Click on the links below for a brief description of the scientific goals of each team.
- Dynamics and Cohesion of Materials Interfaces and Confined Phases Under Stress
- Predictive Capability for Strongly Correlated Systems
- Multiscale Simulation of Thermo-Mechanical Processes in Irradiated Fission-Reactor Materials
- Multiscale Studies of the Formation and Stability of Surface-Based Nanostructures
- Fundamentals of Dirty Interfaces: From Atoms to Alloy Microstructures
- Microstructural Effects on the Mechanics of Materials
- Magnetic Materials Bridging Basic and Applied Science
- Excited-State Electronic Structure and Response Functions
- Mark Asta, University of California at Davis
- Alain Karma, Northeastern University
- Anthony Rollett, Carnegie Mellon University
This project brings together a team of researchers with a highly successful record of collaboration under previous CMSN support, to address new and outstanding scientific issues related to the properties of grain boundaries and associated confined interfacial liquid phases under stress. The project addresses challenging new methodological developments required to understand at a fundamental level the physics governing complex interface dominated processes associated with the breakdown of crystal cohesion and failure of stressed polycrystalline materials. This new focus represents a natural extension, and stronger unification, of the team's previous collaborations examining grain boundary and solid-liquid interface properties and their role in governing microstructure evolution. In the currrent project, development and validation of multiscale simulation methodologies are being undertaken in the context of four technologically important and thematically linked processes relevant to the processing and lifetime of materials for diverse DOE-related applications ranging from energy generation to stockpile stewardship. Specifically, we are seeking to gain new insights into the mechanisms of whisker growth, liquid-metal embrittlement, hot tearing and hot-ductility-dip cracking, with an overall goal of developing predictive models to aid in the prevention or control of these phenomena in practical applications.
- Richard T. Scalettar, University of California at Davis
- Warren Pickett, University of California at Davis
There are classes of materials that are important to DOE and to the science and technology community in general which have proven very difficult to understand and to simulate in a material-specific manner. These range from actinides, which are central to the DOE mission, to transition metal oxides, which include the most promising components of new spin electronics applications, to intermetallic compounds whose quantum critical behavior has given rise to some of the most active areas in condensed matter theory. After decades of study from a variety of often quite approximate viewpoints, a material-specific, predictive capability for many of these correlated electron systems is now a realistic goal. This exciting possibility is based on (1) new theoretical innovations, (2) coupling of experts in many-body theory with electronic structure practitioners, and (3) development of novel computational algorithms to solve the resulting equations. These new capabilities are arising at a time when there are extensive and novel experimental probes to provide data for a theory-computation-experiment feedback loop that enables the most rapid progress, and also extended computational power to bring to bear on solving the resulting numerical problem. The objective of the proposed cooperative research team is to assemble the required expertise into a coherent team and focus on the application of these new methodologies to the specific issue of Mott transitions, multi-electron magnetic moments, and dynamical properties of correlated materials. The goals are (i) to provide specific, detailed understanding of the complex correlation effects in strongly correlated systems, with specific emphasis on our compound of choice - MnO - through the application and further development of formal methods and numerical algorithms, and (ii) to make available to materials modelers efficient and accurate computer codes, which can then be used more widely for strongly correlated systems. Success in this undertaking will have a clear impact by moving the community toward the longer-term goal of opening up the entire periodic table to simulations with predictive capability.
- Dieter Wolf, Idaho National Laboratory
- Blas Uberuaga, Los Alamos National Laboratory
- Ram Devanathan, Pacific Northwewst National Laboratory
- Simon R. Phillpot, University of Florida
Overview: The objective of this Computational Materials Science Network (CMSN) project on Multiscale Simulation of Thermo-Mechanical Processes in Irradiated Fission-Reactor Materials is to merge the expertise in the simulation of damage cascades in single crystals with the expertise in multiscale simulation of microstructural evolution in polycrystalline materials. This will enable us to elucidate the thermo-mechanical behavior of model fission-reactor materials under irradiation across all the relevant length- and time-scale regimes, with particular focus on the complex interplay between irradiation effects and materials microstructure. Phenomena to be studied include the coupling of irradiation, for example, with phase behavior and precipitation, diffusion creep, fission-gas bubble formation and migration through the microstructure, grain growth, embrittlement and crack propagation. The predictive, materials-physics-based simulation capability to be developed under this coordinated, multi-institutional thrust provides the methodology to systematically elucidate microstructural processes and parameters as input into higher-level, applied types of simulation codes for nuclear-fuel modeling.
