Yevgeny Rakita

Sustainability of energy conversion materials depends on their functional resilience. Such can be achieved by self-healing, SH, which requires mass transfer inside the material. Unfortunately, we lack guidelines as to which physical and chemical material properties can help predict if a material can self-heal and how. We report a data-driven approach to find such properties, using experimental and computational data from materials databases. We focus on four properties: optical deformation potential (ODP), relative structural polarization (RSP), ionicity, and hardness to distinguish SH materials from others. ODP with RSP predict the two main SH mechanisms in semiconductors: mass transfer of kinetically stabilized (class I) or thermodynamically stabilized (class II) defects. In crystals with covalent bonding, the correlation of hardness with ionicity & RSP emphasizes effects of the nature of the chemical bonding on the SH mechanism. Our approach and results present first steps to find SH materials, especially for energy conversion.