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This study presents novel predictive models using Graph Neural Networks (GNNs) for simulating thermal dynamics in Laser Powder Bed Fusion (L-PBF) processes. By developing and validating Single-Laser GNN (SL-GNN) and Multi-Laser GNN (ML-GNN)…

The design of shape memory alloys (SMAs) with high transformation temperatures and large mechanical work output remains a longstanding challenge in functional materials engineering. Here, we introduce a data-driven framework based on…

The cryogenic performance of GaN-based HEMTs (high-electron-mobility transistors) is systematically investigated by the direct current (DC) and low-frequency noise (LFN) characteristics within the temperature (T) range from 300 K to 4.2 K.…

The recently reported gate-tunable superconductivity in monolayer WTe$_2$ [Science 362, 922 (2018); Science 362, 926 (2018); Nat. Phys. 20, 269 (2024); PRR 7, 013224 (2025)] exhibits several striking anomalies beyond the standard paradigm,…

Materials able to rapidly switch between thermally conductive states by external stimuli such as electric or magnetic fields can be used as all-solid-state thermal switches and open a myriad of applications in heat management, power…

We present a combined computational and experimental investigation of the thermal properties of uranium nitride (UN), focusing on the development of a machine learning interatomic potential (MLIP) using the moment tensor potential (MTP)…

In this research, we developed a graph-based framework to represent various aspects of optimal thermal management system design, with the aim of rapidly and efficiently identifying optimal design candidates. Initially, the graph-based…

The mechanical behavior of inelastic materials with microstructure is very complex and hard to grasp with heuristic, empirical constitutive models. For this purpose, multiscale, homogenization approaches are often used for performing…

Wurtzite GaN:Mn films on sapphire substrates were successfully grown by use of the molecular beam epitaxy (MBE) system. The film has an extremely high Curie temperature of around 940 K, although the Mn concentration is only about 3 ~ 5 %.…

Heat management becomes more and more critical, especially in miniaturized modern devices, so the exploration of highly thermally conductive materials with electrical insulation and favorable mechanical properties is of great importance.…

In this study, we improve a neural network (NN) parameterization of deep convection in the global atmosphere model ARP-GEM. To take into account the sporadic nature of convection, we develop a NN parameterization that includes a triggering…

Wurtzite LaN (wz-LaN) is a semiconducting nitride with favorable piezoelectric and ferroelectric properties, making it promising for applications in electronics. We use first-principles density functional theory with a hybrid functional to…

Considerable efforts have been devoted recently to synthesize diluted magnetic semiconductors having ferromagnetic properties at room temperature because of their technological impacts for spintronic devices. In 2001 successful growth of…

This work presents a novel Gallium nitride (GaN) high-electron-mobility transistor (HEMT) based ultraviolet photodetector architecture integrating advanced material and structural design strategies to enhance detection performance and…

The impact of decorated dislocations on the effective thermal conductivity of GaN is investigated by means of equilibrium molecular dynamics simulations via the Green-Kubo approach. The formation of "nanowires" by a few atoms of In in the…

Hydrogen's role is growing as an energy carrier, increasing the need for efficient production, with methane steam reforming being the most widely used technique. This process is crucial for applications like fuel cells, where hydrogen is…

This paper reports the impacts of temperature variation on the inference accuracy of pre-trained all-ferroelectric FinFET deep neural networks, along with plausible design techniques to abate these impacts. We adopted a pre-trained…

Predicting effective thermal conductivity by solving a Partial Differential Equation (PDE) defined on a high-resolution Representative Volume Element (RVE) is a computationally intensive task. In this paper, we tackle the task by proposing…

Developing enzymes with desired thermal properties is crucial for a wide range of industrial and research applications, and determining temperature stability is an essential step in this process. Experimental determination of thermal…

We investigate temperature dependent thermal conductivity k(T) in a single Ge nanowire (NW) using Optothermal Raman Spectroscopy which utilizes the temperature dependence of Raman lines as a local probe for temperature. The experiment was…