- Kai-Ming Ho, Ames Lab
- Zhenyu Zhang, Oak Ridge National Lab
In this CMSN project, a team of distinguished researchers with highly complementary expertise is assembled to carry out multiscale studies of the formation, stability, and novel physical properties of important classes of surface-based nanostructures: nanoclusters and quantum dots (zero-dimensional, or 0D), quantum wires and quantum wire superlattices (1D) and ultrathin quantum films and platelets (2D). As is widely recognized, the ability to precisely control the formation of innovative nanostructures of technological significance, as well as to preserve their integrity under diverse practical conditions, is a grand challenge in nanoscience and nanotechnology. In particular, ordered arrays of quantum dots, quantum wires, and quantum wire superlattices of alternating magnetic and nonmagnetic (or insulating) elements are among the most desirable artificially-structured nanosystems of the experimental community, owing to their huge potential as elemental building blocks in future device applications. Our primary objective is to make major conceptual advances in growth science, characterized by fundamental understanding and accurate prediction of the evolution of the prototype nanostructures. This objective is to be achieved through collaborative computational efforts and development of new mathematical tools and algorithms to provide a coherent study of the problems from the electronic and atomistic to the continuum levels. Such advances in better structural control will not only facilitate more reliable property studies of such low-dimensional nanostructures, but will also enable direct comparison with experiments. The multiscale models and computational methods to be developed through the integrated efforts of the cooperative research team (CRT) will be optimized for application in other important areas of nanoscience as well.
- Tony Rollett, Carnegie Mellon University
- Alain Karma, Northeastern University
Overview: There are two main streams of activity in materials science. The first, materials discovery, is based either on serendipity and/or Edisonian research. The second, material optimization, is ideally based upon our understanding of the relationship between composition, structure and properties and our ability to process materials to achieve target compositions and structure. While materials discovery is inherently fascinating and important, it is the area of materials optimization that presents the greatest opportunities. Arguably, the most important applications of advances in computational power and algorithms to materials science has been in the area of materials optimization, in general, and materials processing, in particular. These advances have primarily been in the area of application of continuum methods for matter and heat transport. These models typically invoke empirical constitutive relations to describe how a material will behave. As a result, these methods can be routinely used to predict the final shape of a specimen following deformation processing and its temperature history, but is of little use in determining, predicting, or manipulating the internal structure or microstructure of the material. It is the microstructure that controls the properties of a material and it is the primary knob that we materials scientists and engineers have at our disposal to optimize material properties.
- Richard LeSar, Los Alamos National Laboratory
- Dieter Wolf, Argonne National Laboratory
Overview: This team brings together a diverse set of researchers, each with their own approaches and skills, to develop a hierarchically structured, integrated approach towards materials modeling across all the inherent physical length and time scales relevant to microstructural effects in materials mechanics. To focus the efforts of the team, we investigate the interplay between dislocation and grain microstructures in polycrystal plasticity. Our specific goal is to elucidate the fundamental dislocation and grain-boundary processes thought to be responsible for the crossover in the well-known Hall-Petch effect, from "normal" behavior at larger grain sizes to the "inverse" behavior for grain sizes less than typically 20 nm in grain size. Insights gained from this study will naturally lead to a better understanding and predictive capability for related, but more complex deformation processes in polycrystalline materials, such as superplastic forming of metals and ceramics. By focusing the efforts of a variety of researchers with broad scientific and computational expertise on the same problem, perhaps the most important outcome of this team effort will not only be the development of a conceptual framework enabling the bridging of length and time scales in materials modeling but also the emergence of new scientific ideas and more predictive models in this important area of materials science.
- Malcolm Stocks, Oak Ridge National Laboratory
- Bruce Harmon, Ames Laboratory
Overview: While the underlying mechanisms responsible for the magnetism of materials involve electronic interactions at the atomic level, the bulk properties of permanent magnets are governed at a larger length scale and are greatly influenced by microstructure. The magnetics literature (probably from the time of the ancient Greeks) is rich in recipes for enhancing magnet performance by modifying the microstructure during processing (sometimes by rather crude heat and beat techniques). The magnetics communities are now in position to better understand and control the relevant microstructure for optimizing magnet performance. High performance computing is enabling researchers to model magnetic devices at smaller and smaller length scales, while at the same time accurate first principles calculations of magnetic properties now extend to systems involving thousands of atoms. The two different approaches: continuum versus discrete, and physics versus engineering, are approaching each other at mesoscopic length scales. There is a great opportunity to bring both communities together, and that is the goal of this project. The five subtasks of this project are: 1) Fundamental Physics, 2) First Principles derived parameters, 3) Domain Walls, 4)Coarse Graining, and 5) Micro-magnetics Code Development. Approximately 25 scientists from DOE labs, universities, other government laboratories, and industry are involved in one or more of the subtasks.
- Steven Louie, University of California, Berkeley
- John Rehr, University of Washington
Many important materials science applications (e.g. microelectronic devices, optics, solar cells, and semiconductor lasers) depend, for their functionality, on electronic excited-state properties of materials. Likewise, most experimental probes create excitations and consequent materials' response. Modern photon sources (synchrotrons, ultra-fast lasers, etc.) now probe materials with unprecedented resolution and offer the potential for novel materials studies. In recent decades, computational physics has achieved enormous successes in describing ground-state properties; however, quantitative and reliable descriptions of excitations and response functions are just emerging. The objective of the proposed cooperative research team (CRT) is to attack these challenging, but timely, scientific and computational issues. The proposal has specific short- and long-term objectives, aimed at creating a deeper theoretical understanding through predictive calculations of materials' properties involving excited states. Our effort naturally breaks into three interconnected parts, a) experimental processes and applications; b) fundamental electronic excitations and correlations; and c) time-dependent phenomena and non-linear effects. We plan to develop compatible computational tools that can be shared between groups in a way that fosters parallel, interrelated, and compatible efforts.