Greener Nano 2012: Nanoinformatics Tools and Resources Workshop

Transcription

1 Greener Nano 2012: Nanoinformatics Tools and Resources Workshop

2 Greener Nano 2012: Nanoinformatics Tools and Resources Workshop Courtyard Marriott Portland City Center Portland, OR July 30, 2012 The quantity of information on nanomaterial properties and behavior continues to grow exponentially. Without a concerted effort to organize and mine disparate information coming out of current research efforts, the value and effective use of this information will be limited at best. At worst, erroneous conclusions will be drawn and data will not be translated to knowledge. Nanoinformatics inherently supports a community-based approach to filter the noise and enhance the value of global information in nanoscience and nanotechnology. Much progress has been made through grassroots efforts in nanoinformatics resulting in a multitude of resources and tools for nanoscience researchers. At this point, it is important to critically evaluate and refine nanoinformatics applications in order to best inform the science and support the future of predictive nanotechnology. GN12 will bring together informatics groups with materials scientists and active nanoscience researchers to evaluate and reflect on the tools/resources that have recently emerged in support of predictive nanotechnology. The goals of this workshop are to establish a better understanding of current applications and clearly define immediate and projected informatics infrastructure needs for the nanotechnology community. We will use the theme of nanoehs to provide real-world, concrete examples on how informatics can be utilized to advance our knowledge and guide nanoscience. In preparation for the workshop, we will host two preliminary webinars. Part I Webinar will provide 15 minute overviews of current nanoinformatics tools with detailed information on our current state-ofthe-science. Part II Webinar will provide live interactions with the developers of those nanoinformatics tools and resources. An line will be opened 24 hours in advance of the Part II live webinar for interested parties to submit questions, comments and feedback. Workshop organizers will select an expert panel of materials scientists from diverse sectors of nanomaterials research and development to participate in the workshop and to serve as a formalized pool of experts on which the nanoinformatics community can draw expertise. 2

3 Workshop Steering Committee Jessica Adamick, National Nanomanufacturing Network Nathan Baker, Pacific Northwest National Laboratory Yoram Cohen, University of California, Los Angeles Stacey Harper, Oregon State University/Oregon Nanoscience and Microtechnologies Institute Mark Hoover, National Institute for Occupational Safety and Health Jim Hutchison, University of Oregon Gerhard Klimeck, Purdue University Andre Nel, UC CEIN/University of California Los Angeles Michelle Ostraat, RTI International Sally Tinkle, National Nanotechnology Coordination Office Mark Tuominen, National Nanomanufacturing Network Sponsored By Safer Nanomaterials and Nanomanufacturing Initiative National Nanomanufacturing Network UC Center for Environmental Implications of Nanotechnology NCI Nanotechnology Working Group Nanotechnology Now In Coordination With Nanotechnology Knowledge Infrastructure Signature Initiative 3

4 Agenda Monday, July 30 7:30 8:00 AM Continental Breakfast Sequoia Ballroom 8:00 8:10 AM Opening Remarks and workshop charge Stacey Harper, Oregon State University/Oregon Nanoscience and Microtechnologies Institute 8:10 8:40 AM Signature Initiatives Discussion Sally Tinkle, National Nanotechnology Coordination Office 8:40 10:10 AM Concurrent Breakout Sessions Data Lifecycle to Support a Sustainable Cyber-Toolbox Sequoia Ballroom Sequoia Ballroom Aspen Cypress Maple Alder 10:10 10:30 AM Break Sequoia Ballroom 10:30 AM 12:00 PM Concurrent Breakout Sessions Use of Nanoinformatics for Predictive Modeling 12:00-1:20 PM Lunch Keynote address: Materials Genome Initiative Interface Krishna Rajan, Iowa State University Aspen Cypress Maple Alder Sequoia Ballroom 1:20 1:40 PM Breakout Session 1 report-in (5 min. each group) Sequoia Ballroom 1:40 2:00 PM Breakout Session 2 report-in (5 min. each group) Sequoia Ballroom 2:00 3:30 PM Concurrent Breakout Sessions Nanoinformatics Integration Aspen Cypress Maple Alder 3:30 3:50 PM Break Sequoia Ballroom 3:50 4:10 PM Breakout Session 3 report-in (5 min. each group) Sequoia Ballroom 4:10 5:30 PM Final comments/discussions on Breakout Sessions 1-3 and report planning Sequoia Ballroom 4

5 BREAKOUT SESSION 1 - DATA LIFECYCLE TO SUPPORT A SUSTAINABLE CYBER-TOOLBOX Session 1 Leaders: Jim Hutchison (University of Oregon), Raul Cachau (Frederick National Laboratory for Cancer Research), Victor Maojo (Universidad Politécnica de Madrid), and Michele Ostraat (RTI International) What does the IDEAL data lifecycle look like? Comparison with our CURRENT lifecycle. What are the data gaps? What are the barriers to move from current to ideal? Session Outputs: recommendation on IDEAL data lifecycle; identification of data gaps and barriers to sustainable nanoinformatics 5

6 BREAKOUT SESSION 2 - USE OF NANOINFORMATICS FOR PREDICTIVE MODELING Session 2 Leaders: Nathan Baker (Pacific Northwest National Laboratory), Yoram Cohen (University of California Los Angeles), Sharon Gaheen (SAIC-Frederick), and Mark Tuominen (National Nanomanufacturing Network) What outputs are expected from predictive toxicology and mechanistic models? What level of nanomaterial representation/description is required to parameterize these models? What examples can be used to illustrate NI as a model for materials assessment towards a predictive toxicological approach? Session Outputs: recommendation on nanomaterial description requirements for predictive modeling; examples to illustrate utility of NI approach 6

7 BREAKOUT SESSION 3 - NANOINFORMATICS INTEGRATION Session 3 Leaders: Jeff Steevens (US Army Engineer Research and Development Center), Stacey Harper (Oregon State University), Sally Tinkle (National Nanotechnology Coordination Office), and Jeff Morse (National Nanomanufacturing Network) How will the data and the predictive models be used to make decisions (in context of the value chain: materials development manufacturing use post-use)? How can the different nanoinformatics needs throughout the value chain and lifecycle be coordinated, integrated and balanced between sectors, technologies, designer/manufacturer/user-based informatics? How do existing grassroots efforts in nanoinformatics (additional informatics efforts not focused on nanomaterials) fit into an integrated framework for informatics infrastructure? Which bits of informatics need to be unified/standardized, which just need to be functionally linked and what is missing? Session Outputs: recommendation on standards to catalyze nanoscience and support nanoinformatics approaches and modeling; plan for data sharing and informatics integration; identification of informatics gaps 7

8 Greener Nano 2012: Nanoinformatics Tools and Resources Workshop Participants First Name Last Name Affiliation Address Jessica Adamick National Nanomanufacturing Network Bah Jeremia Angye Farmers Trust Don Baer Pacific Northwest National Laboratory Nathan Baker Pacific Northwest National Laboratory David Balshaw NIEHS Celine Beamer The University of Montana Amy Bednar US Army Engineer Research and Development Center David Boehm US Army Engineer Research and Development Center Scott Broderick Iowa State University Raul Cachau Frederick National Laboratory for Cancer Research Vasant Chabukswar Nowrosjee Wadia College Jyoti Chawla MRIU Lung-Chi Chen NYU School of Medicine Vanessa Clive Industry Canada Yoram Cohen UCLA Shareena Dasari Jackson State University Ozioma Michael Ejiofor East Ukrainian National University Ukraine. Mohammad Esmaeillou The International NanoScience Elaine Faustman University of Washington Joseph Fisher Oregon State University Charles Frevert University of Washington Sharon Gaheen SAIC-Frederick Panos Georgopoulos RW Johnson Medical School and EOHSI Rajakumar Govindasamy C.Abdul Hakeem College, Tamil Nadu, India. David Grainger University of Utah Wanda Greaves- Holmes University Of Central Florida William Griffith University of Washington Kimberly Guzan RTI International Stacey Harper Oregon State University Bryan Harper Oregon State University Taimur Hassan UC CEIN Albelda Hisyam VHS of Nahyada Global Julie Hoogenstryd OHSU Mark Hoover NIOSH Jim Hutchison University of Oregon Hai-Yong Kang DTSC Griffith Kundahl Center of Innovation for Nanobiotechnology Rong Liu UC-CEIN Bettye Maddux SNNI Victor Maojo Universidad Politecnica de Madrid Mitchell Martin Roche Scott McNeil SAIC-Frederick, Inc./Frederick National Lab Karmann Mills RTI International Som Mitra NJIT C Gopi Mohan Jeff Morse National Nanomanufacturing Network Andre Nel University of California Los Angeles Petros Nezis Eurocheck Group Steven Oldenburg nanocomposix, Inc Galya Orr PNNL galya.orr@pnl.gov

