A novel approach for the quantification of scratch healing of polymers. (October 2020)

• Record Type: Journal Article
• Authors: Abend, Marcus; Tianis, Lukas; Kunz, Clemens; Zechel, Stefan; Gräf, Stephan; Müller, Frank A.; Schubert, Ulrich S.; Hager, Martin D.
• Is Part Of: Polymer testing. Volume 90(2020)
• Publication Date: 2020-10
• Subjects: Self-healing polymers -- Quantification of self-healing -- Laser-scanning microscopy; Polymers -- Testing -- Periodicals; Polymères -- Tests -- Périodiques; 620.1920287
• DOI: 10.1016/j.polymertesting.2020.106699
• Languages: English
• ISSNs: 0142-9418

Abstract

Abstract: Self-healing polymers based on the novel damage management concept were introduced several years ago. Since then different concepts have been successfully developed. However, the analysis and characterization of the self-healing process represents still a significant challenge, in particular for the quantification of scratch healing. Consequently, the comparability of the reported healing efficiencies of different polymers (materials) is often not provided. Within the variety of different characterization methods, different parameters like defect-area, length and width are utilized for the determination of the healing efficiency; however, the precise quantification is still problematic. For this reason, the present study focuses on two different methods, the mechanical analysis with the scratch tester MST 3 and the optical analysis using laser scanning microscopy (LSM). For this purpose, a previously reported metallopolymer was damaged mechanically with an indenter and optically with a laser, respectively. Both types of defects were analyzed with the two characterization methods. By this manner, 3D images of the defects could also be obtained. The step-wise healing enabled a detailed analysis of the healing behavior of the polymer. Noteworthy, the optical analysis provided a high comparability enabling a precise quantification of the self-healing efficiency. The user-independent evaluation is crucial. As a consequence, a MATLAB® script was developed, which processes the data of the LSM measurements. Hereby, the data set and the microscope image are processed simultaneously and provide a combined result leading finally to the visualization (3D image) and quantification of the healing process. Highlights: Quantification of the scratch healing of self-healing metallopolymers by two methods. Generation of uniform and reproducible defect structures. Detailed 3D images of the scratches. MATLAB program to evaluate the scratches and the healing processes. Automatic (user-independent) method to determine the healing efficiency.