No Arabic abstract
X-ray absorption spectroscopy (XAS) and X-ray magnetic circular dichroism (XMCD) were used to probe the oxidation state and element specific magnetic moments of Mn in Heusler compounds with different crystallographic structure. The results were compared with theoretical calculations, and it was found that in full Heusler alloys, Mn is metallic (oxidation state near 0) on both sublattices. The magnetic moment is large and localized when octahedrally coordinated by the main group element, consistent with previous theoretical work, and reduced when the main group coordination is tetrahedral. By contrast, in the half Heusler compounds the magnetic moment of the Mn atoms is large and the oxidation state is +1 or +2. The magnetic and electronic properties of Mn in full and half Heusler compounds are strongly dependent on the structure and sublattice, a fact that can be exploited to design new materials.
The prediction of ultra-low magnetic damping in Co 2 MnZ Heusler half-metal thin-film magnets is explored in this study and the damping response is shown to be linked to the underlying electronic properties. By substituting the Z elements in high crystalline quality films (Co 2 MnZ with Z=Si, Ge, Sn, Al, Ga, Sb), electronic properties such as the minority spin band gap, Fermi energy position in the gap and spin polarization can be tuned and the consequence on magnetization dynamics analyzed. The experimental results allow us to directly explore the interplay of spin polarization, spin gap, Fermi energy position and the magnetic damping obtained in these films, together with ab initio calculation predictions. The ultra-low magnetic damping coefficients measured in the range 4.1 10-4-9 10-4 for Co 2 MnSi, Ge, Sn, Sb are the lowest values obtained on a conductive layer and offers a clear experimental demonstration of theoretical predictions on Half-Metal Magnetic Heusler compounds and a pathway for future materials design.
Titanium nitride (TiN) shows low resistivity at room temperature, high thermal stability and thus has the potential to serve as seed layer in magnetic tunnel junctions. High quality TiN thin films with regard to the crystallographic and electrical properties were grown and characterized by X-ray diffraction and 4-terminal transport measurements. Element specific X-ray absorption spectroscopy revealed pure TiN in the bulk. To investigate the influence of a TiN seed layer on a ferro(i)magnetic bottom electrode, an out-of-plane magnetized Mn2.45Ga as well as in- and out-of-plane magnetized Co2FeAl thin films were deposited on a TiN buffer, respectively. The magnetic properties were investigated using a superconducting quantum interference device (SQUID) and anomalous Hall effect (AHE) for Mn2.45Ga. Magneto optical Kerr effect (MOKE) measurements were carried out to investigate the magnetic properties of Co2FeAl. TiN buffered Mn2.45Ga thin films showed higher coercivity and squareness ratio compared to unbuffered samples. The Heusler compound Co2FeAl showed already good crystallinity when grown at room temperature.
The Ohmic spin diode (OSD) is a recent concept in spintronics, which is based on half-metallic magnets (HMMs) and spin-gapless semiconductors (SGSs). Quaternary Heusler compounds offer a unique platform to realize the OSD for room temperature applications as these materials possess very high Curie temperatures as well as half-metallic and spin-gapless semiconducting behavior within the same family. Using state-of-the-art first-principles calculations combined with the non-equilibrium Greens function method we design four different OSDs based on half-metallic and spin-gapless semiconducting quaternary Heusler compounds. All four OSDs exhibit linear current-voltage ($I-V$) characteristics with zero threshold voltage $V_T$. We show that these OSDs possess a small leakage current, which stems from the overlap of the conduction and valence band edges of opposite spin channels around the Fermi level in the SGS electrodes. The obtained on/off current ratios vary between $30$ and $10^5$. Our results can pave the way for the experimental fabrication of the OSDs within the family of ordered quaternary Heusler compounds.
Based on high throughput density functional theory calculations, we performed systematic screening for spin-gapless semiconductors (SGSs) in quaternary Heusler alloys XX 0 YZ (X, X 0 , and Y are transition metal elements without Tc, and Z is one of B, Al, Ga, In, Si, Ge, Sn, Pb, P, As, Sb, and Bi). Following the empirical rule, we focused on compounds with 21, 26, or 28 valence electrons, resulting in 12, 000 possible chemical compositions. After systematically evaluating the thermodynamic, mechanical, and dynamical stabilities, we successfully identified 70 stable SGSs, confirmed by explicit electronic structure calculations with proper magnetic ground states. It is demonstrated that all four types of SGSs can be realized, defined based on the spin characters of the bands around the Fermi energy, and the type-II SGSs show promising transport properties for spintronic applications. The effect of spin-orbit coupling is investigated, resulting in large anisotropic magnetoresistance and anomalous Nernst effects.
The half-Heusler compound has drawn attention in a variety of fields as a candidate material for thermoelectric energy conversion and spintronics technology. This is because it has various electronic structures, such as semi-metals, semiconductors, and a topological insulator. When the half-Heusler compound is incorporated into the device, the control of high lattice thermal conductivity owing to high crystal symmetry is a challenge for the thermal manager of the device. The calculation for the prediction of lattice thermal conductivity, which is an important physical parameter for controlling the thermal management of the device, requires a calculation cost of several 100 times as much as the usual density functional theory calculation. Therefore, we examined whether lattice thermal conductivity prediction by machine learning was possible on the basis of only the atomic information of constituent elements for thermal conductivity calculated by the density functional theory calculation in various half-Heusler compounds. Consequently, we constructed a machine learning model, which can predict the lattice thermal conductivity with high accuracy from the information of only atomic radius and atomic mass of each site in the half-Heusler type crystal structure. Applying our results, the lattice thermal conductivity for an unknown half-Heusler compound can be immediately predicted. In the future, low-cost and short-time development of new functional materials can be realized, leading to breakthroughs in the search of novel functional materials.