38 citations · 78 across the 6 of their papers we have counts for
3 papers · 1 filter
Universal Design Methodology for Printable Microstructural Materials via a New Deep Generative Learning Model: Application to a Piezocomposite
Mohammad Saber Hashemi, Khiem Nguyen, Levi Kirby +2
We devised a general heterogeneous microstructural design methodology applied to a specific material system, elasto-electro-active piezoelectric ceramic embedded plastics, which ha…
A peridynamic-informed deep learning model for brittle damage prediction
Roozbeh Eghbalpoor, Azadeh Sheidaei
In this study, a novel approach that combines the principles of peridynamic (PD) theory with PINN is presented to predict quasi-static damage and crack propagation in brittle mater…
Linking Properties to Microstructure in Liquid Metal Embedded Elastomers via Machine Learning
Abhijith Thoopul Anantharanga, Mohammad Saber Hashemi, Azadeh Sheidaei
Liquid metals (LM) are embedded in an elastomer matrix to obtain soft composites with unique thermal, dielectric, and mechanical properties. They have applications in soft robotics…