Three-Dimensional Printing of Magnetic Data Storage Structures
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MRS Advances © 2019 Materials Research Society DOI: 10.1557/adv.2019.87
Three-Dimensional Printing of Magnetic Data Storage Structures Authors: Corey Breznak and Paris von Lockette Affiliations: The Pennslyvania State University, 160 Hammond Building
University Park, PA 16803, U.S.A.
Abstract
Bar codes and quick response codes are the standard methods of visual data storage. These codes rely on changes in visual patterns to encode data into a binary format. Problems with these methods include limited data storage capacity and poor visual appeal in product marketing. This work examined magnetic patterns as an alternative to visual patterns as a potential means to encode data. Using magnetic patterns it is theorized that data storage capacity can be improved, while embedding the code within a tagged object. Magnetic patterns were formed using neodymium magnets, which yielded results that are similar to a bar code. Lines of high magnetic field strength followed by regions of low magnetic field strength at different spacing produced different overall magnetic patterns. Next, magnetic patterns were 3-dimensionally printed using an iron and polylactic acid commercial filament. The effect of infill density and the print line of the magnetic regions were studied by measuring the attractive force between the sample and a neodymium magnet attached to a force gauge for different print configurations. As expected the infill density of 100% had the highest force, which was roughly 330 mN, while the 10% sample had the lowest force being about 120 mN. It was expected that print line should not have an influence on magnetic force, but in this experiment magnetic regions with print lines at 0° were about 10 mN higher than samples printed at 90°. The cause of this was likely due to the printer error. Future work will study print plane, which is another processing variable in 3-dimensional printing. The target goal of matching the data storage capability of QR codes will also be work towards.
INTRODUCTION Currently, bar codes and quick response (QR) codes are a primary method of data storage. Bar codes encode data in a binary format by using groups of parallel lines with varying distance between them. The more complex QR code is a 2-dimensional form of the standard bar code. Unlike a bar code, it can scanned from any direction. QR
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codes more importantly, hold roughly 350 times more data than a bar code [1]. Since the data is extracted visually from these codes, smart phones have become a useful tool in reading data encoded in bar codes and QR codes [2,3]. The patterns and structures within a QR code have the following main functions: symbol alignment, sampling grid determination and error correction [4]. Data is encoded using black and white modules containing several pixels. The struct
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