Search results for: hybrid reactor
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2417

Search results for: hybrid reactor

1247 Biocellulose as Platform for the Development of Multifunctional Materials

Authors: Junkal Gutierrez, Hernane S. Barud, Sidney J. L. Ribeiro, Agnieszka Tercjak

Abstract:

Nowadays the interest on green nanocomposites and on the development of more environmental friendly products has been increased. Bacterial cellulose has been recently investigated as an attractive environmentally friendly material for the preparation of low-cost nanocomposites. The formation of cellulose by laboratory bacterial cultures is an interesting and attractive biomimetic access to obtain pure cellulose with excellent properties. Additionally, properties as molar mass, molar mass distribution, and the supramolecular structure could be control using different bacterial strain, culture mediums and conditions, including the incorporation of different additives. This kind of cellulose is a natural nanomaterial, and therefore, it has a high surface-to-volume ratio which is highly advantageous in composites production. Such property combined with good biocompatibility, high tensile strength, and high crystallinity makes bacterial cellulose a potential material for applications in different fields. The aim of this investigation work was the fabrication of novel hybrid inorganic-organic composites based on bacterial cellulose, cultivated in our laboratory, as a template. This kind of biohybrid nanocomposites gathers together excellent properties of bacterial cellulose with the ones displayed by typical inorganic nanoparticles like optical, magnetic and electrical properties, luminescence, ionic conductivity and selectivity, as well as chemical or biochemical activity. In addition, the functionalization of cellulose with inorganic materials opens new pathways for the fabrication of novel multifunctional hybrid materials with promising properties for a wide range of applications namely electronic paper, flexible displays, solar cells, sensors, among others. In this work, different pathways for fabrication of multifunctional biohybrid nanopapers with tunable properties based on BC modified with amphiphilic poly(ethylene oxide-b-propylene oxide-b-ethylene oxide) (EPE) block copolymer, sol-gel synthesized nanoparticles (titanium, vanadium and a mixture of both oxides) and functionalized iron oxide nanoparticles will be presented. In situ (biosynthesized) and ex situ (at post-production level) approaches were successfully used to modify BC membranes. Bacterial cellulose based biocomposites modified with different EPE block copolymer contents were developed by in situ technique. Thus, BC growth conditions were manipulated to fabricate EPE/BC nanocomposite during the biosynthesis. Additionally, hybrid inorganic/organic nanocomposites based on BC membranes and inorganic nanoparticles were designed via ex-situ method, by immersion of never-dried BC membranes into different nanoparticle solutions. On the one hand, sol-gel synthesized nanoparticles (titanium, vanadium and a mixture of both oxides) and on the other hand superparamagnetic iron oxide nanoparticles (SPION), Fe2O3-PEO solution. The morphology of designed novel bionanocomposites hybrid materials was investigated by atomic force microscopy (AFM) and scanning electron microscopy (SEM). In order to characterized obtained materials from the point of view of future applications different techniques were employed. On the one hand, optical properties were analyzed by UV-vis spectroscopy and spectrofluorimetry and on the other hand electrical properties were studied at nano and macroscale using electric force microscopy (EFM), tunneling atomic force microscopy (TUNA) and Keithley semiconductor analyzer, respectively. Magnetic properties were measured by means of magnetic force microscopy (MFM). Additionally, mechanical properties were also analyzed.

Keywords: bacterial cellulose, block copolymer, advanced characterization techniques, nanoparticles

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1246 Preparation and Quality Control of a New Radiolabelled Complex of Spion

Authors: H. Yousefnia, SJ. Ahmadi, S. Sajadi, S. Zolghadri, A. Bahrami-Samani, M. Bagherzadeh

Abstract:

Nowadays, superparamagnetic iron oxide nanoparticles (SPIONs) as the multitask agents have showed advantageous characteristics. The aim of this study was the preparation and quality control of 153Sm-DTPA-DA-SPION complex. Samarium-153 was produced by neutron irradiation of the enriched 152Sm2O3 in a research reactor for 5 d. For radiolabeling purposes, 8 mg of the ligand was added to the vial containing 153SmCl3 and the mixture was sonicated 30 min, while pH was adjusted to 7-8. The radiochemical purity of the complex was checked by the ITLC method using NH4OH:MeOH:H2O (0.2:2:4) as the mobile phase. This new radiolabeled complex was prepared with a radiochemical purity of higher than 98% in 30 min at the optimized condition. The complex was kept at room temperature and in human serum at 37 °C for 48 h, showed no loss of 153Sm from the complex. Considering all of these features, this new radiolabeled complex can be considered as a good therapeutic agent; however, further studies on its biological behavior are still needed.

Keywords: iron nanoparticles, preparation, quality control, 153Sm

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1245 Efficient Corporate Image as a Strategy for Enhancing Profitability in Hotels

Authors: Lucila T. Magalong

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The hotel industry has been using their corporate image and reputation to maintain service quality, customer satisfaction, and customer loyalty and to leverage themselves against competitors and facilitate their growth strategies. With the increasing pressure to perform, hotels have even created hybrid service strategy to fight in the niche markets across pricing and level-off service parameters.

