Integrated Computational Materials Engineering CIMM ICME Integrated Computational Materials Engineering Mark Jarrell (LSU), Tom Bishop (LATech), Ka Ming Tam (LSU)

Subject Technical Page(s) 1. Overview 2. Summary of the present ICME accomplishments a. CIMMHub b. First principles potential fitting (poster by Nick Walker) c. Workflows (poster by Ka Ming Tam) 3. CIMM milestones table 4. Demo of the HDF5 data format 5. Conclusion and Moving forward

ICME Integrated Computational Materials Engineering Goal: Implement and manage a sustainable ICME data-handling framework to support metal- and alloy-based manufacturing linked to other ongoing national efforts. Small, new effort

ICME role/objective From Strategic Plan: By adopting a user interface and content management system for collecting, archiving, and sharing computational and experimental data relevant to the two STTs, establishing partnerships with mature ICME efforts, and by providing training, initiate and sustain the use of automated workflows for managing data and simulation ensembles to accelerate materials and process discovery relevant to advanced manufacturing. Content Management: CIMMHub (HUBZero) Training, April CIMMHub, today HDF5 Workflows and simulation ensembles, posters

CIMMHub Ka Ming Tam Karthik Poobal CIMMHub an instance of HUBZero (Ka Ming Tam) http://cimmhub.lsu.edu Over 50 registered users Very difficult to install! Poorly supported software. CIMMHub moved to Regents (Karthik Poobal) https://cimmhub.laepscor.org/ Tremendous opportunity for other projects which need a HUBZero. Tutorial at last meeting. Next: build a database ab initio Molecular Dynamics data “HUBzero ® is a powerful, open source software platform for creating dynamic web sites that support scientific research and educational activities” Content management system Facebook for scientists

MD potentials from first principles Ka Ming Tam Brian Novak Nick Walker Multiscale simulations are an important part of CIMM DFT MD takes us from the electronic to the atomic scale A bridge between classical and ab initio molecular dynamics can be formed by fitting an effective classical potential to the ab initio data Further manipulation of simulation and fitting parameters must be performed to improve the results. Next: mixtures (Al Ti), CIMMHub based ab initio MD database, validation of classical MD. See poster by Nick Walker. Figure 2: workflow diagram of the simulation and optimization processes

Workflows (Pegasus) Ka Ming Tam Multiscale problems require simulations at multiple length scales and hence multiple packages. Workflow software, like Pegasus, is use to manage this complexity As an example, we studied the multifractal nature of surface growth using Pegasus Next: we will apply workflows to Ab initio MD data which is fit to obtain potentials. See poster by Ka Ming Tam.

On Track or ahead of schedule Accomplished

Conclusions and Moving Forward Initiated a ICME effort Installed a HUBZero (CIMMHub) Moved to Regents, opportunity for others Experiments with workflow software Ab Initio MD  Classical potentials Work on mixtures Validation runs for classical calculations. Establish a Initio MD database