Effect of iron nitrate modification on elimination of organic matter from landfill leachate by sludge-based activated carbon.

Sludge-based activated carbons (SACs) prepared from sewage sludge and corn straw, were modified by ferric nitrate, and the unmodified SAC and modified SAC were used as the adsorbing agent to treat the landfill leachate, the elimination capacity for chemical oxygen demand (COD) and organic matter in leachate were studied. Based on this, the physicochemical properties of SACs and the components changes in leachate were analyzed and characterized by X-ray photoelectron spectroscopy and three-dimensional fluorescence spectroscopy. The results showed that under optimal experimental conditions, the elimination capacities of SAC372 for COD, biological oxygen demand over 5 days, and NH4+-N in the leachate were 81.58%, 54.73%, and 69.08%, respectively; while the adsorption capacities of modified SAC for these three substances were 86.25%, 63.51%, and 79.15%, respectively. The ferric nitrate modification improved the ability of SAC to eliminate COD and organic matter from leachate slightly, and made the adsorption occurred easily. The adsorption process of unmodified SAC was dominated by multi-layer adsorption, while the adsorption process of modified SAC was dominated by monolayer adsorption. The mass fraction of Fe (2p) in modified SAC remarkably increased, from 0.70% to 26.01%, organic functional groups certain phase of Fe oxides with different valence states were generated in SAC, which provided a substrate for iron-carbon micro electrolysis. After adsorbed by unmodified SAC and modified SAC adsorption, the total fluorescence intensity of in the leachate increased by 17.01% and 116.84%, respectively. Both two SACs could decompose the humic acid-like substances into aromatic protein organic compounds, and modified SAC could further decompose the soluble microbial byproduct-like substances.

Optical analog computing of spatial differentiation and edge detection with dielectric metasurfaces.

We propose and demonstrate that optical analog computing of spatial differentiation and edge detection can be realized with a single layer of dielectric metasurface. The optical transfer function for second-order derivation is obtained by engineering the spatial dispersion of electric dipole resonance supported by the silicon nanodisks in the metasurface. Benefiting from this unique mechanism of electric dipole resonance, spatial differentiation can be performed for two dimensions and arbitrary polarization with a large spatial bandwidth and high efficiency at the visible wavelength. Explicitly, we have numerically validated the application with one-dimensional spatial functions as well as an image, and the results show excellent performance. Our study can facilitate the research of optical computing with artificial nanostructures.

Investigation on the relationship between the fine particle emission and crystallization characteristics of gypsum during wet flue gas desulfurization process.

The relationship between the fine particles emitted after desulfurization and gypsum crystals in the desulfurization slurry was investigated, and the crystallization characteristics varying with the operation parameters and compositions of the desulfurization slurry were discussed. The results showed that the fine particles generated during the desulfurization process were closely related to the crystal characteristics in the desulfurization slurry by comparison of their morphology and elements. With the higher proportion of fine crystals in the desulfurization slurry, the number concentration of fine particles after desulfurization was increased and their particle sizes were smaller, indicating that the optimization of gypsum crystallization was beneficial for the reduction of the fine particle emission. The lower pH value and an optimal temperature of the desulfurization slurry were beneficial to restrain the generation of fine crystals in the desulfurization slurry. In addition, the higher concentrations of the Fe3+ ions and the F- ions in the desulfurization slurry both promoted the generation of fine crystals with corresponding change of the morphology and the effect of the Fe3+ ions was more obvious. With the application of the desulfurization synergist additive, it was beneficial for the inhibition of fine crystals while the thinner crystals were generated.

Development and Application of Traditional Chinese Medicine Using AI Machine Learning and Deep Learning Strategies.

