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Related papers: Accurate estimation of interfacial thermal conduct…

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Whether diffuse mismatch model for electrons (DMMe) hold true in more general cases remains largely unexplored, especially in cases where at least one material does not behave like a free-electron metal and/or the interface is smooth enough…

Materials Science · Physics 2023-11-21 Dian Li , Joseph Feser

Cubic silicon carbide phonon thermal conductivity has been calculated using anharmonic phonon analysis. The atomic interaction model was built using displacement-force data obtained with the High Efficiency Configuration Space Sampling…

Materials Science · Physics 2025-06-19 Paweł T. Jochym , Jan Łażewski

Phonons play a critical role in determining various material properties, but conventional methods for phonon calculations are computationally intensive, limiting their broad applicability. In this study, we present an approach to accelerate…

Materials Science · Physics 2024-07-16 Huiju Lee , Vinay I. Hegde , Chris Wolverton , Yi Xia

The existed theories and methods for calculating interfacial thermal conductance of solid-solid interface lead to diverse values that deviate from experimental measurements. In this letter, We propose a model to estimate the ITC at high…

Materials Science · Physics 2020-11-20 Jinxin Zhong , Zhiguo Wang , Xiaobo Li , Jun Liu , Jun Zhou

The integration of high-thermal-conductivity diamond films onto silicon carbide (SiC) substrates offers a promising pathway for thermal management in high-power electronic devices. Here, we investigate the depth-dependent thermal…

Materials Science · Physics 2026-04-15 Kexin Zhang , Xiaosong Han , Ershuai Yin , Xin Qian , Junjun Wei , Puqing Jiang

We demonstrate that a high-dimensional neural network potential (HDNNP) can predict the lattice thermal conductivity of semiconducting materials with an accuracy comparable to that of density functional theory (DFT) calculation. After a…

Materials Science · Physics 2019-08-16 Emi Minamitani , Masayoshi Ogura , Satoshi Watanabe

The temperature-dependent phonons are a generalization of interatomic force constants varying in T, which as found widespread use in computing the thermal transport of materials. A formal justification for using this combination to access…

Materials Science · Physics 2025-01-31 Aloïs Castellano , J. P. Alvarinhas Batista , Olle Hellman , Matthieu J. Verstraete

Controlling the thermal conductivity of semiconductors is of practical interest in optimizing the performance of thermoelectric and phononic devices. The insertion of inclusions of nanometer size in a semiconductor is an effective means of…

We develop ion-ion pair potentials for Al, Na and K for densities and temperatures relevant to the warm-dense-matter (WDM) regime. Furthermore, we emphasize non-equilibrium states where the ion temperature $T_i$ differs from the electron…

Materials Science · Physics 2015-03-19 Louis Harbour , M. W. Chandre Dharma-wardana , Dennis D. Klug , Laurent J. Lewis

Two-dimensional van der Waals (vdW) materials exhibit a broad palette of unique and superlative properties, including high electrical and thermal conductivities, paired with the ability to exfoliate or grow and transfer single layers onto a…

Materials Science · Physics 2023-02-22 Cameron Foss , Zlatan Aksamija

We have examined the commonly used Tersoff and Brenner empirical interatomic potentials in the context of the phonon dispersions in graphene. We have found a parameter set for each empirical potential that provides improved fits to some…

Mesoscale and Nanoscale Physics · Physics 2015-05-18 L. Lindsay , D. A. Broido

In silicon, lattice thermal conductivity plays an important role in a wide range of applications such as thermoelectric and microelectronic devices. Grain boundaries (GBs) in polycrystalline silicon can significantly reduce lattice thermal…

Computational Physics · Physics 2021-05-26 Susumu Fujii , Atsuto Seko

Nickel (Ni) is a magnetic transition metal with two allotropic phases, stable face-centered cubic (FCC) and metastable hexagonal close-packed (HCP), widely used in structural applications. Magnetism affects many mechanical and defect…

Machine learning (ML) based interatomic potentials are emerging tools for materials simulations but require a trade-off between accuracy and speed. Here we show how one can use one ML potential model to train another: we use an existing,…

Materials Science · Physics 2022-09-20 Joe D. Morrow , Volker L. Deringer

Probing detailed spectral dependence of phonon transport properties in bulk materials is critical to improve the function and performance of structures and devices in a diverse spectrum of technologies. Currently, such information can only…

Materials Science · Physics 2015-12-23 Yanguang Zhou , Xiaoliang Zhang , Ming Hu

The evolution of electron conductance in the presence of inelastic effects is studied as an atomic gold contact is formed evolving from a low-conductance regime (tunneling) to a high-conductance regime (contact). In order to characterize…

Mesoscale and Nanoscale Physics · Physics 2007-06-25 Thomas Frederiksen , Nicolas Lorente , Magnus Paulsson , Mads Brandbyge

We present a machine learning (ML) method for efficient computation of vibrational thermal expectation values of physical properties from first principles. Our approach is based on the non-perturbative frozen phonon formulation in which…

Materials Science · Physics 2026-03-16 Niraj Aryal , Sheng Zhang , Weiguo Yin , Gia-Wei Chern

It is well known that conventional harmonic lattice dynamics cannot be applied to energetically unstable crystals at 0 K, such as high temperature body centered cubic (BCC) phase of crystalline Zr. Predicting phonon spectra at finite…

Materials Science · Physics 2019-01-02 Xin Qian , Ronggui Yang

The formally exact framework of equilibrium Density Functional Theory (DFT) is capable of simultaneously and consistently describing thermodynamic and structural properties of interacting many-body systems in arbitrary external potentials.…

The effect on the vibrational and thermal properties of gradually interconnected nanoinclusions embedded in an amorphous silicon matrix is studied using MD simulations. The nanoinclusion arrangement ranges from an aligned sphere array to an…

Mesoscale and Nanoscale Physics · Physics 2021-05-10 Paul Desmarchelier , Alice Carré , Konstantinos Termentzidis , Anne Tanguy