[HTML][HTML] An interpretable deep learning approach for designing nanoporous silicon nitride membranes with tunable mechanical properties

AK Shargh, N Abdolrahim - npj Computational Materials, 2023 - nature.com
The high permeability and strong selectivity of nanoporous silicon nitride (NPN) membranes
make them attractive in a broad range of applications. Despite their growing use, the …

Computational Homogenization of Precipitated Shape Memory Alloys: A Comparative Study of FFT Versus FEA

JK Joy, A Cruzado, A Solomou, AA Benzerga… - Shape Memory and …, 2022 - Springer
Aging heat treatments in Shape Memory Alloys (SMAs) often lead to formation of
precipitates, which affect phase transformation. In order to analyze the effects of volume …

Modeling a sample size-dependency of martensitic phase transformation using a mesoscale framework

M Vasoya, DC Lagoudas - International Journal of Plasticity, 2023 - Elsevier
Predicting a sample size-dependency of the constitutive response of any material system
when it is being used in nano-and micro-scale devices, such as NEMS and MEMS, is very …

[HTML][HTML] Cyclic Stability of Two-Way Shape Memory Effect in Aged Ni50.3Ti32.2Hf17.5 Polycrystals after Various Thermomechanical Treatments

EY Panchenko, AI Tagiltsev, EE Timofeeva… - Materials, 2023 - mdpi.com
In the present paper, the cyclic stability of the high-temperature two-way shape memory
effect was studied in high-strength Ni50. 3Ti32. 2Hf17. 5 polycrystals after various …

Thermodynamic, Kinetic and Mechanical Modeling to Evaluate CO2-induced Corrosion via Oxidation and Carburization in Fe, Ni alloys

A Sundar, A Feinauer, B Kinzer, J Petrasch, L Qi… - arXiv preprint arXiv …, 2023 - arxiv.org
A computational framework integrating thermodynamics, kinetics, and mechanical stress
calculations is developed to study supercritical CO2 induced corrosion in model Fe-based …