Weyl Metal Phase in Delafossite Oxide PtNiO2_2

On the basis of density functional theory calculations we predict Weyl points in rhombohedral structure of PtNiO$_2$ having symmorphic symmetry. From the formation energy and phonon calculations, PtNiO$_2$ is found to be structurally stable. The magnetic ground state is ferromagnetic with an effective magnetic moment of 1.01 $\mu_B$ per unit cell. The electronic structure shows major contributions from Pt-$5d$, Ni-$3d$ and O-$2p$ orbitals with band crossing close to the Fermi level. The orbital contribution around 8 eV above the Fermi level are from the Pt-$s,p$ orbitals forming a kagome like electronic structure confirmed by surface Fermi surface spectral function. We found 20 pairs of confirmed Weyl nodes along the magnetic easy axis [100]. These results are expected to provide a useful and exciting platform for exploring and understanding the magnetic Weyl physics in delafossites.Comment: 14 pages, 4 figure

Exploring topological phase transition in Pt2Hg1−xTlxSe3

The transition from trivial to non-trivial phase in two-dimensional materials are called a topological phase transition (TPT). The Berry phase, non-local string order parameter, and edge states define the topological nature of the system. A newly discovered jacutingaite ma- terial Pt2HgSe3 is a layered material which occurs naturally in the form of minerals. The material can be exfoliated and was predicted as a quantum spin Hall insulator. Here, on the basis of density functional theory and tight-binding calculations, we explore Pt2Hg1−xTlxSe3 (x = 0.25, 0.50, 0.75, 1) to understand the electronic and topological properties. We start with the parent material Pt2HgSe3 wherein Hg is replaced partially with x amount of Tl, to tune the topological phases. From the electronic structure calculations, Pt2HgSe3 is found to be a non-trivial semimetal in it’s bulk. Upon electron doping, the material transforms to strong topological metallic phase. The topological Z2 invariant calculation shows TPT in Pt2Hg1−xTlxSe3 with weak topological insulating state (0;001) for x=0, to strong topological metal (1;000) for x=1, respectively

Exploring topological phase transition in Pt2Hg1−xTlxSe3

The transition from trivial to non-trivial phase in two-dimensional materials are called a topological phase transition (TPT). The Berry phase, non-local string order parameter, and edge states define the topological nature of the system. A newly discovered jacutingaite ma- terial Pt2HgSe3 is a layered material which occurs naturally in the form of minerals. The material can be exfoliated and was predicted as a quantum spin Hall insulator. Here, on the basis of density functional theory and tight-binding calculations, we explore Pt2Hg1−xTlxSe3 (x = 0.25, 0.50, 0.75, 1) to understand the electronic and topological properties. We start with the parent material Pt2HgSe3 wherein Hg is replaced partially with x amount of Tl, to tune the topological phases. From the electronic structure calculations, Pt2HgSe3 is found to be a non-trivial semimetal in it’s bulk. Upon electron doping, the material transforms to strong topological metallic phase. The topological Z2 invariant calculation shows TPT in Pt2Hg1−xTlxSe3 with weak topological insulating state (0;001) for x=0, to strong topological metal (1;000) for x=1, respectively

Machine learning driven prediction of lattice constants in transition metal dichalcogenides

Machine learning represents an emerging branch of artificial intelligence, centering on the enhancement of algorithms in computer programs through the utilization of data and the accumulation of research-driven knowledge. The requirement for artificial intelligence in materials science is essential due to the significant need for innovative high-performance materials on a large scale. In this report, the gradient boosting regression tree model of machine learning was applied to predict the lattice constants of cubic and trigonal MX2 systems (M=transition metal and X=chalcogen atoms). The theoretical/experimental values of the materials were compared to the predicted values to calculate the standard errors such as RMSE (root mean square error) and MAE (mean absolute error). The features used to predict lattice constants were ionic radius, lattice angles, bandgap, formation energy, total magnetic moment, density and oxidation states. The features versus contribution barplot has been drawn to reveal the contribution level of each parameter in the degree of [0,1] to obtain the predictions. This report provides a precise account of the prediction methodology for lattice parameters of the transition metal dichalcogenides family, a process that was previously not reported

