Thermodynamics of dye adsorption on electrochemically exfoliated graphene

Graphene sheets prepared by electrochemical exfoliation have been used for the adsorption of methylene blue (MB), a cationic dye from aqueous solution. The maximum adsorbed amount of MB on exfoliated graphene (EG) reaches 511.7 mg g(-1) when the initial concentration of MB is 500 mg L-1, with EG whose dosage is 10 mg. Further study on the adsorption mechanism of EG includes isothermal adsorption equilibrium, thermodynamics, and kinetics. The study on isothermal adsorption equilibrium shows that the adsorption follows the Langmuir isotherm. Various thermodynamic parameters such as Gibbs free energy (Delta G(0)), enthalpy (Delta H-0), and entropy (Delta S-0) change were also evaluated. It indicates that the adsorption is a spontaneous, endothermic, and physical adsorption process. The kinetic data reveals that the adsorption process of MB fits well with the pseudo second-order model. The Weber&#39;s intra-particle diffusion model demonstrates that the adsorption rate is controlled by both external diffusion and intra-particle diffusion. EG as a cationic dye scavenger displays high speed and efficiency.</p

Fusion algorithm of visible and infrared image based on anisotropic diffusion and image enhancement (capitalize only the first word in a title (or heading), the first word in a subtitle (or subheading), and any proper nouns).

Aiming at the situation that the existing visible and infrared images fusion algorithms only focus on highlighting infrared targets and neglect the performance of image details, and cannot take into account the characteristics of infrared and visible images, this paper proposes an image enhancement fusion algorithm combining Karhunen-Loeve transform and Laplacian pyramid fusion. The detail layer of the source image is obtained by anisotropic diffusion to get more abundant texture information. The infrared images adopt adaptive histogram partition and brightness correction enhancement algorithm to highlight thermal radiation targets. A novel power function enhancement algorithm that simulates illumination is proposed for visible images to improve the contrast of visible images and facilitate human observation. In order to improve the fusion quality of images, the source image and the enhanced images are transformed by Karhunen-Loeve to form new visible and infrared images. Laplacian pyramid fusion is performed on the new visible and infrared images, and superimposed with the detail layer images to obtain the fusion result. Experimental results show that the method in this paper is superior to several representative image fusion algorithms in subjective visual effects on public data sets. In terms of objective evaluation, the fusion result performed well on the 8 evaluation indicators, and its own quality was high