Results 71 to 80 of about 24,296 (209)

Spin-polarization and electronic properties of half-metallic Heusler alloys calculated from first-principles

open access: yes, 2006
Half-metallic Heusler alloys are amongst the most promising materials for future magnetoelectronic applications. We review some recent results on the electronic properties of these compounds.
Galanakis, I., Mavropoulos, Ph.
core   +1 more source

Balancing the Competing Effects of Carrier and Phonon Transport Mechanisms to Enhance the Thermoelectric Properties of p‐Type Ti2Zr2−xHf2Nb2Fe5.6Ni2.4Sb8 Double Half‐Heusler Alloys via Cation Vacancy Engineering

open access: yesENERGY &ENVIRONMENTAL MATERIALS, Volume 9, Issue 2, March 2026.
By designing Zr vacancy‐filled p‐type Ti2Zr2Hf2Nb2Fe5.6Ni2.4Sb8‐based thermoelectric materials, multi‐physics mechanisms and multi‐scale microstructural defects are induced to optimize electrical properties and phonon transport while suppressing the bipolar diffusion effect.
Chaoyue Wang   +8 more
wiley   +1 more source

The emergence of Heusler alloy catalysts

open access: yesScience and Technology of Advanced Materials, 2019
For over a century, Heusler alloys (X2YZ; X, Y: transition metals, Z: typical metals) have attracted attention as magnetic materials. Nowadays, they are also popular as thermoelectric and shape memory materials.
Takayuki Kojima   +2 more
doaj   +1 more source

A first-principles approach to half-Heusler thermoelectrics: Accelerated prediction and understanding of material properties

open access: yesJournal of Materiomics, 2016
Half-Heusler alloys are an exciting class of thermoelectric materials that have shown great improvements in the thermoelectric figure of merit, ZT, during the past 15 years.
Alexander Page   +2 more
doaj   +1 more source

Finding unprecedentedly low-thermal-conductivity half-Heusler semiconductors via high-throughput materials modeling

open access: yes, 2014
The lattice thermal conductivity ({\kappa}{\omega}) is a key property for many potential applications of compounds. Discovery of materials with very low or high {\kappa}{\omega} remains an experimental challenge due to high costs and time-consuming ...
Carrete, Jesús   +4 more
core   +2 more sources

Experimental realization of a semiconducting full Heusler compound: Fe2TiSi

open access: yes, 2014
Single-phase films of the full Heusler compound Fe2TiSi have been prepared by magnetron sputtering. The compound is found to be a semiconductor with a gap of 0.4eV.
Arenholz, Elke   +8 more
core   +1 more source

Numerical Simulation and Synthesized Material Ranking for High‐Temperature Thermoelectric Power Generation

open access: yesEnergy Technology, Volume 14, Issue 3, March 2026.
The graphical abstract presents thermoelectric power generation driven by a temperature gradient (ΔT), highlighting electrical conductivity (σ), Seebeck coefficient (S), and thermal conductivity (κ). Material performance is compared across temperature regimes using experimental data and numerical modeling, identifying holmium–antimony–tellurium (Ho–Sb ...
Christian Idogho   +4 more
wiley   +1 more source

Spontaneous formation of nanostructures during pulsed laser deposition of epitaxial half-Heusler TiNiSn on MgO(001)

open access: yesAPL Materials, 2019
The half-Heusler alloy TiNiSn is a promising material for thermoelectric applications that is inexpensive and non-toxic. We demonstrate the epitaxial growth of smooth TiNiSn thin films on MgO(001) single crystal substrates by pulsed ...
R. W. H. Webster   +4 more
doaj   +1 more source

Competition between cubic and tetragonal phases in all-d-metal Heusler alloys, X2−xMn1+xV (X = Pd, Ni, Pt, Ag, Au, Ir, Co; x = 1, 0): a new potential direction of the Heusler family

open access: yesIUCrJ, 2019
In this work, a series of all-d-metal Heusler alloys, X2 − xMn1 + xV (X = Pd, Ni, Pt, Ag, Au, Ir, Co; x; = 1, 0), were predicted by first principles.
Yilin Han   +7 more
doaj   +1 more source

Machine learning modeling of lattice constants for half-Heusler alloys

open access: yesAIP Advances, 2020
The Gaussian process regression model is developed as a machine learning tool to find statistical correlations among lattice constants, a0, of half-Heusler compounds, ionic radii, and Pauling electronegativity of their alloying elements.
Yun Zhang, Xiaojie Xu
doaj   +1 more source

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