Keywords: corporate image, hotel industry, service quality, customer expectations

Procedia PDF Downloads 465
1244 Multi Biomertric Personal Identification System Based On Hybird Intellegence Method

Authors: Laheeb M. Ibrahim, Ibrahim A. Salih

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Biometrics is a technology that has been widely used in many official and commercial identification applications. The increased concerns in security during recent years (especially during the last decades) have essentially resulted in more attention being given to biometric-based verification techniques. Here, a novel fusion approach of palmprint, dental traits has been suggested. These traits which are authentication techniques have been employed in a range of biometric applications that can identify any postmortem PM person and antemortem AM. Besides improving the accuracy, the fusion of biometrics has several advantages such as increasing, deterring spoofing activities and reducing enrolment failure. In this paper, a first unimodel biometric system has been made by using (palmprint and dental) traits, for each one classification applying an artificial neural network and a hybrid technique that combines swarm intelligence and neural network together, then attempt has been made to combine palmprint and dental biometrics. Principally, the fusion of palmprint and dental biometrics and their potential application has been explored as biometric identifiers. To address this issue, investigations have been carried out about the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. Also the results of the multimodal approach have been compared with each one of these two traits authentication approaches. This paper studies the features and decision fusion levels in multimodal biometrics. To determine the accuracy of GAR to parallel system decision-fusion including (AND, OR, Majority fating) has been used. The backpropagation method has been used for classification and has come out with result (92%, 99%, 97%) respectively for GAR, while the GAR) for this algorithm using hybrid technique for classification (95%, 99%, 98%) respectively. To determine the accuracy of the multibiometric system for feature level fusion has been used, while the same preceding methods have been used for classification. The results have been (98%, 99%) respectively while to determine the GAR of feature level different methods have been used and have come out with (98%).

Keywords: back propagation neural network BP ANN, multibiometric system, parallel system decision-fusion, practical swarm intelligent PSO

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1243 A CFD Analysis of Hydraulic Characteristics of the Rod Bundles in the BREST-OD-300 Wire-Spaced Fuel Assemblies

Authors: Dmitry V. Fomichev, Vladimir V. Solonin

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This paper presents the findings from a numerical simulation of the flow in 37-rod fuel assembly models spaced by a double-wire trapezoidal wrapping as applied to the BREST-OD-300 experimental nuclear reactor. Data on a high static pressure distribution within the models, and equations for determining the fuel bundle flow friction factors have been obtained. Recommendations are provided on using the closing turbulence models available in the ANSYS Fluent. A comparative analysis has been performed against the existing empirical equations for determining the flow friction factors. The calculated and experimental data fit has been shown. An analysis into the experimental data and results of the numerical simulation of the BREST-OD-300 fuel rod assembly hydrodynamic performance are presented.

Keywords: BREST-OD-300, ware-spaces, fuel assembly, computation fluid dynamics

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1242 Liquid Fuel Production via Catalytic Pyrolysis of Waste Oil

Authors: Malee Santikunaporn, Neera Wongtyanuwat, Channarong Asavatesanupap

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Pyrolysis of waste oil is an effective process to produce high quality liquid fuels. In this work, pyrolysis experiments of waste oil over Y zeolite were carried out in a semi-batch reactor under a flow of nitrogen at atmospheric pressure and at different reaction temperatures (350-450 oC). The products were gas, liquid fuel, and residue. Only liquid fuel was further characterized for its composition and properties by using gas chromatography, thermogravimetric analyzer, and bomb calorimeter. Experimental results indicated that the pyrolysis reaction temperature significantly affected both yield and composition distribution of pyrolysis oil. An increase in reaction temperature resulted in increased fuel yield, especially gasoline fraction. To obtain high amount of fuel, the optimal reaction temperature should be higher than 350 oC. A presence of Y zeolite in the system enhanced the cracking activity. In addition, the pyrolysis oil yield is proportional to the catalyst quantity.

Keywords: gasoline, diesel, pyrolysis, waste oil, Y zeolite

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1241 The Effect of Additives on Characterization and Photocatalytic Activity of Ag-TiO₂ Nanocomposite Prepared via Sol-Gel Process

Authors: S. Raeis Farshid, B. Raeis Farshid

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Ag-TiO₂ nanocomposites were prepared by the sol-gel method with and without additives such as carboxy methyl cellulose (CMC), polyethylene glycol (PEG), polyvinyl pyrrolidone (PVP), and hydroxyl propyl cellulose (HPC). The characteristics of the prepared Ag-TiO₂ nanocomposites were identified by Fourier Transform Infra-Red spectroscopy (FTIR), X-Ray Diffraction (XRD), and scanning electron microscopy (SEM) methods. The additives have a significant effect on the particle size distribution and photocatalytic activity of Ag-TiO₂ nanocomposites. SEM images have shown that the particle size distribution of Ag-TiO₂ nanocomposite in the presence of HPC was the best in comparison to the other samples. The photocatalytic activity of the synthesized nanocomposites was investigated for decolorization of methyl orange (MO) in water under UV-irradiation in a batch reactor, and the results showed that the photocatalytic activity of the nanocomposites had been increased by CMC, PEG, PVP, and HPC, respectively.

