Understanding molecular scale effects during photoresist processing
type: CreativeWork
description: The dimensional tolerances of photoresist features are now at the nanometer scale, where effects of individual molecules are important. In recognition of the industrial need for a molecular-scale understanding of photoresist performance, mechanistic models have been developed for each of the several photolithography processes that are used with positive-tone, chemically amplified photoresists: film creation, exposure, post exposure bake, and development. These models are based on experimental studies that have clarified details of photoresist function including the photochemical quantum efficiency of photoresist exposure, the reaction-diffusion properties of exposure photoproducts, and the complex dissolution behavior of phenolic homopolymers and copolymers in aqueous base. A dynamic Monte Carlo simulation has been developed to test the experimentally derived models and further examine the underlying physical processes relevant to photoresist patterning. This mesoscale simulation consists of distinct modules for each processing step, each of which captures the appropriate chemical and physical phenomena at the molecular scale. The several simulation modules have yielded results that are qualitatively correct for every major resist processing step. The inputs to the simulation are fundamental and measurable material and processing parameters and empirical calibrations are not required. The chemical detail included in the models enables investigation of the wide formulation variable space. Furthermore, the mesoscale nature of the simulation offers the unique ability to study the stochastic processes that contribute to resist feature roughness. This simulation thus provides a useful predictive tool to guide the rational design of new photoresist materials and the optimization of photolithography processes.
abstract: The dimensional tolerances of photoresist features are now at the nanometer scale, where effects of individual molecules are important. In recognition of the industrial need for a molecular-scale understanding of photoresist performance, mechanistic models have been developed for each of the several photolithography processes that are used with positive-tone, chemically amplified photoresists: film creation, exposure, post exposure bake, and development. These models are based on experimental studies that have clarified details of photoresist function including the photochemical quantum efficiency of photoresist exposure, the reaction-diffusion properties of exposure photoproducts, and the complex dissolution behavior of phenolic homopolymers and copolymers in aqueous base. A dynamic Monte Carlo simulation has been developed to test the experimentally derived models and further examine the underlying physical processes relevant to photoresist patterning. This mesoscale simulation consists of distinct modules for each processing step, each of which captures the appropriate chemical and physical phenomena at the molecular scale. The several simulation modules have yielded results that are qualitatively correct for every major resist processing step. The inputs to the simulation are fundamental and measurable material and processing parameters and empirical calibrations are not required. The chemical detail included in the models enables investigation of the wide formulation variable space. Furthermore, the mesoscale nature of the simulation offers the unique ability to study the stochastic processes that contribute to resist feature roughness. This simulation thus provides a useful predictive tool to guide the rational design of new photoresist materials and the optimization of photolithography processes.
author: Schmid, Gerard Michael
language: eng
keywords: Photoresists, Photolithography
date published: 2003-05
date modified: 2026-07-24T05:01:22Z
provider: University of Texas
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: The University of Texas at Austin

PropertyValue
property ID: Handle
value: http://hdl.handle.net/2152/12503