相关论文: Designing magnetism in Fe-based Heusler alloys: a …
Machine learning (ML) can facilitate efficient thermoelectric (TE) material discovery essential to address the environmental crisis. However, ML models often suffer from poor experimental generalizability despite high metrics. This study…
Structure optimizations were performed for 1 and 2 monolayers (ML) of Fe on a 5 ML W(110) substrate employing the all-electron full-potential linearized augmented plane-wave (FP-LAPW) method. The magnetic moments were also obtained for the…
The electronic and magnetic bulk properties of half-metallic Heusler alloys such as Co$_{2}$FeSi, Co$_{2}$FeAl, Co$_{2}$MnSi and Co$_{2}$MnAl are investigated by means of {\em ab initio} calculations in combination with Monte Carlo…
The random substitutional solid solution between the antiferromagnetic (AFM) full-Heusler alloy Ru$_2$MnSn and the ferromagnetic (FM) full-Heusler alloy Ru$_2$FeSn provides a rare opportunity to study FM-AFM phase competition in a…
We have explored, computationally and experimentally, the magnetic properties of \fecob{} alloys. Calculations provide a good agreement with experiment in terms of the saturation magnetization and the magnetocrystalline anisotropy energy…
The review treats Heusler alloys that display distinctive functional properties, including shape-memory behavior and magnetocaloric effects. Particular emphasis is placed on Heusler systems in which half-metallic ferromagnetism and…
Murunskite (K$_2$FeCu$_3$S$_4$) is a bridging compound between the only two known families of high-temperature superconductors. It is a semiconductor like the parent compounds of cuprates, yet isostructural to metallic iron-pnictides.…
In this study, we employ the Wien2k code to conduct ab-initio study of a novel potential all-d-metal Heusler alloy Co$_2$MnNb. The analysis utilizes the comparison of local spin density approximations (LDA) with Perdew-Burke-Ernzerh…
The local magnetic moments and hyperfine magnetic fields (HFF) in the ordered alloys Fe_{15}Sn and Fe_{15}Si are calculated with the first-principles full-potential linear augmented plane wave (FP LAPW) method. The results are compared with…
Heusler alloy Co2FeAl was employed as ferromagnetic layers in Co2FeAl/Ru/Co2FeAl synthetic antiferromagnet structures. The experimental results show that the structure with a Ru thickness of 0.45 nm takes on strongly antiferromagnetic…
We discover many new crystalline solid materials with fast single crystal Li ion conductivity at room temperature, discovered through density functional theory simulations guided by machine learning-based methods. The discovery of new solid…
Two-dimensional materials and their heterostructures have opened up new possibilities for magnetism at the nanoscale. In this study, we utilize first-principles simulations to investigate the structural, electronic, and magnetic properties…
We review the electronic and magnetic properties of the quinternary full Heusler alloys of the type Co$_2$[Cr$_{1-x}$Mn$_x$][Al$_{1-y}$Si$_y$] employing three different approaches : (i) the coherent potential approximation (CPA), (ii) the…
In this work, high throughput DFT calculations are performed on the alkali metal-based half Heusler alloys; LiY$_p$Y$^\prime_{1-p}$S (Y, Y$^\prime$ = V, Cr, Mn, Fe, Co, Ni and $\mathit{p}$ = 0, 0.25, 0.5, 0.75, 1). Starting with 243…
Permanent magnets draw their properties from a complex interplay of chemical composition and phase, each with their associated intrinsic magnetic properties. Gaining an understanding of these interactions is the key to deciphering the…
The advent of computational statistical disciplines, such as machine learning, is leading to a paradigm shift in the way we conceive the design of new compounds. Today computational science does not only provide a sound understanding of…
Half-Heuslers are a promising family for thermoelectric (TE) applications, yet only a small fraction of their potential chemistries has been experimentally explored. In this work, we introduce a distinct computational high-throughput…
Nowdays, multiferroic materials with magnetoelectric coupling have many real-world applications in the fields of novel memory devices. It is challenging is to create multiferroic materials with strongly coupled ferroelectric and…
We demonstrate a machine learning approach designed to extract hidden chemistry/physics to facilitate new materials discovery. In particular, we propose a novel method for learning latent knowledge from material structure data in which…
We present a comprehensive investigation of the influence of Ru concentration on the lattice parameters, atomic magnetic moments, electronic structure, and magnetic anisotropy energy of the full Heusler L2$_1$-type Mn$_2$Ru$_{1-x_p}$Ga…