Uncovering compounds by synergy of cluster expansion and high-throughput methods.

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Predicting from first-principles calculations whether mixed metallic elements phase-separate or form ordered structures is a major challenge of current materials research. It can be partially addressed in cases where experiments suggest the underlying lattice is conserved, using cluster expansion (CE) and a variety of exhaustive evaluation or genetic search algorithms. Evolutionary algorithms have been recently introduced to search for stable off-lattice structures at fixed mixture compositions. The general off-lattice problem is still unsolved. We present an integrated approach of CE and high-throughput ab initio calculations (HT) applicable to the full range of compositions in binary systems where the constituent elements or the intermediate ordered structures have different lattice types. The HT method replaces the search algorithms by direct calculation of a moderate number of naturally occurring prototypes representing all crystal systems and guides CE calculations of derivative structures. This synergy achieves the precision of the CE and the guiding strengths of the HT. Its application to poorly characterized binary Hf systems, believed to be phase-separating, defines three classes of alloys where CE and HT complement each other to uncover new ordered structures.






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Levy, Ohad, Gus LW Hart and Stefano Curtarolo (2010). Uncovering compounds by synergy of cluster expansion and high-throughput methods. J Am Chem Soc, 132(13). pp. 4830–4833. 10.1021/ja9105623 Retrieved from https://hdl.handle.net/10161/4053.

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Stefano Curtarolo

Edmund T. Pratt Jr. School Distinguished Professor of Mechanical Engineering and Materials Science


  • Artificial Intelligence Materials Science
  • Autonomous Materials Design
  • Computational Materials Science
  • High-Entropy Disordered and Amorphous Systems
  • Materials for Energy Applications
  • Materials for Aerospace Applications
  • Materials for Deep Space Exploration

The research is multidisciplinary and makes use of state of the art techniques from fields like materials science, chemistry, physics, quantum mechanics, mathematics and computer science.

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