We present a new version of the Ogre open source Python package with the capability to perform structure prediction of epitaxial inorganic interfaces by lattice and surface matching. In the lattice matching step a scan over combinations of substrate and film Miller indices is performed to identify the domain-matched interfaces with the lowest mismatch. Subsequently, surface matching is conducted by Bayesian optimization to find the optimal interfacial distance and inplane registry between the substrate and film. For the objective function, a geometric score function is proposed, based on the overlap and empty space between atomic spheres at the interface. The score function reproduces the results of density functional theory (DFT) at a fraction of the computational cost. The optimized interfaces are pre-ranked using a score function based on the similarity of the atomic environment at the interface to the bulk environment. Final ranking of the top candidate structures is performed with DFT. Ogre streamlines DFT calculations of interface energies and electronic properties by automating the construction of interface models. The application of Ogre is demonstrated for two interfaces of interest for quantum computing and spintronics, Al/InAs and Fe/InSb.

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Background Nearly half of American adults fail to meet national guidelines for physical activity (PA). As a major contributor to the development of preventable chronic diseases, insufficient PA is an important target for health behaviour interventions. Exercise is Medicine (EIM) aims to increase PA levels among primary care patients through routine PA evaluation, prescription, brief counselling, and referral to community resources. PA is treated as a vital sign with the goal of increasing PA levels in prescribed manageable doses. EIM is currently being implemented in UC San Diego Health System’s primary care clinics. Objective (i) To collect and summarize patient perceptions of EIM and its components. (ii) To identify discrepancies between patient-reported feedback and primary care provider (PCP) documentation in corresponding visit notes in the electronic medical record (EMR). Methods Patient recall of EIM components was measured using a 10-item survey distributed via MyChart. PCP documentation of EIM was tracked in the EMR system. Results Patient feedback (n = 316) about EIM components was positive and reinforced patients’ confidence in their ability to increase PA. Approximately 70% of patients reported having a PA discussion with their PCP at their most recent visit, but only approximately 21% of these discussions were documented by PCPs using the preprogrammed smartphrase in the EMR. Conclusion Overall, patients reported positive perceptions of EIM. While patient perceptions of EIM suggested that PA discussions with PCPs are happening during the majority of visits, PCP documentation fell behind. Documentation via smartphrase may need to be modified for physicians to use.

The use of molten salts as coolants, fuels, and tritium breeding blankets in the next generation of fission and fusion nuclear reactors benefits from furthering the characterization of the molecular structure of molten halide salts, paving the way to predictive capability of chemical and thermo-physical properties of molten salts. Due to its neutronic, chemical, and thermo-chemical properties, 2LiF−BeF2 is a candidate molten salt for several fusion and fission reactor designs. We perform neutron and X-ray total scattering measurements to determine the atomic structure of 2LiF−BeF2. We also perform ab-initio and neural network molecular dynamics simulations to predict the structure obtained by neutron and X-ray diffraction experiments. The use of machine learning provides improvements to the efficiency in predicting the structure at a longer length scales than is achievable with ab-initio simulations at significantly lower computational expense while retaining near ab-initio accuracy. The comparison among experimental and modeling results at a higher resolution and efficiency than previous measurements provides the opportunity to explore the structural determination of 2LiF−BeF2 beyond the first-nearest neighbor analysis that had been previously achieved with X-ray diffraction measurements of a FLiBe melt. This work may serve as a reference for future studies of salt structure and macroscopic properties with and without the addition of solutes.

We report the results of constant-potential molecular dynamics simulations of the double- layer interface between molten FLiBe and FLiNaK fluoride mixtures and idealized solid electrodes. Employing methods similar to those used in studies of chloride double layers, we compute the structure and differential capacitance of molten fluoride electric double layers as a function of applied voltage. The role of molten salt structure is probed through comparisons between FLiBe and FLiNaK, which serve as models for strong and weak associate- forming salts, respectively. In FLiBe, screening involves changes in Be-F-Be angles and alignment of the oligomers parallel to the electrode, while in FLiNaK the electric field is screened mainly by rearrangement of individual ions, predominantly the polarizable potassium cation.