TY - JOUR
T1 - Synergistic computational and experimental discovery of novel magnetic materials
AU - Balasubramanian, Balamurugan
AU - Sakurai, Masahiro
AU - Wang, Cai Zhuang
AU - Xu, Xiaoshan
AU - Ho, Kai Ming
AU - Chelikowsky, James R.
AU - Sellmyer, David J.
N1 - Funding Information:
This research is primarily supported by the U.S. National Science Foundation – Designing Materials to Revolutionize and Engineer our Future: Sustainable Chemistry, Engineering, and Materials (NSF-DMREF: SusChEM) under the grant numbers 1729202, 1729288, and 1729677. Research at Nebraska is also partly supported by the U.S. Department of Energy (DOE) under the award number DE-FG02-04ER46152 and performed in part in the Nebraska Nanoscale Facility: National Nanotechnology Coordinated Infrastructure and the Nebraska Center for Materials and Nanoscience, which are supported by the U.S. NSF under award NNCI-1542182, and the Nebraska Research Initiative (NRI). HPC resources were provided by the Texas Advanced Computing Center (TACC), through the Extreme Science and Engineering Discovery Environment (XSEDE) allocation, and the National Energy Research Scientific Computing Center (NERSC). The development of adaptive genetic algorithm (AGA) method was supported by the U.S DOE, Basic Energy Sciences, Division of Materials Science and Engineering, under Contract No. DE-AC02-07CH11358, including a grant of computer time at the NERSC in Berkeley, CA. We thank Xin Zhao, Manh Cuong Nguyen, Wenyong Zhang, Ralph Skomski, Haohan Wang, Shah R. Valloppilly, Xingzhong Li and Rabindra Pahari for helpful discussions.
Funding Information:
This research is primarily supported by the U.S. National Science Foundation Designing Materials to Revolutionize and Engineer our Future: Sustainable Chemistry, Engineering, and Materials (NSF-DMREF: SusChEM) under the grant numbers 1729202, 1729288, and 1729677. Research at Nebraska is also partly supported by the U.S. Department of Energy (DOE) under the award number DE-FG02-04ER46152 and performed in part in the Nebraska Nanoscale Facility: National Nanotechnology Coordinated Infrastructure and the Nebraska Center for Materials and Nanoscience, which are supported by the U.S. NSF under award NNCI-1542182, and the Nebraska Research Initiative (NRI). HPC resources were provided by the Texas Advanced Computing Center (TACC), through the Extreme Science and Engineering Discovery Environment (XSEDE) allocation, and the National Energy Research Scientific Computing Center (NERSC). The development of adaptive genetic algorithm (AGA) method was supported by the U.S DOE, Basic Energy Sciences, Division of Materials Science and Engineering, under Contract No. DE-AC02-07CH11358, including a grant of computer time at the NERSC in Berkeley, CA. We thank Xin Zhao, Manh Cuong Nguyen, Wenyong Zhang, Ralph Skomski, Haohan Wang, Shah R. Valloppilly, Xingzhong Li and Rabindra Pahari for helpful discussions.
Publisher Copyright:
© 2020 The Royal Society of Chemistry.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - New magnetic materials for energy and information-processing applications are of paramount importance in view of significant global challenges in environmental and information security. The discovery and design of materials requires efficient computational and experimental approaches for high throughput and efficiency. When increasingly powerful computational techniques are combined with special non-equilibrium fabrication methods, the search can uncover metastable compounds with desired magnetic properties. Here we review recent results on novel Fe-, Co-and Mn-rich magnetic compounds with high magnetocrystalline anisotropy, saturation magnetization, and Curie temperature created by combining experiments, adaptive genetic algorithm searches, and advanced electronic-structure computational methods. We discuss structural and magnetic properties of such materials including Co-and/or Fe-X compounds (X = N, Si, Sn, Zr, Hf, Y, C, S, Ti, or Mn), and their prospects for practical applications.
AB - New magnetic materials for energy and information-processing applications are of paramount importance in view of significant global challenges in environmental and information security. The discovery and design of materials requires efficient computational and experimental approaches for high throughput and efficiency. When increasingly powerful computational techniques are combined with special non-equilibrium fabrication methods, the search can uncover metastable compounds with desired magnetic properties. Here we review recent results on novel Fe-, Co-and Mn-rich magnetic compounds with high magnetocrystalline anisotropy, saturation magnetization, and Curie temperature created by combining experiments, adaptive genetic algorithm searches, and advanced electronic-structure computational methods. We discuss structural and magnetic properties of such materials including Co-and/or Fe-X compounds (X = N, Si, Sn, Zr, Hf, Y, C, S, Ti, or Mn), and their prospects for practical applications.
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U2 - 10.1039/d0me00050g
DO - 10.1039/d0me00050g
M3 - Review article
AN - SCOPUS:85088586022
VL - 5
SP - 1098
EP - 1117
JO - Molecular Systems Design and Engineering
JF - Molecular Systems Design and Engineering
SN - 2058-9689
IS - 6
ER -