A Prospective Look at the MGI After Five Years: Keynote Session
Sponsored by: TMS: Materials Innovation Committee
Program Organizers: Charles Ward, Air Force Research Laboratory; Kevin Hemker, Johns Hopkins University; John Allison, University of Michigan
Monday 3:25 PM
February 27, 2017
Location: San Diego Convention Ctr
Session Chair: Charles Ward, Air Force Research Laboratory; Kevin Hemker, Johns Hopkins University; John Allison, The University of Michigan
3:25 PM Introductory Comments
3:30 PM Keynote
Spatiotemporally Integrated Theory, Computation and Experiments: A Frontier of the Materials Genome Initiative: Dennis Dimiduk1; 1BlueQuartz Software, LLC and Ohio State University
Inception of the Materials Genome Initiative (MGI) focused attention on accelerating materials discovery and deployment through transformational communal digital tools. Theory and computing are evolving beyond isolated computational materials sciences, and multiscale materials modeling, toward robust search and better integration with advanced experimental methods. Five years of MGI progress also reveals that an under-developed foundational taxonomy, ontology, and digital tool set, for spatiotemporal, hierarchical materials structure, limits advances across modeling, simulations and experiments. Thus, building reciprocity relationships between materials models, structure characterization, and measured responses is key for broad-based progress through the coming decade.
4:00 PM Keynote
The Materials Genome Initiative – Leading a Culture Shift in Materials Research: Kevin Anderson1; 1Brunswick Corporation – Mercury Marine Division
In 2011, President Obama launched a broad set of tangible initiatives to revitalize U.S. manufacturing. A healthy, vibrant, competitive manufacturing industry transcends politics and improves the lives of all Americans. As materials are an integral part of almost every manufactured product, the Materials Genome Initiative (MGI) was therefore launched as a key initiative by the President. In alignment with its’ goals, the MGI has greatly reduced the time and costs associated with new material innovations in just 5 years. The MGI has resulted in a cultural transformation within our nations’ materials innovation processes. The speaker will discuss and provide examples of the improved cultural interaction between academia, our national and federal laboratories, and industry. The speaker will also discuss and provide examples of the impact of the MGI in bringing a new culture of innovation and problem solving directly onto the manufacturing floors of our country.
4:30 PM Keynote
Democratizing Large-scale Data and Machine Learning in Materials Research: Bryce Meredig1; 1Citrine Informatics
Over the first five years of the Materials Genome Initiative (MGI), the materials community has gained new appreciation for the enormous potential of digital data in the research enterprise. Nonetheless, the fact remains that the vast majority of materials research data is neither widely accessible nor readily computable (i.e., amenable to statistical analyses and machine learning). In this talk, we will discuss the past five years of MGI-related data infrastructure work that has made it possible today to store all essential research data for the entire materials community. We will further discuss a set of key incentives that we believe--when implemented within data infrastructure--will lead to a critical mass of materials researchers contributing their data to a widely accessible, computable infrastructure. If we characterize the first five years of the MGI as the infrastructure-building period, we anticipate that the next five years of MGI will be marked by rapid proliferation of machine learning within materials research, and a concomitant flourishing of newly-enabled, data-driven discoveries.
5:00 PM Keynote
The Materials Genome after Five Years: An Academic Perspective: Tresa Pollock1; 1University of California Santa Barbara
This talk will highlight progress toward major goals of the MGI in the areas of materials science research and workforce development from the academic perspective. The MGI aims to integrate theory, simulation and experimentation at all length scales; recent examples of successful integration and development of new tools within collaborative academic research programs will be discussed. The evolving landscape of instrumentation and the computational infrastructure pose both challenges and opportunities. The future workforce will ideally operate in a model-based infrastructure for materials discovery, development and design through development of a high level of expertise in basic computational methods, image processing, data and machine learning tools, statistical methods and familiarity with "industry standard" software packages. The associated educational resources, curriculum development and programs to "educate the educators" will be reviewed.