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Literature Review: Self-healing problem for Materials
This “Ten Problems for Materials in the 2020s” booklet identifies ten relevant areas from very recent contributions put forward at academic level in the form journal articles, conference proceedings and students theses. Ten freely accessible internet references have been selected for each area and direct links are provided at the end of each chapter for own consultation. Our selected references do not intend to mirror ranking indexes nor establish novel classifications. On the contrary, they are meant to represent peer-reviewed, diverse and scientifically-sound case studies for vertical dissemination aimed at non-specialist readers. They will also be able to scoop even more references through the bibliography that is reported at the end of each selected reference.
Without further ado, these are the ten problems that we are going to introduce in this booklet:
Each problem has its own dedicated chapter made of an introductory section, a short presentation of the ten selected references and a conclusions section.
The final chapter of this booklet will report the conclusions from each chapter again in order to provide a complete executive summary.
THE PROBLEM — Self-healing materials exhibit adaptive capabilities to external stimuli, such as physical, mechanical or chemical changes in their environment. On the whole, the vast majority of research deals with polymer composites and cementitious materials. Metals, ceramics and biomaterials are also under investigation.
CASE STUDIES — … buy this booklet from Amazon …
CONCLUSIONS — In the last several years, various methods have been developed to produce self-healing materials but can overall be grouped into two categories: induced and autonomous healing. Two sets of metrics for technical self-healing and environmental sustainability of immortal products can converge and be potentially explored as one model. The knowledge of basic principle of solid state diffusion is essential for understanding the self-repair processes, such as phase transformation, precipitation and shape memory effects taking place in titanium and other alloys. Three typical machine learning methods, namely regression, classification, and ensemble, can be employed to predict self-healing efficiency. Self healing requires the tunability of the healing response or controlling variables such as the repair time, the properties of the resulting repaired system, and how much of the material is healed. In terms of reversibility, the majority of healing substances are classified as thermoplastic. Self-healing injectable hydrogel biomaterials uniquely enable precise therapeutic deposition and deployment at specific bodily locations through versatile and minimally invasive processes that can preserve cargo integrity and cell viability. In laboratory studies, self-sensing materials have shown excellent mechanical property and durability, long service life, as well as easy installation and maintenance. Through mechanical properties tests, a waterborne polyurethane films exhibit higher self-healing properties, its self-healing efficiency can reach to 80%.
TEN FREE REFERENCES FROM THE INTERNET — … buy this booklet from Amazon …