Computational Materials Genome Initiative by High-Throughput Approaches
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2013
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Recently, in materials innovations, computational methods are used more frequently than in past decades. In this thesis, the materials genome initiative, an advanced new framework, will be introduced. With this blueprint, our efficient high-throughput software, AFLOW, has been implemented with several compatible functions for ma- terials properties investigations, such as prototype searching, phase diagram studying and magnetic properties discovering. With this effective tool, we apply ab initio cal- culations to discover new generation of specific materials properties.
An efficient algorithm for prototypes comparision has been designed and imple- mented into our high-throughput framework AFLOW. In addition, prototypes clas- sification was utilized to differentiate the our materials database. This classification will accelerate the materials properties searching speed. With respect to structure prototypes, low temperature phase diagrams were used for binary and ternary alloy systems stability investigation. The alogrithms have been integrated into AFLOW. With this tool, we systematically explored the binary Ru systems and Tc systems and predicted new stable compounds.
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Xue, Junkai (2013). Computational Materials Genome Initiative by High-Throughput Approaches. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/8041.
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