical precision and accuracy demanded by the industry.

This project will focus on the development needs for the 3D nanoscale characterization by TEM/APT of 5 nm node (and below) single devices. This would require:

a)     Learning FIB, TEM and APT methodologies relevant to future CMOS based memory and logic device fabrication.

b)  Evaluating and understanding the role of TEM/APT specimen thickness, associated ion beam damage and/or beam-driven dynamics on analysis results and analytical power (artefacts, spatial and quantification uncertainty, limitations, etc.).


c)     Developing analytical workflows, data processing and physics-based analysis protocols (data correlation, de-noising, background correction, etc.) to enable high resolution, quantitative 3D hybrid metrology.

d)    Understanding root-causes and physical mechanisms behind quantification inaccuracy in APT and EDX/STEM tomography. Developing appropriate correction schemes to improve the 3D chemical quantification accuracy of heterogeneous nanostructures for hybrid analysis. Benchmarking and validating of analysis results against complementary techniques such RBS, SIMS, etc. when applicable.

e) Understanding the physics that lead to artifacts in the APT spatial reconstruction and optimizing the reconstruction procedures relying on TEM information.

Through this PhD, the successful applicant will interact with the integration, test, design, and analysis groups at imec in order to map out metrology process flows with optimization of TEM and APT insertion points being of primary interest. This could also include examination/development of hybrid approaches (pulling in information from other metrology techniques and/or feed-forward approaches) as well as Machine Learning approaches (have the machine do the predefined applications).

To be eligible, applicant must have a master’s degree in either physics, nanoscience or chemistry, with a strong background in solid-state physics, material science and/or materials characterization. As the PhD will include a large amount of experimental work on complex systems, previous analytical experience would be beneficial. A basic knowledge of semiconductor process flows would also be a plus.



Required background: Master physics/chemistry/materials science/nanotechnology

Type of work: 70% experimental, 30% theoretical

Supervisor: Sara Bals

Co-supervisor: Claudia Fleischmann

Daily advisor: Olivier Richard, Jeroen Scheerder

The reference code for this position is 2021-006. Mention this reference code on your application form.

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