@article{26da81f989354294906dfd89ba22d011,
title = "Discovering chemical site occupancy- modulus correlations in Ni based intermetallics via statistical learning methods",
abstract = "We show how one may extract spectral features from the density of states (DOS) of L12-Ni3Al alloys that can serve as signatures or electronic “fingerprints” which capture the correlation between site occupancy of dopants and elastic properties. Based on this correlation, we have developed a computational approach for rapidly identifying the impact of the selection of dopant chemistries on bulk moduli of intermetallics. Our results show for example that Cr preferentially occupies the Al site in Ni3Al which is confirmed by scanning transmission electron microscopy (STEM) energy dispersed X-ray spectroscopy (EDS) analysis. We further show that this preference is due to a sensitivity of Cr to the DOS at −1.7 and 0.2 eV relative to the Fermi energy. In terms of similarity in chemistry-property correlations, we find Cr has a similar effect to Ce when occupying an Al site, while Cr occupying a Ni site has similar correlation as La on a Ni site. This logic can be utilized in targeted design of new alloy chemistries based on similar property correlations and for targeted DOS modification.",
author = "Broderick, {Scott R.} and Aakash Kumar and Oni, {Adedapo A.} and LeBeau, {James M.} and Sinnott, {Susan B.} and Krishna Rajan",
note = "Funding Information: We gratefully acknowledge support of this work under Air Force Office of Scientific Research (AFOSR) Grant No. FA9550-12-1-0456 and NSF Grant No. DMR-13-07811. SB and KR acknowledge support from NSF DIBBs Award Number ACI-1640867. KR also acknowledges support from the Erich Bloch Endowed Chair at the University at Buffalo-State University of New York. All the DFT calculations were performed using computational resources provided by the University of Florida Research Computing (http://researchcomputing.ufl.edu/). AAO and JML acknowledge the use of the Analytical Instrumentation Facility (AIF) at North Carolina State University, which was supported by the State of North Carolina and the National Science Foundation. Funding Information: We gratefully acknowledge support of this work under Air Force Office of Scientific Research (AFOSR) Grant No. FA9550-12-1-0456 and NSF Grant No. DMR-13-07811 . SB and KR acknowledge support from NSF DIBBs Award Number ACI-1640867. KR also acknowledges support from the Erich Bloch Endowed Chair at the University at Buffalo-State University of New York . All the DFT calculations were performed using computational resources provided by the University of Florida Research Computing ( http://researchcomputing.ufl.edu/ ). AAO and JML acknowledge the use of the Analytical Instrumentation Facility (AIF) at North Carolina State University, which was supported by the State of North Carolina and the National Science Foundation . Publisher Copyright: {\textcopyright} 2017 Elsevier B.V.",
year = "2018",
month = mar,
doi = "10.1016/j.cocom.2017.11.001",
language = "English (US)",
volume = "14",
pages = "8--14",
journal = "Computational Condensed Matter",
issn = "2352-2143",
publisher = "Elsevier BV",
}