Mesoscale simulation of the photoresist process and hydrogel biosensor array platform indexed by shape

Advances in microlithography have driven the rapid progression of semiconductor technology. However, the number and complexity of issues facing microlithography engineers have also increased significantly. Today, it is neither time nor cost-efficient to run large optimization experiment matrices. Instead, simulators are used to explore the huge process space, so that only small, fine-tuning experiments are necessary. Current commercial simulators make use of empirically derived continuum models. This approach has many advantages, especially computation speed, but it is not without limitations. The predictive power of empirically fit models is severely limited outside the input parameter range and stochastic processes such as shot noise and acid diffusion are not considered. These limitations make it difficult to simulate and diagnose molecular-scale effects such as line edge roughness (LER) that are becoming significant problems. To address these issues, a first-principles “mesoscale” photoresist simulator was devised by past researchers, and further developed by the author. A base quencher model was added to help elucidate the effects of base on LER. Quantum mechanical estimation techniques were used to calculate more accurate interaction energies; these calculations led to aggregation of photoacid generator molecules in the photoresist, which was quantified. A serious limitation of mesoscale simulation is relatively long computation times. Thus, several efforts were made to improve the speed of the models. The advances of the biochemistry and semiconductor fields in the 1980s led to the development of biochips in the 1990s. These devices enable rapid and simultaneous screening of a large number of biological analytes in a compact space, for a variety of applications. Cancer diagnosis through DNA typing, public water systems testing, and airline cargo screening are just a few of the active biochip research areas. To achieve these ends, DNA, RNA, proteins, and even living cells are being employed as sensing mediators. However, current microarray fabrication techniques are either too expensive or too limiting to achieve usage outside of specialized settings. The limitations of current biochip platforms led the author and colleagues to develop an alternative system using lithographically produced hydrogel biosensors. Hydrogel sensors (”MUFFINS”) were made that use their shape to index chemical and biological function. This platform utilizes self-assembly and pattern recognition techniques to create compact, computer-readable sensor arrays.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Business Administration

Grantor

The University of Texas at Austin

Year dc:date.issued

2005

Author dc:creator

• Meiring, Jason Elliot

Advisor dc:contributor.advisor

• Willson, C. G. (C. Grant), 1939-

Statement dc:rights

• Copyright is held by the author. Presentation of this material on the Libraries' web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works.

Language dc:language.iso

eng

Identifier

b60809565

OAI identifier oai:identifier

oai:repositories.lib.utexas.edu:2152/2034