First-principles and Many-Body Methods: Implementations and Applications to Study Spintronic Materials

Diluted magnetic semiconductors (DMSs) and magnetoresistive materials are instrumental for the development of spintronic technology. Before we are able to engineer spintronic devices, it is necessary to understand the properties of materials from which spintronic devices are made, otherwise time and other resources will be wasted. In this thesis, we investigate some aspects of diluted magnetic semiconductors and a magnetoresistive material Ta2PdSe6 with first-principle and many-body methods. Particularly, we investigate the Mn valence in (Ga,Mn)N and derive low-energy models of (Ga,Mn)N by making use of a first-principles Wannier-function analysis. Additionally, we also study the disorder-driven localization in DMSs with the typical-medium theory (TMT). Finally, we present a discussion about the investigation of the mechanism behind Ta2PdSe6 magnetoresistance. From a first-principles Wannier-function analysis, we find unambiguously the Mn valence in (Ga,Mn)N to be close to 2+ (d5), but in a mixed spin configuration with average magnetic moments of 4μB. By integrating out high-energy degrees of freedom differently, we further derive for the first time from first-principles two low-energy pictures that reflect the intrinsic dual nature of the doped holes in the (Ga,Mn)N: 1) an effective d4 picture ideal for local physics, and 2) an effective d5 picture suitable for extended properties. Furthermore, our results further reveal a few novel physical effects and pave the way for future realistic studies of magnetism. Our study not only resolves one of the outstanding key controversies of the field, but also exemplifies the general need for multiple effective descriptions to account for the rich low-energy physics in many-body systems in general. Meanwhile, by implementing a geometrical average of the local density of states to define an order parameter, the typical density of states (TDOS), we find that the TDOS vanishes below a critical doping concentration, indicating an Anderson localization transition in the system. Our results qualitatively explain why at concentrations lower than a critical value DMSs are insulating and non-magnetic, whereas at larger concentrations they are ferromagnetic bad metals. On the investigation of Ta2PdSe6, our density functional theory (DFT) calculations show that the material is a semimetal that has two types of charge carriers with the same density. This result, together with the magnetoresistance behavior of the two-band model, leads to the conclusion that the mechanism responsible for Ta2PdSe6 magnetoresistance is charge compensation

What is the valence of Mn in Ga1−x_{1-x}Mnx_xN?

We investigate the current debate on the Mn valence in Ga$_{1-x}$Mn$_x$N, a diluted magnetic semiconductor (DMSs) with a potentially high Curie temperature. From a first-principles Wannier-function analysis, we unambiguously find the Mn valence to be close to $2+$ ($d^5$), but in a mixed spin configuration with average magnetic moments of 4$\mu_B$. By integrating out high-energy degrees of freedom differently, we further derive for the first time from first-principles two low-energy pictures that reflect the intrinsic dual nature of the doped holes in the DMS: 1) an effective $d^4$ picture ideal for local physics, and 2) an effective $d^5$ picture suitable for extended properties. In the latter, our results further reveal a few novel physical effects, and pave the way for future realistic studies of magnetism. Our study not only resolves one of the outstanding key controversies of the field, but also exemplifies the general need for multiple effective descriptions to account for the rich low-energy physics in many-body systems in general.Comment: 4 figure

First-Principles Chemical Bonding Study of Manganese Carbodiimide, MnNCN, As Compared to Manganese Oxide, MnO

We have performed an in-depth study of the chemical bonding in manganese oxide (MnO) and carbodiimide (MnNCN) from correlated spin-polarized density functional calculations. The chemical-bonding data were produced using the LOBSTER package, which has recently been enabled to process PAW-based output from Quantum ESPRESSO. Our results show that the ground states of MnO and MnNCN are similar, namely, antiferromagnetic structures whose axes are the MnO cubic [111] and the MnNCN hexagonal [001] axes, in agreement with experimental results. The results also evidence MnNCN being more covalent than MnO, in harmony with chemical intuition and spectroscopic data. In addition, the crystal orbital Hamilton population (COHP) analysis evidences that adopting the ground-state magnetic structures by MnO and MnNCN makes the cation–anion bonds optimized and annihilates obvious instability issues, that is, the existence of antibonding states in the vicinity of the Fermi level. We also detail the interactions involved in the systems using the recently introduced density-of-energy analysis and by partitioning the total and band-structure energies. While it is trivial that the total energy points toward the true magnetic ground state taken, the COHP integral of the metal–nonmetal bond is also capable of correctly delivering that particular information

