Group name: Computational Materials Design Group

Group leader: David L. McDowell

Location: Georgia Institute of Technology

Further information:

David McDowell.
David McDowell.
Georgia Tech IMat Executive Director David McDowell in the Mechanical Properties Characterization Facility.
Georgia Tech IMat Executive Director David McDowell in the Mechanical Properties Characterization Facility.
David McDowell with several of his graduate students (left to right, Adrienne Muth, Aaron Tallman, and Ted Zirkle) in the computational materials design laboratory.
David McDowell with several of his graduate students (left to right, Adrienne Muth, Aaron Tallman, and Ted Zirkle) in the computational materials design laboratory.

Structural materials such as cast and wrought metal alloys are commonly selected for applications on the basis of their mechanical and physical properties. In contrast to trial-and-error selection, advances in modeling and simulation over the past quarter of a century have enabled materials scientists and engineers to take a systematic approach to tailoring materials for applications.

David L. McDowell, Regents’ Professor and Carter N. Paden, Jr. Distinguished Chair in Metals Processing at Georgia Institute of Technology, is doing just that by bringing together computational simulation tools for metals processing and mechanical behavior at various length scales with state-of-the-art mechanical testing and characterization tools.

Having joined Georgia Tech in 1983, McDowell served as Director of the Mechanical Properties Research Laboratory (MPRL) from 1992-2012 prior to founding the Institute for Materials (IMat). He has served as Executive Director of IMat since 2012.

Over the course of his career, he has authored or co-authored over 330 journal articles and received the 1997 ASME Materials Division Nadai Award for career achievement and the 2008 Khan International Medal for lifelong contributions to the field of metal plasticity. A Fellow of SES, ASM International, ASME and AAM, McDowell also serves on the editorial boards of several journals, and is co-Editor of the International Journal of Fatigue.

David L. McDowell talked to Materials Today about his research, his institute, and his future plans for both...

How long has your team been running?

My research group has been operating over 30 years and has produced 50 doctoral students and over 40 masters degree students during this time. These students have subsequently contributed to a broad spectrum of government, academic, and industry research enterprises.

How many staff makes up your team?

The composition of my computational materials design group is balanced between graduate students from the School of Materials Science and Engineering and the Woodruff School of Mechanical Engineering. Students work at the interface of materials science, physics, and engineering science/mechanics, with emphasis on computational methods. We also consider uncertainty in both modeling and experiments, as well as in methods to inform parameter calibration and decision support for materials design. 

I currently advise or co-advise eight doctoral students, two MS students, and work with two post docs along with collaborating faculty. I tend to keep my research group size at around 10 in order to facilitate direct interactions, as I favor a horizontal rather than vertical management and mentoring approach to assimilating emerging research and defining innovative pathways. I like to learn new fields together with my students and post docs.

What are your broader university leadership responsibilities?

I also devote half of my time to serving as Executive Director of IMat, a crosscutting, interdisciplinary research institute that reports to the Executive VP Research and serves over 130 participating faculty from the Colleges of Sciences and Engineering. The effort is supported by administrative, communications, and finance staff, Deputy Director Jud Ready, Associate Director for Shared Resources Eric Vogel, and Innovation Strategists Surya Kalidindi and Rampi Ramprasad. IMat pursues two primary initiatives: (i) consolidation and administration of a campus-wide shared Materials Characterization Facility, MCF ( in collaboration with the Institute for Electronics and Nanotechnology (IEN); and (ii) fostering development of new research directions to realize accelerated discovery and development of materials.

We emphasize the integration of the emergent field of materials data science and informatics with Georgia Tech’s core materials strengths, and have helped to generate grant funding to support approximately 30 PhD students working at the interface of data science and materials research between 2014-2019. One example is our National Science Foundation (NSF) graduate education and research traineeship program led by Professors Richard Fujimoto and Surya Kalidindi (

IMat support has also spawned a platform, MATIN (, which serves as an e-collaboration backbone of our fusion of data science, digital workflows for research and development, and materials data science community building.

With regard to future workforce development, we have developed two Massive Open Online Courses (MOOCs) in high throughput methods ( and materials informatics (, both of which are well subscribed and accessible to the public at no fee.

