Serial crystallography is the field of science that studies the structure and properties of crystals via diffraction patterns. In this paper, we introduce a new serial crystallography dataset comprised of real and synthetic images; the synthetic images are generated through the use of a simulator that is both scalable and accurate. The resulting dataset is called DiffraNet, and it is composed of 25,457 512x512 grayscale labeled images. We explore several computer vision approaches for classification on DiffraNet such as standard feature extraction algorithms associated with Random Forests and Support Vector Machines but also an end-to-end CNN topology dubbed DeepFreak tailored to work on this new dataset. All implementations are publicly available and have been fine-tuned using off-the-shelf AutoML optimization tools for a fair comparison. Our best model achieves 98.5% accuracy on synthetic images and 94.51% accuracy on real images. We believe that the DiffraNet dataset and its classification methods will have in the long term a positive impact in accelerating discoveries in many disciplines, including chemistry, geology, biology, materials science, metallurgy, and physics.

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A digital tracer scanner for studies of longitudinal selfdiffusion in thin films Rev. Sci. Instrum. 45, 9 (1974); 10.1063/1.1686456Errata: ``SelfDiffusion in Pb at 300°C by an Absorption Tracer Technique''

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Several countries in regional Latin America, including Argentina, Brazil, Chile, Mexico, and Peru, have active nuclear programs. Most of these programs involve small research reactors typically used to create various isotopes for medical and research purposes. Until recently, the highly radioactive spent fuel from these reactors was transported to the United States when it was removed from the various reactor sites. The United States has decided to cease acceptance of these waste materials, thereby requiring these Latin American countries to develop their own methods for dealing with the highly radioactive materials. The International Atomic Energy Agency (IAEA), the arm of the United Nations (UN) that deals with all forms of radioactive materials from weapons inspections to nuclear reactor safety, has undertaken a leadership role in the development of regional Latin America’s spent fuel storage/disposal plan. Acting as an IAEA mission expert, the author of this paper has aided in the development of the teams responsible for the development of both a Type B transportation cask and a long-term storage cask for these materials. This paper will discuss the overall scope and current status of these projects as well as detail the involvement of the author in helping to develop the ability of the design team members to find viable solutions to this problem.