activity
20192023
most citedMachine Learning-Driven Process of Alumina Ceramics Laser Machining

32 citations · 40 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CE2023★ 2 cited

Designing architectured ceramics for transient thermal applications using finite element and deep learning

Elham Kiyani, Hamidreza Yazdani Sarvestani, Hossein Ravanbakhsh +4

Topologically interlocking architectures can generate tough ceramics with attractive thermo-mechanical properties. This concept can make the material design pathway a challenging t…

cs.CE2022★ 32 cited

Machine Learning-Driven Process of Alumina Ceramics Laser Machining

Razyeh Behbahani, Hamidreza Yazdani Sarvestani, Erfan Fatehi +4

Laser machining is a highly flexible non-contact manufacturing technique that has been employed widely across academia and industry. Due to nonlinear interactions between light and…

cond-mat.mtrl-sci2021

Micromagnetic simulations of clusters of nanoparticles with internal structure: Application to magnetic hyperthermia

Razyeh Behbahani, Martin L. Plumer, Ivan Saika-Voivod

Micromagnetic simulation results on dynamic hysteresis loops of clusters of iron oxide nanoparticles (NPs) with internal structure composed of nanorods are compared with the widely…

cond-mat.mes-hall2020★ 6 cited

Multiscale modelling of magnetostatic effects on magnetic nanoparticles with application to hyperthermia

Razyeh Behbahani, Martin L. Plumer, Ivan Saika-Voivod

We extend a renormalization group-based course-graining method for micromagnetic simulations to include properly scaled magnetostatic interactions. We apply the method in simulatio…

cond-mat.mtrl-sci2019

Coarse-graining in micromagnetic simulations of dynamic hysteresis loops

Razyeh Behbahani, Martin L. Plumer, Ivan Saika-Voivod

Micromagnetic simulations based on the stochastic Landau-Lifshitz-Gilbert equation are used to calculate dynamic magnetic hysteresis loops relevant to magnetic hyperthermia. With t…