Computational Modeling of Intelligent Soft Matter: Shape Memory Polymers and Hydrogels

Computational Modelling of Intelligent Soft Matter: Shape Memory Polymers and Hydrogels explores the multiphysics response of smart polymer materials, including shape memory polymers and hydrogels, and outlines thermo–chemo-mechanical constitutive models for their real-world applications.

Format: Paperback / softback
Length: 382 pages
Publication date: 22 February 2023
Publisher: Elsevier - Health Sciences Division

Computational Modelling of Intelligent Soft Matter: Shape Memory Polymers and Hydrogels delves into the intricate multiphysics response of a diverse range of smart polymer materials, encompassing temperature-sensitive shape memory polymers and temperature/chemosensitive hydrogels. A comprehensive overview of thermo–chemo-mechanical constitutive models for these innovative materials is provided, highlighting their real-world applications. Additionally, the numerical counterparts of each introduced constitutive model are presented, empowering readers to tackle practical problems involving thermomechanical responses of these materials and design and analyze structures constructed from them.

Shape memory polymers (SMPs) are a class of materials that possess the unique ability to remember their original shape upon exposure to a specific stimulus, such as temperature or chemical agents. These materials are composed of a polymer backbone and a shape-memory component, which can be triggered by the aforementioned stimuli. SMPs find applications in various fields, including aerospace, automotive, and medical devices.

One of the key advantages of SMPs is their ability to adapt to changing environmental conditions. For example, they can be used to create deployable structures that can change shape in response to temperature or pressure, allowing them to navigate through different environments. SMPs can also be used in medical devices, such as stents or artificial joints, to mimic the behavior of natural tissues and improve their performance.

Another application of SMPs is in the field of energy storage. SMPs can be used to create energy-storing devices, such as batteries or supercapacitors, that can store and release energy quickly. These devices can be used in electric vehicles, renewable energy systems, and other applications where efficient energy storage is required.

Despite their many advantages, SMPs also face several challenges. One of the main challenges is the development of materials that have a high shape memory effect and a long-term stability. Additionally, SMPs are often sensitive to environmental factors, such as temperature and humidity, which can affect their performance.

To address these challenges, researchers have developed a variety of techniques to improve the performance of SMPs. One of these techniques is the use of additives, such as nanoparticles or fibers, to enhance the material's properties. Another technique is the development of new processing methods, such as 3D printing, to create complex shapes and structures.

In conclusion, shape memory polymers are a promising class of materials that have the potential to revolutionize various industries. Their unique ability to adapt to changing environmental conditions and their potential for energy storage make them an attractive option for a wide range of applications. However, there is still much work to be done to improve the performance and stability of SMPs, and researchers will continue to explore new techniques to achieve this goal.

Weight: 450g
ISBN-13: 9780443194207