Process Modeling for Dip Pen Nanolithography
Department
Mechanical and Aerospace Engineering
Major
Mechanical Engineering
Research Advisor
Bristow, Douglas A.
Advisor's Department
Mechanical and Aerospace Engineering
Abstract
Dip Pen Nanolithography (DPN) is 2-D nanoscale printing process. In DPN, an Atomic Force Microscope (AFM) probe is dipped into a specially formulated ink and then moved across a substrate to print the desired pattern. Although this process is commonly applied in research, the focus is on developing inks, not manufacturing. As such, the sophisticated transport models that have been developed do not translate easily to process planning and predicting product quality. This work develops a basic process modeling framework and process models for 16-Mercaptohexadecanoic acid (MHA). Samples of lines and dots are printed at varying speeds, pause times, and patterns. In addition to the process modeling, the printed patterns also reveal characteristics of the AFM such as hysteresis, that are as critical as the process model in obtaining desired patterns. The models developed in this work are the first steps toward process planning and control for high quality DPN.
Biography
Emily Briggs is currently a Mechanical Engineering junior who is an active member and officer of the Missouri S&T Robotics Competition Team for the past three years. Emily is also plays in the University and Community Symphony Orchestra.
Research Category
Engineering
Presentation Type
Poster Presentation
Document Type
Poster
Location
Upper Atrium/Hallway
Presentation Date
07 Apr 2010, 1:00 pm - 3:00 pm
Process Modeling for Dip Pen Nanolithography
Upper Atrium/Hallway
Dip Pen Nanolithography (DPN) is 2-D nanoscale printing process. In DPN, an Atomic Force Microscope (AFM) probe is dipped into a specially formulated ink and then moved across a substrate to print the desired pattern. Although this process is commonly applied in research, the focus is on developing inks, not manufacturing. As such, the sophisticated transport models that have been developed do not translate easily to process planning and predicting product quality. This work develops a basic process modeling framework and process models for 16-Mercaptohexadecanoic acid (MHA). Samples of lines and dots are printed at varying speeds, pause times, and patterns. In addition to the process modeling, the printed patterns also reveal characteristics of the AFM such as hysteresis, that are as critical as the process model in obtaining desired patterns. The models developed in this work are the first steps toward process planning and control for high quality DPN.
