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

2. 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

3. 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

4. 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

5. CIMMHub Ka Ming Tam Karthik Poobal
CIMMHub an instance of HUBZero (Ka Ming Tam)
Over 50 registered users
Very difficult to install!
Poorly supported software.
CIMMHub moved to Regents (Karthik Poobal)
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

6. 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

7. 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.

8. On Track or ahead of schedule
Accomplished

9. 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