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R&D: Inquiry-Based Introduction to Atomic Force Microscopy Techniques through Optical Storage Disc Surface Imaging

Guided inquiry investigation presented here introduces students to design and basic functions of AFM through identification of 3 unknown OSD samples (CD, DVD, or Blu-ray).

Journal of Chemical Education has published an article written by Senetta F. Bancroft, School of Education, Southern Illinois University Carbondale, 625 Wham Drive, Mail Code 4610, Carbondale, Illinois 62901, United States, and School of Chemical and Biomolecular Sciences, Southern Illinois University Carbondale 1245 Lincoln Drive, Mail Code 4409, Carbondale, Illinois 62901, United States, M. Aswad Ali, and Punit Kohli, School of Chemical and Biomolecular Sciences, Southern Illinois University Carbondale 1245 Lincoln Drive, Mail Code 4409, Carbondale, Illinois 62901, United States.

Abstract: Scanning probe microscopy such as atomic force microscopy has become increasingly integrated and relevant in undergraduate laboratory investigations. As the ‘hands and eyes of the nanoworld’, atomic force microscopes (AFMs) continue to be used to innovate the nanowriting process for data storage and in the exploration of novel materials suitable for ultrafast, nonvolatile, high density memory storage. Optical storage discs (OSDs) coevolved with AFM technology, are relatively inexpensive, and are easily available for purchase. They can, consequently, serve as a relevant phenomenon for undergraduate students to explore nanoscale material structure and macroscopic function through an AFM. The guided inquiry investigation presented here introduces students to the design and basic functions of an AFM through their identification of three unknown OSD samples (CD, DVD, or Blu-ray). The surface of each OSD is explored through students’ collection and interpretation of topographic and force curve data using an AFM to identify differences in the structure of the grooves containing pits and lands, estimation of theoretical storage capacity, and finally distinguish OSD types by comparing their data and calculations to known structures and capacities.

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