9 Greener Nano 2012: Nanoinformatics Tools and Resources Workshop Participants Michele Ostraat RTI International Steven Parton Tejasvi S V R V Parupudi Purdue University sparupud@purdue.edu Krishna Rajan Iowa State University krajan@iastate.edu Mohd Ashraf Rather Central Institute of Fisheries Education mashraf38@gmail.com Skip Rung ONAMI skip@onami.us Christopher Schaupp University of Washington cschaupp@u.washington.edu David Scoville University of Washington dkscov@uw.edu Mahdi Shahmiri UPM msar1387@yahoo.com Vishal Sharma Govt. G M Science College, Jammu vishalsharma_jmu@yahoo.co.in David Skinner LBNL deskinner@lbl.gov Gitika Srivastava Amity Institute of Nanotechnology (Noida, India) gitika.aint@gmail.com Jeff Steevens US Army Engineer Research and Development Center Jeffery.A.Steevens@usace.army.mil Kaizhi Tang Intelligent Automation, Inc. ktang@i-a-i.com Sally Tinkle NNCO stinkle@nnco.nano.gov Mark Tuominen University of Massachusetts tuominen@physics.umass.edu Jaya Verma Central University of Jharkhand, Ranchi, India earn_self@yahoo.co.in Marvin Warner PNNL marvin.warner@pnnl.gov Leah Wehmas Oregon State University wehmasl@onid.orst.edu Min Wu California State DTSC mwu@dtsc.ca.gov Lynn Zentner Network for Computational Nanotechnology lzentner@purdue.edu Jeffrey I. Zink UCLA zink@chem.ucla.edu

10 NNI Signature Initiative: Nanotechnology Knowledge Infrastructure May 14,2012 NSTC COMMITTEE ON TECHNOLOGY SUBCOM:\>lITTEE ON NANOSCALE SCIENCE, ENGINEERING, AND TECHNOLOGY Nanotechnology Signature Initiative Nanotechnology Knowledge Infrastructure: Enabling National Leadership in Sustainable Design Collaborating Agencies: i CPSC, DOD, EPA, FDA, NASA, NIH, NIOSH, NIST, NSF, OSHA National Need Addressed Nanotechnology solves global challenges by generating and applying new multidisciplinary knowledge of nanoscale phenomena and engineered nanoscale materials, structures, and products. The data underlying this new knowledge are vast, disconnected, and challenging to integrate into the broad scientific body of knowledge. The Federal agencies participating in the National Nanotecnology Initiative (NNI)-in conjunction with the broader nanoscale science, engineering, and technology communities-have identified the building of a formal knowledge infrastructure as critical to sustainable progress in nanotechnology [1-4]. This reflects a desire to coordinate existing NNI member agency programmatic efforts that accelerate the vetting of new knowledge and that enable effective data utilization. Nanoinformatics is the science and practice of developing and implementing effective mechanisms for the nanotechnology community to collect, validate, store, share, mine, analyze, model, and apply nanotechnology information. Nanoinformatics is integrated throughout the entire nanotechnology landscape, impacting all aspects of research, development, and application. An improved nanoinformatics infrastructure will ensure the sustainability of our national nanotechnology proficiency by improving the reproducibility and distribution of experimental data as well as by promoting the development and validation of tools and models to transform data into information and applications. A focused national emphasis on nanoinformatics will provide a strong basis for the rational design of nanomaterials and products, prioritization of research, and assessment of risk throughout product lifecycles and across sectors that include energy; environment, health, and safety (EHS); medicine; electronics; transportation; and national security. In this manner the effort described here will also contribute substantially to the Materials Genome Initiative, a related Federal interagency priority outlined on page 10 [5]. This signature initiative, Nanotechnology Knowledge Infrastructure: Enabling National Leadership in Sustainable Design, will provide a community-based, solutions-oriented knowledge infrastructure to accelerate nanotechnology discovery and innovation. This will be accomplished within four major thrust areas that focus member agency efforts on cooperative, interdependent development of: I Please note that "collaborating ageneies" is meant in the broadest sense and does not necessarily imply that agencies provide additional funds or incur obligations to do so. Agencies are listed in alphabetical order. Page I of 11

11 NNI Signature Initiative: Nanotechnology Knowledge Infrastructure May 14, A diverse collaborative community of scientists, engineers, and technical staff to support research, development, and applications of nanotechnology to meet national challenges 2. An agile modeling network for multidisciplinary intellectual collaboration that effectively couples experimental basic research, modeling, and applications development 3. A sustainable cyber-toolbox to enable effective application of models and knowledge to nanomaterials design 4. A robust digital nanotechnology data and information infrastructure to support effective data sharing, collaboration, and innovation across disciplines and applications Through these four thrusts, the Nanotechnology Knowledge Infrastructure (NKI) signature initiative will leverage and extend existing and emerging resources, programs, and technologies to create an architecture for nanoscale science and engineering in the 21 SI century. Specifically, several NNI agency-supported databases, portals, and resources containing data on nanomaterials will provide the foundation for this infrastructure; these are highlighted in Table 1. Modem digital technologies such as the life sciences dialogue at WikiGenes [6], the digital physical sciences library ArXiv [7], and the use of Twitter and blogs for scientific debate [8] have already demonstrated their potential to augment and expedite scientific exchange while respecting intellectual property and authorship. These technologies, applications, and systems will be instrumental in working towards establishing a robust modeling and data information infrastructure-including a central access point for existing and emerging modeling, simulation, and data efforts-that will support the research needs identified by the NNI member agencies and relevant stakeholders as outlined in the NNI Strategic Plan [9] and the NNI Environmental, Health, and Safety Research Strategy [10]. The NKI will coordinate the nanoscale science, engineering, and technology commumties around the fundamental, interconnected elements of collaborative modeling, a cyber-toolbox, and data infrastructure that will capitalize on American strengths in innovation, shorten the time from research to new product development, and maintain U.S. leadership in sustainable design of engineered nanoscale materials. Technical Program As outlined above and shown graphically in Figure 1, the NKI contains four thrusts that synergistically develop a community that will create and harness the tools necessary to aid in advancing nanotechnology. Thrust 1 outlines the important role of the NKI in strengthening and connecting researchers across academia, government, and industry to advance nanoscale science, engineering, and technology. Thrust 1 further focuses on educating and training the nextgeneration workforce that will develop, maintain, and use the outputs from Thrust 2 (models and data), Thrust 3 (a cyber-toolbox of validated tools), and Thrust 4 (digital data and information infrastructure). Figure I. Overview, Nanotechnology Knowledge Infrastructure Signature Initiative Page 2 of II

12 NNI Signature Initiative: Nanotechnology Knowledge Infrastructure May 14,2012 Table 1. Foundational Resources Supporting Thrust Areas Identified in the Nanotechnology Knowledge Infrastructure Signature Initiative cananolab Extreme Science and Engineering Discovery Environment project (XSEDE; follow-on to Teragrid) InterNano Nano-Hub Nanomaterial-Biological Interactions Knowledgebase Nanomaterials Registry Nanoparticle Information Libra Description of NNI-Supported Resource Cancer Nanotechnology Laboratory portal of NIH INa tiona 1 Cancer Ins,tj'tute~; cabig.nci.nih.gov/tools/cananolab. NSF-supported advanced digital network of 16 supercomputers and high-end visualization/data analysis resources; nanomanufacturing resource run by the National 'ng Network; F- supported online simulation resources operated by the Network for mputational Nanotechnology; nanohub.orgl. The Nanomaterial-Biological Interactions Knowledgebase, hosted at Oregon State University and supported by EPA, NSF, DOD/Air Force, and NIH; nbi.oregonstate.edu!. Web-based registry project in development by RTI International and three NIH institutes-nci, NIEHS, and NIBIB-for biomedical and environmental applications of nanomaterials; t1tormfltlon on nano,techno\ogy a I Toxcast EPA program to define and evaluate predictive toxicity signatures of over 10,000 chemicals; Thrust 2 seeks to encourage rapid and early modeling collaboration, evaluation, and peer-review through sharing of experimental data, models, and modeling results. This fosters critical relationships between theorists, modelers, and experimentalists through the exchange of data and information that will aid in developing the larger nanotechnology community outlined in Thrust 1. As the new models created in Thrust 2 become validated and verified computational tools, they will become integrated into the cyber-toolbox for broad use throughout the community, as addressed by Thrust 3. The verified data generated in Thrust 3 will further be incorporated into the digital data and information infrastructure addressed in Thrust 4. This overall access to models, validated simulations, and reproducible data will ultimately help ensure that scientific advances are responsibly translated into products through informed design processes. Described below are the underlying technical details of the NKI thrusts as well as the anticipated outcomes that leverage existing agency efforts. In addition to the NNI agency programs highlighted in Table I, agency roles and contributions are discussed on page 8. Thrust 1: Build a diverse collaborative community of scientists, engineers, and technical stalf to support research, development, and applications of nanotechnology to meet national challenges. A highly-skilled workforce is essential to U.S. nanotechnology research, development, and applications. Such communities require time to develop purposeful policies and programs. These communities are the backbone of U.S. nanotechnology competitiveness. They consist of (a) experimentalists, computational scientists, and theoreticians to develop and advance the science; (b) engineers and other researchers to apply the science to address national challenges; and (c) Page 3 of 11

