Doctoral Dissertations

Orcid ID

Date of Award


Degree Type


Degree Name

Doctor of Philosophy


Chemical Engineering

Major Professor

Manolis Doxastakis and Gila E. Stein

Committee Members

Bamin Khomami, Stephen J. Paddison, Ioannis Sgouralis


Quantitative reaction-diffusion models are critical for the development of high-resolution lithographic processes based on chemically amplified resists (CARs). CARs consist of a glassy polymer resin with a photoacid generator. Patterns are formed through a coupled reaction-diffusion process. It is known that reaction kinetics is controlled by the slow diffusion of acid-anion pairs (catalysts), and catalyst diffusion lengths partly control the pattern resolution and uniformity. However, it is difficult to quantify the diffusivity during reaction, let alone examine the roles of polymer-ion and ion-ion interactions on catalyst mobility, using direct measurements. This work presents a concerted experimental and computational effort to probe catalyst diffusion in a model CAR. Depth profiling experiments using time-of-flight secondary ion mass spectrometry offered a direct measure of catalyst diffusion lengths at moderate temperatures, while reaction kinetics was monitored with in-situ Fourier transform infrared spectroscopy. Multi-microsecond molecular dynamics simulations provided insight into ion-ion association, polymer-ion interactions, and transport mechanisms that influence diffusivities at temperatures well above the glass transition. By studying both reactive and inert CARs, it was shown that catalyst diffusion is significantly accelerated by reaction. It was hypothesized that this acceleration stems from plasticization by photoactivation and/or reaction byproducts, the generation of excess free volume following reaction, or a combination of these effects. Experiments confirmed that byproducts were present in the film and could contribute to accelerated catalyst diffusion, but this alone could not account for the discrepancy between reactive and inert CARs. Simulations showed that generation of excess free volume transiently accelerates local catalyst diffusivities, and that clustering of catalysts influences local reaction rates. A kinetic Monte Carlo model of transient local catalyst diffusivities was developed and captured the reaction kinetics determined from both simulations and experiments. Outcomes of the model demonstrated that accelerated catalyst diffusion could originate from generated excess free volume, and that deviations from the expected scaling of reaction rates with catalyst concentration are due to catalyst clustering. The methodology and insights can guide the development of predictive CAR models, thereby enabling studies of the physical and chemical processes that control pattern formation in next-generation materials.

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