Adsorption of Phosphate from Aqueous Solution Using an Iron-Zirconium Binary Oxide Sorbent

In this study, an iron-zirconium binary oxide with a molar ratio of 4:1 was synthesized by a simple coprecipitation process for removal of phosphate from water. The effects of contact time, initial concentration of phosphate solution, temperature, pH of solution, and ionic strength on the efficiency of phosphate removal were investigated. The adsorption data fitted well to the Langmuir model with the maximum P adsorption capacity estimated of 24.9 mg P/g at pH 8.5 and 33.4 mg P/g at pH 5.5. The phosphate adsorption was pH dependent, decreasing with an increase in pH value. The presence of Cl-, SO (4) (2-) , and CO (3) (2-) had little adverse effect on phosphate removal. A desorbability of approximately 53 % was observed with 0.5 M NaOH, indicating a relatively strong bonding between the adsorbed PO (4) (3-) and the sorptive sites on the surface of the adsorbent. The phosphate uptake was mainly achieved through the replacement of surface hydroxyl groups by the phosphate species and formation of inner-sphere surface complexes at the water/oxide interface. Due to its relatively high adsorption capacity, high selectivity and low cost, this Fe-Zr binary oxide is a very promising candidate for the removal of phosphate ions from wastewater

A novel integrated method of detection-grasping for specific object based on the box coordinate matching

To better care for the elderly and disabled, it is essential for service robots to have an effective fusion method of object detection and grasp estimation. However, limited research has been observed on the combination of object detection and grasp estimation. To overcome this technical difficulty, a novel integrated method of detection-grasping for specific object based on the box coordinate matching is proposed in this paper. Firstly, the SOLOv2 instance segmentation model is improved by adding channel attention module (CAM) and spatial attention module (SAM). Then, the atrous spatial pyramid pooling (ASPP) and CAM are added to the generative residual convolutional neural network (GR-CNN) model to optimize grasp estimation. Furthermore, a detection-grasping integrated algorithm based on box coordinate matching (DG-BCM) is proposed to obtain the fusion model of object detection and grasp estimation. For verification, experiments on object detection and grasp estimation are conducted separately to verify the superiority of improved models. Additionally, grasping tasks for several specific objects are implemented on a simulation platform, demonstrating the feasibility and effectiveness of DG-BCM algorithm proposed in this paper

Analysis of Wind Pressure Coefficients for Single-Span Arched Plastic Greenhouses Located in a Valley Region Using CFD

The wind pressure coefficient is essential for calculating the wind loads on greenhouses. The wind pressure on single-span arched greenhouses built in valleys differs from those in plain regions. To promote our understanding of wind characteristics and ensure the structural safety of greenhouses in valley areas, an analysis of the distribution law of wind pressure on greenhouses is required. Firstly, we carried out a survey on greenhouse distribution and undulate terrain distribution near greenhouses in Tibet and measured the air density in Lhasa, Tibet. Then, employing the validated realizable k-ε turbulence model and the verification of grid independence, the wind pressure on greenhouses with different greenhouse azimuths was investigated. According to the survey results, values, such as the distance between the greenhouse and the mountain in addition to the greenhouse azimuth, were also obtained for calculating the wind pressure on greenhouses placed in valleys. A calculation model considering the relationship between the mountain distance and the wind pressure coefficient is proposed, whose results fit well with the results from computational fluid dynamics. The relative errors between the two different results are within 15%. Research shows that there is a canyon wind effect in the valley area, and its effect on wind pressure should be considered in greenhouse design. This research is valuable for the design of plastic greenhouses built in Tibet or other valley regions

Facile Preparation of One-Dimensional Wrapping Structure: Graphene Nanoscroll-Wrapped of Fe₃O₄ Nanoparticles and Its Application for Lithium-Ion Battery

Graphene nanoscroll (GNS) is a spirally wrapped two-dimensional (2D) graphene sheet (GS) with a 1D tubular structure resembling that of a multiwalled carbon nanotube (MWCNT). GNS provide open structure at both ends and interlayer galleries that can be easily intercalated and adjusted, which show great potential applications in energy storage. Here we demonstrate a novel and simple strategy for the large-scale preparation of GNSs wrapping Fe₃O₄ nanoparticles (denoted as Fe₃O₄@GNSs) from graphene oxide (GO) sheets by cold quenching in liquid nitrogen. When a heated aqueous mixed suspension of GO sheets and Fe₃O₄ nanoparticles is immersed in liquid nitrogen, the in-situ wrapping of Fe₃O₄ nanoparticles with GNSs is easily realized. The structural conversion is closely correlated with the initial temperature of mixed suspension, the zeta potential of Fe₃O₄ nanoparticles and the immersion way. Remarkably, such hybrid structure provides the right combination of electrode properties for high-performance lithium-ion batteries. Compared with other wrapping structure, such 1D wrapping structure (GNSs wrapping) effectively limits the volume expansion of Fe₃O₄ nanoparticles during the cycling process, consequently, a high reversible capacity, good rate capability, and excellent cyclic stability are achieved with the material as anode for lithium storage. The results presented here may pave a way for the large-scale preparation of GNS-based materials in electrochemical energy storage applications

Improving the Secretion Yield of the β‑Galactosidase Bgal1‑3 in Pichia pastoris for Use as a Potential Catalyst in the Production of Prebiotic-Enriched Milk

In this study, three kinds of milk were treated with the β-galactosidase Bgal1-3 (4 U/mL), resulting in 7.2–9.5 g/L galactooligosaccharides (GOS) at a lactose conversion of 90–95%. Then, Bgal1-3 was secreted from Pichia pastoris X33 under the direction of an α-factor signal peptide. After cultivation for 144 h in a flask culture with shaking, the extracellular activity of Bgal1-3 was 4.4 U/mL. Five more signal peptides (HFBI, apre, INU1A, MF4I, and W1) were employed to direct the secretion, giving rise to a more efficient signal peptide, W1 (11.2 U/mL). To further improve the secretion yield, recombinant strains harboring two copies of the <i>bgal1-3</i> gene were constructed, improving the extracellular activity to 22.6 U/mL (about 440 mg/L). This study successfully constructed an engineered strain for the production of the β-galactosidase Bgal1-3, which is a promising catalyst in the preparation of prebiotic-enriched milk