Investigation of nickel-impregnated zeolite catalysts for hydrogen/syngas production from the catalytic reforming of waste polyethylene

Catalytic steam reforming of waste high density polyethylene for the production of hydrogen/syngas has been investigated using different zeolite supported nickel catalysts in a two-stage pyrolysis-catalytic steam reforming reactor system. Experiments were conducted into the influence of the type of zeolite where Ni/ZSM5-30, Ni/β-zeolite-25 and the Ni/Y-zeolite-30 catalysts were compared in relation to hydrogen and syngas production. Results showed that the Ni/ZSM5-30 catalyst generated the maximum syngas production of 100.72 mmol g‾¹ plastic , followed by the Ni/β-zeolite-25 and Ni/Y-zeolite-30 catalyst. In addition, the ZSM-5 supported nickel catalyst showed excellent coke resistance and thermal stability. It was found that the Y type zeolite supported nickel catalyst possessed narrower pores than the other catalysts, which in turn, promoted coke deactivation of the catalyst. Large amounts of filamentous carbons were observed on the surface of the Ni/Y-zeolite-30 catalyst from scanning electron microscope images. In addition, the influence of Si:Al molar ratio for the Ni/ZSM-5 catalysts in relation to hydrogen and syngas yield was inv estigated. The results indicated that hydrogen production was less affected by the Si:Al ratio than the type of zeolite support. Also, the Ni/ZSM5-30 catalyst was further investigated to determine the influence of different process parameters on hydrogen and syngas yield via different reforming temperatures (650, 750, 850 °C) and steam feeding rate (0, 3, 6 g h‾¹). It was found that increasing both the temperature and steam feeding rate favoured hydrogen production from the pyrolysis-catalytic reforming of waste polyethylene. The optimum catalytic performance in terms of syngas production was achieved when the steam feeding rate was 6 g h‾¹ and catalyst temperature was 850 °C in the presence of Ni/ZSM5-30 catalyst, with production of 66.09 mmol H 2 g‾¹(plastic) and 34.63 mmol CO gg‾¹(plastic)

Bimetallic carbon nanotube encapsulated Fe-Ni catalysts from fast pyrolysis of waste plastics and their oxygen reduction properties

Carbon-based bimetallic electrocatalysts were obtained by catalytic pyrolysis of waste plastics with Fe-Ni-based catalysts and were used as efficient oxygen reduction reaction (ORR) catalysts in this study. The prepared iron-nickel alloy nanoparticles encapsulated in oxidized carbon nanotubes (FeNi-OCNTs) are solid products with a unique structure. Moreover, the chemical composition and structural features of FeNi-OCNTs were determined. The iron-nickel alloy nanoparticles were wrapped in carbon layers, and the carbon nanotubes had an outer diameter of 20–50 nm and micron-scale lengths. FeNi-OCNT with a Fe/Ni ratio of 1:2 (FeNi-OCNT12) exhibited remarkable electrochemical performance as an ORR catalyst with a positive onset potential of 1.01 V (vs. RHE) and a half-wave potential of 0.87 V (vs. RHE), which were comparable to those of a commercial 20% Pt/C catalyst. Furthermore, FeNi-OCNT12 exhibited promising long‐term stability and higher tolerance to methanol than the commercial 20% Pt/C catalyst in an alkaline medium. These properties were attributable to the protective OCNT coating of the iron-nickel alloy nanoparticles

The oyster genome reveals stress adaptation and complexity of shell formation

The Pacific oyster Crassostrea gigas belongs to one of the most species-rich but genomically poorly explored phyla, the Mollusca. Here we report the sequencing and assembly of the oyster genome using short reads and a fosmid-pooling strategy, along with transcriptomes of development and stress response and the proteome of the shell. The oyster genome is highly polymorphic and rich in repetitive sequences, with some transposable elements still actively shaping variation. Transcriptome studies reveal an extensive set of genes responding to environmental stress. The expansion of genes coding for heat shock protein 70 and inhibitors of apoptosis is probably central to the oyster's adaptation to sessile life in the highly stressful intertidal zone. Our analyses also show that shell formation in molluscs is more complex than currently understood and involves extensive participation of cells and their exosomes. The oyster genome sequence fills a void in our understanding of the Lophotrochozoa. © 2012 Macmillan Publishers Limited. All rights reserved