13 NNI Signature Initiative: Nanotechnology Knowledge Infrastructure May 14,2012 well-trained technicians to execute material synthesis processes, to ensure quality control, to perform advanced tests, to assess risk and benefit, and to employ nanotechnology in practice. The NKI will foster such a community by: Enhancing communication mechanisms within the nanoinformatics community by promoting digital networks and network events Promoting the development of training tools and courses to efficiently train staff with the required skill levels to accommodate rapid advances in knowledge, methods, and techniques Developing an infrastructure to support the synergistic interaction of scientists and engineers to define frontier nanoscale science and engineering problems and to develop strategies to tackle difficult problems of national importance Reducing barriers to educational opportunities and careers for economically, geographically, and other disadvantaged or underrepresented communities Creating awareness in the community of the relevance and impact of nanotechnology in the United States by promoting educational events aimed at students and the general population Expected outcomes for Thrust 1 are as follows: An integrated and highly skilled nanoinformatics community to build and sustain nanotechnology-enabled U.S. industries Education and training of the next-generation modeling network to sustain the intellectual infrastructure for future nanotechnology Thrust 2: Foster an agile modeling network for multidisciplinary intellectual collaboration that effectively couples experimental basic research, modeling, and applications development. Modeling is the essential mechanism that couples our conceptual understanding of nanomaterials and the empirical knowledge gained from experimentation. For example, reliable computational models will ultimately enable prediction and design of new nanoscale materials with desired properties, inform risk assessment and management of nanomaterials, and likely will have additional applications not yet conceived. Models also play an important role in developing new concepts to expand our understanding of materials, biological systems, and phenomena at the nanoscale. As models and experimental results are shared more rapidly across this network, critical components of the needed intellectual infrastructure will more efficiently connect basic research to applications development. Critical, near-term nanotechnology modeling needs include: Models that combine first-principles concepts and link theory, simulations, and experimental results over diverse scales of length and time to expand our knowledge of nanoscale materials and phenomena Models motivated by specific real-world problems and validated experimentally in the appropriate biological or physical system A dynamic mechanism for sharing, combining, and refining models in accordance with the emergence of new experimental data and new theoretical concepts Page 4 of 11

14 NNI Signature Initiative: Nanotechnology Knowledge Infrastructure May 14,2012 By developing an enhanced modeling network for technical collaboration, it will be possible to solve compelling questions across scientific domains; more efficiently bridge the gaps between concept, design, product development, and manufacturing; and identify and take effective measures to maximize the benefit of nanomaterials to humans and the environment while minimizing the risk. This technical collaboration will be intrinsically multidisciplinary and interdisciplinary and will facilitate education of young scientists who will create the next generation of nanoscale models. Expected outcomes for Thrust 2 are as follows: A robust technical network of professionals who will collaboratively develop and work to validate a library of models and simulations to address the spectrum of nanotechnology questions-from grand challenges and problems of national priority to modest problems that fill essential global and social needs Improved structural models for nanomaterials on several levels: models to address detailed interactions at the atomic level, molecular level, and particle level; models to address the polydispersity, conformations, and transformations of nanomaterials; and models that link particulate information to simulation of the effects of nanomaterials in models of cellular, tissue, organ, organism, and ecosystem environments Broader access to relevant experimental results that are technically sound and important to model, but may not otherwise be considered novel enough for publication Shortened development time to achieve similar quality models, due to early and more detailed, frequent, and constructive peer review Models with sufficient reliability and validity to design sustainable materials that maximize beneficial properties and minimize potential hazards Models that are easily accessible to broader communities and stakeholders, such as communities focusing on other length scales A dynamic compendium of "lessons learned" from the modeling activities, including positive and negative results, that will clarify data gaps and inform the design of new experiments and new models Thrust 3: Build a sustainable nanotechnology cyber-toolbox to enable application of models and knowledge to nanomaterials design. A suite of computational tools that facilitate the analysis of experiments and the understanding of nanomaterials is essential to complete the Nanotechnology Knowledge Infrastructure. Establishing a single access point for available tools will ensure that such a toolbox will have wide-reaching impacts on both the utilization of nanomaterials and the communication of knowledge among the diverse scientific domains of nanotechnology. The central components of this toolbox are computationally efficient software tools to enable reliable and robust simulation of nanomaterial properties and behaviors. Simulation is a process consisting of a set of computer instructions based on well-designed numerical algorithms that utilize models to solve physical, biological, or engineering problems. There is an acute need for the development of new software that is well maintained and broadly accessible to the community to ensure that nanotechnology models will be accurate, predictive, and useful in Page 5 of 11

15 NNI Signature Initiative: Nanotechnology Knowledge Infrastructure May 14,2012 accelerating science. Data mining software will enable the discovery of correlations among materials properties and phenomena that are not apparent or are difficult to show in current theoretical frameworks. The software performing simulations and the models underlying them will enable analysis and interpretation of experimental results, prediction of nanoscale phenomena, and sustainable design and control of nanoscale materials and systems. The software must be validated for specific computer architectures because compilation of the source code on different machines could have an impact on its performance. Documentation of the software will include specific information on its range of validity, representative run-time parameters and files, and other associated information necessary to duplicate example results. Based on multidisciplinary collaborations between theorists and experimentalists, a cybertoolbox of validated, easily accessible, and well-maintained simulations will inform the design and development of nanomaterials and will enable understanding of nanomaterial behavior from a product lifecycle perspective. Expected outcomes for Thrust 3 are as follows: A nanotechnology cyber-toolbox that will house the collaboratively developed and validated models to enable understanding of nanomaterials' properties, behavior, and impact on biological and environmental systems A nanotechnology cyber-toolbox that will include a suite of theoretical, computational, statistical, and visualization tools to facilitate the planning, execution, and analysis of experiments A central access point on the NNI website and administered by the National Nanotechnology Coordination Office for linking existing interdisciplinary cyber-toolbox components to improve user accessibilityii Educational opportunities that will integrate the cyber-toolbox and the Nanotechnology Knowledge Infrastructure into the intellectual framework of nanoscale science and engineering and aid in developing the next-generation workforce as discussed in Thrust 1 Thrust 4: Create a robust digital nanotechnology data and information infrastructure to support effective data sharing, collaboration, and innovation across disciplines and applications. The nanotechnology community has an immediate need for an overarching digital-data infrastructure that will integrate validated experimental and modeling data and information on nanomaterials design, synthesis, properties, phenomena, and biological and environmental impact from distributed, multidisciplinary databases. Open-source, open-access practices, freely available software, search capabilities, and common formats for data transfer and archiving provide an initial starting point to organize datasets within an overarching infrastructure. While scientists would continue to store and manage access to their own data, this effort will further facilitate collaborations to incorporate consensus-driven improvements in their individual databases and create meaningful connections among databases. Standardized vocabularies and mapped ontologies will be developed through open, online dialogues to provide a shared ii NNI website; Page 6 of II