Keywords: sol-gel method, Ag-TiO₂, decolorization, photocatalyst, nanocomposite

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1240 Zinc Oxide Nanorods Decorated Nanofibers Based Flexible Electrodes for Capacitive Energy Storage Applications

Authors: Syed Kamran Sami, Saqib Siddiqui

Abstract:

In recent times, flexible supercapacitors retaining high electrochemical performance and steadiness along with mechanical endurance has developed as a spring of attraction due to the exponential progress and innovations in energy storage devices. To meet the rampant increasing demand of energy storage device with the small form factor, a unique, low cost and high-performance supercapacitor with considerably higher capacitance and mechanical robustness is required to recognize their real-life applications. Here in this report, synthesis route of electrode materials with low rigidity and high charge storage performance is reported using 1D-1D hybrid structure of zinc oxide (ZnO) nanorods, and conductive polymer smeared polyvinylidene fluoride–trifluoroethylene (P(VDF–TrFE)) electrospun nanofibers. The ZnO nanorods were uniformly grown on poly (3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT: PSS) coated P(VDF-TrFE) nanofibers using hydrothermal growth to manufacture light weight, permeable electrodes for supercapacitor. The PEDOT: PSS coated P(VDF-TrFE) porous web of nanofibers act as framework with high surface area. The incorporation of ZnO nanorods further boost the specific capacitance by 59%. The symmetric device using the fabricated 1D-1D hybrid electrodes reveals fairly high areal capacitance of 1.22mF/cm² at a current density of 0.1 mA/cm² with a power density of more than 1600 W/Kg. Moreover, the fabricated electrodes show exceptional flexibility and high endurance with 90% and 76% specific capacitance retention after 1000 and 5000 cycles respectively signifying the astonishing mechanical durability and long-term stability. All the properties exhibited by the fabricated electrode make it convenient for making flexible energy storage devices with the low form factor.

Keywords: ZnO nanorods, electrospinning, mechanical endurance, flexible supercapacitor

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1239 NiSe-Ni₃Se₂/Multiwalled Carbon Nanotubes as Efficient Electrocatalysts for the Oxygen Evolution Reaction in Alkaline Media

Authors: Oluwaseun A. Oyetade, Roelof J. Kriek

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The development of effective catalysts for the oxygen evolution reaction (OER) is of great importance to combat energy-related concerns in the environment. Herein, we report a one-step solvothermal method employed for the fabrication of nickel selenide hybrids (NiSe-Ni₃Se₂) and a series of nickel selenide hybrid/multiwalled carbon nanotube composites (NiSe-Ni₃Se₂/MWCNT) as electrocatalysts for OER in alkaline media. The catalytic activities of these catalysts were investigated via several electrochemical characterization techniques, such as linear sweep voltammetry, chronoamperometric studies at constant potential, electrochemical surface area determination, and Tafel slope calculation, under alkaline conditions. Morphological observations demonstrated the agglomeration of non-uniform NiSe-Ni₃Se₂ microspheres around carbon nanotubes (CNTs), demonstrating the successful synthesis of NiSe-Ni₃Se₂/MWCNT nanocomposites. Among the tested electrocatalysts, the 20% NiSe-Ni₃Se₂/MWCNT nanocomposite demonstrated the highest activity, exhibiting an overpotential of 325 mV to achieve a current density of 10 mA.cm⁻² in 0.1 mol.dm⁻³ KOH solution. The NiSe-Ni₃Se₂/MWCNT nanocomposites showed improved activity toward OER compared to bare NiSe-Ni₃Se₂ hybrids and MWCNTs, exhibiting an overpotential of 528, 392 and 434 mV for 10%, 30% and 50% NiSe-Ni₃Se₂/MWCNT nanocomposites, respectively. These results compare favourably to the overpotential of noble catalysts, such as RuO₂ and IrO₂. Our results imply that the addition of MWCNTs increased the activity of NiSe-Ni₃Se₂ hybrids due to an increased number of catalytic sites, dispersion of NiSe-Ni₃Se₂ hybrid nanoparticles, and electronic conductivity of the nanocomposites. These nanocomposites also demonstrated better long-term stability compared to NiSe-Ni₃Se₂ hybrids and MWCNTs. Hence, NiSe-Ni₃Se₂/MWCNT nanocomposites possess the potential as effective electrocatalysts for OER in alkaline media.

Keywords: carbon nanotubes, electrocatalysts, nanocomposites, nickel selenide hybrids, oxygen evolution reaction

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1238 Optimization of Biodiesel Production from Sunflower Oil Using Central Composite Design

Authors: Pascal Mwenge, Jefrey Pilusa, Tumisang Seodigeng

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The current study investigated the effect of catalyst ratio and methanol to oil ratio on biodiesel production by using central composite design. Biodiesel was produced by transesterification using sodium hydroxide as a homogeneous catalyst, a laboratory scale reactor consisting of flat bottom flask mounts with a reflux condenser, and a heating plate was used to produce biodiesel. Key parameters, including time, temperature, and mixing rate was kept constant at 60 minutes, 60 oC and 600 RPM, respectively. From the results obtained, it was observed that the biodiesel yield depends on catalyst ratio and methanol to oil ratio. The highest yield of 50.65% was obtained at catalyst ratio of 0.5 wt.% and methanol to oil mole ratio 10.5. The analysis of variances of biodiesel yield showed the R Squared value of 0.8387. A quadratic mathematical model was developed to predict the biodiesel yield in the specified parameters ranges.

Keywords: ANOVA, biodiesel, catalyst, transesterification, central composite design

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1237 Sustainable Cities: Viability of a Hybrid Aeroponic/Nutrient Film Technique System for Cultivation of Tomatoes

Authors: D. Dannehl, Z. Taylor, J. Suhl, L. Miranda, R., Ulrichs, C., Salazar, E. Fitz-Rodriguez, I. Lopez-Cruz, A. Rojano-Aguilar, G. Navas-Gomez, U. Schmidt

Abstract:

