Multi-objective Optimization for Materials Discovery via Adaptive Design
Author:
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
http://www.nature.com/articles/s41598-018-21936-3.pdf
Reference45 articles.
1. Meenakshisundaram, V., Hung, J.-H. & Simmons, D. S. Neural-Network-Biased Genetic Algorithms for Materials Design: Evolutionary Algorithms That Learn. ACS Combinatorial Science 19, 96–107 (2017).
2. Xue, D. et al. An informatics approach to transformation temperatures of NiTi-based shape memory alloys. Acta Materialia 125, 532–541, ISSN 1359–6454, https://doi.org/10.1016/j.actamat.2016.12.009 (2017).
3. Lookman, T. et al. A perspective on materials informatics: state-of-the-art and challenges. In Lookman, T., Alexander, F. J. & Rajan, K. (Eds), Information Science for Materials Discovery and Design, Springer Series in Materials Science, vol. 225 (Springer International Publishing, 3–12, 2016).
4. Saad, Y. et al. Data mining for materials: Computational experiments with AB compounds. Phys. Rev. B 85, 104104 (2012).
5. Balachandran, P. V., Broderick, S. R. & Rajan, K. Identifying the “inorganic gene” for high temperature piezoelectric perovskites through statistical learning. Proc. R. Soc. A: Math., Phys. Eng. Sci. 467, 2271–2290 (2011).
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