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Prediction of the ab-initio theory

Magnetism and Neutron response in correlated solids Kristjan Haule , Rutgers Univesity New Brunswick, DMR 0746395 . Prediction of the ab-initio theory. Intelectual Merit

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Prediction of the ab-initio theory

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  1. Magnetism and Neutron response in correlated solids Kristjan Haule, Rutgers Univesity New Brunswick, DMR 0746395 Prediction of the ab-initio theory Intelectual Merit We developed ab-initio method and computer algorithms to describe physical properties of complex correlated materials in which the interactions between electrons are too intense to be well described by standard methods of band structure theory. The method named Dynamical Mean Field Theory [1] successfully describes properties of many correlated solids, such as transition metal oxides, heavy fermions, and unconventional high temperature superconductirs. We recently developed a neutron spectroscopy tool, as part of this ab-initio method, to understand and interpret experimental neutron spectroscopy measurements, and to gain deeper understanding of magnetism in correlated materials. Fig.1 shows theoretical and experimental magnetic excitation spectra in iron-pnictide superconductor, published in Ref.[2]. Fig.2 shows theoretical prediction for magnetic moments across all families of iron-pnictide and iron-chalchogenide superconductors together with their measured values, published in Ref.[3] [1] G. Kotliar, S. Y. Savrasov, K. Haule, V. S. Oudovenko, O. Parcollet, and C. A. Marianetti Rev. Mod. Phys. 78, 865 (2006). [2] Hyowon Park, Kristjan Haule, Gabriel Kotliar, Phys. Rev. Lett. 107, 137007 (2011). [3]Z. P. Yin, K. Haule, G. Kotliar, Nature Materials 10, 932-935 (2011) Neutron scattering Experiment

  2. Magnetism and Neutron response in correlated solids KristjanHaule, Rutgers Univesity New Brunswick, DMR 0746395 General first-principles framework for predicting physical properties of complex correlated solids and an online repository for storing and analyzing results of material specific calculations. We have development an automated software package DMFT+Wien2K (a combination of Dynamical Mean Field Theory and Density Functional Theory in its Wien2K implementation) to predict properties of correlated solids from first principles. The code is geared for research and education and is freely available at http://hauleweb.rutgers.edu/downloads/ DMFT+Wien2K was used in a graduate Computational Physics course helping students explore concepts of solid state and electron correlations and predict electronic structure properties from first principles. Graduate and undergraduate students as well as a high school intern participate in code development

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