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Self-heating is a severe problem for high-power GaN electronic and optoelectronic devices. Various thermal management solutions, e.g. flip-chip bonding or composite substrates have been attempted. However, temperature rise still limits…

Methane is considered being a good choice as a propellant for future reusable launch systems. However, the heat transfer prediction for supercritical methane flowing in cooling channels of a regeneratively cooled combustion chamber is…

Ultra-wide-band-gap group-III nitrides are of interest for applications in deep-ultraviolet optoelectronics and power electronics. Such devices must be able to efficiently dissipate heat generated from their operation, making the thermal…

Heat generated in gallium nitride (GaN) high-electron-mobility transistors (HEMTs) is often concentrated in nanoscale regions and must dissipate through multiple heterostructures. However, the influence of non-uniform heat sources on the…

Accurate and efficient temperature prediction is critical for optimizing the preheating process of PET preforms in industrial microwave systems prior to blow molding. We propose a novel deep learning framework for generalized temperature…

Gallium nitride (GaN) is a wide-bandgap semiconductor of significant interest for applications in solid-state lighting, power electronics, and radio-frequency amplifiers. An important limitation of this semiconductor is its low intrinsic…

Galliumnitride has become a strategic superior material for space, defense and civil applications, primarily for power amplification at RF and mm-wave frequencies. For AlGaN/GaN high electron mobility transistors (HEMT), an outstanding…

AlN is an ultra-wide bandgap semiconductor which has been developed for applications including power electronics and optoelectronics. Thermal management of these applications is the key for stable device performance and allowing for long…

We develop a neuroevolution-potential (NEP) framework for generating neural network based machine-learning potentials. They are trained using an evolutionary strategy for performing large-scale molecular dynamics (MD) simulations. A…

Efficient thermal management is essential for the reliability of modern power electronics, where increasing device density leads to severe heat dissipation challenges. However, in thin-film systems, thermal transport is often compromised by…

Nearly 30% increase of the ferromagnetic phase transition temperature has been achieved in strained MnAs nanocrystals embedded in a wurtzite GaAs matrix. Wurtzite GaAs exerts tensile stress on hexagonal MnAs nanocrystals, preventing a…

Electric fields commonly exist in semiconductor structures of electronics, bringing to bear on phonon thermal transport. Also, it is a popular method to tune thermal transport in solids. In this work, phonon and thermal transport properties…

The thermal conductivity of a crystal is sensitive to the presence of surfaces and nanoscale defects. While this opens tremendous opportunities to tailor thermal conductivity, a true "phonon engineering" of nanocrystals for a specific…

Graphane and graphene are both two-dimensional materials but of different bonding configurations, which can result in distinct thermal conduction properties. We simulate thermal conduction in graphane nanoribbons (GANRs) using the…

In recent years, three-dimensional GaN-based transistors have been intensively studied for their dramatically improved output power, better gate controllability, and shorter channels for speedup and miniaturization. However, thermal…

Low dimensional systems, nanowires, in particular, have exhibited excellent optical and electronic properties. Understanding the thermal properties in semiconductor nanowires is very important for their applications in their electronic…

We present surrogate models for heat transfer and pressure drop prediction of complex fin geometries generated using composite Bezier curves. Thermal design process includes iterative high fidelity simulation which is complex,…

Semiconductor membranes find their widespread use in various research fields targeting medical, biological, environmental, and optical applications. Often such membranes derive their functionality from an inherent nanopatterning, which…

Much research in recent years has focused on using empirical machine learning approaches to extract useful insights on the structure-property relationships of superconductor material. Notably, these approaches are bringing extreme benefits…

The present work investigates the less explored thermoelectric properties of n-type GaN semiconductors by combined both the experimental and computational tools. Seebeck coefficients of epitaxial thin films of GaN were experimentally…