Additive Manufacturing of Shape Memory Materials: Techniques, Characterization, Modeling and Applications

Additive Manufacturing of Shape Memory Materials: Techniques, Characterization, Modeling, and Applications outlines an array of techniques and applications for additive manufacturing (AM) and the use of various shape memory materials, covering corrosion properties, material sensitivity to thermal, magnetic, and electrical effects, as well as sensitivity of shape memory properties to AM parameters, including part geometry effects and post-process treatments.

Design for AM and a number of different AM methods are discussed, with materials covered including shape memory alloys, shape memory polymers, high-temperature shape memory alloys, and magnetic shape memory alloys. Characterization and modeling methods are also included, as is a chapter dedicated to real-world applications of these production techniques and materials.

• Provides an overview of various shape memory materials, their additive manufacturing techniques and processes, their applications, and opportunities and challenges related to their production and use
• Outlines the thermomechanical and functional properties of shape memory alloys that can be applied to their additive manufacturing processes
• Covers techniques for additive manufacturing of shape memory polymers, shape memory alloys, high-temperature shape memory alloys, and magnetic shape memory alloys
• Discusses characterization, post-processing, modeling, and applications of shape memory materials

Mehrshad Mehrpouya earned his Ph.D. degree through a fellowship program from Sapienza University of Rome, Italy. He is currently an Assistant Professor in the Department of Design, Production, and Management (DPM) at the University of Twente (UT). His research interests are directed toward Advanced Manufacturing, 3D/4D Printing, Functional Materials, and modeling.

Mohammad Elahinia is currently a Professor of Mechanical, Industrial and Manufacturing Engineering (MIME) and also serves as Director of the Dynamic and Smart Systems Laboratory at University of Toledo, where has been a faculty member since 2004. He graduated from Villanova University with an MS degree and from Virginia Tech with a Ph.D. in Mechanical Engineering respectively in 2001 and 2004. Dr. Elahinia’s research interests are in smart and active materials. His current research is focused on additive manufacturing of functional materials such as shape memory alloys for aerospace and biomedical application.