Expanding the Boundaries of Materials Science: Unconventional Collaborations: Multidisciplinary Research
Program Organizers: Sourabh Bhagwan Kadambi, Idaho National Laboratory; Alex Hsain, North Carolina State University; Brady Dowdell, North Carolina State University; Benjamin Anthony, University of Florida
Monday 8:00 AM
February 24, 2020
Room: 4
Location: San Diego Convention Ctr
Session Chair: Alex Hsain, North Carolina State University; Sourabh Kadambi, North Carolina State University
8:00 AM Introductory Comments
8:05 AM Invited
Innovation in Materials Research Collaborations: DOE Basic Energy Sciences: Linda Horton1; 1Department of Energy - Basic Energy Sciences
Basic Energy Sciences (BES) supports fundamental research to understand, predict, and ultimately control matter and energy at electronic, atomic, and molecular levels to provide foundations for new energy technologies. BES has long-standing strategic planning processes, including BES advisory committee reports and topical in-depth community workshops and reports. Beyond research directions, this planning has defined innovations in how science is funded. Historically, the major funding modality was single investigators at universities and small groups at national laboratories. However, aggressive strategic planning, begun in 2002, identified more complex energy challenges and the need to add a funding modality for large research teams. These recommendations led to Energy Frontier Research Centers, and contributed to Energy Innovation Hubs and Computational Materials Sciences activities. These research teams, often at multiple institutions, can make significant advances by working across disciplines in a focused, synergistic manner. This presentation will overview the success and impact of these modalities.
8:35 AM Invited
Mechanical Properties of Molecular Crystals--Connecting with Chemistry: Ramamurty Upadrasta1; 1NTU
Nanoindentation is a technique with which mechanical properties of materials, even when they are available only in small quantities, can be measured with high precision. As a result of this particular advantage, this technique can be utilized for inter-disciplinary research between chemists and materials engineers. Our recent work had demonstrated that the mechanical properties of single crystals of molecular solids can not only be measured, but also connected to the underlying structural features and intermolecular interactions. Further, we have demonstrated that the knowledge so gained can be utilized for identifying the design principles for organic materials with desired properties as well as for the study of the 'microstructure' in them. This talk will illustrate these through the presentation of a few representative examples of our studies.
9:05 AM Invited
Integrating Experiment, Data, and Computations to Accelerate the Design of Materials: Peter Voorhees1; Greg Olson1; Juan DePablo2; 1Northwestern University; 2University of Chicago
The classical method for designing materials to achieve certain performance goals involves a laborious procedure wherein intuition drives the design of a material that is then created, and tested. In most cases, the performance goals are not achieved, and this costly procedure is repeated. By integrating data, computations, and artificial intelligence it is possible to break this expensive cycle and bring innovative new materials to the marketplace faster and at a lesser expense. The Center for Hierarchical Materials Design (CHiMaD) is focusing on developing the next generation of computational tools, databases, and experimental techniques in order to enable the accelerated design of novel materials and their integration into industry. Illustrations of the power of this enhanced materials design strategy will be provided through examples of the design of materials from cobalt superalloys to 2D-material heterostructures.
9:35 AM Break
10:00 AM Invited
Convergence: Supporting Multidisciplinary Research at the National Science Foundation: Alexis Lewis1; 1National Science Foundation
As one of the US National Science Foundation's "Ten Big Ideas for Future Investment," Convergence of scientific disciplines has emerged as an exciting opportunity. This presentation will describe NSF's efforts in promoting and supporting Convergent Research, with an emphasis on programs related to Materials Science and Engineering. The types of boldly interdisciplinary collaborations in which Materials Scientists and Engineers are engaged will be described, and details will be provided of funding opportunities and upcoming activities designed to promote and support convergent collaborations in fundamental scientific research.
10:30 AM Invited
Machine Learning for Materials Design and Discovery: Bryce Meredig1; 1Citrine Informatics
The rise of machine learning (ML) in materials science has led to interdisciplinary research drawing from the materials, computer science, and statistics fields. In this talk, we will describe ways in which materials design is a unique application area for ML, and also ways in which research threads from computer science and statistics are enriching materials informatics.
11:00 AM
Regularization of Materials Failure Data for Damage Mechanism Categorization by Machine Learning: John Hasier1; Keo-Yuan Wu2; Rachel Wittman1; 1Intertek; 2UCLA
Material failures in power generation are messy, expensive events that generate large amounts of variable quality data. Machine learning classification of failure mechanisms can enable a move from material failure correction, currently requiring multidisciplinary teams of experts, to failure prevention. A machine learning driven expertise engine for operators and engineers can provide just-in-time knowledge to assist in critical decisions. Regularization of data is a critical and often trivialized step for the application of modern machine learning techniques to solve domain specific problems, as machine learning techniques fail to provide useful insights if the data fed to them is not well curated. This talk uses the creation of a training dataset based on decades of power generation failure analysis reporting as a vehicle to explore the challenges encountered by materials engineers and data scientists in sculpting real-world material science data into a useful input for modern data analytics techniques.