相关论文: Hyperparameter Optimization and Force Error Correc…

The wurtzite III-Nitrides family of semiconductors, which include the compounds GaN, InN, and AlN, along with their derivative ternary alloys, is highly priced for its wide range of bandgaps, lattice constant tunability, high breakdown…

Magnesium Selenide (MgSe) is a wide bandgap semiconductor with applications in optoelectronics and energy conversion technologies. Understanding thermal conductivity (k) of MgSe is critical for optimum design of thermal transport in these…

We contrasted the performance of deep neural networks - Convolutional Neural Network (CNN) and Graph Neural Network (GNN) - to current state of the art energy regression methods in a finely 3D-segmented calorimeter simulated by GEANT4. This…

We calculate the electronic and thermal transport properties of devices based on finite graphene antidot lattices (GALs) connected to perfect graphene leads. We use an atomistic approach based on the $\pi$-tight-binding model, the Brenner…

Thermal conductivities are routinely calculated in molecular dynamics simulations by keeping the boundaries at different temperatures and measuring the slope of the temperature profile in the bulk of the material, explicitly using Fourier's…

As the characteristic dimensions of modern top-down devices are getting smaller, such devices reach their operational limits given by quantum mechanics. Thus, two-dimensional (2D) structures appear as one of the best solutions to meet the…

The use of optimal transport cost for learning generative models has become popular with Wasserstein Generative Adversarial Networks (WGAN). Training of WGAN relies on a theoretical background: the calculation of the gradient of the optimal…

We develop a high frequency, wide bandwidth radiometer operating at room temperature, which augments the traditional technique of Johnson noise thermometry for nanoscale thermal transport studies. Employing low noise amplifiers and an…

We present large-scale molecular dynamics (MD) simulations based on a machine-learning interatomic potential to investigate the wet etching behavior of various GaN facets in alkaline solution-a process critical to the fabrication of…

Ternary pnictides semiconductors with II-IV-V2 stoichiometry hold potential as cost effective thermoelectric materials with suitable electronic transport properties, but their lattice thermal conductivities ($\kappa$) are typically too…

This paper presents a modeling and optimization framework to minimize the energy consumption of a fully electric powertrain by optimizing its design and control strategies whilst explicitly accounting for the thermal behavior of the…

In the present work, we propose a self-optimization wavelet-learning method (SO-W-LM) with high accuracy and efficiency to compute the equivalent nonlinear thermal conductivity of highly heterogeneous materials with randomly hierarchical…

Ultrawide bandgap (UWBG) semiconductors exhibit exceptional electrical and thermal properties, offering strong potential for high power and high frequency electronics. However, efficient doping in UWBG materials is typically limited to…

Semiconductor nanostructures hold great promise for high-efficiency waste heat recovery exploiting thermoelectric energy conversion, a technological breakthrough that could significantly contribute to providing environmentally friendly…

Accurate evaluation of the thermal conductivity of a material can be a challenging task from both experimental and theoretical points of view. In particular for the nanostructured materials, the experimental measurement of thermal…

Layered perovskite lithium yttrium titanate ($\rm LiYTiO_4$) has recently emerged as a promising low-potential, ultrahigh-rate intercalation-type anode material for lithium-ion batteries; however, its lattice dynamics and thermal transport…

Effective data center cooling is crucial for reliable operation; however, cooling systems often exhibit inefficiencies that result in excessive energy consumption. This paper presents a three-stage, physics-guided machine learning framework…

Estimating heat flux in the nuclear fusion device EAST is a critically important task. Traditional scientific computing methods typically model this process using the Finite Element Method (FEM). However, FEM relies on grid-based sampling…

We present temperature-dependent conductivity data obtained on a sample set of nanogranular Pt-C with finely tuned inter-grain tunnel coupling strength g. For samples in the strong-coupling regime g > g_C, characterized by a finite…

The thermal conductivities k of wurtzite InxGa1-xN are investigated using equilibrium molecular dynamics (MD) method. The k of InxGa1-xN rapidly declines from InN (k_InN = 141 W/mK) or GaN (k_GaN = 500 W/mK) to InxGa1-xN, and reaches a…