Digital Materials Design: Computational Methodologies as a Discovery Tool
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Introduction The discovery of new materials always stretches the human imagination. Nowadays, when even walking in space has been realized, the desire for “wonder materials” has not been damped but enhanced. The disastrous loss of the space shuttle Columbia in 20031 constantly reminds us of the challenges inherent in new materials discovery. On the social and economic front, the development of a globalized and knowledge-based economy increasingly pushes every country to cope with the dynamic market demands for new products, ensuring faster design, better quality, and lower cost. The traditional trial-and-error experimental approach is no longer an efficient way to produce the required new materials in a timely way. New research strategies have to be invented. Computational science, combined with experiments,
can play a significant role in this new economy. High-performance computing techniques based on fundamental equations of quantum mechanics for solids and molecules are well established. A detailed examination of materials behavior, at the atomic and electronic levels, can be carried out by computer modeling and simulation, although the powerful first-principles methods at present still fall short of representing a more realistic system configuration with millions or billions of atoms. On the other hand, computational thermochemistry has been used in chemistry and chemical engineering research for many decades. Recently, data-mining and artificial intelligence techniques have also been applied in combinatorial chemistry and chemical engineering research. At the
MRS BULLETIN • VOLUME 31 • DECEMBER 2006 • www/mrs.org/bulletin
Institute of High Performance Computing in Singapore, we have developed a unique approach to integrating these modeling techniques and have set up a digital materials design (DMD) platform that has been applied successfully in the design of new materials.5–9,23–28 In this article, an illustration of different computer modeling and simulation techniques in DMD will be given, followed by a discussion of applications in materials design, especially the design of chemical additives and the realization of p-type ZnO. Finally, future research will be discussed.
Computational Techniques Integrated in DMD Molecular modeling, thermochemical computations, and data-mining techniques are the building blocks of DMD. Many wellknown reviews discuss the applications of these techniques in materials research.2 Therefore, only those techniques directly used in DMD will be discussed here. The goal of digital materials design is to develop a novel software environment to support materials design across many length and time scales. On the theoretical front, we used atomistic simulation at the nanoscale level and chemical thermodynamics/kinetics as well as finite element analysis for bulk systems. Furthermore, we developed chemical informatics to link the nanosystem to the bulk.23–28 A brief introduction will be given for each of these subjects.
Atomistic Simulation Atomistic simulation addresses fundamental pr
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