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Integrate Experiments, Computation, and Theory

Goal 2: Integrate Expreiments, Computation, and Theory

  • Create a MGI Network of Resources
  • Enable Creation of Accurate, Reliable Simulations
  • Improve Experimental Tools -- From Materials Discovery through Deployment
  • Develop Data Analytics to enhance the Value of Experimental and Computational Data

MGI emphasizes integration of tools, theories, models, and data from basic scientific research with the processing, manufacturing, and deployment of materials. The Materials Innovation Infrastructure will enable this integration by providing access to digital resources that contain the property data of known materials as well as the computational and experimental tools to predict these characteristics for new and emerging materials. Example applications include using integrated tool sets to identify replacements for critical materials, and then translating these new materials into the production pipeline. Ultimately, seamless integration of fundamental, validated understanding can be incorporated into the simulation and modeling tools used for materials discovery, product and manufacturing designs, component life predictions, and informed maintenance protocols.

The Center for Materials in Extreme Dynamic Environments (CMEDE)

The Center for Materials in Extreme Dynamic Environments (CMEDE) is a multi-institution collaborative research center housed within the Hopkins Extreme Materials Institute at Johns Hopkins University. The Center brings together academia, industry, and the Army Research Laboratory (ARL) to address fundamental science issues in materials in extreme dynamic environments through a highly collaborative effort: the Materials in Extreme Dynamic Environments (MEDE) Collaborative Research Alliance (CRA).

The Nanoporous Materials Genome Center

The Nanoporous Materials Genome Center (NMGC) discovers and explores microporous and mesoporous materials, including metal-organic frameworks (MOFs), zeolites, and porous polymer networks (PPNs). These materials find use as separation media and catalysts in many energy-relevant processes and their next generation computational design offers a high-payoff opportunity. Towards that end, the NMGC develops state-of-the-art predictive modeling tools and employs them to increase the pace of materials discovery.

Rational Design of Advanced Polymeric Capacitor Films Multidisciplinary University Research Initiative (MURI)

The primary objective of this integrated research program is to design new classes of polymeric materials with high dielectric constant and high breakdown strength, suitable for application in high voltage, high energy density capacitor technologies. We seek to achieve this objective through state-of-the-art "scale-bridging" computations, synthesis, processing, and electrical characterization, and through the creation of a relational database.

PRedictive Integrated Structural Materials Science (PRISMS) Center

At the PRISMS Center integration drives everything we do. Our science is integrated with our computational codes and with the results from our experimentalists who identify new phenomena and fill in missing details. Our Materials Commons repository allows groups to collaborate and share data and provide it to the broader technical community. And our computational software is seamlessly integrating the latest multi-length scale scientific software into open source codes.

Center for Hierarchical Materials Design (CHiMaD)

Center for Hierarchical Materials Design (CHiMaD) is a NIST-sponsored center of excellence for advanced materials research focusing on developing the next generation of computational tools, databases and experimental techniques in order to enable the accelerated design of novel materials and their integration to industry, one of the primary goals of the Obama administration’s Materials Genome Initiative (MGI).

Multidisciplinary University Research Initiative: Managing the Mosaic of Microstructure

The ability to digitally design materials with microstructures optimized to achieve desired properties, is one of the long term goals of the materials field. Simulation-based materials design has the potential to dramatically reduce the need for expensive down-stream characterization and testing. However, this requires reliable algorithms and methodologies that incorporate variability and uncertainty in the design process, and are validated against physics-based models and experiments.

Data and Computational Tools for Advanced Materials Design: Structural Materials Applications - Cobalt Based Superalloys

The development of a materials innovation infrastructure (MII) that will enable rapid and significant reductions in the development time for new materials with improved properties is a critical element of the Materials Genome Initiative (MGI). Within this infrastructure materials data and modeling tools will be integrated to optimize material properties for a given set of design criteria. Case studies will be used to determine which data structure and tools need to be implemented to facilitate efficient advanced materials design and establish standards for the MII. This project highlights a materials design approach to the design of a high temperature cobalt-based superalloys for the aerospace and power generation industries.

Currently in the aerospace industry it takes approximately 18 months to design a part, but it can take over 10 years to design the ideal material from which to make the designed part. The goal of this project is to dramatically reduce the time to design a new material for a specific application. For the specific case study of a new class of γ/γ´ Cobalt-based superalloys, the two most important design criteria are:

  • Increased homologous operating temperature (> 50 degrees higher that current Ni-based superalloys), which will increase the turbine engine efficiency and thus decrease fuel consumption and emissions.
  • Increased wear resistance, which will increase the service life of the engine and lower operational costs.