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As new alloys are being developed for additive manufacturing (AM) applications, questions related to the temperature-dependent structural and compositional stability of these alloys remain. In this work, the benefits and limitations of a unique method for testing this stability are presented. This system employs the use of polychromatic synchrotron light to perform energy-dispersive x-ray diffraction (ED-XRD) on an electrostatically levitated sample at high temperatures. In comparison with a traditional angular-dispersive setup, the container-less electrostatic levitation method has unique advantages, including quicker acquisition times, simultaneous compositional information through fluorescence emissions, a reduction in background noise, and, importantly, concurrent/subsequent measurement of thermophysical properties. This combined method is ideal for phase transition studies by holding the levitated sample at a stable position and temperature through controlled heating and temperature management. To illustrate these capabilities, we show ED-XRD data of the well-known martensitic phase transition (hcp to bcc) in Ti–6Al–4V. In addition, results from the novel alloy Ni51Cu44Cr5 are presented. This alloy is shown to maintain an fcc structure upon heating. However, the concentration of Cu is reduced at high temperatures, resulting in a decrease in the lattice constant. As concurrent thermophysical properties are probed, these preliminary structure and composition experiments demonstrate the capabilities of this technique to determine the composition–processing–structure–properties of metal alloys for AM. 

Abstract Molecular Dynamics (MD) simulation of biomolecules provides important insights into conformational changes and dynamic behavior, revealing critical information about folding and interactions with other molecules. The collection of simulations stored in computers across the world holds immense potential to serve as training data for future Machine Learning models that will transform the prediction of structure, dynamics, drug interactions, and more. Ideally, there should exist an open access repository that enables scientists to submit and store their MD simulations of proteins and protein-drug interactions, and to find, retrieve, analyze, and visualize simulations produced by others. However, despite the ubiquity of MD simulation in structural biology, no such repository exists; as a result, simulations are instead stored in scattered locations without uniform metadata or access protocols. Here, we introduce MDRepo, a robust infrastructure that provides a relatively simple process for standardized community contribution of simulations, activates common downstream analyses on stored data, and enables search, retrieval, and visualization of contributed data. MDRepo is built on top of the open-source CyVerse research cyber-infrastructure, and is capable of storing petabytes of simulations, while providing high bandwidth upload and download capabilities and laying a foundation for cloud-based access to its stored data. 

BackgroundMolecular Dynamics (MD) simulation of biomolecules provides important insights into conformational changes and dynamic behavior, revealing critical information about folding and interactions with other molecules. This enables advances in drug discovery and the design of therapeutic interventions. The collection of simulations stored in computers across the world holds immense potential to serve as training data for future Machine Learning models that will transform the prediction of structure, dynamics, drug interactions, and more. A needIdeally, there should exist an open access repository that enables scientists to submit and store their MD simulations of proteins and protein-drug interactions, and to find, retrieve, analyze, and visualize simulations produced by others. However, despite the ubiquity of MD simulation in structural biology, no such repository exists; as a result, simulations are instead stored in scattered locations without uniform metadata or access protocols. A solutionHere, we introduce MDRepo, a robust infrastructure that supports a relatively simple process for standardized community contribution of simulations, activates common downstream analyses on stored data, and enables search, retrieval, and visualization of contributed data. MDRepo is built on top of the open-source CyVerse research cyberinfrastructure, and is capable of storing petabytes of simulations, while providing high bandwidth upload and download capabilities and laying a foundation for cloud-based access to its stored data. 

MOF NU-1000 was employed to host Ni tripodal complexes prepared from new organometallic precursors [HNi(κ4(E,P,P,P)-E(o-C 6 H 4 CH 2 PPh 2 ) 3 ], E = Si (Ni-1), Ge (Ni-2). The new heterogenous catalytic materials, Ni-1@NU-1000 and Ni-2@NU-1000 show the advantages of both homogenous and heterogeneous catalysts. They catalyze the hydroboration of aldehydes and ketones more efficiently than the homogenous Ni-1 and Ni-2, under aerobic conditions, and allowing recyclability of the catalyst.