Growing environmental and sustainability concerns have driven continual modernization of horticultural practices, especially for urban farming. Controlled environment and soilless production methods are increasing in popularity because of their efficient resource use and intensive cropping capabilities. However, some popular substrates used for hydroponic cultivation, particularly rock wool, represent a large environmental burden in regard to their manufacture and disposal. Substrate-less hydroponic systems are effective in producing short cropping cycle plants such as lettuce or herbs, but less information is available for the production of plants with larger root-systems and longer cropping times. Here, we investigated the viability of a hybrid aeroponic/nutrient film technique (AP/NFT) system for the cultivation of greenhouse tomatoes (Solanum lycopersicum ‘Panovy’). The plants grown in the AP/NFT system had a more compact phenotype, accumulated more Na+ and less P and S than the rock wool grown counterparts. Due to forced irrigation interruptions, we propose that the differences observed were cofounded by the differing severity of water-stress for plants with and without substrate. They may also be caused by a higher root zone temperature predominant in plants exposed to AP/NFT. However, leaf area, stem diameter, and number of trusses did not differ significantly. The same was found for leaf pigments and plant photosynthetic efficiency. Overall, the AP/NFT system appears to be viable for the production of greenhouse tomato, enabling the environment to be relieved by way of lessening rock wool usage.

Keywords: closed aeroponic systems, fruit quality, nutrient dynamics, substrate waste reduction, urban farming systems, water savings

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1236 Data Mining Model for Predicting the Status of HIV Patients during Drug Regimen Change

Authors: Ermias A. Tegegn, Million Meshesha

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Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome (HIV/AIDS) is a major cause of death for most African countries. Ethiopia is one of the seriously affected countries in sub Saharan Africa. Previously in Ethiopia, having HIV/AIDS was almost equivalent to a death sentence. With the introduction of Antiretroviral Therapy (ART), HIV/AIDS has become chronic, but manageable disease. The study focused on a data mining technique to predict future living status of HIV/AIDS patients at the time of drug regimen change when the patients become toxic to the currently taking ART drug combination. The data is taken from University of Gondar Hospital ART program database. Hybrid methodology is followed to explore the application of data mining on ART program dataset. Data cleaning, handling missing values and data transformation were used for preprocessing the data. WEKA 3.7.9 data mining tools, classification algorithms, and expertise are utilized as means to address the research problem. By using four different classification algorithms, (i.e., J48 Classifier, PART rule induction, Naïve Bayes and Neural network) and by adjusting their parameters thirty-two models were built on the pre-processed University of Gondar ART program dataset. The performances of the models were evaluated using the standard metrics of accuracy, precision, recall, and F-measure. The most effective model to predict the status of HIV patients with drug regimen substitution is pruned J48 decision tree with a classification accuracy of 98.01%. This study extracts interesting attributes such as Ever taking Cotrim, Ever taking TbRx, CD4 count, Age, Weight, and Gender so as to predict the status of drug regimen substitution. The outcome of this study can be used as an assistant tool for the clinician to help them make more appropriate drug regimen substitution. Future research directions are forwarded to come up with an applicable system in the area of the study.

Keywords: HIV drug regimen, data mining, hybrid methodology, predictive model

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1235 Combining Ability for Maize Grain Yield and Yield Component for Resistant to Striga hermmonthica (Del) Benth in Southern Guinea Savannah of Nigeria

Authors: Terkimbi Vange, Obed Abimiku, Lateef Lekan Bello, Lucky Omoigui

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In 2014 and 2015, eight maize inbred lines resistant to Striga hermonthica (Del) Benth were crossed in 8 x 8 half diallel (Griffing method 11, model 1). The eight parent inbred lines were planted out in a Randomized Complete Block Design (RCBD) with three replications at two different Striga infested environments (Lafia and Makurdi) during the late cropping season. The objectives were to determine the combining ability of Striga resistant maize inbred lines and identify suitable inbreds for hybrids development. The lines were used to estimate general combining ability (GCA), and specific combining ability (SCA) effects for Striga related parameters such as Striga shoot counts, Striga damage rating (SDR), plant height and grain yield and other agronomic traits. The result of combined ANOVA revealed that mean squares were highly significant for all traits except Striga damage rating (SDR1) at 8WAS and Striga emergence count (STECOI) at 8WAS. Mean squares for SCA were significantly low for all traits. TZSTR190 was the highest yielding parent, and TZSTR166xTZST190 was the highest yielding hybrid (cross). Parent TZSTR166, TZEI188, TZSTR190 and TZSTR193 shows significant (p < 0.05) positive GCA effects for grain yield while the rest had negative GCA effects for grain yield. Parent TZSTR166, TZEI188, TZSTR190, and TZSTR193 could be used for initiating hybrid development. Also, TZSTR166xTZSTR190 cross was the best specific combiner followed by TZEI188xTZSTR193, TZEI80xTZSTR193, and TZSTR190xTZSTR193. TZSTR166xTZSTR190 and TZSTR190xTZSTR193 had the highest SCA effects. However, TZEI80 and TZSTR190 manifested a high positive SCA effect with TZSTR166 indicating that these two inbreds combined better with TZSTR166.

Keywords: combining ability, Striga hermonthica, resistance, grain yield

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1234 A Hybrid-Evolutionary Optimizer for Modeling the Process of Obtaining Bricks

Authors: Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu, Costel Anton

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Natural sciences provide a wide range of experimental data whose related problems require study and modeling beyond the capabilities of conventional methodologies. Such problems have solution spaces whose complexity and high dimensionality require correspondingly complex regression methods for proper characterization. In this context, we propose an optimization method which consists in a hybrid dual optimizer setup: a global optimizer based on a modified variant of the popular Imperialist Competitive Algorithm (ICA), and a local optimizer based on a gradient descent approach. The ICA is modified such that intermediate solution populations are more quickly and efficiently pruned of low-fitness individuals by appropriately altering the assimilation, revolution and competition phases, which, combined with an initialization strategy based on low-discrepancy sampling, allows for a more effective exploration of the corresponding solution space. Subsequently, gradient-based optimization is used locally to seek the optimal solution in the neighborhoods of the solutions found through the modified ICA. We use this combined approach to find the optimal configuration and weights of a fully-connected neural network, resulting in regression models used to characterize the process of obtained bricks using silicon-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. Thus, the purpose of our approach is to determine by simulation the working conditions, including the manufacturing mix recipe with the addition of different materials, to minimize the emissions represented by CO and CH4. Our approach determines regression models which perform significantly better than those found using the traditional ICA for the aforementioned problem, resulting in better convergence and a substantially lower error.