Machine learning driven prediction of lattice constants in transition metal dichalcogenides

Machine learning represents an emerging branch of artificial intelligence, centering on the enhancement of algorithms in computer programs through the utilization of data and the accumulation of research-driven knowledge. The requirement for artificial intelligence in materials science is essential due to the significant need for innovative high-performance materials on a large scale. In this report, the gradient boosting regression tree model of machine learning was applied to predict the lattice constants of cubic and trigonal MX2 systems (M=transition metal and X=chalcogen atoms). The theoretical/experimental values of the materials were compared to the predicted values to calculate the standard errors such as RMSE (root mean square error) and MAE (mean absolute error). The features used to predict lattice constants were ionic radius, lattice angles, bandgap, formation energy, total magnetic moment, density and oxidation states. The features versus contribution barplot has been drawn to reveal the contribution level of each parameter in the degree of [0,1] to obtain the predictions. This report provides a precise account of the prediction methodology for lattice parameters of the transition metal dichalcogenides family, a process that was previously not reported

Electronic structure and estimation of Curie temperature in Ca\u3csub\u3e2\u3c/sub\u3eBIrO\u3csub\u3e6\u3c/sub\u3e(B = Cr, Fe) double perovskites

We investigate the electronic and magnetic properties of Ca 2 CrIrO 6 and Ca 2 FeIrO 6 by means of density functional theory. These materials belong to a family of recently synthesized Ca 2 CrOsO 6 whose properties show possible applications in a room temperature regime. Upon replacement of Os by Ir in Ca 2 CrOsO 6, we found the system to exhibit a stable ferrimagnetic configuration with a bandgap of ∼0.25 eV and an effective magnetic moment of ∼2.58 μ B per unit cell. Furthermore, when chemical doping is considered by replacing Cr with Fe and Os with Ir, the material retains the insulating state but with a reduced bandgap of 0.13 eV and large increment in the effective magnetic moment of ∼6.68 μ B per unit cell. These observed behaviors are noted to be the consequence of the cooperative effect of spin-orbit coupling; Coulomb correlations from Cr-3d, Fe-3d, and Ir-5d electrons; and the crystal field effect of the materials. These calculations suggest that by chemical tuning, one can manipulate the bandgap and their effective magnetic moment, which may help in material fabrication for device applications. To check further the suitability and applicability of Ca 2 CrIrO 6 and Ca 2 FeIrO 6 at higher temperatures, we estimate the Curie temperature (T C) by calculating the spin-exchange coupling. We found that our findings are in a valid T C trend similar to other perovskites. Our findings are expected to be useful in experimental synthesis and transport measurement for potential applications in modern technological devices

Creating Weyl nodes and controlling their energy by magnetization rotation

As they do not rely on the presence of any crystal symmetry, Weyl nodes are robust topological features of an electronic structure that can occur at any momentum and energy. Acting as sinks and sources of Berry curvature, Weyl nodes have been predicted to strongly affect the transverse electronic response, like in the anomalous Hall or Nernst effects. However, to observe large anomalous effects the Weyl nodes need to be close to or at the Fermi-level, which implies the band structure must be tuned by an external parameter, e.g. chemical doping or pressure. Here we show that in a ferromagnetic metal tuning of the Weyl node energy and momentum can be achieved by rotation of the magnetization. Taking Co$_3$Sn$_2$S$_2$ as an example, we use electronic structure calculations based on density-functional theory to show that not only new Weyl fermions can be created by canting the magnetization away from the easy axis, but also that the Weyl nodes can be driven exactly to the Fermi surface. We also show that the dynamics in energy and momentum of the Weyl nodes strongly affect the calculated anomalous Hall and Nernst conductivities.Comment: Supp. Material adde