Deciphering the Reaction Mechanism in EUV Photoresist Models

The semiconductor industry has started to use extreme ultraviolet (EUV) lithography for printing ever smaller nanometer-sized features on wafers to produce integrated circuits. Especially metal-containing photosensitive materials, such as tin metal-oxide clusters, are yielding promising results because of their higher absorption cross section in the EUV compared to organic materials. This is important for keeping the exposure dose low and the throughput high in a commercial EUV scanner. However, the knowledge on the chemical mechanism in EUV resists is still scarce. Gas phase experiments on model molecules for resists allow to isolate the interaction of EUV photons with the material and contribute to building a step-by-step picture of the reaction sequence in EUV photoresists upon exposure.

In this project the photoionization of a metal oxide model molecule will be studied in the gas phase employing EUV synchrotron radiation during a one-week beamtime at Elettra Sincrotrone Trieste, Italy (June 2023). The photoelectron and ion mass spectra as well as an electron-ion coincidence detection scheme will yield deep insights into the photoemission and fragmentation of this resist prototype upon interaction with EUV photons. The experimental findings will be complemented by a computational study in order to model the reaction mechanism. These insights are useful to understand the chemistry of metal-oxide resists, especially the formation of unwanted reactive intermediates. This will help photoresist companies to develop new materials requiring lower doses, enable higher resolution and lead to less pattern defects, which will enable the economic production of better integrated circuits.

The scope of this work is to use and develop tools for the analysis of multiplexed experimental data and modeling the chemical mechanism employing quantum chemistry simulations. The candidate will have some freedom in setting the focus either on the former or the latter. Basic experience in the use of data analysis programs and/or quantum chemical software packages is required.

10 % experimental, 45 % data analysis, 45 % simulations