Traditional Chinese medicine (TCM) has been used for thousands of years and has been proven to be effective at treating many complicated illnesses with minimal side effects. The application and advancement of TCM are, however, constrained by the absence of objective measuring standards due to its relatively abstract diagnostic methods and syndrome differentiation theories. Ongoing developments in machine learning (ML) and deep learning (DL), specifically in computer vision (CV) and natural language processing (NLP), offer novel opportunities to modernize TCM by exploring the profound connotations of its theory. This review begins with an overview of the ML and DL methods employed in TCM; this is followed by practical instances of these applications. Furthermore, extensive discussions emphasize the mature integration of ML and DL in TCM, such as tongue diagnosis, pulse diagnosis, and syndrome differentiation treatment, highlighting their early successful application in the TCM field. Finally, this study validates the accomplishments and addresses the problems and challenges posed by the application and development of TCM powered by ML and DL. As ML and DL techniques continue to evolve, modern technology will spark new advances in TCM.

A review of dielectric optical metasurfaces for spatial differentiation and edge detection.

Dielectric metasurfaces-based planar optical spatial differentiator and edge detection have recently been proposed to play an important role in the parallel and fast image processing technology. With the development of dielectric metasurfaces of different geometries and resonance mechanisms, diverse on-chip spatial differentiators have been proposed by tailoring the dispersion characteristics of subwavelength structures. This review focuses on the basic principles and characteristic parameters of dielectric metasurfaces as first- and second-order spatial differentiators realized via the Green's function approach. The spatial bandwidth and polarization dependence are emphasized as key properties by comparing the optical transfer functions of metasurfaces for different incident wavevectors and polarizations. To present the operational capabilities of a two-dimensional spatial differentiator in image information acquisition, edge detection is described to illustrate the practicability of the device. As an application example, experimental demonstrations of edge detection for different biological cells and a flower mold are discussed, in which a spatial differentiator and objective lens or camera are integrated in three optical pathway configurations. The realization of spatial differentiators and edge detection with dielectric metasurfaces provides new opportunities for ultrafast information identification in biological imaging and machine vision.

Adsorption of dissolved organic matter from landfill leachate using activated carbon prepared from sewage sludge and cabbage by ZnCl2.

Sewage sludge and cabbage (Brassica oleracea) were used to prepare activated carbon by high-temperature inert carbonization with the activator ZnCl2. The physicochemical characteristics of the sludge-based activated carbon (SAC) were analyzed, and the effects on the removal of chemical oxygen demand (COD) from the landfill leachate by the adsorbent dosage, adsorption time, and the solution pH were investigated in different adsorbents. Three-dimensional fluorescence spectroscopy and gas chromatography-mass spectrometry were used to analyze the organic compounds in the leachate before and after adsorption. The results demonstrated that the average iodine content of the SAC was 535.01 mg/g. The average specific surface area was 917.72 m2/g, and the dominant pore size was in the mesoporous range. The optimum parameters for adsorption were a dosage of 3%, adsorption time of 60 min, and pH = 8, and the COD removal rate reached 85.61%. The adsorption of COD on the SAC was best fitted by the Freundlich model. Additionally, the SAC was found to have a high removal efficiency for refractory organic matter and short-chain alkanes, such as humic acid-like substances, in the leachate but was not effective for long-chain alkanes.

Removal characteristics of sulfuric acid aerosols from coal-fired power plants.

With increasing attention on sulfuric acid emission, investigations on the removal characteristics of sulfuric acid aerosols by the limestone gypsum wet flue gas desulfurization (WFGD) system and the wet electrostatic precipitator (WESP) were carried out in two coal-fired power plants, and the effects of the WFGD scrubber type and the flue gas characteristics were discussed. The results showed that it was necessary to install the WESP device after desulfurization, as the WFGD system was inefficient to remove sulfuric acid aerosols from the flue gas. The removal efficiency of sulfuric acid aerosols in the WFGD system with double scrubbers ranged from 50% to 65%, which was higher than that with a single scrubber, ranging from 30% to 40%. Furthermore, the removal efficiency of WESP on the sulfuric acid aerosols was from 47.9% to 52.4%. With increased concentrations of SO3 and particles in the flue gas, the removal efficiencies of the WFGD and the WESP on the sulfuric acid aerosols were increased. IMPLICATIONS: Investigations on removal of sulfuric acid aerosols by the WFGD and the WESP in the power plants were aimed at the control of sulfuric acid emission. The results showed that the improvement of the WFGD system was beneficial for the reduction of sulfuric acid emission, while the WESP system was essential to control the final sulfuric acid aerosol concentration.