Traditionally, design with materials has been a sub-discipline of design engineering which addresses materials selection based on material properties various applications. This traditional empirical approach has been emphasized in engineering curricula for the last 20 years, but is increasingly shifting towards design of materials to achieve some form of optimized functionality, driven largely by advances in theoretical modeling, process modeling and analytical materials characterization.
Integrating computational materials science and mechanics with manufacturing and design of products is a major opportunity made possible by the confluence of advances in modeling and simulation tools, high performance computing, and quantitative materials characterization. This integration represents a significant leap beyond materials selection in design, as traditionally taught and practiced in engineering. The recent emphasis on Integrated Computational Materials Engineering (ICME) demands integration of computational modeling and simulation with product development, and has much common ground with the notion of tailoring materials to achieve targeted properties or responses, commonly referred to as Materials Design. ICME includes various aspects of materials processing, manufacturing, fabrication, and performance/property projections, and involves materials science and mechanics, computing, experimental methods and validation methodologies, and multidisciplinary design optimization, among other disciplines and sub-disciplines. ICME has been elaborated upon by the recent report “Integrated Computational Materials Engineering: a transformational discipline for improved competitiveness and national security” by the Committee on Integrated Computational Materials Engineering, National Materials Advisory Board, National Research Council of the National Academies, The National Academies Press, Washington, DC ISBN 13:978-0-309-11999-3, 2008. ICME has been further reinforced by the 2011 federal Materials Genome Initiative, which seeks to discover and develop new and improved materials at half the cost in half the time.
The important point is that design is a top-down, inductive pursuit, in contrast to the inherently bottom-up, forward nature of modeling and simulation methods. This duality presents a challenge to decision-based design, which necessarily must extract information and guidance from experiments, models and simulations conducted at judiciously selected scales of material hierarchy associated with the dominant design degrees of freedom, as shown at right. We have been collaborating extensively with other groups to develop methods to combine bottom-up modeling and simulation with top-down decision based design, as highlighted in papers listed at the bottom of this page.
Leadership from the Paden Chair in the field of materials design goes back to the NSF-sponsored Workshop held in October 1998 on Materials Design Science and Engineering (MDS&E) in Atlanta that was co-hosted by Georgia Tech (D.L. McDowell) and Morehouse College:
You may be interested in how far we have come in the last decade and where we are headed by reading the following:
- Plasticity-Related Microstructure-Property Relations for Materials Design (3.2MB PDF)
- Simulation-Assisted Materials Design for the Concurrent Design of Materials and Products (2.4MB PDF)
- Concurrent Design of Hierarchical Materials and Structures, co-authored with Greg Olson (1.2MB PDF)
- Our recent book from Elsevier: Integrated Design of Multiscale, Multifunctional Materials and Products ( PDF)
Also please consult these articles:
- McDowell, D.L. and Backman, D., “Simulation-Assisted Design and Accelerated Insertion of Materials,” Ch. 19 in Computational Methods for Microstructure-Property Relationships, Eds. S. Ghosh and D. Dimiduk, Springer, 2010, ISBN 978-1-4419-0642-7.
- McDowell, D.L., “Critical Path Issues in ICME,” Models, Databases, and Simulation Tools Needed for the Realization of Integrated Computational Materials Engineering, Proc. Symposium held at Materials Science and Technology 2010, Oct. 18-20, Houston, Tx, S.M. Arnold and T.T. Wong, eds., ASM International, 2011, pp. 31-37.
- Panchal, J.H., Kalidindi, S.R., and McDowell, D.L., “Key Computational Modeling Issues in ICME,” Computer-Aided Design, Vol. 45, No. 1, 2013, pp. 4–25.
- McDowell, D.L., “Sharing Data in Materials Science: Incentivize Sharing,” Nature, Vol. 503, Nov. 2013, pp. 463-464.