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Optical heating of plasmonic nanostructures is a critical challenge in nanoscale systems. Although plasmonic effects enable enhanced optical functionalities, the associated temperature rise can degrade performance in heat-sensitive…
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…
Thermal conductivity is a fundamental material property that plays an essential role in technology, but its accurate evaluation presents a challenge for theory. In this work, we demonstrate the application of $E(3)$-equivariant neutral…
The lattice thermal conductivity ($\kappa_{\ell}$) is a key materials property in power electronics, thermal barriers, and thermoelectric devices. Identifying a wide pool of compounds with low $\kappa_{\ell}$ is particularly important in…
The electronic and thermal transport properties have been systematically investigated in monolayer C$_4$N$_3$H with first-principles calculations. The intrinsic thermal conductivity of monolayer C$_4$N$_3$H was calculated coupling with…
Graphene oxide (GO) exhibits rich chemical heterogeneity that strongly influences its structural, thermal, and mechanical properties, yet quantitatively linking reduction chemistry to heat transport remains challenging. In this work, we…
Unlike the electrical conductance that can be widely modulated within the same material even in deep nanoscale devices, tuning the thermal conductance within a single material system or nanostructure is extremely challenging and requires a…
Boron phosphide (BP) is a (super)hard semiconductor constituted of light elements, which is promising for high demand applications at extreme conditions. The behavior of BP at high temperatures and pressures is of special interest but is…
Using first-principles density functional perturbation theory based calculations of length-dependent lattice thermal conductivity (\k{appa} L ) and using our previously calculated results (Phys Rev B 95 085435 (2017)) of electrical…
Metallic glasses are a promising class of materials celebrated for their exceptional thermal and mechanical properties. However, accurately predicting and understanding the melting temperature (T_m) and glass transition temperature (T_g)…
The efficiency of phonon-mediated heat transport is limited by the intrinsic atomistic properties of materials, seemingly providing an upper limit to heat transfer in materials and across their interfaces. The typical speeds of conductive…
Accurate structural relaxation is critical for advanced materials design. Traditional approaches built on physics-derived first-principles calculations are computationally expensive, motivating the creation of machine-learning interatomic…
The rapid development and large body of literature on machine learning interatomic potentials (MLIPs) can make it difficult to know how to proceed for researchers who are not experts but wish to use these tools. The spirit of this review is…
Several layered transition metal borides can now be realized by a simple and general fabrication method [Fokwa et al.,Adv. Mater. 2018, 30, 1704181],inspiring our interest to transition metal borides monolayer. Here, we predict a new…
We review the Raman shift method as a non-destructive optical tool to investigate the thermal conductivity and demonstrate the possibility to map this quantity with a micrometer resolution by studying thin film and bulk materials for…
Carbon-fiber-reinforced polymers (CFRPs) are some of the most useful materials for building spacecraft and aerospace tools. They are especially valuable for systems that work at extremely cold (cryogenic) temperatures because they are…
Features of thermal transport in multilayered porous silicon nanostructures are considered. Such nanostructures were fabricated by electrochemical etching of monocrystalline Si substrates by applying periodically changed current density.…
Fast, and accurate prediction of ionic migration barriers ($E_m$) is crucial for designing next-generation battery materials that combine high energy density with facile ion transport. Given the computational costs associated with…
High Nb-containing TiAl alloys exhibit exceptional high-temperature strength and room-temperature ductility, making them widely used in hot-section components of automotive and aerospace engines. However, the lack of accurate interatomic…
Machine learning interatomic potentials (MLIPs) have massively changed the field of atomistic modeling. They enable the accuracy of density functional theory in large-scale simulations while being nearly as fast as classical interatomic…