Materials Informatics
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The term “informatics” has been defined as the use of computer software to gather, store, manipulate, retrieve, and classify information. This issue of MRS Bulletin will focus on materials informatics—the application of computational methodologies to processing and interpreting scientific and engineering data concerning materials. Modern materials science and engineering research produces a large amount of heterogeneous data. Computational methods are then used to organize, manage, interpret, analyze, and visualize these data. Using a combination of computational methods, like density functional theory (DFT), to calculate structure and properties, combined with data mining of properties databases to identify trends and systematics in property data, it is possible, then, to identify suitable candidate starting materials for a variety of materials science and engineering applications. These computational methods are now becoming important tools for use by materials scientists and engineers in materials and product development.
Materials informatics can be broadly divided into three main parts: data generation (synthesis), data management, and knowledge discovery (analysis). New experimental methods, such as combinatorial materials science1 and diffusion multiple approaches,2 are synthesizing large amounts of structural and property data—physical, chemical, and engineering. Combinatorial materials science is an experimental approach to quickly analyze materials and to test for their physical and structural properties. A diffusion multiple approach is the result of an assembly of three or more metals, in close contact, that is subject to high temperatures to allow thermal interdiffusion. The large amount of data generated by these methods needs to be stored, analyzed, and mined for further applications. More recently, “computational” combinatorial methods or high-throughput ab initio computations, based on density functional theory (DFT)3 (see also the September 2006 issue of MRS Bulletin) are being employed to calculate the structure
MRS BULLETIN • VOLUME 31 • DECEMBER 2006 • www/mrs.org/bulletin
and properties of materials systematically across a wide parameter space.4 DFT, based on quantum mechanical methods, is used in computational materials science for the calculation of structural, electronic, optical, and magnetic properties of materials. These advances, which have been made possible with increases in computational speed, and the parallel development of robust ab initio techniques, are also generating enormous amounts of property data. The use of these complementary methods—computational experiment and theory—to generate data, coupled with methods for data checking and estimation5 for the filling in of “holes” in materials property space,6 are providing routes to predict new feasible materials compositions and their properties,7–9 thus improving materials design and selection capabilities. For the successful design of components for engineering applications, data, and knowledge relating to the selection of t
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