Upcycling plastic waste into syngas by staged chemical looping gasification with modified Fe-based oxygen carriers

A novel staged approach, termed staged chemical looping gasification (SCLG) was proposed in this work, for the efficient upcycling of plastic waste into H2-rich syngas with exceptional carbon conversion reaching up to 99%. In such staged system, plastic was firstly pyrolyzed to generate hydrocarbon volatiles, followed by chemical looping reforming in the presence of oxygen carriers, and steam and air was also feed in sequence for carbon removal, syngas regulation and lattice oxygen recovery. A series of Fe-M-Al oxygen carriers (OCs, where M represents Mg, Ca, Mn, Mo, La, Ce) were synthesized and employed for SCLG of waste disposable masks. The performance and stability of these OCs were thoroughly investigated and compared in terms of H2 content and syngas production, while the physicochemical properties characterized by various techniques such as N2 isothermal adsorption-desorption, FESEM, XRD, TPO, and H2-TPR. Results showed that compared with the controlled Fesingle bondAl sample, all the six modified OCs exhibited higher activity towards syngas production, due to the simultaneously enhanced both partial oxidation reactions and thermal decomposition reactions during the proposed SCLG process. However, the modifiers displayed different role for promoting gasification. Specifically, the addition of Ca significantly promoted the thermal cracking of plastic pyrolysis volatiles and lead to the deep extraction of carbon and H2, whereas the deposited carbon was further gasified into syngas in steam stage. As a result, Fe-Ca-Al showed the highest syngas yield and carbon conversion of 177.89 mmol/gOC and 99.03%, respectively. Fe-Mg-Al possessed relatively high CO selectivity, with the CO/(CO + CO2) ratio of 90.40%. The presence of MoO3 made the Fe-Mo-Al equipped with strong oxygen supply ability, leading to high content of oxygen-containing gases. Furthermore, the cycle stability of OCs was also conducted. The slight decrease in activity of Fe-Ca-Al was due to the metal sintering, whereas Fe-Mo-Al presented relatively stable syngas yield. The proposed staged chemical looping gasification with modified Fesingle bondAl was demonstrated as a promising upcycling utilization of disposal plastic waste

Experimental development process of similar material of water resisting layer in physical model test

The stability evaluation of water resisting layer in the process of coal mining is the key to study the law of water and soil loss and prevent the loss of water resources. The development and proportioning of similar materials are the basis to study the stability of water resisting layer by physical simulation. A new type of similar material considering water characteristics was developed through orthogonal experiments. The similar material was composed of river sand, bentonite, silicone oil, vaseline, and water. Determine the best test development process. First of all, the proportion test scheme is designed based on the orthogonal test. Then, the influence of cement concentration, mass ratio of silicone oil to vaseline and other components on the density, uniaxial compressive strength, elastic model and Poisson’s ratio of similar materials was analyzed by range analysis. Finally, the multiple linear regression equation between the parameters and the composition of similar materials for water resisting layer is obtained, and the optimal composition ratio is further determined according to the relationship between the test influencing factors and the mechanical properties of similar materials. The results show that the selected raw materials and their proportioning method are feasible. The content of river sand plays a major role in controlling the density and Poisson’s ratio of similar materials. The mass ratio of aggregate to binder is the main factor affecting the uniaxial compressive strength and elastic modulus of similar materials, while the cementing concentration has the second largest influence on the density, uniaxial compressive strength, elastic modulus and Poisson’s ratio of similar materials. Determining the cementing concentration that matches the design of similar material model tests is critical to improving test accuracy and provides a reference for the preparation of similar materials for water resisting layer under different requirements during the development of similar materials