Keywords: optimization, biologically inspired algorithm, regression models, bricks, emissions

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1233 A Comprehensive Study of a Hybrid System Integrated Solid Oxide Fuel cell, Gas Turbine, Organic Rankine Cycle with Compressed air Energy Storage

Authors: Taiheng Zhang, Hongbin Zhao

Abstract:

Compressed air energy storage become increasingly vital for solving intermittency problem of some renewable energies. In this study, a new hybrid system on a combination of compressed air energy storage (CAES), solid oxide fuel cell (SOFC), gas turbine (GT), and organic Rankine cycle (ORC) is proposed. In the new system, excess electricity during off-peak time is utilized to compress air. Then, the compressed air is stored in compressed air storage tank. During peak time, the compressed air enters the cathode of SOFC directly instead of combustion chamber of traditional CAES. There is no air compressor consumption of SOFC-GT in peak demand, so SOFC- GT can generate power with high-efficiency. In addition, the waste heat of exhaust from GT is recovered by applying an ORC. Three different organic working fluid (R123, R601, R601a) of ORC are chosen to evaluate system performance. Based on Aspen plus and Engineering Equation Solver (EES) software, energy and exergoeconomic analysis are used to access the viability of the combined system. Besides, the effect of two parameters (fuel flow and ORC turbine inlet pressure) on energy efficiency is studied. The effect of low-price electricity at off-peak hours on thermodynamic criteria (total unit exergy cost of products and total cost rate) is also investigated. Furthermore, for three different organic working fluids, the results of round-trip efficiency, exergy efficiency, and exergoeconomic factors are calculated and compared. Based on thermodynamic performance and exergoeconomic performance of different organic working fluids, the best suitable working fluid will be chosen. In conclusion, this study can provide important guidance for system efficiency improvement and viability.

Keywords: CAES, SOFC, ORC, energy and exergoeconomic analysis, organic working fluids

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1232 Integrated Manufacture of Polymer and Conductive Tracks for Functional Objects Fabrication

Authors: Barbara Urasinska-Wojcik, Neil Chilton, Peter Todd, Christopher Elsworthy, Gregory J. Gibbons

Abstract:

The recent increase in the application of Additive Manufacturing (AM) of products has resulted in new demands on capability. The ability to integrate both form and function within printed objects is the next frontier in the 3D printing area. To move beyond prototyping into low volume production, we demonstrate a UK-designed and built AM hybrid system that combines polymer based structural deposition with digital deposition of electrically conductive elements. This hybrid manufacturing system is based on a multi-planar build approach to improve on many of the limitations associated with AM, such as poor surface finish, low geometric tolerance, and poor robustness. Specifically, the approach involves a multi-planar Material Extrusion (ME) process in which separated build stations with up to 5 axes of motion replace traditional horizontally-sliced layer modeling. The construction of multi-material architectures also involved using multiple print systems in order to combine both ME and digital deposition of conductive material. To demonstrate multi-material 3D printing, three thermoplastics, acrylonitrile butadiene styrene (ABS), polyamide 6,6/6 copolymers (CoPA) and polyamide 12 (PA) were used to print specimens, on top of which our high viscosity Ag-particulate ink was printed in a non-contact process, during which drop characteristics such as shape, velocity, and volume were assessed using a drop watching system. Spectroscopic analysis of these 3D printed materials in the IR region helped to determine the optimum in-situ curing system for implementation into the AM system to achieve improved adhesion and surface refinement. Thermal Analyses were performed to determine the printed materials glass transition temperature (Tg), stability and degradation behavior to find the optimum annealing conditions post printing. Electrical analysis of printed conductive tracks on polymer surfaces during mechanical testing (static tensile and 3-point bending and dynamic fatigue) was performed to assess the robustness of the electrical circuits. The tracks on CoPA, ABS, and PA exhibited low electrical resistance, and in case of PA resistance values of tracks remained unchanged across hundreds of repeated tensile cycles up to 0.5% strain amplitude. Our developed AM printer has the ability to fabricate fully functional objects in one build, including complex electronics. It enables product designers and manufacturers to produce functional saleable electronic products from a small format modular platform. It will make 3D printing better, faster and stronger.

