21 citations · 31 across the 11 of their papers we have counts for
11 papers
Phase-field investigation of non-isothermal solidification coupled with melt flow dynamics
Timileyin David Oyedeji, Aaron Brunk, Yangyiwei Yang +3
Solidification, coupled with melt flow, plays a critical role in determining the microstructure and properties of materials in several manufacturing processes. Phase-field models c…
Machine learning-enabled inverse design of bimaterial thermoelastic lattice metamaterials
Xiang-Long Peng, Bai-Xiang Xu
The thermoelastic metamaterial based on a bimaterial hybrid-honeycomb structure, exhibiting simultaneously negative Poisson's ratios and negative thermal expansion coefficients is…
Thermal and Microstructural Simulations of Photonic Sintering of Oxide Ceramics: A Two-Scale Scheme
Junlong Ma, Yangyiwei Yang, Julian N. Ebert +2
Photonic sintering (PS) offers an ultra-fast, contact-free alternative to conventional sintering and has demonstrated its potential for enhancing the sinterability of acceptor-dope…
Direct observation of nanoscale pinning centers in Ce(Co0.8Cu0.2)5.4 permanent magnets
Nikita Polin, Shangbin Shen, Fernando Maccari +15
Permanent magnets containing rare earth elements are essential components for the electrification of society. Ce(Co1-xCux)5 permanent magnets are a model system known for their sub…
Multiphysics simulations of microstructure influence on hysteresis and eddy current losses of electrical steel
Patrick Kühn, Yangyiwei Yang, Guanyu Chen +3
Improving efficiency of electrical machines requires fundamental knowledge on the mechanisms behind magnetic and eddy current losses of the magnetic core materials, with Fe-Si allo…
Coercivity influence of nanostructure in SmCo-1:7 magnets: Machine learning of high-throughput micromagnetic data
Yangyiwei Yang, Patrick Kühn, Mozhdeh Fathidoost +9
As a pinning-controlled permanent magnet, tailoring the cellular nanostructure of samarium-cobalt-based 1:7-type (SmCo-1:7) magnets remains crucial for improving magnetic performan…
ML-extendable framework for multiphysics-multiscale simulation workflow and data management using Kadi4Mat
Somnath Bharech, Yangyiwei Yang, Michael Selzer +2
As material modeling and simulation has become vital for modern materials science, research data with distinctive physical principles and extensive volume are generally required fo…
What can machine learning help with microstructure-informed materials modeling and design?
Xiang-Long Peng, Mozhdeh Fathidoost, Binbin Lin +2
Machine learning techniques have been widely employed as effective tools in addressing various engineering challenges in recent years, particularly for the challenging task of micr…
Unraveling impacts of polycrystalline microstructures on ionic conductivity of ceramic electrolytes by computational homogenization and machine learning
Xiang-Long Peng, Bai-Xiang Xu
The ionic conductivity at the grain boundaries (GBs) in oxide ceramics is typically several orders of magnitude lower than that within the grain interior. This detrimental GB effec…
Variational approximation for a non-isothermal coupled phase-field system: Structure-preservation & Nonlinear stability
Aaron Brunk, Oliver Habrich, Timileyin David Oyedeji +2
A Cahn-Hilliard-Allen-Cahn phase-field model coupled with a heat transfer equation, particularly with full non-diagonal mobility matrices, is studied. After reformulating the probl…
Elasto-plastic residual stress analysis of selective laser sintered porous materials based on 3D-multilayer thermo-structural phase-field simulations
Yangyiwei Yang, Somnath Bharech, Nick Finger +3
Residual stress and plastic strain in additive manufactured materials can exhibit significant microscopic variation at the powder scale, profoundly influencing the overall properti…