Security Service Function Chain Based on Graph Neural Network

With the rapid development and wide application of cloud computing, security protection in cloud environment has become an urgent problem to be solved. However, traditional security service equipment is closely coupled with the network topology, so it is difficult to upgrade and expand the security service, which cannot change with the change of network application security requirements. Building a security service function chain (SSFC) makes the deployment of security service functions more dynamic and scalable. Based on a software defined network (SDN) and network function virtualization (NFV) environment, this paper proposes a solution to the particularity optimization algorithm of network topology feature extraction using graph neural network. The experimental results show that, compared with the shortest path, greedy algorithm and hybrid bee colony algorithm, the average success rate of the graph neural network algorithm in the construction of the security service function chain is more than 90%, far more than other algorithms, and far less than other algorithms in construction time. It effectively reduces the end-to-end delay and increases the network throughput

Security Service Function Chain Based on Graph Neural Network

With the rapid development and wide application of cloud computing, security protection in cloud environment has become an urgent problem to be solved. However, traditional security service equipment is closely coupled with the network topology, so it is difficult to upgrade and expand the security service, which cannot change with the change of network application security requirements. Building a security service function chain (SSFC) makes the deployment of security service functions more dynamic and scalable. Based on a software defined network (SDN) and network function virtualization (NFV) environment, this paper proposes a solution to the particularity optimization algorithm of network topology feature extraction using graph neural network. The experimental results show that, compared with the shortest path, greedy algorithm and hybrid bee colony algorithm, the average success rate of the graph neural network algorithm in the construction of the security service function chain is more than 90%, far more than other algorithms, and far less than other algorithms in construction time. It effectively reduces the end-to-end delay and increases the network throughput

Hydrogen production from catalytic reforming of the aqueous fraction of pyrolysis bio-oil with modified Ni-Al catalysts

Hydrogen production from renewable resources has received extensive attention recently for a sustainable and renewable future. In this study, hydrogen was produced from catalytic steam reforming of the aqueous fraction of crude bio-oil, which was obtained from pyrolysis of biomass. Five Ni-Al catalysts modified with Ca, Ce, Mg, Mn and Zn were investigated using a fixed-bed reactor. Optimized process conditions were obtained with a steam reforming temperature of 800 °C and a steam to carbon ratio of 3.54. The life time of the catalysts in terms of stability of hydrogen production and prohibition of coke formation on the surface of the catalyst were carried out with continuous feeding of raw materials for 4 h. The results showed that the Ni-Mg-Al catalyst exhibited the highest stability of hydrogen production (56.46%) among the studied catalysts. In addition, the life-time test of catalytic experiments showed that all the catalysts suffered deactivation at the beginning of the experiment (reduction of hydrogen production), except for the Ni-Mg-Al catalyst; it is suggested that the observation of abundant amorphous carbon formed on the surface of reacted catalysts (temperature programmed oxidation results) may be responsible for the initial reduction of hydrogen production. In addition, the Ni-Ca-Al catalyst showed the lowest hydrogen production (46.58%) at both the early and stabilized stage of catalytic steam reforming of bio-oil

MP Resulting in Autophagic Cell Death of Microglia through Zinc Changes against Spinal Cord Injury

Methylprednisolone pulse therapy (MPPT), as a public recognized therapy of spinal cord injury (SCI), is doubted recently, and the exact mechanism of MP on SCI is unclear. This study sought to investigate the exact effect of MP on SCI. We examined the effect of MP in a model of SCI in vivo and an LPS induced model in vitro. We found that administration of MP produced an increase in the Basso, Beattie, and Bresnahan scores and motor neurons counts of injured rats. Besides the number of activated microglia was apparently reduced by MP in vivo, and Beclin-1 dependent autophagic cell death of microglia was induced by MP in LPS induced model. At the same time, MP increases cellular zinc concentration and level of ZIP8, and TPEN could revert effect of MP on autophagic cell death of microglia. Finally, we have found that MP could inhibit NF-κβ in LPS induced model. These results show that the MP could result in autophagic cell death of microglia, which mainly depends on increasing cellular labile zinc, and may be associated with inhibition of NF-κβ, and that MP can produce neuroprotective effect in SCI