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/Job opportunities/Ab initio modeling of Extreme UV - Matter interactions

Ab initio modeling of Extreme UV - Matter interactions

PhD - Leuven | More than two weeks ago

Unlock the next generation of lithography by pushing the frontier of polymer excited states chemistry

For many decades, progress in the electronics industry has been, driven by the miniaturization of integrated circuits (ICs). Besides getting smaller, the circuit designs are also getting more and more complex. Creating the patterns to realize these circuits on a chip is performed by using a photolithography step. In photolithography, a mask is combined with a chemical photoresist to selectively irradiate, by a laser light source, a desired sensitized pattern. The latter is afterwards etched away. The wavelength of the laser light ultimately restricts how small the dimensions of the printed patterns can be made. To produce the patterns of the next generation of nanoelectronics, imec is using a 13nm laser light, referred to as being an Extreme UltraViolet (EUV) source. With such a source of excitation, the irradiation is strongly impacting on the electronic structure of the irradiated materials, leading to complex structural degradation of both the mask and chemical photoresist. Which such an energy (90eV), the light source does not directly interact with the valence electrons, which participate in chemical bonding, but with much more strongly bound core electrons. Working at these high energies, therefore, makes for a much more complex chemistry than traditionally used in. Developing a better understanding of this radiative chemistry is hence essential to keep on enabling the design of new polymer blends to support the fabrication of the next generation of electronic devices.

To investigate the fundamentals of photoresist chemistry at EUV energies, imec has built a new spectroscopic facility, where the signatures of the photoresists can be monitored starting from only tens of attoseconds after the interaction with an EUV pulse. Changes in various spectroscopic spectra indicate the occurrence of reaction steps and build a unique signature of the material degradation process. However, determining what is happening at the atomic level from the lone reading of spectra is far from being a trivial task.

Through this Ph.D. proposal, we aim solving this issue by taking advantage of the predicting power of atomistic simulations to allow a comparison of the measured spectra to state-of-the-art quantum chemical calculations and to understand the degradation mechanisms that take place. Performing these calculations and building fundamental insights of the full process will help developing the much-needed understanding of what happens in EUV photoresists and constitutes the skeleton of this PhD. project.

In the course of this project, the PhD. student will be performing state-of-the-art ab initio calculations. Carrying-on this correctly and efficiently requires a proper understanding of the theoretical concepts on which the methods are based and on their implementation in computer code to be executed on super computers. The type of simulations to perform also requires an understanding of the relevant chemistry. During the project the understanding and the necessary skills will be trained at imec.

To be eligible, applicants must have a Master degree in, either physics or chemistry, focusing on theoretical aspects. Due to the complexity and the high amount of individual calculations, an efficient and robust automation and data processing infrastructure is essential. We continuously develop and improve such an infrastructure for all our calculations, written in python. Good knowledge of this language is hence required. A strong motivation, a good knowledge of solid-state physics or quantum chemistry and UNIX/LINUX are a plus. Excellent writing and oral communication skills are desired.

Required background: Master degree in physics or chemistry

Type of work: literature 10 % and 90 % modeling

Supervisor: Michel Houssa, ,

Daily advisor: Michiel van Setten

The reference code for this position is 2020-041. Mention this reference code on your application form.