16 NNI Signature Initiative: Nanotechnology Knowledge Infrastructure May 14,2012 tenninology for scientific discourse bridging the multiple disciplines encompassed by the nanotechnology research community. Successful development of this nanotechnology data and infonnation infrastructure will provide a framework to share vetted existing and emerging data and infonnation on nanomaterial design, synthesis, and properties using standardized fonnats and vocabulary; provide more reliable data and access to the broader research community; and augment and accelerate scientific discourse, discovery, and innovation in all sectors. Expected outcomes for Thrust 4 are as follows: Strategic development of interoperable systems to enable best practices for data capture, curation, organization, evaluation, dissemination, and incorporation into computer models Standards and procedures for data management and use to facilitate significantly more efficient utilization of the databases, including lifecycle data management Expansion of reliable and efficient data analysis tools, including computer intelligence, data pattern recognition, data visualization, and multivariable structure-property correlation Development of robust validation procedures and reference data standards Mechanisms for assessing and meeting the evolving needs of scientists for data and model acquisition, sharing, and archiving Agency Roles and Contributions A concerted, interagency effort that addresses challenges spanning multiple diverse disciplines, including materials science, chemistry, biology, engineering, and advanced measurement and characterization science, will establish this critically needed Nanotechnology Knowledge Infrastructure. The NKI will leverage Federal agencies' existing and emerging efforts, such as those highlighted in the Big Data Research and Development Initiative [11], to create the infrastructure necessary to accelerate the pace of nanoscale science, engineering, and technology. Databases supported by different agencies and stakeholders will continue to be curated by their respective data experts. However, a central access point on the NNI website will allow data to be stored, administered, annotated, and shared in an easily accessible manner by the broader community. In addition to involving several Federal agencies, the NKI will continue NNI agency engagement of stakeholders in industry, academia, and nonprofit organizations in order to generate an infrastructure that is flexible enough to meet the needs of the greater community. Ongoing activities along these lines exemplify existing interactions and suggest possible approaches and opportunities for further NKI efforts: NIOSH collaborates with key NNI agencies and external stakeholders on the development and deployment of the GoodNanoGuide, a wiki-based collection of good risk management practices. In 2013, NIOSH plans to integrate activities in nanoinfonnatics with the GoodNanoGuide [12]. Page 7 of 11

17 NNI Signature Initiative: Nanotechnology Knowledge Infrastructure May 14,2012 NSF established the National Nanotechnology Infrastructure Network, which provides extensive support in nanoscale fabrication, synthesis, characterization, modeling, design, computation, and hands-on training in an open, hands-on environment available to all qualified users [12]. NIST's expanded nanoscale EHS program is supporting ongoing work in development of standard reference materials, measurement protocols, and predictive models that is coordinated with manufacturers of engineered nanomaterials and engineered nanomaterial-based products; with other NNI agencies, particularly NIOSH, OSHA, CPSC, and EPA; and with major nanoscale EHS university centers [12]. Table 2 illustrates areas of expected agency contributions to each of the key NKI thrust areas and agency overviews outlined below. Table 2. Expected Agency Contributions by Thrust Area Thrust Area CPSC DOD EPA FDA NASA NIH NIOSH NIST NSF OSHA 1. Diverse Community Development 2. Modeling Network 3. Validated Cyber- Toolbox 4. Data and Information Infrastructure Specific expertise and perspective that each participating agency will bring to this effort are as follows: CPSC: CPSC staff will provide support for risk-modeling approaches and expertise in data collection and interpretation of data assessing potential effects from exposure to nanomaterials. DOD: DOD scientists across many laboratories and fields are actively engaged in research to investigate the novel properties, potential uses, human-health and environmental effects, and other interesting and important aspects of nanomaterials. These investigations include laboratory work to generate data; development and application of modeling tools to fill gaps in that data; and development of databases, publications, and software platforms to use and share these results with the broader scientific population. EPA: EPA's efforts will include experimental testing and characterization data for reference and other nanomaterials, standardized relational databases that will support sharing of results, and models linking properties and bioactivity of nanomaterials that will be developed and shared. FDA: Coordinated databases, portals, and resources containing data on nanomaterials will provide FDA an opportunity to share its published findings on characterization of nanotechnology-based products and models for safety and efficacy assessment as well as to study the behavior of nan om ate rials in biological systems and their effects on human health. NASA: NASA is supporting R&D efforts, both in-house and with industry and academia, to develop, mature, and demonstrate high-impact nanotechnologies for use in future planetary exploration and earth and space science missions, and in the development of next-generation, environmentally benign aircraft. These efforts include a combination of experimental activities Page 8 of 11

18 NNI Signature Initiative: Nanotechnology Knowledge Infrastructure May 14,2012 and data collection, modeling, and simulation to develop new materials and devices for these applications. NASA will support the Nanotechnology Knowledge Infrastructure Signature Initiative through collaborations to develop multi scale modeling and database tools and provide experimental data to support these activities and validate computational tools. NIH: NIH will guide the nanotechnology field with a set of minimal information about nanomaterials (MIAN), ontology, and standards developed through a community effort with broad representation, that will serve as the foundation for sharing the nanomaterial data, building the modeling infrastructure, validating models against experimental data, and developing modeling tools. NIH will also contribute to building databases and registries to store and index information on nanomaterials and protocols needed for their characterization, defining standards for nanomedicine data sharing and exchange, and providing vocabulary and semantic support to the nanotechnology community. NIH will also support the development of experimentally-validated multiscale models that allow predictions across scales of space, biological organization, and time as well as data and predictive models on the toxicological implications of exposure to engineered nanomaterials. NIOSH: NIOSH's contribution will include the Nanoparticle Information Library, nanoinformatics tools, and real-life data on current and emerging nanotechnology practice in the workplace; data on workplace exposures; experimental evidence and modeling of toxic effects from exposures to categories of nanomaterials; knowledge and data on efficacy of controls; recommended exposure limits; and tools and guidance to support sustainable nanotechnology. NIST: NIST's contributions to this signature initiative will leverage its long-standing expertise in metrology and data information science. Activities at NIST in support of this NSI include the Advanced Materials for Industry program, which is focused on the development of reference data standards and data management infrastructures that will enable reliable computer modeling and simulation for materials discovery and optimization. This activity will be coordinated with other agencies' efforts on software and experimental tool design, including at DOE and NSF. NSF: This Nanotechnology Signature Initiative will build on NSF's investments in Cyberenabled Discovery and Innovation and on efforts within its Cyberinfrastructure Framework for the 21 st Century program such as Software Infrastructure for Sustained Innovation. These NSF programs will also contribute to the foundations of the NKI through specific databases for nanoscale materials and processes; transformative thinking about models for linkage of properties and behaviors at different scales; extension of computational and statistical techniques to support development and use of the nanotechnology cyber-toolbox to accelerate nanomaterials discovery and manufacturing; advances in fundamental theory and modeling; software optimized for specific computer architectures that includes documentation, representative run-time parameters and files, and other associated information necessary to duplicate example results; techniques across the scales from first principles to coarse-graining to phase-field modeling; and education to integrate the cyber-toolbox into the fabric of next-generation science and to train the next-generation modeling community. OSHA: OSHA will provide expertise and support in the area of data collection and interpretation of the biological and toxicological effects of exposure to various categories of nanomaterials. Page 9 of II

19 NNI Signature Initiative: Nanotechnology Knowledge Infrastructure May 14,2012 Coordination with the Materials Genome Initiative The Materials Oenome Initiative (MOl) [12] is a multi stakeholder effort to accelerate domestic advanced materials discovery and deployment. Synergistic areas for the NKI and the MOl exist in all four thrust areas of the NKI and in particular include community-building, protocols and best practices for data. Engagement with, and connection to, the MOl will bring mutual and reciprocal benefits to the NKI. Thus, the NKI activity described here is a Nanotechnology Signature Initiative that contributes directly to both the NNI and the MOl, making it a first-of-itskind effort in linking, impacting, and implementing multiple related Federal interagency initiatives. The NKI is intended to advance the development and curation of modeling, simulation tools, and databases that enable the prediction of specific phenomena on the nanometer length scale and in the sub-microsecond regime. The MOl scope more broadly covers materials information over a range of length scales and timeframes, including those at the nanoscale as well as the inherent properties of bulk materials. Activities of the NKI that effectively bridge the spatial and temporal spectrum are expanded upon in other MOl-related efforts including standardization of data formatting, linking experimentalists to theorists to accelerate the production of "materials by design," and fostering communication between multidisciplinary stakeholders to develop a community that pushes technologies forward. Similarly, approaches, protocols, and standards developed through other MOl activities may be initially explored, tested, or evaluated specifically for nanoscale materials under NKI efforts. This cross-fertilization between the NNI and MOl will yield broader knowledge dissemination and can be facilitated by the proposed NKI effort. Through continual dialogue, the integrated, easily accessible infrastructural elements generated by interagency coordination under these initiatives will support materials development across length and time scales and across the innovation pipeline to ensure U.S. competitiveness. References 1. National Nanomanufacturing Network, Nanoinformatics 2020 Roadmap (2011); eprints.internano.org/607/liroadmap FINAL0413I1.pdf. 2. President's Council of Advisors on Science and Technology (PCAST), Report to the President and Congress on the Third Assessment of the National Nanotechnology Initiative (2010); www. whi tehouse. gov / si tes/ defaultlfiles/mi crosi tes/ ostp/pcast -nano-report. pdf. 3. National Research Council, A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials (2012); id= President's Couneil of Advisors on Science and Technology (PCAST), Ensuring American Leadership in Advanced Manufacturing (2012); 5. National Scienee and Technology Council, Materials Genome Initiativefor Global Competitiveness (2011); genome initiativefinal.pdf. 6. R. Hoffman, A wiki for the life sciences where authorship matters, Nature Genetics (2008) 40, ; Also see 7. Cornell University Library, arxiv.org/. Page 10 of II