IMat interacts closely with external industry, federal government agencies, national laboratories, and other academic institutions to advance broader initiatives, such as the US Materials Genome Initiative (MGI) and Integrated Computational Materials Engineering (ICME).

What are the major themes of research in your lab?

My focus is to advance the frontiers of metals research by developing:

  • Novel approaches for microstructure-sensitive computational simulation of fatigue of metals and alloys, focusing on rare event crack phenomena in complex three-dimensional microstructures;
  • Multiscale modeling, including novel atomistic-continuum and continuum-continuum transitions, addressing associated uncertainty;
  • Systems-based materials design of materials with emphasis on structure-property relations.

How and why did you come to work in these areas?

I started my career 35 years ago with a primary focus on experimental techniques for studying the effects of combined multiaxial stress states on cyclic inelastic deformation of metals, along with constitutive modeling. I could clearly see by the early 1990s that computational methods for modeling materials at various length and time scales were advancing rapidly along with computing power and this would form the basis for many important discoveries and research streams in the 21st century. Accordingly, I gradually invested more time and energy into computation.

Today, my program is largely computational in nature. I have the benefit of perspective gained from having run major materials research labs in both experimental (20 years) and computational (20 years) research within the university setting. The beauty of the university environment lies in the capacity for re-invention and evolution of interests and capabilities.

What facilities and equipment does your lab have?

Our primary facilities include various computer-controlled servohydraulic load frames in the Mechanical Properties Characterization Facility (MPCF,, currently directed by Richard Neu, and the PACE high performance computing cluster ( administered by the Office of Information Technology at Georgia Tech, in which I maintain parallel computing nodes.

What do you think has been your most influential work to date?

The most influential research outcomes in collaboration with my students have addressed multiscale modeling of inelastic (dislocation-mediated) behavior of metals and alloys [1-2] and strategies for microstructure-sensitive fatigue modeling [3-4]. Along with collaborators in systems engineering and former PhD students, we also published one of the first ICME-related monographs on integrated design of multiscale materials and products [5] and have articulated outstanding issues in computational modeling of materials to support ICME [6].

Collaborations with Youping Chen and various students within the past decade have facilitated the development of a new stream of coarse-grained atomistic modeling [7] we call the ‘concurrent atomistic-continuum’ (CAC) method, which is useful for resolving atomistic phenomena near interfaces, for example, while modeling large dimensions into the bulk.

Working within the context of IMat has allowed me to collaborate with other faculty at Georgia Tech to articulate a vision for how universities can be configured to best educate and train the future workforce at the intersection of materials discovery, development, and manufacturing [8-9], including the coupling of computation and material data science. As one might guess, the professional communities associated with these different research streams are fairly distinct, so I end up attending conferences and symposia with groups of researchers who do not normally mingle, which is on one hand challenging but on the other rewarding in terms of knowledge transfer across disciplines.

As director of the MPCF (formerly the MPRL) for 20 years, I was gratified to see Georgia Tech continue to develop a strong presence in fatigue and fracture research, serving important industry needs even while federal funding for this area declined. Our innovative faculty effectively combines computational simulation with experiments at multiple length and time scales to shed new light on the role of microstructure in fatigue and fracture.

The consolidation of distributed characterization equipment within the centralized MCF, launched in 2015, represented a substantial advance in the quality and sustainability of the experimental materials research environment at Georgia Tech.

Over the past few years, working with the Executive VP Research, IEN, and various academic units such as the School of Materials Science and Engineering, IMat has directed substantial investments at expanding our transmission electron microscopy (TEM) facilities, including in situ capabilities, user support, specimen preparation, coupling with data science techniques, and a new aberration-corrected scanning TEM. Seeing the positive impact this has on the research careers of colleagues and their students is most gratifying.

What is the key to running a successful lab?

The key to running a successful research group in multiscale computational materials science and mechanics is to support the development of students’ expertise working at different levels of materials hierarchy with distinct classes of models. It is essential for students to explore how information is exchanged between models, and how experiments are used to inform models at various scales. So, in addition to meetings with subsets of students working with models at specific levels of hierarchy (e.g. atomistic vs. continuum), group meetings allow students to present their views and discuss the gaps and challenges across a wide range of scales. 

