The research objective of this award is to develop theories and algorithms for tip-specimen shape interaction modeling for an emerging class of scanning probe microscopy (SPM) instruments. The resulting methods will support imaging general 3D structures with vertical sidewalls and undercut features at the nanometer or even atomic scale. The current image produced by such a microscope is a distorted representation of the specimen due to the dilation produced by the finite size of the tip. The tip-specimen shape interaction must be modeled to understand the relationship among tip shape, specimen surface, and the resulting SPM image in order to remove the distortion of the image. This research uses a tri-dexel for tip and specimen shape representation. Principled methods based on 3D mathematical morphology and their efficient implementation on graphics hardware will be developed for fast SPM imaging simulation, accurate surface reconstruction, and robust tip estimation. Experimental validation will draw specimens from state-of-the-art semiconductor and data storage devices.

If successful, the results of this research will provide a means to understand and correct potential dimensional bias in SPM imaging of general 3D nanostructures. It will lead to high accuracy and high throughput 3D reconstruction in nano-imaging of these structures. The collaboration with Veeco and NIST provide ample opportunity to testbed these methods on highly reentrant and morphologically complex nanostructures typically found in industrial settings. It can positively impact the entire spectrum of industries that use SPM such as semiconductor, data storage, MEMS, and molecular imaging industries. It will thus provide a metrological basis for nanoscale manufacturing. Through its integrated research, education and outreach activities, this project will provide advanced knowledge in mathematical morphology and nano-imaging for students from high school to graduate school and will increase domestic students' interest in science and engineering resulting in strengthened competitiveness in the global workforce.

Project Start
Project End
Budget Start
2008-09-01
Budget End
2012-08-31
Support Year
Fiscal Year
2008
Total Cost
$320,237
Indirect Cost
Name
Illinois Institute of Technology
Department
Type
DUNS #
City
Chicago
State
IL
Country
United States
Zip Code
60616