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Unique tags are often added to items to prevent counterfeiting and tampering. While there are many techniques for generating unique patterns, tags that are inexpensive, scalable, easy to read, and difficult to replicate are particularly useful for tracking applications. In this work, we present a novel tagging concept that utilizes self-assembly methods to create physically unclonable patterns using magnetic particles. By combining a distribution of Nd-Fe-B magnetic particles with a hard polymer inside a strong magnetic field, patterns are generated that are easily read using magneto-optic techniques. Image processing and template matching techniques are then used to determine the likelihood that two different magnetic tags are classified as the same. For optimal selections of particle percent mass, statistical analysis predicts that pattern matching yields at most one false positive for every 1015 true positives. Results further illustrate that variations in particle size and particle percent mass have a strong effect on the predicted pattern uniqueness. Finally, a magnetic field model was then used to help predict broad trends in pattern statistics and particle structures. This paper shows that magnetic self-assembly patterns hold promise as unique embedded tags for a large range of applications from microelectronics to luxury goods to low-cost off-the-shelf items.

Recent work in the development of glass-ceramic scintillators at the Georgia Tech Research Institute (GTRI) has focused on modifying formulation of the oxide host glass and scintillating crystal phase, secondary heat treatment (ceramization) schedule, and processing improvement to ensure optical quality. These efforts have yielded considerable performance improvements to glass-ceramic scintillators, and have made them among the most promising composite scintillators under investigation. However, these materials still fall short of current commercially-available single crystal scintillators, and so new avenues must be pursued for continued improvements. The present investigation uses predictive simulations to inform the materials selection and process design for high refractive index layers to improve light extraction from the scintillator, and increased light output via bulk or surface plasmon interactions.

The field of quantum information processing is rapidly advancing. As the control of quantum systems approaches the level needed for useful computation, the physical hardware underlying the quantum systems is becoming increasingly complex. It is already becoming impractical to manually code control for the larger hardware implementations. In this chapter, we will employ an approach to the problem of system control that parallels compiler design for a classical computer. We will start with a candidate quantum computing technology, the surface electrode ion trap, and build a system instruction language which can be generated from a simple machine-independent programming language via compilation. We incorporate compile time generation of ion routing that separates the algorithm description from the physical geometry of the hardware. Extending this approach to automatic routing at run time allows for automated initialization of qubit number and placement and additionally allows for automated recovery after catastrophic events such as qubit loss. To show that these systems can handle real hardware, we present a simple demonstration system that routes two ions around a multi-zone ion trap and handles ion loss and ion placement. While we will mainly use examples from transport-based ion trap quantum computing, many of the issues and solutions are applicable to other architectures.