How do you balance your own research and your IMat leadership responsibilities?

I split my time evenly between my personal research group and directing IMat. Running a large, campus-wide infrastructure support organization such as IMat is a very different type of activity, since it serves the needs of the broad community of materials researchers. Success in this case hinges on objectively assessing and representing Georgia Tech’s research strengths in materials, addressing gaps in capabilities and opportunities, fostering the formation of new research communities via workshops and seed funding support, engaging in dialogue with external stakeholders in industry, government, professional societies and other academic institutions, fostering and supporting faculty leadership of cross-cutting research and education efforts, and identifying and pursuing important future workforce development opportunities in areas such as accelerated materials development and materials data science and informatics.

Although directing IMat is quite time intensive, it has opened up many new domains of learning for me in various materials classes that have significantly enhanced my own research and level of effectiveness as a communicator, teacher, and faculty colleague.

How do you plan to develop your own research and IMAT in the future?

At this stage of my career, the production of books or monographs in several key areas is high on my priority list, including nonequilibrium evolution of microstructures, microstructure-sensitive fatigue modeling, coarse-graining methods in atomistic modeling of defects, and application of uncertainty methods in materials discovery and development. As the years go by, I tend to place more emphasis on the success and contributions of my former and current students. I am interested in continued efforts towards gaining fundamental new understanding in the role of interfaces in dislocation-mediated plasticity, as well as phase transitions and growth of dislocation substructures.

With regard to IMat, I would very much like to see some of our concepts related to the materials innovation ecosystem ‘catch hold’ and expand more broadly into materials curriculum and regional/national network interactions aimed at accelerating materials discovery and development. The updated 2017 strategic plan for IMat calls for emphasis on coupling data science with in situ experimental methods for synthesis and characterization, development of new approaches for lab-to-cloud digital materials infrastructure, and future workforce development in materials innovation. In spite of its large footprint in materials, Georgia Tech by itself is far too limited to realize all these aims alone; by definition, the development of a data science-enabled future of materials research and development lies in the hands of many stakeholders with common interests and objectives.

Key publications

  1. D.L. McDowell. Viscoplasticity of heterogeneous metallic materials. Materials Science and Engineering R: Reports 62 (2008) 67-123
  2. D.L. McDowell. A perspective on trends in multiscale plasticity. International Journal of Plasticity, Special Issue in honor of David L. McDowell 26 (2010) 1280-1309
  3. D.L. McDowell, F.P.E. Dunne. Microstructure-sensitive computational modeling of fatigue crack formation. International Journal of Fatigue, Special Issue on Emerging Frontiers in Fatigue, 32 (2010) 1521-1542
  4. G.M. Castelluccio, W.D. Musinski, D.L. McDowell. Recent developments in assessing microstructure-sensitive early stage fatigue of polycrystals. Current Opinion in Solid State and Materials Science 18 (2014) 180-187
  5. D.L. McDowell, J.H. Panchal, H.-J. Choi, C.C. Seepersad, J.K. Allen, F. Mistree. Integrated design of multiscale, multifunctional materials and products. Elsevier, (2009).
  6. J.H. Panchal, S.R. Kalidindi, D.L. McDowell. Key computational modeling issues in ICME. Computer-Aided Design 45 (2013) 4–25
  7. S. Xu, R. Che, L. Xiong, Y. Chen, D.L. McDowell. A quasistatic implementation of the concurrent atomistic-continuum method for FCC crystals. International Journal of Plasticity 72 (2015) 91-126
  8. D.L. McDowell, S.R. Kalidindi. The Materials Innovation Ecosystem:  a key enabler for the Materials Genome Initiative. MRS Bulletin 41 (2016) 326-335
  9. D.L. McDowell, New and improved materials in the next production revolution, Chapter 6, in: The Next Production Revolution: Implications for Governments and Business, Organization for Economic Cooperation and Development (OEDC) Publishing, Paris, (2017), pp. 215-239.