20 NNI Signature Initiative: Nanotechnology Knowledge Infrastructure May 14, F. Diep, Parsing the Twitterverse, Scientific American Magazine, August 2011; 9. National Science and Technology Council Subcommittee on Nanoscale Scicnce, Engineering, and Technology, National Nanotechnology Initiative Strategic Plan (2011); nano.gov/sites/defaultlfiies/pub resource/20 11 strategic plan.pdf. 10. National Science and Technology Council Subcommittee on Nanoscale Science, Engineering, and Technology, NNI Environmental, Health, and Safety Research Strategy (2011); nano.gov/sites/default/fiies/pub resource/nni 2011 ehs research strategy. pdf. 11. U.S. Office of Science and Technology Policy, "Big Data Across the Federal Government" (2012); data fact sheet final 1. pdf. 12. National Science and Technology Council Subcommittee on Nanoscale Science, Engineering, and Technology, NNI Supplement to the President's 2013 Budget (2012); resource/nni 2013 budget supplement.pdf Page II of 11

21 About the National Science and Technology Council MATERIALS GENOME INITIATIVE FOR GLOBAL COMPETITIVENESS June 2011 The National Science and Technology Council (NSTC) was established by Executive Order on November 23, This Cabinetlevel Council is the principal means within the executive branch to coordinate science and technology policy across the diverse entities that make up the federal research and development enterprise. Chaired by the President, the NSTC is made up of the Vice President, the Director of the Office of Science and Technology Policy, Cabinet Secretaries and Agency Heads with significant science and technology responsibilities, and other White House officials. For more information visit About the Office of Science and Technology Policy The Office of Science and Technology Policy (OSTP) was established by the National Science and Technology Policy, Organization and Priorities Act of OSTP s responsibilities include advising the President in policy formulation and budget development on all questions in which science and technology are important elements and articulating the President s science and technology policies and programs. For more information visit EXECUTIVE OFFICE OF THE PRESIDENT NATIONAL SCIENCE AND TECHNOLOGY COUNCIL WASHINGTON, D.C June 24, 2011 Dear Colleague: In much the same way that silicon in the 1970s led to the modern information technology industry, the development of advanced materials will fuel many of the emerging industries that will address challenges in energy, national security, healthcare, and other areas. Yet the time it takes to move a newly discovered advanced material from the laboratory to the commercial market place remains far too long. Accelerating this process could significantly improve U.S. global competitiveness and ensure that the Nation remains at the forefront of the advanced materials marketplace. This Materials Genome Initiative for Global Competitiveness aims to reduce development time by providing the infrastructure and training that American innovators need to discover, develop, manufacture, and deploy advanced materials in a more expeditious and economical way. Prepared by an ad hoc group of the National Science and Technology Council, this initiative proposes a new national infrastructure for data sharing and analysis that will provide a greatly enhanced knowledgebase to scientists and engineers designing new materials. This effort will foster enhanced computational capabilities, data management, and an integrated engineering approach for materials deployment to better leverage and complement existing Federal investments. The success of this initiative will require a sustained effort from the private sector, universities, and the Federal Government. I look forward to working with you to make this vision a reality. Sincerely, John P. Holdren Assistant to the President for Science and Technology Director, Office of Science and Technology Policy INTRODUCTION A genome is a set of information encoded in the language of DNA that serves as a blueprint for an organism s growth and development. The word genome, when applied in non-biological contexts, connotes a fundamental building block toward a larger purpose. The Materials Genome Initiative is a new, multi-stakeholder effort to develop an infrastructure to accelerate advanced materials discovery and deployment in the United States. Over the last several decades there has been significant Federal investment in new experimental processes and techniques for designing advanced materials. This new focused initiative will better leverage existing Materials Genome Initiative for Global Competiveness

22 Federal investments through the use of computational capabilities, data management, and an integrated approach to materials science and engineering. What follows describes a vision of how the development of advanced materials can be accelerated through advances in computational techniques, more effective use of standards, and enhanced data management. Detailed benchmarks and milestones will be laid out in later documents. This document is written for all stakeholders in the materials development community from experimental and theoretical scientists conducting basic research to industrial engineers qualifying new material products for market. These stakeholders span academic institutions, small businesses, large industrial enterprises, professional societies, and government. With the engagement of all stakeholders in the up-front planning and execution, this initiative will ensure the Nation remains competitive in the manufacturing and use of advanced materials. VISION STATEMENT Advanced materials are essential to economic security and human well-being, with applications in multiple industries, including those aimed at addressing challenges in clean energy, national security, and human welfare. Accelerating the pace of discovery and deployment of advanced material systems will therefore be crucial to achieving global competitiveness in the 21st century. The Materials Genome Initiative will create a new era of materials innovation that will serve as a foundation for strengthening domestic industries in these fields. This initiative offers a unique opportunity for the United States to discover, develop, manufacture, and deploy advanced materials at least twice as fast as possible today, at a fraction of the cost. MATERIALS DEPLOYMENT The Challenge In much the same way that silicon in the 1970s led to the modern information technology industry, advanced materials could fuel emerging multi-billion-dollar industries aimed at addressing challenges in energy, national security, and human welfare. Since the 1980s, technological change and economic progress have grown ever more dependent on new materials developments. 1,2 To secure its competitive advantage in global markets and succeed in the future of advanced materials development and deployment, the United States must operate both faster and at lower cost than is possible today. At present, the time frame for incorporating new classes of materials into applications is remarkably long, typically about 10 to 20 years from initial research to first use. For example, the lithium ion battery, which is ubiquitous in today s portable electronic devices, altered the landscape of modern information technologies; however, it took 20 years to move these batteries from a laboratory concept proposed in the mid 1970s to wide market adoption and use in the late 1990s. 3,4 Even now, 40 years later, lithium ion batteries have yet to be fully incorporated in the electric car industry, where they stand to play a pivotal role in transforming our transportation infrastructure. It is clear that the pace of development of new materials has fallen far behind the speed at which product development is conducted. As today s scientists and engineers explore a new generation of advanced materials to solve the grand challenges of the 21st century, reducing the time required to bring these discoveries to market will be a key driving force behind a more competitive domestic manufacturing sector and economic growth. 5 The lengthy time frame for materials to move from discovery to market is due in part to the continued reliance of materials research and development programs on scientific intuition and trial and error experimentation. Much of the design and testing of materials is currently performed through time-consuming and repetitive experiment and characterization loops. Some of these experiments could potentially be performed virtually with powerful and accurate computational tools, but that level of accuracy in such simulations does not yet exist. An additional barrier to more rapid materials deployment is the way materials currently move through their development continuum (see Figure 1), which is the series of processes that take a new material from conception to market deployment. It comprises seven discrete stages, which may be completed by different engineering or scientific teams at different institutions. This system employs experienced teams at each stage of the process, but with few opportunities for feedback between stages that could accelerate the full continuum. Materials Genome Initiative for Global Competiveness

23 In the discovery stage it is crucial that researchers have access to the largest possible data set upon which to base their models, in order to provide a more complete picture of a material s characteristics. This can be achieved through data transparency and integration. Another factor limiting a scientist s ability to model materials behavior and invent new materials is their knowledge of the underlying physical and chemical mechanisms of a material system. There is currently no standard method for researchers to share predictive algorithms and computational methods. To achieve faster materials development, the materials community must embrace open innovation. Rapid advances in computational modeling and data exchange and more advanced algorithms for modeling materials behavior must be developed to supplement physical experiments; and a data exchange system that will allow researchers to index, search, and compare data must be implemented to allow greater integration and collaboration. Later parts of the continuum are necessarily linear (i.e. certification cannot occur before systems design), but all stages would benefit from increased data transparency and communication. Currently, no infrastructure exists to allow different engineering teams to share data or models. Data transparency may have the largest impact after the material has been deployed, due to the fact that every industry relies on materials as components of product design. A product designer who needs a material of certain specifications may not be aware that the material has already been designed because there is no standard method to search for it. Data transparency encourages cross-industry and multidisciplinary applications. The life cycle of a material does not end with deployment. An issue that is coming more to the attention of industry and consumers is the recyclability and sustainability of materials. Materials engineers must design for the ever-changing parameters and uses of materials after their initial intended purpose; for example, recyclability must become a design parameter. The Materials Genome Initiative will develop the toolsets necessary for a new research paradigm in which powerful computational analysis will decrease the reliance on physical experimentation. Improved data sharing systems and more integrated engineering teams will allow design, systems engineering, and manufacturing activities to overlap and interact (see Figure 2). Materials Genome Initiative for Global Competiveness This new integrated design continuum incorporating greater use of computing and information technologies coupled with advances in characterization and experiment will significantly accelerate the time and number of materials deployed by replacing lengthy and costly empirical studies with mathematical models and computational simulations. Now is the ideal time to enact this initiative; the computing capacity necessary to achieve these advances exists and related technologies such as nanotechnology and bio-technology have matured to enable us to make great progress in reducing time to market at a very low cost. Multiple international entities have recognized these issues and a number of foreign countries have already embarked on programs to address them. 6 The National Research Council of the National Academies of Sciences, in its report on Integrated Computational Materials Engineering, describes the potential outcome:

24 Integrating materials computational tools and information with sophisticated computational and analytical tools already in use in engineering fields [promises] to shorten the materials development cycle from its current years to 2 or 3 years. 7 While it is difficult to anticipate the actual reduction in development time that will result from this initiative, our goal is to achieve a time reduction of greater than 50 percent. ACCELERATING THE MATERIALS CONTINUUM The Materials Genome Initiative would create a materials innovation infrastructure to exploit this unique opportunity. The full Initiative is captured in Figure Developing a Materials Innovation Infrastructure The Materials Genome Initiative will develop new integrated computational, experimental, and data informatics tools. These software and integration tools will span the entire materials continuum, be developed using an open platform, improve best-inclass predictive capabilities, and adhere to newly created standards for quick integration of digital information across the materials innovation infrastructure. This infrastructure will seamlessly integrate into existing product-design frameworks to enable rapid and holistic engineering design. 2. Achieving National Goals With Advanced Materials The infrastructure created by this initiative will enable scientists and engineers to create any number of new advanced materials, many of which will help solve foundational science and engineering problems and address issues of pressing national importance. The Federal government intends to host interagency workshops with all relevant stakeholders to identify high priority material problems, which will be used to develop and coordinate the Initiative and to sustain the long-term process of accelerating materials development outlined in this vision document. 3. Equipping the Next-Generation Materials Workforce Success of this initiative cannot be measured by the tools alone, but rather by the pervasiveness of their use and the outcomes they enable. Equipping our next-generation workforce with the tools and approaches necessary to achieve our national goals will require stakeholders in government, academia, and industry to embrace the scope and contents of the materials innovation infrastructure. This will be achieved with a focus on education, workforce development, and a generational shift toward a new, more integrated approach to materials development. DEVELOPING A MATERIALS INNOVATION INFRASTRUCTURE Computational Tools Major advances in modeling and predicting materials behavior have led to a remarkable opportunity for the use of simulation software in solving materials challenges. New computational tools have the potential to accelerate materials development at all stages of the continuum. For example, software could guide the experimental discovery of new materials by screening a large set of compounds and isolating those with desired properties. Further downstream, virtual testing via computer-aided analysis could Materials Genome Initiative for Global Competiveness

25 replace some of the expensive and time-consuming physical tests currently required for validation and certification of new materials. These computational tools are still not widely used due to industry s limited confidence in accepting non-empirically-based conclusions. Materials scientists have developed powerful computational tools to predict materials behavior, but these tools have fundamental deficiencies that limit their usefulness. The primary problem is that current predictive algorithms do not have the ability to model behavior and properties across multiple spatial and temporal scales; for example, researchers can measure the atomic vibrations of a material in picoseconds, but from that information they cannot predict how the material will wear down over the course of years. In addition, software tools that utilize the algorithms are typically written by academics for academic purposes in separate universities, and therefore lack user-friendly interfaces, documentation, robustness, and the capacity to scale to industrial-sized problems. These deficiencies inhibit efficient software maintenance and can result in software failures. Significant improvements in software and the accuracy of materials behavior models are needed. Open innovation will play a key role in accelerating the development of advanced computational tools. A system that allows researchers to share their algorithms and collaborate on creating new tools will rapidly increase the pace of innovation, which currently occurs in isolated academic settings. An existing system that is a good example of a first step toward open innovation is the nanohub, a National Science Foundation program run through the Network for Computational Nanotechnology. 8 By providing modeling and simulation applications that researchers can download and use on their data, nanohub.org supports the use of computational tools in nanotechnology research. Researchers can access state-of-the-art modeling algorithms and collaborate with colleagues via the website. To rapidly increase knowledge of first principles and advance modeling algorithms, it is essential for the materials industry to accept open innovation and design these tools on an open platform. The ultimate goal is to generate computational tools that enable real-world materials development, that optimize or minimize traditional experimental testing, and that predict materials performance under diverse product conditions. An early benchmark will be the ability to incorporate improved predictive modeling algorithms of materials behavior into existing product design tools. For example, the crystal structure and physical properties of the materials in a product may change during the product s processing, due to varying conditions. It could be disastrous to the performance of a product if, for instance, the tensile strength of its bolts changed during manufacture. The ability to model these morphology and property changes will enable faster and better design. Achieving these objectives will require a focus in three necessary areas: (1) creating accurate models of materials performance and validating model predictions from theories and empirical data; (2) implementing an open-platform framework to ensure that all code is easily used and maintained by all those involved in materials innovation and deployment, from academia to industry; and (3) creating software that is modular and user-friendly in order to extend the benefits to broad user communities. Experimental Tools The emphasis of the Initiative is on developing and improving computational capabilities, but it is essential to ensure that these new tools both complement and fully leverage existing experimental research on advanced materials. Effective models of materials behavior can only be developed from accurate and extensive sets of data on materials properties. Experimental data is required to create models as well as to validate their key results. Where computations based on theoretical frameworks fall short, empirical testing will fill in the gaps. As mentioned previously, most computational models are not yet capable of multi-scale modeling. Empirical data will help the models bridge gaps in the material length scale and significantly accelerate the pace of building fundamental understanding and developing new materials. Once the models are improved by incorporating new data, they will provide faster, more efficient, and more comprehensive performance data than could be generated by experiments alone. One advanced technique that is already implemented in industry is high throughput combinatorial processing. The General Motors Company, for example, has been working on next-generation catalysts for automobile exhaust emission control and on developing detailed kinetics and predictive physics-based models to describe the performance of these catalysts. 9 With support fromthe Department of Energy in 2002, General Motors used high throughput combinatorial techniques to rapidly synthesize and screen a broad range of catalyst materials, the most promising of which were tested on engines and are being considered for commercial use. 10 This type of rapid characterization technique, when complemented by computational capabilities and a highly trained workforce, will help to accelerate the discovery process. Beyond leveraging existing experimental work, there will be specific needs for new techniques in experimentation and characterization to realize the synergy between experiments and computational methods. New experimental and characterization tools must be rooted in fundamental physics, chemistry, and materials science. Materials properties will be measured as a function of key variables, such as composition and processing history, as they relate to empirical theories and existing data. The experimental input required goes far beyond a single set of measurements. In most cases, researchers must combine and calibrate data from many experiments into a single larger data set that represents the entire system and allows the determination of complex Materials Genome Initiative for Global Competiveness

