arXiv subjects

Ole M. Løvvik

Publications and source records attributed to Ole M. Løvvik.

5 recordsLinked to original sources

arXiv2026

Exceptional thermoelectric properties in Na$_2$TlSb enabled by quasi-1D band structure

Materials with reduced dimensionality offer beneficial density-of-states (DOS) profiles for thermoelectric energy conversion, but can be impractical in realistic devices. Encouragingly, bulk high-symmetry materials can also exhibit similar quasi-low-dimensional band structures. A striking example is the full-Heusler compound Na$_2$TlSb, whose valence-band energy isosurfaces can form intersecting two-dimensional pockets, i.e., a box-like structure. The individual energy isosurface sheets resemble those of 1D quantum wires. The combination of high electron velocities (perpendicular to the pockets) and a rapidly increasing DOS with energy in the transport regime (due to the low dimensionality) makes Na$_2$TlSb a representative case where the band structure gives rise to attractive electronic transport properties. However, these beneficial features could be counteracted by high electronic scattering rates due to the large scattering space. In this first principles study of Na$_2$TlSb we find that the electronic scattering rates remain modest. This result is linked to the reduced matrix elements of large-momentum ($\mathbf{q}$) scattering across the delocalized energy isosurfaces. The enhanced free-carrier screening due to the large DOS also contributes to reducing scattering. In combination, the low-dimensional features and modest scattering result in excellent electronic transport properties. Combined with an ultra-low lattice thermal conductivity of $κ_\ell < 1$ W/mK reported in the literature, we predict a thermoelectric figure of merit ranging from 2.4 at 300 K to a 4.4 at 600 K. The $n$-type properties are also favorable, with $zT$ values from 1.5 at 300 K to 3.0 at 600 K.

cond-mat.mtrl-sci↗

arXiv2025

Thermoelectric transport of strained CsK$_2$Sb: The role of electron velocities and scattering within extended Fermi surfaces

In this first-principles study, we investigated the thermoelectric properties of the full-Heusler compound CsK$_2$Sb at different compressive strains. This material exhibits a valence band structure with significant effective mass anisotropy, forming tube-like energy isosurfaces below the band edge, akin to that of two-dimensional (2D) systems. Such systems can have a large number of high-mobility charge carriers and a beneficial density of states profile. In the calculations, we predicted a maximum p-type figure of merit ($zT$) of 2.6 at 800 K, in line with previous predictions of high $zT$. This high $zT$ arises from the low lattice thermal conductivity of 0.35 Wm$^{-1}$K$^{-1}$ and the beneficial electronic band structure. The high density of states significantly increased the electron-scattering space, but this effect was largely compensated by reduced scattering rates of electrons with large momentum ${\mathbf{q}}$. We further explored the effect of enhancing the low-dimensionality through compressive strain. This increased the p-type power factor by up to 66 %; partly due to more strongly pronounced 2D features of the valence band, but primarily due to increased Fermi velocities. However, compressive strain also increased phonon velocities and hence the lattice thermal conductivity. The maximum p-type $zT$ thus only increased slightly, to 2.7 at 1 % compressive strain. In the conduction band, strain aligned the $Γ$- and X-centered valleys, resulting in the optimal n-type $zT$ increasing from 0.9 to 2.3 at 2 % compressive strain. Thus, highly strained CsK$_2$Sb has the potential for both good p- and n-type thermoelectricity.

cond-mat.mtrl-sci↗

arXiv2019

Calculation of the Anisotropic Coefficients of Thermal Expansion: A First-Principles Approach

Predictions of the anisotropic coefficients of thermal expansion are needed to not only compare to experimental measurement, but also as input for macroscopic modeling of devices which operate over a large temperature range. While most current methods are limited to isotropic systems within the quasiharmonic approximation, our method uses first-principles calculations and includes anharmonic effects to determine the temperature-dependent properties of materials. These include the lattice parameters, anisotropic coefficients of thermal expansion, isothermal bulk modulus, and specific heat at constant pressure. Our method has been tested on two compounds (Cu and AlN) and predicts thermal properties which compare favorably to experimental measurement over a wide temperature range.

cond-mat.mtrl-sci↗

arXiv2019

Determining the Optimal Phase-Change Material via High-Throughput Calculations

The discovery and optimization of phase-change and shape memory alloys remain a tedious and expensive process. Here a simple computational method is proposed to determine the ideal phase-change material for a given alloy composed of three elements. Using first-principles calculations, within a high-throughput framework, the ideal composition of a phase-change material between any two assumed phases can be determined. This ideal composition minimizes the interface strain during the structural transformation. Then one can target this ideal composition experimentally to produce compounds with low mechanical failure rates for a potentially wide variety of applications. Here we will provide evidence of the effectiveness of our calculations for a well-known phase-change material in which we predict the ideal composition and compare it to experimental results.

cond-mat.mtrl-sci↗

arXiv2019

Machine Learning for Novel Thermal-Materials Discovery: Early Successes, Opportunities, and Challenges

High-throughput computational and experimental design of materials aided by machine learning have become an increasingly important field in material science. This area of research has emerged in leaps and bounds in the thermal sciences, in part due to the advances in computational and experimental methods in obtaining thermal properties of materials. In this paper, we provide a current overview of some of the recent work and highlight the challenges and opportunities that are ahead of us in this field. In particular, we focus on the use of machine learning and high-throughput methods for screening of thermal conductivity for compounds, composites and alloys as well as interfacial thermal conductance. These new tools have brought about a feedback mechanism for understanding new correlations and identifying new descriptors, speeding up the discovery of novel thermal functional materials.

cond-mat.mtrl-sci↗