Compositional optimization of hard-magnetic phases with machine-learning models

Machine Learning (ML) plays an increasingly important role in the discovery and design of new materials. In this paper, we demonstrate the potential of ML for materials research using hard-magnetic phases as an illustrative case. We build kernel-based ML models to predict optimal chemical compositions for new permanent magnets, which are key components in many green-energy technologies. The magnetic-property data used for training and testing the ML models are obtained from a combinatorial high-throughput screening based on density-functional theory calculations. Our straightforward choice of describing the different configurations enables the subsequent use of the ML models for compositional optimization and thereby the prediction of promising substitutes of state-of-the-art magnetic materials like Nd$_2$Fe$_{14}$B with similar intrinsic hard-magnetic properties but a lower amount of critical rare-earth elements.Comment: 12 pages, 6 figure

Magnetic properties of σ\sigma-FeCr alloy as calculated with the charge and spin self-consistent KKR(CPA) method

Magnetic properties of a $\sigma-$Fe$_{16}$Cr$_{14}$ alloy calculated with the charge and spin self- consistent Korringa-Kohn-Rostoker (KKR) and combined with coherent potential approximation (KKR-CPA) methods are reported. Non-magnetic state as well as various magnetic orderings were considered, i.e. ferromagnetic (FM) and more complex anti-parallel (called APM) arrangements for selected sublattices, as follows from the symmetry analysis. It has been shown that the Stoner criterion applied to non-magnetic density of states at the Fermi energy, $E_F$ is satisfied for Fe atoms situated on all five lattice sites, while it is not fulfilled for all Cr atoms. In FM and APM states, the values of magnetic moments on Fe atoms occupying various sites are dispersed between 0 and 2.5 $\mu_B$, and they are proportional to the number of Fe atoms in the nearest-neighbor shell. Magnetic moments of Cr atoms havin much smaller values were found to be coupled antiparallel to those of Fe atoms. The average value of the magnetic moment per atom was found to be $=0.55 \mu_B$ that is by a factor of 4 larger than the experimental value found for a $\sigma-$Fe$_{0.538}$Cr$_{0.462}$ sample. Conversely, admitting an anti- parallel ordering (APM model) on atoms situated on C and D sites, according to the group theory and symmetry analysis results, yielded a substantial reduction of to 0.20 $\mu_B$. Further diminution of to 0.15 $\mu_B$, which is very close to the experimental value of 0.14 $\mu_B$, has been achieved with the KKR-CPA calculations by considering a chemical disorder on sites B, C and D

Human Rights Violations After 9/11 and the Role of Constitutional Constraints

human rights, terrorism, 9/11, checks and balances, constitutions, constitutional courts

Does Finance Bolster Superstar Companies? Banks, Venture Capital, and Firm Size in Local U.S. Markets

We study the relative effect of venture capital and bank finance on large manufacturing firms in local U.S. markets. Theory predicts that with venture capital, the firm size distribution should become more stretched-out to the right, but it’s ambiguous on the effect of banks on large firms. The empirical evidence suggests that while the average size of firms in the top bin of the firm size distribution has remained unaffected by banking sector developments, it has increased with venture capital investment. We argue that this is due to the emergence of new corporate giants rather than the growth of existing ones. JEL Classification: G24, J24, L11banking, firm size, Venture Capital

Does the euro make a difference? Spatio-temporal transmission of global shocks to real effective exchange rates in an infinite VAR

This paper provides evidence on whether the creation of the euro has changed the way global turbulences affect euro area and other economies. Specifically, it considers the impact of global shocks on the competitiveness of individual euro area countries and assesses whether their responses to such shocks have converged, as well as to what pattern. Technically, the paper applies a newly developed methodology based on infinite VAR theory featuring a dominant unit to a large set of over 60 countries' real effective exchange rates, including those of the individual euro area economies, and compares impulse response functions to the estimated systems before and after EMU with respect to three types of shocks: a global US dollar shock, generalised impulse response function shocks and a global shock to risk aversion. Our results show that the way euro area countries' real effective exchange rates adjust to these shocks has converged indeed, albeit to a pattern that depends crucially on the nature of the shock. This result is noteworthy given the apparent divergence in competitiveness indicators of these countries in the first ten years of EMU, which suggests that this diverging pattern is unlikely to be due to global external shocks with asymmetric effects but rather to other factors, such as country-specific domestic shocks. JEL Classification: C21, C23euro, High-Dimensional VAR, Identification of Shocks, Real Effective Exchange Rates, Weak and Strong Cross Sectional Dependence

Epitaxial strain effects in the spinel ferrites CoFe2O4 and NiFe2O4 from first principles

The inverse spinels CoFe2O4 and NiFe2O4, which have been of particular interest over the past few years as building blocks of artificial multiferroic heterostructures and as possible spin-filter materials, are investigated by means of density functional theory calculations. We address the effect of epitaxial strain on the magneto-crystalline anisotropy and show that, in agreement with experimental observations, tensile strain favors perpendicular anisotropy, whereas compressive strain favors in-plane orientation of the magnetization. Our calculated magnetostriction constants $\lambda_{100}$ of about -220 ppm for CoFe2O4 and -45 ppm for NiFe2O4 agree well with available experimental data. We analyze the effect of different cation arrangements used to represent the inverse spinel structure and show that both LSDA+U and GGA+U allow for a good quantitative description of these materials. Our results open the way for further computational investigations of spinel ferrites