Revealing the Combined Effect of Active Sites and Intra-Particle Diffusion on Adsorption Mechanism of Methylene Blue on Activated Red-Pulp Pomelo Peel Biochar.

Phosphoric acid-activated biochar has been proven to be a promising adsorbent for pollutant removal in an aqueous solution. It is urgent to understand how surface adsorption and intra-particle diffusion synergistically contribute to the adsorption kinetic process of dyes. In this work, we prepared a series of PPC adsorbents (PPCs) from red-pulp pomelo peel under different pyrolysis temperatures (150-350 °C), which have a broad specific surface area range from 3.065 m2/g to 1274.577 m2/g. The active sites on the surface of PPCs have shown specific change laws of decreasing hydroxyl groups and increasing phosphate ester groups occurring as the pyrolysis temperature rises. Both reaction models (PFO and PSO models) and diffusion models (intra-particle diffusion models) have been applied to simulate the adsorption experimental data to verify the hypothesis deduced from the Elovich model. PPC-300 exhibits the highest adsorption capacity of MB (423 mg/g) under given conditions. Due to its large quantities of active sites on the external and internal surfaces (1274.577 m2/g), a fast adsorption equilibrium can be achieved within 60 min (with an initial MB concentration of 100 ppm). PPC-300 and PPC-350 also exhibit an intra-particle-diffusion-controlled adsorption kinetic process with a low initial MB concentration (100 ppm) or at the very beginning and final stage of adsorption with a high initial MB concentration (300 ppm) at 40 °C, considering that the diffusion is likely hindered by adsorbate molecules through internal pore channels at the middle stage of adsorption in these cases.

Fast compressive beamforming with a modified fast iterative shrinkage-thresholding algorithm.

Compressive beamforming has been successfully applied to direction-of-arrival estimation with sensor arrays. The results demonstrated that this technique achieves superior performance when compared with traditional high-resolution beamforming methods. The existing compressive beamforming methods use classical iterative optimization algorithms in their compressive sensing theories. However, the computational complexity of the existing compressive beamforming methods tend to be excessively high, which has limited the use of compressive beamforming in applications with limited computing resources. To address this issue, this paper proposes a fast compressive beamforming method which combines the shift-invariance of the array beam patterns with a fast iterative shrinkage-thresholding algorithm. The evaluation shows that the proposed fast compressive beamforming method successfully reduces the number of floating-point operations by 3 orders of magnitude when compared with the existing methods. In addition, both the simulations and experiments demonstrate that the resolution limit for discerning closely spaced sources of the introduced fast method is comparable to those of the existing compressive beamforming methods, which use classical iterative optimization algorithms.