KITWARE INC — Department of Energy SBIR Phase I: 12a
KITWARE INC — SBIR Phase I award from Department of Energy.
- Amount
- $150,000
- Agency
- Department of Energy
- Program / Phase
- SBIR · Phase I
- Topic
- 12a
- Solicitation
- DE-FOA-0001164
- NAICS
- —
- Place of performance
- NY
- Period
- 2015-02-17 → 2015-11-16
Description
The Materials Genome Initiative, in which DOE is participating through its Basic Energy Sciences program, aims to \support US institutions in the e ort to discover, manufacture, and deploy advanced materials twice as fast at a fraction of the cost". This can only be achieved by making signi cant improvements to the way that we use predictive capabilities to go from initial concept to manufactured and deployed materials. The way that scientists integrate, analyze, use, store and share diverse materials science datasets will be revolutionized by developing a scalable, extensible web framework. The technical approach will leverage best-in-class open-source technologies, and develop new approaches strategically to build an open source web framework for chemical-physics simulations, data and analytics. Features will be developed using a scripting language to glue components together on the server-side, with compiled programs providing optimized implementations and access to existing approaches. The client application will build upon existing frameworks to provide a rich, responsive experience using modern web technologies. The Phase I prototype will include basic structure editing, scheduling of computational simu- lations, ingestion of the results, and addition of pertinent information to the triple store. Data will be stored in a pragmatic form, and interfaces for de ning more complex concepts to pose ques- tions about the data will be explored, including support for natural language queries, de nition of operations performed on results to o er exploration of correlations, e.g. solar energy conver- sion e ciency correlated with chemical concepts such as number of rings, structural similarities, substructure matches, etc. The integration of experimental data to augment predictive capabili- ties of in-silico simulations will be demonstrated, o ering both simple analyses and more complex approaches employing specialized languages. This project will leverage investments made by the DOE and other agencies to provide a powerful web application and software framework for the materials design community. It will create a software platform that can serve as a reference for the community. The use of permissive open source licensing will make the platform available to all, with a simple deployment strategy o ering the ability to keep data close yet make it available to the wider linked semantic web. Keywords: materials science, web framework, discovery, semantic, chemical-physics, simula- tion, experimental data, materials design, web, data, analytics, visualization Summary for Members of Congress: Accelerating the development, manufacturing and deployment of new advanced materials will require a revolution in scienti c knowledge discovery for materials sciences. This project aims to develop a scalable, extensible web framework that will allow scientists integrate diverse materials science datasets and use predictive capabilities to discover next-generation materials.