In advanced technology nodes, where the critical dimensions of devices scale down to sub 10 nm, the structural integrity can be greatly affected by interfacial forces or stresses due to their large surface to volume ratio. This is especially the case for high aspect ratio FinFET or memory structures subjected to a wet processing step, where their stability is determined by the competition between the capillary interactions/surface adhesion and the mechanical rigidity of the structures. In cases where the interaction with the solvent dominates the mechanical integrity of the device, the structure undergoes a pattern collapse process, which can hardly be recovered. Therefore, to find the ultimate limit of scaling for damage-free wet processing, it is important to understand the mechanical properties and the nature of the physicochemical interactions that occur at the nanoscale. This Ph.D. topic aims providing this understanding by combining different advanced characterization techniques together with modeling approaches that will provide insights into the mechanisms that drive the process at both the macroscopic and at the atomistic scales.
In-situ characterization techniques are critical for capturing the dynamic process of capillary interactions with nanostructures. Several advanced techniques have been developed in the past few years1–4. In this project, attenuated total reflectance--Fourier transform infrared (ATR-FTIR) spectroscopy will be used to investigate the impact of different surface chemistry and geometry profile on wetting properties of heterogeneous surfaces2,4. Nanoscale structural bending under the influence of capillary interfaces will be characterized by an environmental TEM3. The impact of reduced dimensions, material stacks, structural profiles and surface functionalization on the mechanical rigidity will be systematically investigated.
The successful candidate should have a background in physics and engineering, with strong problem-solving skills and good writing and oral communication skills. Some basic programming skills are a plus.
1. Xu, X. et al. Capturing wetting states in nanopatterned silicon. ACS Nano 8, 885–93 (2014).
2. Vrancken, N. et al. Superhydrophobic breakdown on nanostructured surfaces characterized by in-situ ATR-FTIR. Langmuir 33, 3601–3609 (2017).
3. Aabdin, Z. et al. Transient clustering of reaction intermediates during wet etching of silicon nanostructures. Nano Lett. 17, 2953–2958 (2017).
4. Vrancken, N. et al. In-situ ATR-FTIR for dynamic analysis of superhydrophobic breakdown on nanostructured silicon surfaces. Sci. Rep. 8, 1–12 (2018).
Type of work: 10% literature, 60% experiments and 30 % modeling
Required background: Engineering Science
Supervisor: Stefan De Gendt
Daily advisors: XiuMei Xu and Geoffrey Pourtois
The reference code for this position is 1812-90. Mention this reference code on your application form.