Session: Research Posters

Paper Number: 114108

114108 - Heterogeneous Self-Healing Mechanisms of Metals at Nano-Scale 

Demand for metallic materials is rising steadily, especially in load-bearing applications in important sectors such as construction, transportation, machining and energy. As they provide wide range of mechanical properties; moduli ranging from 30 to 450 GPa, tensile strength values ranging from 10 to 3000 MPa, failure strains ranging from 0.2 to 5000%, operating temperatures ranging from −273 °C to over 2500 °C.

Nervertheless, voids and nano-cracks have been known as the source to initiate failure and degrade the material properties. Hence, preventing these defects to grow, and rather to heal, is imperative for enhancing the lifespan of the materials.                   Self-healing is defined as the ability of a material to spontaneously heal/ recover/ repair its damages, unlike conventional materials, self-healing materials show a  negative rate of damage formation during lifetime. Self-healing is shown to have positive effects on mechanical, chemical and physical properties of materials. Metals' ability to self-healed has recently gained much interest as compared to self-healed composites, self-healed polymers and self-healed concrete. However in metals, healing is more challenging because of their low atomic mobility due to high melting temperatures which requires higher energy.

There are various approaches of self-healing in metals, which can be categorized into two main categories: 1) autonomous healing methods that depend on intrinsic mechanisms, and 2) assisted healing methods that depend on external stimulus such as temperature or stresses.

On the other side, computational approaches have been commonly used to study self-healing, they either focus on healing micro-cracks using finite element model calculations, or healing nano-scale cracks or voids using atomistic models by molecular dynamics(MD) approaches.

In this study, we present a numerical approach to study self-healing potential of materials at the atomic level with the aid of Molecular Dynamics. We uncover the diverse healing mechanisms exhibited by different materials based on their unique characteristics. For instance, pure metals exhibit healing ability when subjected to shear, which is attributed to dislocation slip. In contrast, metallic alloys exhibit healing ability through vacancy diffusion aided by the compressive stress field of interstitial atoms. In addition, we analyze the effect of volume change resulting from phase transformation in Shape Memory Alloys (SMAs), in specific NiTi, which facilitates its self-healing ability. Additionally, self-healing has been addressed in thin-films where both interface stresses and temperature can introduce self healing capabilities. 

Furthermore, Machine-learning algorithms are used to optimize self-healing conditions such as composition and temperature. This study not only enhances our understanding of the self-healing behavior in various metals but also opens up new and exciting avenues for future research in designing self-healing materials with superior properties.

Presenting Author: Tarek Hatem University of Nevada, Las Vegas

Presenting Author Biography: Mohamed Ibrahim

Authors:

Mohamed Ibrahim Cairo University
Ahmed Shaker The British University in Egypt
Abdulrahman Rabea Muhammad Cairo University
Iman El-Mahallawi Cairo University
Tarek Hatem University of Nevada, Las Vegas