26 properties. One important characterization technique is the visualization of structure in three dimensions. This is typically done by assembling and aligning a large number of two-dimensional images. The final representation may then be combined with compositional, mechanical, electronic, and optical property measurements to give quantitative and complete descriptions of a material. The experimental piece of this initiative will implement existing and new methods and technologies to characterize relevant properties efficiently and quantitatively during synthesis and processing or over a range of operating conditions and environments. In situ characterization techniques to determine materials properties during processing will be paired with computational tools to enable rapid screening of materials, reactions, and processes over a wide range of length and time scales. Experimental outputs will additionally be used to provide model parameters, validate key predictions, and supplement and extend the range of validity and reliability of the models. Digital Data Data whether derived from computation or experiment are the basis of the information that drives the materials development continuum. Data inform and verify the computational models that will streamline the development process. The goal of this initiative is not only to allow researchers to easily incorporate their own data into models but additionally to enable researchers and engineers to incorporate each other s data. The sharing of data will give each research or engineer a broader set of information to work with, which will render more accurate models. A data-sharing system would also facilitate multi-disciplinary communication between scientists and engineers working on different stages of the materials development continuum. The key to accelerating the rate of innovation is streamlining how data are incorporated into models and experiments and enabling data transfer between various software systems at different institutions. Data transparency is also crucial in the later stages of the continuum, after discovery. For product designers looking for a material with certain parameters, a system that would allow them to search for advanced materials would be invaluable. Enabling cross-industry applications will be an important piece of the Initiative. Creating this data transfer system will be a challenge, but not an unprecedented one. Various innovative data transfer methods have been developed, for example, for sharing patient information between different hospitals. As described in a 2010 President s Council of Advisors on Science and Technology report on Health Information Technology, one viable option is tagging medical information with metadata that contains the patient s identifier and can be found via a simple crawl through all the hospitals data. 11 The advantage of a metadata system is that once the data is formatted it can be incorporated into any number of software systems at different institutions for analysis. Standard formats for the different types of materials data let researchers easily understand and incorporate their colleagues findings into their own models. Another potentially useful technology is cloud computing, which allows for efficient remote data storage and sharing of software applications. It will be necessary to devise new approaches to data storage specific to materials data to enable effective retrieval and analysis. Issues surrounding intellectual property naturally arise during discussions of data. There is an unavoidable tension between the scientific need for openness and the industrial concern for protection of intellectual property. Indeed, to be effective, this initiative will need to harmonize with any number of business models. In the example of metadata tagging, participants would be able to tag certain pieces of data as private so that those data would not be included in the crawl. Whatever data-sharing model is adopted, it is essential for companies working at all stages of the materials lifecycle to be free to share information when they feel disclosure would yield a net benefit, yet still keep valuable intellectual property confidential. The digital data contribution to this initiative will establish a data-storage and transfer system for materials researchers and engineers. The system implemented would preferably allow participating institutions to retain their legacy software systems but facilitate data transfer and efficiently integrate the new data into models. The system must also allow institutions to choose which of their data sets are searchable. In addition, this initiative will emphasize accuracy and verifiability of models and experimental tools being developed and support informatics research to enable the most effective retrieval and analysis of materials data in this new paradigm. Advanced data-sharing techniques at all stages of the development continuum will be the driving force behind the Initiative and help build the scholarly record. ACHIEVING NATIONAL GOALS USING ADVANCED MATERIALS The infrastructure created by this initiative will facilitate and expedite the discovery and development of a broad spectrum of advanced materials, to the benefit of scientific inquiry and the national economy. Some of our Nation s most pressing challenges in areas such as clean energy, national security, and human welfare could be addressed by advanced materials. This initiative will Materials Genome Initiative for Global Competiveness

27 foster cross-sector and cross-disciplinary collaboration so that scientists and engineers working on related materials for different purposes can cooperate and provide a better result. The examples that follow are problems that reflect how diverse the field of materials science is and how broad an impact this initiative may have. They are mere examples, however, of the types of problems that could be addressed. Materials for National Security The Department of Defense and the national defense laboratories are significantly invested in materials research. The research labs work on advances in lightweight protection materials, electronic materials, energy storage, and bio-surrogate materials to name a few. While the Department of Defense uses advanced materials to protect and arm our troops, materials also play a role in many other areas of national security. Critical minerals are a relevant example. Material Example: Finding Substitutes for Critical Minerals Minerals are important components of many products civilians use in daily life (e.g., cell phones, computers, and automobiles), as well as crucial military applications (e.g., avionics, radar, precision-guided munitions, and lasers). According to a National Academies study, each person in the United States consumes, on average, 25,000 pounds of non-fuel minerals each year. 12 Yet the United States does not mine or process much of that raw material. The National Academies defines a critical mineral as one whose supply chain is at risk, for which the impact of a supply restriction would be severe, or both. Currently, the American manufacturing sector is struggling to maintain adequate supplies of critical minerals at reasonable costs. As the use of critical minerals increases, this supply shortage may be amplified unless additional domestic supply is identified and captured. Many materials are referred to as critical because supply is highly concentrated in either one country or by a few corporate interests, and because they are used in the production of goods that are important economically or for national security. Today, there is particular concern about materials like platinum, tellurium, and certain rare earth elements because they are essential to the manufacture of products in key high-growth sectors, including clean energy, consumer electronics, and defense, among others. The discovery and development of technology substitutes that deliver the same functionality but replace critical minerals, like the rare earth elements, with those that are more earth-abundant is one strategy that would have the dual benefit of protecting our military capabilities while also addressing the growing dependence on any mineral resource, domestic or foreign, that are unstable or subject to supply disruptions. The infrastructure created by this initiative could assist researchers and engineers to rapidly discover and develop substitutes for technologies and applications that are currently dependent on these critical minerals for which no known alternative is available today. Such applications will range from personal electronics to missile guidance systems. Materials for Human Health and Welfare There are many applications for advanced materials to address challenges in human health and welfare from biocompatible materials like prostheses or artificial organs to protective materials designed to prevent injury. Advanced materials designed to prevent traumatic brain injuries are one example with potential benefits across diverse user groups including athletes and military personnel. Material Example: Preventing Traumatic Brain Injury Traumatic brain injuries (TBI) occur when an external force impacts the head or body, leading to a loss of consciousness, amnesia, and/or alterations in normal brain function. An estimated 360,000 military personnel have been afflicted by a TBI during the conflicts in Iraq and Afghanistan, and each year 1.7 million civilians suffer from TBI due to falls and athletic/vehicle accidents. The medical costs and lost productivity of these injuries are estimated to exceed $60 billion annually. 13,14 Suitably designed protective gear can prevent these injuries. Designing gear that accounts for the wide range of conditions and circumstances that can lead to TBI, however, presents a challenging materials problem. For example, advanced materials might be used in a host of protective technologies for military and passenger vehicles, body armor, and sports equipment to limit the devastating effects of blasts, impacts, and collisions. But in each circumstance, understanding the response of protective gear and the subsequent manner in which impact forces are transmitted to the brain (or body) is paramount for innovative and targeted materials solutions. 15 This initiative could provide tools to assess the requirements of these different applications, optimize materials designed for specific uses, and identify potential overlapping uses for materials in the military and civilian sectors. Materials for Clean Energy Systems Materials Genome Initiative for Global Competiveness

28 Developing sources of clean energy and reducing our dependence on oil are key national priorities. Materials research can help us find new technologies such as better catalysts for the production of biofuels, artificial photosynthesis to derive energy directly from sunlight, novel high-efficiency solar photovoltaics, and portable energy-storage devices. There are also many ways advanced materials could reduce dependence on oil in the transportation sector, as the following example points out. Material Example: Reducing Oil Dependence for Transportation Of the 12 million barrels of oil per day the U.S. imported from foreign sources in 2009, two-thirds was for transportation fuels. 16 Motorized road transport consumes around 19 percent of the global energy supply, 15 and aviation accounts for another 3 percent. 17,18 Improving fuel efficiency in the transportation sector is therefore an important target for decreasing oil consumption. The development of new lightweight materials for vehicles could significantly improve fuel efficiency. Every 10-percent reduction in passenger vehicle weight in a conventional combustion engine car could reduce fuel use by six to eight percent. 19,20 Yet, to be successful, these lightweight materials would still need to meet the structural integrity and safety standards of more traditional materials in use today for both commercial passenger vehicles and those designed for military deployment. In addition, automobile companies are starting to deploy alternative vehicles such as hybrids, electric cars, and hydrogen fuel-cellpowered cars. The technologies used in these vehicles have great potential to replace conventional combustion engines, however there are unresolved issues limiting their widespread use. Current batteries have low energy density and take a long time to charge. Hydrogen fuel cells powerful enough to run a car use significant quantities of high cost metals. This initiative could provide tools to optimize and deploy new materials such as high-performance, cost-effective, lightweight structural materials and better portable energy-storage devices that will address national economic and security challenges through the reduction of oil use in the United States. EQUIPPING THE NEXT-GENERATION WORKFORCE It is clear that a new infrastructure for materials development will not solve real-world problems unless it is widely deployed. Equipping our next-generation workforce with the tools and approaches necessary to achieve our national goals will require stakeholders in government, academia, and industry to embrace and continuously expand the scope and contents of the materials innovation infrastructure. Investments must also be directed toward advancing a culture supporting the routine production and use of the tools developed, illustrating the opportunities and advantages it creates, and guiding its implementation and validation across the entire materials continuum from education of undergraduates through the adoption of these paradigm shifts by industry. The inherently fragmented and multidisciplinary nature of the materials community poses barriers to establishing the required networks for sharing results and information. One of the largest challenges will be encouraging scientists to think of themselves not as individual researchers but as part of a powerful network collectively analyzing and using data generated by the larger community. These barriers must be overcome. Rapid advances in materials discovery and design will be realized not merely through one-on-one interactions or pre-existing relationships, but also through multiple layers of collaboration among government agencies, academia, and industry. The Initiative will develop and support a coordinated effort to establish the infrastructure and protocols to facilitate collaborations among academic, government, and industrial participants, both by function (experimentalists, engineers, theoretical scientists, and computer scientists) and institution (academia, government research laboratories, small and medium enterprises, and large companies). New partnerships will also be stimulated between manufacturers and software developers to rapidly convert science-based materials computational tools into engineering tools. By expanding and facilitating more integrated relationships, the Initiative will bring experimentalists, theorists, computer scientists, and engineers into closer proximity to work in the same research space. Furthermore, the digital data aspects and open platforms that call for more transparency and easy access to data will facilitate a more integrated materials community, thereby expediting the development of more accurate models, highly reproducible and validated work, and a better understanding of materials properties and product design. Support for advanced computation and experimental tools will provide basic research opportunities that will serve to educate researchers, faculty, and students in the critical aspects of contributing to and applying the infrastructure from discovery to deployment. This includes the increased use of modeling and simulation along with understanding how these must be coupled with new experimental and characterization tools. University involvement with the foundational science and engineering problems will further encourage materials scientists and engineers to learn how to integrate their knowledge into quantitative tools that materials and systems design engineers can use to Materials Genome Initiative for Global Competiveness