Keywords: additive manufacturing, conductive tracks, hybrid 3D printer, integrated manufacture

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1231 Combustion Characteristics and Pollutant Emissions in Gasoline/Ethanol Mixed Fuels

Authors: Shin Woo Kim, Eui Ju Lee

Abstract:

The recent development of biofuel production technology facilitates the use of bioethanol and biodiesel on automobile. Bioethanol, especially, can be used as a fuel for gasoline vehicles because the addition of ethanol has been known to increase octane number and reduce soot emissions. However, the wide application of biofuel has been still limited because of lack of detailed combustion properties such as auto-ignition temperature and pollutant emissions such as NOx and soot, which has been concerned mainly on the vehicle fire safety and environmental safety. In this study, the combustion characteristics of gasoline/ethanol fuel were investigated both numerically and experimentally. For auto-ignition temperature and NOx emission, the numerical simulation was performed on the well-stirred reactor (WSR) to simulate the homogeneous gasoline engine and to clarify the effect of ethanol addition in the gasoline fuel. Also, the response surface method (RSM) was introduced as a design of experiment (DOE), which enables the various combustion properties to be predicted and optimized systematically with respect to three independent variables, i.e., ethanol mole fraction, equivalence ratio and residence time. The results of stoichiometric gasoline surrogate show that the auto-ignition temperature increases but NOx yields decrease with increasing ethanol mole fraction. This implies that the bioethanol added gasoline is an eco-friendly fuel on engine running condition. However, unburned hydrocarbon is increased dramatically with increasing ethanol content, which results from the incomplete combustion and hence needs to adjust combustion itself rather than an after-treatment system. RSM results analyzed with three independent variables predict the auto-ignition temperature accurately. However, NOx emission had a big difference between the calculated values and the predicted values using conventional RSM because NOx emission varies very steeply and hence the obtained second order polynomial cannot follow the rates. To relax the increasing rate of dependent variable, NOx emission is taken as common logarithms and worked again with RSM. NOx emission predicted through logarithm transformation is in a fairly good agreement with the experimental results. For more tangible understanding of gasoline/ethanol fuel on pollutant emissions, experimental measurements of combustion products were performed in gasoline/ethanol pool fires, which is widely used as a fire source of laboratory scale experiments. Three measurement methods were introduced to clarify the pollutant emissions, i.e., various gas concentrations including NOx, gravimetric soot filter sampling for elements analysis and pyrolysis, thermophoretic soot sampling with transmission electron microscopy (TEM). Soot yield by gravimetric sampling was decreased dramatically as ethanol was added, but NOx emission was almost comparable regardless of ethanol mole fraction. The morphology of the soot particle was investigated to address the degree of soot maturing. The incipient soot such as a liquid like PAHs was observed clearly on the soot of higher ethanol containing gasoline, and the soot might be matured under the undiluted gasoline fuel.

Keywords: gasoline/ethanol fuel, NOx, pool fire, soot, well-stirred reactor (WSR)

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1230 4-Chlorophenol Degradation in Water Using TIO₂-X%ZnS Synthesized by One-Step Sol-Gel Method

Authors: M. E. Velásquez Torres, F. Tzompantzi, J. C. Castillo-Rodríguez, A. G. Romero Villegas, S. Mendéz-Salazar, C. E. Santolalla-Vargas, J. Cardoso-Martínez

Abstract:

Photocatalytic degradation, as an advanced oxidation technology, is a promising method in organic pollutant degradation. In this sense, chlorophenols should be removed from the water because they are highly toxic. The TiO₂ - X% ZnS photocatalysts, where X represents the molar percentage of ZnS (3%, 5%, 10%, and 15%), were synthesized using the one-step sol-gel method to use them as photocatalysts to degrade 4-chlorophenol. The photocatalysts were synthesized by a one-step sol-gel method. They were refluxed for 36 hours, dried at 80°C, and calcined at 400°C. They were labeled TiO₂ - X%ZnS, where X represents the molar percentage of ZnS (3%, 5%, 10%, and 15%). The band gap was calculated using a Cary 100 UV-Visible Spectrometer with an integrating sphere accessory. Ban gap value of each photocatalyst was: 2.7 eV of TiO₂, 2.8 eV of TiO₂ - 3%ZnS and TiO₂ - 5%ZnS, 2.9 eV of TiO₂ - 10%ZnS and 2.6 eV of TiO2 - 15%ZnS. In a batch type reactor, under the irradiation of a mercury lamp (λ = 254 nm, Pen-Ray), degradations of 55 ppm 4-chlorophenol were obtained at 360 minutes with the synthesized photocatalysts: 60% (3% ZnS), 66% (5% ZnS), 74% (10% ZnS) and 58% (15% ZnS). In this sense, the best material as a photocatalyst was TiO₂ -10%ZnS with a degradation percentage of 74%.

Keywords: 4-chlorophenol, photocatalysis, water pollutant, sol-gel

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1229 Integration of Educational Data Mining Models to a Web-Based Support System for Predicting High School Student Performance

Authors: Sokkhey Phauk, Takeo Okazaki

Abstract:

The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

Procedia PDF Downloads 107
1228 Study of the Hysteretic I-V Characteristics in a Polystyrene/ZnO-Nanorods Stack Layer

