Modeling the nanoscratching of self-healing materials

An Overview of Self-Healable Polymers and Recent Advances in the Field

The search for materials with better performance, longer service life, lower environmental impact, and lower overall cost is at the forefront of polymer science and material engineering. This has led to the development of self-healing polymers with a range of healing mechanisms including capsular-based, vascular, and intrinsic self-healing polymers. The development of self-healable systems has been inspired by the healing of biological systems such as skin wound healing and broken bone reconstruction. The goal of using self-healing polymers in various applications is to extend the service life of polymers without the need for replacement or human intervention especially in restricted access areas such as underwater/underground piping where inspection, intervention, and maintenance are very difficult. Through an industrial and scholarly lens, this paper provides (a) an overview of self-healing polymers, (b) classification of different self-healing polymers and polymer-based composites, (c) mechanical, thermal, and electrical analysis characterization, (d) applications in coating, composites, and electronics, (e) modeling and simulation, and (f) recent development in the past 20 years . This review highlights the importance of healable polymers for an economically and environmentally sustainable future, the most recent advances in the field, and current limitations in fabrication, manufacturing, and performance. This article is protected by copyright. All rights reserved.

An Analytic Model of Tissue Self-Healing and Its Network Implementation: Application to Fibrosis and Aging

Here we present a model capable of self-healing and explore its ability to resolve pathological alterations in biological tissue. We derive a simple analytic model consisting of an agent representing a cell that exhibits anabolic or catabolic activity, and which interacts with its tissue substrate according to tissue stiffness. When perturbed, this system returns toward a stable fixed point, a process corresponding to self-healing. We implemented this agent-substrate mechanism numerically on a hexagonal elastic network representing biological tissue. Agents, representing fibroblasts, were placed on the network and allowed to migrate around while they remodeled the network elements according to their activity which was determined by the stiffnesses of network elements that each agent encountered during its random walk. Initial injury to the network was simulated by increasing the stiffness of a single central network element above baseline. This system also exhibits a fixed point represented by the uniform baseline state. During the approach to the fixed point, interactions between the agents and the network create a transient spatially extended halo of stiffer network elements around the site of initial injury, which aids in overall injury repair. Non-equilibrium constraints generated by persistent injury prohibit the network to return to baseline and results in progressive stiffening, mimicking the development of fibrosis. Additionally, reducing anabolic or catabolic rates delay self-healing, reminiscent of aging. Our model thus embodies what may be the simplest set of attributes required of a spatiotemporal self-healing system, and so may help understand altered self-healing in chronic fibrotic diseases and aging.

Modeling Self-Healing Mechanisms in Coatings: Approaches and Perspectives

There is a wide range of self-healing mechanisms that provide the recovery of specific functionalities in coatings. Moreover, it is well known that computational simulation is a complementary tool that can help in the optimization and cost reduction of the experimental development of materials. This work critically discusses the current status of the models that are of interest for the advance of self-healing coatings, and proposes future paths of improvement.

Designing silk-silk protein alloy materials for biomedical applications

Fibrous proteins display different sequences and structures that have been used for various applications in biomedical fields such as biosensors, nanomedicine, tissue regeneration, and drug delivery. Designing materials based on the molecular-scale interactions between these proteins will help generate new multifunctional protein alloy biomaterials with tunable properties. Such alloy material systems also provide advantages in comparison to traditional synthetic polymers due to the materials biodegradability, biocompatibility, and tenability in the body. This article used the protein blends of wild tussah silk (Antheraea pernyi) and domestic mulberry silk (Bombyx mori) as an example to provide useful protocols regarding these topics, including how to predict protein-protein interactions by computational methods, how to produce protein alloy solutions, how to verify alloy systems by thermal analysis, and how to fabricate variable alloy materials including optical materials with diffraction gratings, electric materials with circuits coatings, and pharmaceutical materials for drug release and delivery. These methods can provide important information for designing the next generation multifunctional biomaterials based on different protein alloys.