相关论文: Equivariant graph neural network interatomic poten…
In crystalline materials, low lattice thermal conductivity is often associated with strong anharmonicity, which can cause significant deviations from the expected Lorentzian lineshape of phonon spectral functions. These deviations,…
The nanometer-scale size-dependent electronic transport properties of crystalline (c-) and amorphous (a-) germanium telluride (GeTe) ultrathin films sandwiched by titanium nitride (TiN) electrodes are investigated using ab initio molecular…
Machine-learned interatomic potentials enable realistic finite temperature calculations of complex materials properties with first-principles accuracy. It is not yet clear, however, how accurately they describe anharmonic properties, which…
An analysis of thermal transients from non-equilibrium ab initio molecular-dynamics simulations can be used to calculate the thermal conductivity of materials with a short phonon mean-free path. We adapt the approach-to-equilibrium…
Thermal transport properties bear a pivotal role in influencing the performance of phase change memory (PCM) devices, in which the PCM operation involves fast and reversible phase change between amorphous and crystalline phases. In this…
With the rapid advance of high-performance computing and electronic technologies, understanding thermal conductivity in materials has become increasingly important. This study presents a novel method: the Site-projected Thermal Conductivity…
GeTe is a prototypical phase change material of high interest for applications in optical and electronic non-volatile memories. We present an interatomic potential for the bulk phases of GeTe, which is created using a neural network (NN)…
We propose an efficient scheme, which combines density functional theory (DFT) with deep potentials (DP), to systematically study the convergence issues of the computed electronic thermal conductivity of warm dense Al (2.7 g/cm$^3$,…
Germanium telluride (GeTe), a phase-change material, is known to exhibit four different structural phases: three at room temperature (one amorphous and two crystalline, $\alpha$ and $\gamma$) and one at high temperature (crystalline…
Ab initio Green-Kubo (aiGK) simulations of heat transport in solids allow for assessing lattice thermal conductivity in anharmonic or complex materials from first principles. In this work, we present a detailed account of their practical…
Tantalum nitride (TaN) has attracted considerable attention due to its unique electronic and thermal properties, high thermal conductivity, and applications in electronic components. However, for the {\theta}-phase of TaN, significant…
In this paper we describe a spatial decomposition of the thermal conductivity, what we name "site-projected thermal conductivity", a gauge of the thermal conduction activity at each site. The method is based on the Green-Kubo formula and…
The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been scarcely investigated despite its relevance to thermal…
Magnetism governs key properties of materials used in energy, data storage, and spintronic technologies, yet its complex coupling to lattice and electronic degrees of freedom challenges conventional first-principles approaches. We introduce…
Calculations of heat transport in crystalline materials have recently become mainstream, thanks to machine-learned interatomic potentials that allow for significant computational cost reductions while maintaining the accuracy of…
Molecular dynamics simulations play an important role in studying heat transport in complex materials. The lattice thermal conductivity can be computed either using the Green-Kubo formula in equilibrium MD (EMD) simulations or using…
We propose an efficient approach for simultaneous prediction of thermal and electronic transport properties in complex materials. Firstly, a highly efficient machine-learned neuroevolution potential is trained using reference data from…
Foundational machine-learned interatomic potentials have emerged as powerful tools for atomistic simulations, promising near first-principles accuracy across diverse chemical spaces at a fraction of the cost of quantum-mechanical…
Recently discovered double gamma/beta ({\gamma}/\b{eta}) polymorph Ga2O3 structures constitute a class of novel materials providing an option to modulate functional properties across interfaces without changing chemical compositions of…
Thermal conductivity is a fundamental material property that plays a crucial role in understanding the dynamics and evolution of planetary interiors. Despite its importance, the thermal conductivity of seifertite and pyrite-type SiO$_2$…