Authors: You-Lin Wu, Yi-Hsing Sung, Shih-Hung Lin, Jing-Jenn Lin

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Performance improvement in optoelectronic devices such as solar cells and photodetectors has been reported when a polymer/ZnO nanorods stack is used. Resistance switching of polymer/ZnO nanocrystals (or nanorods) hybrid has also gained a lot of research interests recently. It has been reported that high- and low-resistance states of a metal/insulator/metal (MIM) structure diode with a polystyrene (PS) and ZnO hybrid as the insulator layer can be switched by applied bias after a high-voltage forming process, while the same device structure merely with a PS layer does not show any forming behavior. In this work, we investigated the current-voltage (I-V) characteristics of an MIM device with a PS/ZnO nanorods stack deposited on fluorine-doped tin oxide (FTO) glass substrate. The ZnO nanorods were grown by a hydrothermal method using a mixture of zinc nitrate, hexamethylenetetramine, and DI water. Following that, a PS layer was deposited by spin coating. Finally, the device with a structure of Ti/ PS/ZnO nanorods/FTO was completed by e-gun evaporated Ti layer on top of the PS layer. Semiconductor parameters analyzer Agilent 4156C was then used to measure the I-V characteristics of the device by applying linear ramp sweep voltage with sweep sequence of 0V → 4V → 0V → 3V → 0V → 2V → 0V → 1V → 0V in both positive and negative directions. It is interesting to find that the I-V characteristics are bias dependent and hysteretic, indicating that the device Ti/PS/ZnO nanorods/FTO structure has ferroelectricity. Our results also show that the maximum hysteresis loop height of the I-V characteristics as well as the voltage at which the maximum hysteresis loop height of each scan occurs increase with increasing maximum sweep voltage. It should be noticed that, although ferroelectricity has been found in ZnO at its melting temperature (1975℃) and in Li- or Co-doped ZnO, neither PS nor ZnO has ferroelectricity at room temperature. Using the same structure but with a PS or ZnO layer only as the insulator does not give and hysteretic I-V characteristics. It is believed that a charge polarization layer is induced near the PS/ZnO nanorods stack interface and thus causes the ferroelectricity in the device with Ti/PS/ZnO nanorods/FTO structure. Our results show that the PS/ZnO stack can find a potential application in a resistive switching memory device with MIM structure.

Keywords: ferroelectricity, hysteresis, polystyrene, resistance switching, ZnO nanorods

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1227 Nursing Education in the Pandemic Time: Case Study

Authors: Jaana Sepp, Ulvi Kõrgemaa, Kristi Puusepp, Õie Tähtla

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COVID-19 was officially recognized as a pandemic in late 2019 by the WHO, and it has led to changes in the education sector. Educational institutions were closed, and most schools adopted distance learning. Estonia is known as a digitally well-developed country. Based on that, in the pandemic time, nursing education continued, and new technological solutions were implemented. To provide nursing education, special focus was paid on quality and flexibility. The aim of this paper is to present administrative, digital, and technological solutions which support Estonian nursing educators to continue the study process in the pandemic time and to develop a sustainable solution for nursing education for the future. This paper includes the authors’ analysis of the documents and decisions implemented in the institutions through the pandemic time. It is a case study of Estonian nursing educators. Results of the analysis show that the implementation of distance learning principles challenges the development of innovative strategies and technics for the assessment of student performance and educational outcomes and implement new strategies to encourage student engagement in the virtual classroom. Additionally, hospital internships were canceled, and the simulation approach was deeply implemented as a new opportunity to develop and assess students’ practical skills. There are many other technical and administrative changes that have also been carried out, such as students’ support and assessment systems, the designing and conducting of hybrid and blended studies, etc. All services were redesigned and made more available, individual, and flexible. Hence, the feedback system was changed, the information was collected in parallel with educational activities. Experiences of nursing education during the pandemic time are widely presented in scientific literature. However, to conclude our study, authors have found evidence that solutions implemented in Estonian nursing education allowed the students to graduate within the nominal study period without any decline in education quality. Operative information system and flexibility provided the minimum distance between the students, support, and academic staff, and likewise, the changes were implemented quickly and efficiently. Institution memberships were updated with the appropriate information, and it positively affected their satisfaction, motivation, and commitment. We recommend that the feedback process and the system should be permanently changed in the future to place all members in the same information area, redefine the hospital internship process, implement hybrid learning, as well as to improve the communication system between stakeholders inside and outside the organization. The main limitation of this study relates to the size of Estonia. Nursing education is provided by two institutions only, and similarly, the number of students is low. The result could be generated to the institutions with a similar size and administrative system. In the future, the relationship between nurses’ performance and organizational outcomes should be deeply investigated and influences of the pandemic time education analyzed at workplaces.

Keywords: hybrid learning, nursing education, nursing, COVID-19

Procedia PDF Downloads 121
1226 A Greener Approach towards the Synthesis of an Antimalarial Drug Lumefantrine

Authors: Luphumlo Ncanywa, Paul Watts

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Malaria is a disease that kills approximately one million people annually. Children and pregnant women in sub-Saharan Africa lost their lives due to malaria. Malaria continues to be one of the major causes of death, especially in poor countries in Africa. Decrease the burden of malaria and save lives is very essential. There is a major concern about malaria parasites being able to develop resistance towards antimalarial drugs. People are still dying due to lack of medicine affordability in less well-off countries in the world. If more people could receive treatment by reducing the cost of drugs, the number of deaths in Africa could be massively reduced. There is a shortage of pharmaceutical manufacturing capability within many of the countries in Africa. However one has to question how Africa would actually manufacture drugs, active pharmaceutical ingredients or medicines developed within these research programs. It is quite likely that such manufacturing would be outsourced overseas, hence increasing the cost of production and potentially limiting the full benefit of the original research. As a result the last few years has seen major interest in developing more effective and cheaper technology for manufacturing generic pharmaceutical products. Micro-reactor technology (MRT) is an emerging technique that enables those working in research and development to rapidly screen reactions utilizing continuous flow, leading to the identification of reaction conditions that are suitable for usage at a production level. This emerging technique will be used to develop antimalarial drugs. It is this system flexibility that has the potential to reduce both the time was taken and risk associated with transferring reaction methodology from research to production. Using an approach referred to as scale-out or numbering up, a reaction is first optimized within the laboratory using a single micro-reactor, and in order to increase production volume, the number of reactors employed is simply increased. The overall aim of this research project is to develop and optimize synthetic process of antimalarial drugs in the continuous processing. This will provide a step change in pharmaceutical manufacturing technology that will increase the availability and affordability of antimalarial drugs on a worldwide scale, with a particular emphasis on Africa in the first instance. The research will determine the best chemistry and technology to define the lowest cost manufacturing route to pharmaceutical products. We are currently developing a method to synthesize Lumefantrine in continuous flow using batch process as bench mark. Lumefantrine is a dichlorobenzylidine derivative effective for the treatment of various types of malaria. Lumefantrine is an antimalarial drug used with artemether for the treatment of uncomplicated malaria. The results obtained when synthesizing Lumefantrine in a batch process are transferred into a continuous flow process in order to develop an even better and reproducible process. Therefore, development of an appropriate synthetic route for Lumefantrine is significant in pharmaceutical industry. Consequently, if better (and cheaper) manufacturing routes to antimalarial drugs could be developed and implemented where needed, it is far more likely to enable antimalarial drugs to be available to those in need.

