activity
20202024
most citedA Supervised Machine Learning Approach for Accelerating the Design of Particulate Composites: Application to Thermal Conductivity

38 citations · 78 across the 6 of their papers we have counts for

collaborators

6 papers

cond-mat.mtrl-sci2024★ 3 cited

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…

eess.IV2023

Predicting Bone Degradation Using Vision Transformer and Synthetic Cellular Microstructures Dataset

Mohammad Saber Hashemi, Azadeh Sheidaei

Bone degradation, especially for astronauts in microgravity conditions, is crucial for space exploration missions since the lower applied external forces accelerate the diminution…

cond-mat.mtrl-sci2023

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…

cond-mat.mtrl-sci2022★ 9 cited

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…

physics.comp-ph2020★ 38 cited

A Supervised Machine Learning Approach for Accelerating the Design of Particulate Composites: Application to Thermal Conductivity

Mohammad Saber Hashemi, Masoud Safdari, Azadeh Sheidaei

A supervised machine learning (ML) based computational methodology for the design of particulate multifunctional composite materials with desired thermal conductivity (TC) is prese…

physics.app-ph2020★ 28 cited

Optimum Design of Printable Tunable Stiffness Metamaterial for Bone Healing

Mohammad Saber Hashemi, Karl H. Kraus, Azadeh Sheidae

A tunable stiffness bone rod was designed, optimized, and 3D printed to address the common shortcomings of existing bone rods in the healing of long fractured bones. The common def…