Improving reproducibility and automation in atomistic simulations

Atomistic simulations, such as molecular dynamics, are becoming more widely used in a variety of areas, including industrial research and development. However, there are still barriers to the broad use of these methods, both on their own and as part of an Integrated Computational Materials Engineering or multiscale/hierarchical approach. One of the major challenges relates to reproducibility of interatomic potentials and simulations. In this discussion, we will discuss our efforts in the area of interatomic potential evaluations and simulation automation. We will also discuss how this fits into the Materials Genome Initiative and highlight major issues identified in the annual NIST “Atomistic Simulations for Industrial Needs” workshops that are designed to facilitate interactions between industrial and academic researchers

20 Meter Solar Sail Analysis and Correlation

This presentation discusses studies conducted to determine the element type and size that best represents a 20-meter solar sail under ground-test load conditions, the performance of test/Analysis correlation by using Static Shape Optimization Method for Q4 sail, and system dynamic. TRIA3 elements better represent wrinkle patterns than do QUAD3 elements Baseline, ten-inch elements are small enough to accurately represent sail shape, and baseline TRIA3 mesh requires a reasonable computation time of 8 min. 21 sec. In the test/analysis correlation by using Static shape optimization method for Q4 sail, ten parameters were chosen and varied during optimization. 300 sail models were created with random parameters. A response surfaces for each targets which were created based on the varied parameters. Parameters were optimized based on response surface. Deflection shape comparison for 0 and 22.5 degrees yielded a 4.3% and 2.1% error respectively. For the system dynamic study testing was done on the booms without the sails attached. The nominal boom properties produced a good correlation to test data the frequencies were within 10%. Boom dominated analysis frequencies and modes compared well with the test results

Fulfilling the promise of the materials genome initiative with high-throughput experimental methodologies

The Materials Genome Initiative, a national effort to introduce new materials into the market faster and at lower cost, has made significant progress in computational simulation and modeling of materials. To build on this progress, a large amount of experimental data for validating these models, and informing more sophisticated ones, will be required. High-throughput experimentation generates large volumes of experimental data using combinatorial materials synthesis and rapid measurement techniques, making it an ideal experimental complement to bring the Materials Genome Initiative vision to fruition. This paper reviews the state-of-the-art results, opportunities, and challenges in high-throughput experimentation for materials design. A major conclusion is that an effort to deploy a federated network of high-throughput experimental (synthesis and characterization) tools, which are integrated with a modern materials data infrastructure, is needed