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Cyberinfrastructure for Materials Discovery and Innovation * * Some Assembly Required. Daryl W. Hess Program Director, DMR [email protected]. Big Data Request for Input Closes November 14 https://www.nitrd.gov/bigdata/rfi/02102014.aspx. - PowerPoint PPT Presentation
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Discovery and Innovation*
*Some Assembly Required
Daryl W. Hess
Program Director, DMR
Big Data Request for Input Closes November 14https://www.nitrd.gov/bigdata/rfi/02102014.aspx
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Opportunities to Shape How Science is DoneData plays a key role …
• The way computation, data, experiment & theory interact• Enhanced Connectivity
– Unprecedented Communication of Results– What didn’t work, not just what did
• The Data is getting bigger ….– Simulations – New instruments
• How do we handle BIG data?– Distributed, Inhomogeneous– Provenance? Access? “Presentation?” Will it be there tomorrow?– Discovery tool? – A gateway to new problems?– ….
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OSTP: Big Data is a Big DealPresident: … an “all hands on deck” effort.
By improving our ability to extract knowledge and insights from large and complex collections of digital data, the initiative promises to help accelerate the pace of discovery in science and engineering, strengthen our national security, and transform teaching and learning.” more than $200 million from 6 Federal departments and agencies Big Data: data sets so large, complex, or rapidly-generated that they can’t
be processed by traditional information and communication technologies
Year 2: Obama Administration encourages federal agencies, industry, academia, state and local governments to develop and participate in Big Data initiatives. advance core Big Data technologies; use Big Data to advance national goals use competitions and challenges
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To help businesses discover, develop, and deploy new materials twice as fast, we’re launching what we call the Materials Genome Initiative. The invention of silicon circuits and lithium ion batteries made computers and iPods and iPads possible, but it took years to get those technologies from the drawing board to the market place. We can do it faster.
-President Obama Carnegie Mellon University, June 2011
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The Materials Genome Imitative
Discovery-to-market in less than half the time at half the cost
A Materials Innovation
Infrastructure is Required
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MGI for Global CompetitivenessA strategy for acceleration
Time(yrs)
Num
ber
of M
ater
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“to
Mar
ket”
3- 5 years
4
1 2 35 6 7
1
23
45
67
1. Discovery
2. Development
3. Property Optimization
4. System Design & Integration
5. Certification
7. Deployment & Sustainment
6. Manufacturing
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Nanotechnology Knowledge Infrastructure:Enabling National Leadership in Sustainable Design
A Nanotechnology Signature Initiative
A community-based knowledge infrastructure to accelerate nanotechnology discovery and innovationhttp://www.nano.gov/NSINKI
Thrust
Foster an agile
modeling networkfor multidisciplinary
collaboration.
Thrust
Create a robust digital nanotechnology
data and information
infrastructure
Thrust
Build a sustainable nanotechnology
cybertoolbox
Thrust
Nurture a diverse collaborative community to create nanotechnology to meet national challenges
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NSF WorkshopThe Materials Genome Initiative:
The Interplay of Experiment, Theory and Computation
J.J. de Pablo, B. Jones, C. Lind-Kovacs, V. Ozolins, A. P. Ramirez. Current Opinion in Solid State and Materials Science 18, 99–117 (April, 2014)
“… a seamless interplay between experiment, computation and demonstration is essential.”
A key role for data
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Consider a university researcher with an idea for a new battery material …
She queries a large database of experimental and computational data
accesses an online simulation service and suggests other promising compounds …
… [Others] make some of the materials … and upload energy storage performance data to the database.
… other computational researchers show why the new materials are effective.
The new material is made in several labs and … stimulating industry. Commercial scale fabrication and scale-up are taken into consideration by industrial scientists and engineers as materials are being developed. All of this happens faster than the time it takes for a single research paper to be published today. (highly abridged)
J.J. de Pablo, B. Jones, C. Lind-Kovacs, V. Ozolins, A. P. Ramirez. Current Opinion in Solid State and Materials Science 18, 99–117 (April, 2014)
NSF WorkshopThe Materials Genome Initiative:
The Interplay of Experiment, Theory and Computation
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Designing Materials to Revolutionize and Engineer our Future
NSF’s signature response to the MGI
What: … activities that accelerate materials discovery and development by building the fundamental knowledge base needed to progress towards designing and making a material with a specific and desired function or property from first principles.
DMREF goal: to control material properties through design: this is to be accomplished by understanding the interrelationships of composition, processing, structure, properties, performance, and process control.
How: … the proposed research must be a collaborative and iterative process wherein theory guides computational simulation, computational simulation guides experiments, and experiments further guide theory.