LOBSTER : Local orbital projections, atomic charges, and chemical-bonding analysis from projector-augmented-wave-based density-functional theory

We present an update on recently developed methodology and functionality in the computer program Local Orbital Basis Suite Toward Electronic-Structure Reconstruction (LOBSTER) for chemical-bonding analysis in periodic systems. LOBSTER is based on an analytic projection from projector-augmented wave (PAW) density-functional theory (DFT) computations (Maintz et al., J. Comput. Chem. 2013, 34, 2557), reconstructing chemical information in terms of local, auxiliary atomic orbitals and thereby opening the output of PAW-based DFT codes to chemical interpretation. We demonstrate how LOBSTER has been improved by taking into account timereversal symmetry, thereby speeding up the DFT and LOBSTER calculations by a factor of 2. Over the recent years, the functionalities have also been continually expanded, including accurate projected densities of states (DOSs), crystal orbital Hamilton population (COHP) analysis, atomic and orbital charges, gross populations,and the recently introduced k-dependent COHP. The software is offered free-ofchargefor non-commercial research

LOBSTER: Local Orbital Projections, Atomic Charges, and Chemical Bonding Analysis from Projector-Augmented-Wave-Based DFT

We present an update on recently developed methodology and functionality in the computer program LOBSTER (Local Orbital Basis Suite Towards Electronic-Structure Reconstruction) for chemical-bonding analysis in periodic systems. LOBSTER is based on an analytic projection from projector-augmented wave (PAW) densityfunctional theory (DFT) computations [J. Comput. Chem. 2013, 34, 2557], reconstructing chemical information in terms of local, auxiliary atomic orbitals and thereby opening the output of PAW-based DFT codes to chemical interpretation. We demonstrate how LOBSTER has been improved by taking into account time reversal symmetry, thereby speeding up the DFT and LOBSTER calculations by a factor of 2. Over the recent years, the functionalities have also been continually expanded, including accurate projected densities of states (DOS), crystal orbital Hamilton population (COHP) analysis, atomic and orbital charges, gross populations, and the recently introduced -dependent COHP. The software is offered free-of-charge for non-commercial research

Automated Bonding Analysis with Crystal Orbital Hamilton Populations

Understanding crystalline structures based on their chemical bonding is growing in importance. In this context, chemical bonding can be studied with the Crystal Orbital Hamilton Population (COHP), allowing to quantify interatomic bond strength. Here we present a new set of tools to automate the calculation of COHP and analyze the results. We use the program packages VASP and LOBSTER and the Python packages atomate and pymatgen. The analysis produced by our tools includes plots, a textual description, and key data in machine-readable format. To illustrate those capabilities, we have selected simple test compounds (NaCl, GaN), the oxynitrides BaTaO2N, CaTaO2N, and SrTaO2N, and the thermoelectric material Yb14Mn1Sb11. We show correlations between bond strengths and stabilities in the oxynitrides, as well as the influence of the Mn-Sb bonds on the magnetism in Yb14Mn1Sb11. Our contribution enables high-throughput bonding analysis and will facilitate the use of bonding information for machine learning studies

Automated Bonding Analysis with Crystal Orbital Hamilton Populations

Understanding crystalline structures based on their chemical bonding is growing in importance. In this context, chemical bonding can be studied with the Crystal Orbital Hamilton Population (COHP), allowing for quantifying interatomic bond strength. Here we present a new set of tools to automate the calculation of COHP and analyze the results. We use the program packages VASP and LOBSTER, and the Python packages atomate and pymatgen. The analysis produced by our tools includes plots, a textual description, and key data in a machine-readable format. To illustrate those capabilities, we have selected simple test compounds (NaCl, GaN), the oxynitrides BaTaO2N, CaTaO2N, and SrTaO2N, and the thermoelectric material Yb14Mn1Sb11. We show correlations between bond strengths and stabilities in the oxynitrides and the influence of the Mn