English
Related papers

Related papers: Hyperparameter Optimization and Force Error Correc…

200 papers

High-efficient heat dissipation plays critical role for high-power-density electronics. Experimental synthesis of ultrahigh thermal conductivity boron arsenide (BAs, 1300 W m-1K-1) cooling substrates into the wide-bandgap semiconductor of…

Materials Science · Physics 2024-01-25 Jing Wu , E Zhou , An Huang , Hongbin Zhang , Ming Hu , Guangzhao Qin

Significant differences exist among literature for thermal conductivity of various systems computed using molecular dynamics simulation. In some cases, unphysical results, for example, negative thermal conductivity, have been found. Using…

Materials Science · Physics 2012-06-26 X. W. Zhou , S. Aubry , R. E. Jones , A. Greenstein , P. K. Schelling

We present a comprehensive computational study of the electronic, thermal, and thermoelectric (TE) properties of gallium nitride nanowires (NWs) over a wide range of thicknesses (3--9 nm), doping densities ($10^{18}$--$10^{20}$ cm$^{-3}$),…

Mesoscale and Nanoscale Physics · Physics 2014-05-21 A. H. Davoody , E. B. Ramayya , L. N. Maurer , I. Knezevic

Machine learned potentials (MLPs) have been widely employed in molecular dynamics (MD) simulations to study thermal transport. However, literature results indicate that MLPs generally underestimate the lattice thermal conductivity (LTC) of…

Materials Science · Physics 2024-09-12 Xiguang Wu , Wenjiang Zhou , Haikuang Dong , Penghua Ying , Yanzhou Wang , Bai Song , Zheyong Fan , Shiyun Xiong

Gallium nitride (GaN), a wide band-gap semiconductor, has been broadly used in power electronic devices due to its high electron mobility and high breakdown voltage. Its relatively high thermal conductivity makes GaN a favorable material…

Materials Science · Physics 2021-05-05 Yujie Quan , Sheng-Ying Yue , Bolin Liao

Gallium nitride (GaN) is a typical wide-bandgap semiconductor with a critical role in a wide range of electronic applications. Ballistic thermal transport at nanoscale hotspots will greatly reduce the performance of a device when its…

Mesoscale and Nanoscale Physics · Physics 2022-08-22 Dezhao Huang , Qiangsheng Sun , Zeyu Liu , Shen Xu , Ronggui Yang , Yanan Yue

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

Wurtzite gallium nitride (GaN) has great potential for high-frequency and high-power applications due to its excellent electrical and thermal transport properties. However, enhancing the performance of GaN-based power electronics relies on…

Recent molecular dynamics simulation methods have enabled thermal conductivity of bulk materials to be estimated. In these simulations, periodic boundary conditions are used to extend the system dimensions to the thermodynamic limit. Such a…

Materials Science · Physics 2012-06-26 X. W. Zhou , R. E. Jones , S. Aubry

Thermoelectric materials, which can convert waste heat to electricity or be utilized as solid-state coolers, hold promise for sustainable energy applications. However, optimizing thermoelectric performance remains a significant challenge…

Mesoscale and Nanoscale Physics · Physics 2025-04-25 Yang Xiao , Yuqi Liu , Zihan Tan Bohan Zhang , Ke Xu , Zheyong Fan , Shunda Chen , Shiyun Xiong , Haikuan Dong

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…

Materials Science · Physics 2025-08-06 Zhicheng Zong , Yangjun Qin , Jiahong Zhan , Haisheng Fang , Nuo Yang

Investigation of charged defects is necessary to understand the properties of semiconductors. While density functional theory calculations can accurately describe the relevant physical quantities, these calculations increase the…

Materials Science · Physics 2022-04-01 Koji Shimizu , Ying Dou , Elvis F. Arguelles , Takumi Moriya , Emi Minamitani , Satoshi Watanabe

Using the atomic cluster expansion (ACE) framework, we develop a machine learning interatomic potential for fast and accurately modelling the phonon transport properties of wurtzite aluminum nitride. The predictive power of the ACE…

Materials Science · Physics 2024-02-23 Guang Yang , Yuan-Bin Liu , Lei Yang , Bing-Yang Cao

In this study, by means of classical molecular dynamics simulations, we investigated the thermal transport properties of hexagonal single-layer, zinc-blend and wurtzite phases of BN, AlN, and GaN crystals, which are very promising for the…

Mesoscale and Nanoscale Physics · Physics 2020-04-13 Yenal Karaaslan , Haluk Yapicioglu , Cem Sevik

Bulk thermal conductivity estimates based on predictions from non-equilibrium molecular dynamics (NEMD) using the so-called direct method are known to be severely under-predicted since finite simulation length-scales are unable to mimic…

Computational Physics · Physics 2018-07-13 Manav Vohra , Ali Yousefzadi Nobakht , Seungha Shin , Sankaran Mahadevan

Machine-learned potentials (MLPs) have been extensively used to obtain the lattice thermal conductivity via atomistic simulations. However, the impact of force errors in various MLPs on thermal transport has not been widely recognized and…

Materials Science · Physics 2025-01-22 Wenjiang Zhou , Nianjie Liang , Xiguang Wu , Shiyun Xiong , Zheyong Fan , Bai Song

First-principles molecular dynamics simulations of heat transport in systems with large-scale structural features are challenging due to their high computational cost. Here, using polycrystalline graphene as a case study, we demonstrate the…

Materials Science · Physics 2024-10-21 Xiaoye Zhou , Yuqi Liu , Benrui Tang , Junyuan Wang , Haikuan Dong , Xiaoming Xiu , Shunda Chen , Zheyong Fan

We present a comprehensive investigation of self-heating in gallium nitride (GaN) high-electron-mobility transistors (HEMTs) through technology computer-aided design (TCAD) simulations and phonon Monte Carlo (MC) simulations. With…

Applied Physics · Physics 2024-01-25 Yang Shen , Bing-Yang Cao

Predicting and interpreting thermal performance under oscillating flow in porous structures remains a critical challenge due to the complex coupling between fluid dynamics and geometric features. This study introduces a data-driven…

Fluid Dynamics · Physics 2025-09-16 Lichang Zhu , Laura Schaefer , Leitao Chen , Ben Xu

We report calculated, electronic and related properties of wurtzite and zinc blende gallium nitrides (w-GaN, zb-GaN). We employed a local density approximation (LDA) potential and the linear combination of atomic orbital (LCAO) formalism.…

‹ Prev 1 2 3 10 Next ›