A Set of Moment Tensor Potentials for Zirconium with Increasing Complexity.

Machine learning force fields (MLFFs) are an increasingly popular choice for atomistic simulations due to their high fidelity and improvable nature. Here we propose a hybrid small-cell approach that combines attributes of both offline and active learning to systematically expand a quantum-mechanical (QM) database while constructing MLFFs with increasing model complexity. Our MLFFs employ the moment tensor potential formalism. During this process, we quantitatively assessed the structural properties, elastic properties, dimer potential energies, melting temperatures, phase stability, point defect formation energies, point defect migration energies, free surface energies, and generalized stacking fault (GSF) energies of Zr as predicted by our MLFFs. Unsurprisingly, the model complexity has a positive correlation with prediction accuracy. We also find that the MLFFs were able to predict the properties of out-of-sample configurations without directly including these specific configurations in the training dataset. Additionally, we generated 100 MLFFs of high complexity (1513 parameters each) that reached different local optima during training. Their predictions cluster around the benchmark DFT values, but subtle physical features such as the location of local minima on the GSF energy surface are washed out by statistical noise.

Graphene Oxide Membranes for Isotopic Water Mixture Filtration: Preparation, Physicochemical Characterization, and Performance Assessment.

There is an increasing demand for nuclear reactors, driven by the global need for low CO2 producing energy sources. The use of light (H2O) or heavy water (D2O) in a nuclear reactor environment produces radioactive tritiated heavy (HTO, DTO) water as an inevitable contaminant. Considering the need for tritiated water removal and also the high commercial value of purified water isotopes, technologies that can efficiently separate isotopic mixtures of water in nuclear reactors are highly desirable. This study presents an experimental approach for producing graphene oxide (GO) membranes and assessing their performance in the filtration of isotopic water mixtures. Specifically, using D2O/H2O mixtures as model systems, we investigate the effect of physicochemical properties of GO, as well as membrane preparation conditions on membrane filtration efficiency. We find that membranes assembled using larger GO platelets of lower oxidation level generally exhibit higher deuterated water (HDO, D2O) rejection and filtrate flux. Moreover, membrane preparation conditions have a strong impact on the interlayer space between stacked GO nanoplatelets in the membrane, hence as a direct effect on filtration performance. Our experimental results also show a strong, nonmonotonic dependence of separation performance on operating temperature, as well as the existence of local temperature optima. Our work provides guidelines for simple and scalable preparation of GO membranes with very good mechanical stability, capable of achieving efficient separation of isotopic water.

Effect of He on the Order-Disorder Transition in Ni_{3}Al under Irradiation.

The order-disorder transition in Ni-Al alloys under irradiation represents an interplay between various reordering processes and disordering due to thermal spikes generated by incident high energy particles. Typically, ordering is enabled by diffusion of thermally generated vacancies, and can only take place at temperatures where they are mobile and in sufficiently high concentration. Here, in situ transmission electron micrographs reveal that the presence of He-usually considered to be a deleterious immiscible atom in this material-promotes reordering in Ni_{3}Al at temperatures where vacancies are not effective ordering agents. A rate-theory model is presented, that quantitatively explains this behavior, based on parameters extracted from atomistic simulations. These calculations show that the V_{2}He complex is an effective agent through its high stability and mobility. It is surmised that immiscible atoms may stabilize reordering agents in other materials undergoing driven processes, and preserve ordered phases at temperature where the driven processes would otherwise lead to disorder.

Fast residual stress mapping using energy-dispersive synchrotron X-ray diffraction on station 16.3 at the SRS.

Synchrotron energy-dispersive X-ray diffraction experiments on station 16.3 at the SRS for residual strain mapping are reported. A white beam with an energy-discriminating detector allows measurements to be made through 3 mm Al, Ti, Fe and Cu alloys with acquisition times of approximately 30 s per 0.3 mm(3) sampling volume. The collected profiles were analysed using single-peak fitting and whole-pattern Pawley refinement, and produced strain accuracy better than 10(-4). This configuration is therefore highly efficient for fast strain mapping in thin components using a second-generation synchrotron source.