Flexible, self-healing, and degradable polymeric dielectrics cross-linked through metal–ligand for resistive memory device
Source abstract
Abstract
Abstract The ability to self-heal is a crucial feature in nature, where living organisms can repair themselves when subjected to minor injuries. With an increasing emphasis on environmental sustainability, the concept of biomimetic self-healing polymeric materials has emerged as a prominent trend, promising to significantly extend the lifespan and reliability of products. Studies have shown that one-third of proteins in living organisms require metal cofactors to function properly. It is known that protein-metal interactions can enhance the performance of certain biomaterials, and different choices of metals and ligands can create diverse material properties, influencing characteristics such as hardness, toughness, adhesion, and self-healing abilities. Gelatin is a natural polymer derived from the hydrolysis of collagen, and its unique amino acid structure has led to a wide range of applications. In this research, by introducing aluminum ions that form metal coordination complexes with the carboxyl groups in gelatin, an elastic network with self-healing properties was constructed. This gelatin-based material was utilized as an insulating layer in resistive switching devices. Furthermore, by employing a gelatin substrate of the same composition, the device demonstrated strong interfacial adhesion. The device based on the self-healing gelatin film exhibited excellent electrical performance and mechanical properties. Even after self-healing, it maintained a high ON/OFF ratio of up to 105 and a concentrated distribution of switching parameters. Supported by compelling physical and electrical evidence, this study showcases significant development opportunities for biomimetic materials in green electronic devices.
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Research context
OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Polymer composites and self-healing · Conducting polymers and applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (19)
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