Results 111 to 120 of about 149 (149)
The electronic modulation of Nb‐doped Co3O4 catalyst showcases enhanced activity and extended stability for OER in both alkaline (1M KOH) and acidic (0.5M H2SO4) electrolytes. The higher activity emanated from the synergistic effect between the Nb5+ dopant and Co3O4.
Kassa Belay Ibrahim+7 more
wiley +1 more source
Electro‐Thermal Response of Thin Film Heaters Based on Embedded Periodic Metallic Mesh
“This study systematically investigates the effect of periodic metallic mesh topology on electrical and electro‐thermal behaviours of thin thermal heaters. The derived closed‐form expressions capture the dependence of sheet resistance on design parameters, providing a crucial tool for rapidly exploring a vast design space and accelerating design and ...
Dimitrios Charaklias+3 more
wiley +1 more source
SyMO: A Hybrid Approach for Multi‐Objective Optimization of Crystal Growth Processes
The hybrid SyMO (Symbolic regression Multi‐objective Optimization) framework combines Computational Fluid Dynamics (CFD), machine learning, and mathematical optimization techniques to investigate the effects of various process parameters, furnace geometries, and radiation shield material properties on key crystal quality metrics in Czochralski silicon (
Milena Petkovic, Natasha Dropka
wiley +1 more source
FreqD‐LBM simulates the oscillatory flow at the surface of a QCM‐D resonator in the presence of structured adsorbates. It derives shifts of frequency and bandwidth (equivalent to dissipation) on different overtones. Applications include rough surfaces, adsorbed rigid particles, adsorbed viscoelastic particles, spheres floating freely above the surface,
Diethelm Johannsmann+5 more
wiley +1 more source
This work proposes a surface elasticity‐based nonlocal model for analyzing the vibrations of bi‐directionally graded tapered nanobeam. The results demonstrate that, in absence of surface effect, the increasing value of tapered parameter leads to stiffness‐hardening of the nanobeam. However, the consideration of surface effect changes this trend and the
Chinika Dangi, Susmita Naskar
wiley +1 more source
Machine Learning (ML) and optimization have permeated almost every aspect of engineering applications. Recent years have seen great traction toward ML‐based GaN HEMT modelling. However, ML‐based GaN HEMT models are mostly developed using variants of Artificial Neural Network (ANN).
Saddam Husain+2 more
wiley +1 more source
Increasing half‐cycles intensifies turbulence due to enhanced vortex interactions and flow separation at the diverged‐outlets. Longer wavy ducts are shown to increase flow acceleration, resulting in greater output velocities and more turbulent‐kinetic‐energy production. Wave‐period plays a crucial role in determining turbulent intensity, with amplitude
I. L. Animasaun+2 more
wiley +1 more source
Mathematical modelling: A student optimal control problem and extensions
openaire +2 more sources
Three charge assignment approaches (one quantum chemistry method‐based, the other two machine‐learning (ML) model‐based) are employed to investigate acetylene separation performances of experimental covalent‐organic frameworks. Partial Atomic Charge Predicter for Porous Materials based on Graph Convolutional Neural Network (PACMAN) ML model‐based ...
Hakan Demir, Ilknur Erucar
wiley +1 more source
FMint is introduced as a multi‐modal foundation model that integrates human‐designed solvers and data‐driven methods for fast, accurate simulation of dynamical systems. FMint leverages in‐context learning within a transformer‐based framework to refine coarse numerical solutions.
Zezheng Song, Jiaxin Yuan, Haizhao Yang
wiley +1 more source