A substantial quantity of discarded tires has inflicted harm on the environment. Microwave pyrolysis of discarded tires emerges as an efficient and environmentally friendly method for their recycling. This research innovatively utilizes the characteristics of microwave rapid and selective heating to pyrolyze waste tires into porous graphene under the catalysis of KOH etching. Moreover, this study comprehensively investigates the dielectric characteristics and heating behavior of waste tires and different proportions of waste tire–KOH mixtures. It validates the preparation of graphene through KOH-catalyzed microwave pyrolysis of waste tires, tracking morphological and structural changes under varying temperature conditions. The results indicate that optimal dielectric performance of the material is achieved at an apparent density of 0.68 g/cm3 at room temperature. As the temperature increases, the dielectric constant gradually rises, particularly reaching a notable increase around 700 °C, and then stabilizes around 750 °C. Additionally, the study investigates the penetration depth and reflection loss of mixtures with different proportions, revealing the waste tire–KOH mass ratio of 1:2 demonstrates favorable dielectric properties. This research highlights the impressive microwave responsiveness of the waste tire–KOH mixture, Upon the addition of KOH, the mixed material exhibits an augmented dielectric constant and relative dielectric constant, supporting the viability of KOH-catalyzed microwave pyrolysis for producing porous graphene from waste tires. This method is expected to provide a new method for the valuable reuse of waste tires and a technology for large-scale, efficient and environmentally friendly production of graphene.

Full-disk solar images are provided by many solar telescopes around the world. However, the ob- served images show Non-Radial Variation (NRV) over the disk. In this paper, we propose algorithms for detecting distortions and restoring these images. For detecting NRV, the cross-correlation coefficients matrix of radial profiles is calculated and the minimum value in the matrix is defined as the Index of Non-radial Variation (INV). This index has been utilized to evaluate the H images of GONG, and systemic variations of different instruments are obtained. For obtaining the NRV’s image, a Multi-level Morphological Filter (MMF) is designed to eliminate structures produced by solar activities over the solar surface. Comparing with the median filter, the proposed filter is a better choice. The experimental results show that the effect of our automatic detection and restoration methods is significant for getting a flat and high contrast full-disk image. For investigating the effect of our method on solar features, structural similarity (SSIM) index is utilized. The high SSIM indices (close to 1) of solar features show that the details of the structures remain after NRV restoring.