Benefits from existing software and data and will contribute new data, models, and software
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Software Infrastructure for Sustained Innovation (SI2)
Innovation Resuable and Sustainable Software
NSF 14-520
• Through Division of Advanced Cyberinfrastructure• ~50 Elements & Frameworks projects & 13 potential Institutes
planning projects ( http://bit.ly/sw-ci for current SI2 projects)
SI2-SSI Collaborative Research:A Computational Materials Data and Design Environment
Developing tools to model• Defect energetics/thermodynamics• Solid state diffusion• Charged surfaces
Goal: Develop modular and extensible high-throughput ab-initio tools and critical property databases for materials design
Formation energies
Migration energies
Participants
CyberInfrastructure Impact• Open source tools for easy public use• Workshops on high-throughput computation and the Materials Genome framework.• Integration with Materials Project at LBNL• Training of next generation in automated computational materials design tools
Dane Morgan
Gerbrand Ceder Alan K Dozier,Raphael Finkel
Kristin Persson
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SSI: Scalable, Extensible, and Open Framework for Ground and Excited State Properties of Complex Systems
Sohrab Ismail-Beigi, Yale (139804)Laxmikant Kale, UIUC (1339715) Glenn Martyna, IBM (collaborator)
• Develop a first-principles ground state/excited state and response code
good scaling properties on HPC platforms
• For study of new materials science, condensed matter physics, and chemistry problems.
• An American electronic structure code • Highly scalable codes for HPC that would
open new frontiers through the ability to tackle larger scale problems.
• Helps support sophisticated materials design efforts and the Materials Genome Initiative.
DFT-GGA predicted structure of the ordered nanoscale heterojunction of P3HT polymers (gold, above) anchored covalently by sulfur atoms to the [10-10] surface of a ZnO nanowire (red and purple, bottom). A GW/BSE prediction of the electronic bands and excitons of this interface would help for photo-voltaic applications.
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S2I2 Software InstitutesWhat does materials research need?
• Long-term hubs of excellence in software infrastructure and technologies, research and application communities of substantial size and disciplinary breadth.
• ~ $1-2 Mil./yr.• Conceptualization awards possible
~13 awarded across NSF
Collaborative Research: Scientific Software Innovation Institute for Advanced Analysis of X-Ray and Neutron Scattering Data (SIXNS) - Brent Fultz, CalTech
Collaborative Research: A Scientific Software Innovation Institute for Computational Chemistry and Materials Modeling (S2I2C2M2) - Tom Crawford, VaTech
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Data & NSF: Enabling a Knowledge Infrastructure
Warning: Emphasis will change!
• BIGDATA (NSF 14-542) [$200K/yr. - $500K/yr.]
Critical Techniques and Technologies for Advancing Big Data Science & Engineering
"Foundations" (F): developing or studying fundamental techniques, theories, methodologies, and technologies of broad applicability to Big Data problems.
"Innovative Applications" (IA): developing techniques, methodologies and technologies of key importance to a Big Data problem directly impacting at least one specific application.
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Data & NSF: Enabling a Knowledge Infrastructure
Warning: Emphasis will change!
• DIBBs (NSF 14-542)
Data Infrastructure Building Blocks “… development of robust and shared data-centric cyberinfrastructure capabilities to accelerate interdisciplinary and collaborative research in areas of inquiry stimulated by data.”
Pilot Demonstration Awards (up to $500K/yr.)
Addresses needs of a large number of researchers within a domain Early Implementation Awards (up to $1 Million/yr.)
Multiple research communities in multiple S&E domains
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Community Input Grappling with the *issues
Workshops – NKI: Data Sharing Workshop
• Diverse participants: nanotechnology data producers & users, journal editors, industry, ….
• Cross-cutting needs of the communities
– DMR: Data Workshop • Data Sharing in the context of materials research
* Data curation, completeness, relevance, quality, “code
publication,” ontologies …
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Big Data Request for Inputhttps://www.nitrd.gov/bigdata/rfi/02102014.aspx
“This request encourages feedback from multiple big data stakeholders to inform the development of a framework, set of priorities, and ultimately a strategic plan for the National Big Data R&D Initiative.”
ACTION
ITEMVISION STATEMENT: We envision a Big Data innovation ecosystem in which the ability to analyze, extract information from, and make decisions and discoveries based upon large, diverse, and real-time data sets enables new capabilities for federal agencies and the nation at large; accelerates the process of scientific discovery and innovation; leads to new fields of research and new areas of inquiry that would otherwise be impossible; educates the next generation of 21st century scientists and engineers; and promotes new economic growth.
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Moving ForwardA useful way to think about data ?
DMR MGI Workshop– Shared Data is a focal point for
collaborative research
Data infrastructure across the scales …
Small GroupCollaboration
Intra-CenterCollaborations
Center-CenterCollaboration
Many MixedCollaborations
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Thrust Areas:• A diverse collaborative community of
scientists, engineers, and technical staff to support research, development, and applications of nanotechnology to meet national challenges
• An agile modeling network for multidisciplinary intellectual collaboration that effectively couples experimental basic research, modeling, and applications development
• A sustainable cyber-toolbox to enable effective application of models and knowledge to nanomaterials design
• A robust digital nanotechnology data and information infrastructure to support effective data sharing, collaboration, and innovation across disciplines and applications
Accelerating Nanotechnology discovery and innovationhttp://www.nano.gov/NSINKI
Nanotechnology Knowledge Infrastructure:Enabling National Leadership in Sustainable Design
A Nanotechnology Signature Initiative