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The use of a novel three-dimensional graphene structure allows circumventing the limitations of the two-dimensional nature of graphene and its application in hydrogen absorption. Here we investigate hydrogen-bonding on monolayer graphene…
This work has been carried out to simulate a Resistive Plate Chamber and corroborate it with experimental measurements in order to develop a numerical tool for studying the performance of the device for any gas mixture. This will allow us…
Recently, ternary clathrate hydrides are promising candidates for high-temperature superconductor. However, it is a formidable challenge to effectively hunt high-temperature superconductivity among multinary hydrides due to the expensive…
Hydrogen, while a promising sustainable energy carrier, presents challenges such as the embrittlement of materials due to its ability to penetrate and weaken their crystal structures. Here we investigate Fe4N nitride layers, formed on iron…
The advent of the 5G era means that the concepts of robot, VR/AR, UAV, smart home, smart healthcare based on IoT (Internet of Things) have gradually entered human life. Since then, intelligent life has become the dominant direction of…
Breaching of earthen or sandy dams/dunes by overtopping flow and waves is a complicated process with strong, unsteady flow, high sediment transport, and rapid bed changes in which the interactions between flow and morphology should not be…
In this paper, thermal conductivity measurement of liquids and nanofluids is numerically investigated by the steady state method. In which, it is required to omit the natural convection effects on the inaccuracy of measurement for heat lost…
The extremely high thermal conductivity of graphene has received great attention both in experiments and calculations. Obviously, new feature in thermal properties is of primary importance for application of graphene-based materials in…
Graphene covered metal nanoparticles constitute a novel type of hybrid materials, which provide a unique platform to study plasmonic effects, surface-enhanced Raman scattering (SERS), and metal-graphene interactions at the nanoscale. Such a…
In nature adaptive coloration has been effectively utilized for concealment and signaling. Various biological mechanisms have evolved that can tune the reflectivity for visible and ultraviolet light. These examples inspire many artificial…
Following long-standing predictions associated with hydrogen, high-temperature superconductivity has recently been observed in several hydride-based materials. Nevertheless, these high-$T_c$ phases only exist at extremely high pressures,…
Hydrogen plays an important role in driving decarbonization within the current global energy landscape. As hydrogen infrastructures rapidly expand beyond their traditional applications, there is a need for comprehensive safety practices,…
Suspended membranes of monoatomic graphene exhibit great potential for applications in electronic and nanoelectromechanical devices. In this work, a "hot and dry" transfer process is demonstrated to address the fabrication and patterning…
Measuring the thermal conductivity of sub-surface buried substrates are of significant practical interests. However, this remains challenging with traditional pump-probe spectroscopies due to their limited thermal penetration depths (TPD).…
We have studied solid hydrogen up to pressures of 300 GPa and temperatures of 350 K using density functional theory methods and have found "mixed structures" that are more stable than those predicted earlier. Mixed structures consist of…
We present a novel computational framework to assess the structural integrity of welds. In the first stage of the simulation framework, local fractions of microstructural constituents within weld regions are predicted based on steel…
We propose a novel Skew Gradient Embedding (SGE) framework for systematically reformulating thermodynamically consistent partial differential equation (PDE) models-capturing both reversible and irreversible processes-as generalized gradient…
Recent progress in \emph{Geometric Deep Learning} (GDL) has shown its potential to provide powerful data-driven models. This gives momentum to explore new methods for learning physical systems governed by \emph{Partial Differential…
We created a computational workflow to analyze the potential energy surface (PES) of materials using machine-learned interatomic potentials in conjunction with the minima hopping algorithm. We demonstrate this method by producing a…
Current system thermal-hydraulic codes have limited credibility in simulating real plant conditions, especially when the geometry and boundary conditions are extrapolated beyond the range of test facilities. This paper proposes a…