Encoding data into metal alloys using laser powder bed fusion

• Main Authors: Sofinowski, Karl, Wittwer, Mallory, Seita, Matteo
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Materials; Additive Manufacturing; Laser Powder Bed Fusion
• Online Access: https://hdl.handle.net/10356/162399
• Institution: Nanyang Technological University

Beyond near-net shape manufacturing of parts with complex geometry, additive manufacturing (AM) makes it possible to fabricate materials with distinct, site-specific microstructures. This ability is unique to AM and enables the design of architected materials that were previously unattainable. Here, we leverage this strategy to encode data into metal parts using the microstructure as the medium to store information. We use a novel laser scanning technique to control the local solidification conditions during laser powder bed fusion and embed a linear barcode and Quick Response (QR) code into stainless steel 316 L. The codes use blocks of different crystallographic texture–i.e., regions in which the crystal lattice of most grains is aligned towards a preferred orientation–as the data “bits”. The data may be retrieved by analytical techniques that are sensitive to local microstructure variations. As a demonstration, we decode the barcodes by measuring the scattering of optical light from their etched surface using a technique called directional reflectance microscopy. The resulting texture maps are readable by conventional barcode scanners, such as those found on mobile phones. The ability to embed data has significant potential in fields such as law enforcement, biomedicine, and transportation, where permanent, damage-resistant tracking is essential.