29 identify, optimize, and speed product development. A natural consequence of this integrated and coordinated research approach will be the introduction of new cross-disciplinary courses in undergraduate and graduate curricula that put into practice the fundamental tenets of the Materials Genome Initiative. An added benefit is that the computational toolsets developed through this initiative will become an integral component of all engineering programs, allowing students to explore what if scenarios as part of their regular coursework. This exploratory approach will instill in them the fundamental principles of integrated discovery that underlie this initiative, and ensure that the nextgeneration of scientists and engineers are empowered to fully exploit the power of this new infrastructure, while continuing to expand the tools and knowledgebase on which future advances will depend. Finally, an important extension of these educational efforts into the industrial sector will be continuing education programs to enhance the skills of professionals in industry, who will have an important role as implementers of these materials innovations. Professional societies serving the materials community can utilize and leverage their existing education infrastructure, experience, and expertise to further advance this goal. ACHIEVING THE VISION: NEXT STEPS While this document does not describe specific policy actions for implementation of the Materials Genome Initiative, it does suggest next steps toward achieving the vision outlined here. The Administration will begin a road mapping exercise on all pieces of the materials innovation infrastructure for example, by convening workshops between government agencies, industry, national labs, and universities to elicit suggestions for policy, infrastructure design, and the identification of high priority foundational science and engineering problems. While some government agencies have existing programs that will connect to the goals of this initiative, in FY 2012 the Obama Administration has requested $100M in support for multi-year programs that will launch various components of the Materials Genome Initiative. These programs are across: the Department of Energy (DOE), the National Institute of Standards and Technology (NIST), the National Science Foundation (NSF), and the Department of Defense (DOD) While all aspects of this initiative will be coordinated among the participating agencies, this budget request includes the following new targeted activities: 1. The DOE Office of Science and NSF will work together to enable the development, maintenance, and deployment of reliable, interoperable, and reusable software for the next-generation design of matter. The DOE, through its Computational Materials and Chemistry by Design program, and NSF, through aspects of its Cyberinfrastructure Framework for 21st Century Science and Engineering, will coordinate activities on the development of high quality production software toolkits that both incorporate new algorithms and allow for interoperability with existing software tools. 2. In support of their advanced software programs, both the DOE and NSF will also coordinate activity in the development of nextgeneration characterization tools that provide the fundamental basis for development of and validation of the algorithms and software tools. 3. An Advanced Materials by Design program led by NIST will target the development of standards infrastructure, reference databases, and centers of excellence that will enable reliable computer modeling and simulation for materials discovery and optimization. This activity will be coordinated closely with the DOE and NSF efforts on software and experimental tool design. 4. The DOD will invest in basic and applied computational materials research directed toward enhancing performance and accelerating transition of advanced materials to meet a broad array of national security needs and maintain a technological advantage in defense systems along the full materials continuum from discovery through deployment, including maintenance and recovery of assets. These efforts will be integrated across the science and technology programs of the military services (i.e. Army Research Labs, Office of Naval Research, and Air Force Research Labs). 5. DOE s Energy Efficiency and Renewable Energy Next-Generation Materials program will leverage computational tools to accelerate manufacture and characterization of new materials for energy technologies. It will invest in such areas as: new materials used in manufacturing processes, new hybrid composite material systems with improved materials properties and lower manufacturing cost, modeling and simulation tools for predicting spatial and temporal variability of new materials, and tools for rapidly verifying fitness of new materials for intended use. 6. NSF and DOD will play a lead role in addressing the next-generation workforce goals by: facilitating new partnerships between the relevant science and engineering communities in academia, government and industry to promote a culture supporting and Materials Genome Initiative for Global Competiveness

30 embracing the use of the capabilities developed within this initiative; and engaging with students and colleagues to develop the culture and relevant training of the next-generation workforce. CONCLUSION In summary, advanced materials are essential to human well-being and are the cornerstone for emerging industries. Yet, the time frame for incorporating advanced materials into applications is remarkably long, often taking 10 to 20 years from initial research to first use. The Materials Genome Initiative is an effort that will address this problem through the dedicated involvement of stakeholders in government, education, professional societies, and industry, to deliver: (1) the creation of a new materialsinnovation infrastructure, (2) the achievement of national goals with advanced materials, and (3) the preparation of a nextgeneration materials workforce to sustain this progress. Such a set of objectives will serve a more competitive domestic manufacturing presence one in which the United States will develop, manufacture, and deploy advanced materials at least two times faster than is possible today, at a fraction of the cost. References 1 Markowitz, S. (2009). The Advanced Materials Revolution: Technology and Economic Change in the Age of Globalization.New York: John Wiley and Sons, Inc. 2 Department of Energy Workshop. (2010). Computational Materials Science and Chemistry for Innovation.United States Department of Energy. 3 Whittingham, M. S. (1976, June). Electrical Energy Storage and Intercalation Chemistry. Science, 192(4244), doi: /science Brodd, R. J. (n.d.). Comments on the History of Lithium-Ion Batteries. Retrieved from The Electrochemical Society website: 5 Cummings, P. T., & Glotzer, S. C. (2010). Inventing a New America Through Discovery and Innovation in Science, Engineering, and Medicine. Retrieved from World Technology Evaluation Center and the National Science Foundation website: 6 World Technology Evaluation Center. (2009). WTEC Panel Report on International Assessment of Research and Development in Simulation-Based Engineering and Science. Retrieved from 7 National Research Council. (2008). Integrated Computational Materials Engineering. Washington, DC: The National Academies Press. 8 Network for Computation Nanotechnology. (2009). nanohub. Retrieved from National Science Foundation website: 9 Rao, S., Imam, R., Ramanathan, K., & Pushpavanam, S. (2009, March). Sensitivity Analysis and Kinetic Parameter Estimation in a Three Way Catalytic Converter. Industrial and Engineering Chemistry Research, 8(48), doi: / ie801244w 10 Cooperative Agreement Number: DE-FC26-02NT President s Council of Advisors on Science and Technology. (2010, December). Realizing the Full Potential of Health Information Technology to Improve Healthcare for Americans: The Path Forward. Retrieved from Executive Office of the President website: 12 National Research Council. (2008). Minerals, Critical Minerals, and the U.S. Economy. Washington, DC: The National Academies Press. 13 Division of Injury Response at the National Center for Injury Prevention and Control. (2006, January). Traumatic Brain Injury in the United States: Emergency Department Visits, Hospitalizations, and Deaths. Retrieved from Centers for Disease Control and Prevention, U.S. Department of Health and Human Services website: 14 Finkelstein, E. A., Corson, P. S., & Miller, T. R. (2006). The Incidence and Economic Burden of Injuries in the United States. New York: Oxford University Press. 15 Stuhmiller, J. H. (2008). Blast Injury: Translating Research into Operational Medicine (W. R. Santee, K. E. Friedl, & Walter Reed Army Medical Center Borden Institute, Eds.). TMM Publications. 16 Detailed Statistics Tables. (2009). Petroleum Supply Annual of the Energy Information Administration, 1. Retrieved from ( 17 International Energy Agency. (2008). Key World Energy Statistics Energy Information Administration. (2007). International Energy Outlook United States Department of Energy. 19 National Research Council. (2011). Assessment of Technologies for Improving Light Duty Vehicle Fuel Economy. Washington, DC: The National Academies Press. 20 United States Automotive Materials Partnership. (2007). Magnesium Vision 2020: A North American Automotive Strategic Vision for Magnesium. Materials Genome Initiative for Global Competiveness

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