Keywords: antimalarial, flow, lumefantrine, synthesis

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1225 Approaching the Spatial Multi-Objective Land Use Planning Problems at Mountain Areas by a Hybrid Meta-Heuristic Optimization Technique

Authors: Konstantinos Tolidis

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The mountains are amongst the most fragile environments in the world. The world’s mountain areas cover 24% of the Earth’s land surface and are home to 12% of the global population. A further 14% of the global population is estimated to live in the vicinity of their surrounding areas. As urbanization continues to increase in the world, the mountains are also key centers for recreation and tourism; their attraction is often heightened by their remarkably high levels of biodiversity. Due to the fact that the features in mountain areas vary spatially (development degree, human geography, socio-economic reality, relations of dependency and interaction with other areas-regions), the spatial planning on these areas consists of a crucial process for preserving the natural, cultural and human environment and consists of one of the major processes of an integrated spatial policy. This research has been focused on the spatial decision problem of land use allocation optimization which is an ordinary planning problem on the mountain areas. It is a matter of fact that such decisions must be made not only on what to do, how much to do, but also on where to do, adding a whole extra class of decision variables to the problem when combined with the consideration of spatial optimization. The utility of optimization as a normative tool for spatial problem is widely recognized. However, it is very difficult for planners to quantify the weights of the objectives especially when these are related to mountain areas. Furthermore, the land use allocation optimization problems at mountain areas must be addressed not only by taking into account the general development objectives but also the spatial objectives (e.g. compactness, compatibility and accessibility, etc). Therefore, the main research’s objective was to approach the land use allocation problem by utilizing a hybrid meta-heuristic optimization technique tailored to the mountain areas’ spatial characteristics. The results indicates that the proposed methodological approach is very promising and useful for both generating land use alternatives for further consideration in land use allocation decision-making and supporting spatial management plans at mountain areas.

Keywords: multiobjective land use allocation, mountain areas, spatial planning, spatial decision making, meta-heuristic methods

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1224 CO₂ Capture by Clay and Its Adsorption Mechanism

Authors: Jedli Hedi, Hedfi Hachem, Abdessalem Jbara, Slimi Khalifa

Abstract:

Natural and modified clay were used as an adsorbent for CO2 capture. Sample of clay was subjected to acid treatments to improve their textural properties, namely, its surface area and pore volume. The modifications were carried out by heating the clays at 120 °C and then by acid treatment with 3M sulphuric acid solution at boiling temperature for 10 h. The CO2 adsorption capacities of the acid-treated clay were performed out in a batch reactor. It was found that the clay sample treated with 3M H2SO4 exhibited the highest Brunauer–Emmett–Teller (BET) surface area (16.29–24.68 m2/g) and pore volume (0.056–0.064 cm3/g). After the acid treatment, the CO2 adsorption capacity of clay increased. The CO2 adsorption capacity of clay increased after the acid treatment. The CO2 adsorption by clay, were characterized by SEM, FTIR, ATD-ATG and BET method. For describing the phenomenon of CO2 adsorption for these materials, the adsorption isotherms were modeled using the Freundlich and Langmuir models. CO2 adsorption isotherm was found attributable to physical adsorption.

Keywords: clay, acid treatment, CO2 capture, adsorption mechanism

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1223 A Sustainable Supplier Selection and Order Allocation Based on Manufacturing Processes and Product Tolerances: A Multi-Criteria Decision Making and Multi-Objective Optimization Approach

Authors: Ravi Patel, Krishna K. Krishnan

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In global supply chains, appropriate and sustainable suppliers play a vital role in supply chain development and feasibility. In a larger organization with huge number of suppliers, it is necessary to divide suppliers based on their past history of quality and delivery of each product category. Since performance of any organization widely depends on their suppliers, well evaluated selection criteria and decision-making models lead to improved supplier assessment and development. In this paper, SCOR® performance evaluation approach and ISO standards are used to determine selection criteria for better utilization of supplier assessment by using hybrid model of Analytic Hierchchy Problem (AHP) and Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (FTOPSIS). AHP is used to determine the global weightage of criteria which helps TOPSIS to get supplier score by using triangular fuzzy set theory. Both qualitative and quantitative criteria are taken into consideration for the proposed model. In addition, a multi-product and multi-time period model is selected for order allocation. The optimization model integrates multi-objective integer linear programming (MOILP) for order allocation and a hybrid approach for supplier selection. The proposed MOILP model optimizes order allocation based on manufacturing process and product tolerances as per manufacturer’s requirement for quality product. The integrated model and solution approach are tested to find optimized solutions for different scenario. The detailed analysis shows the superiority of proposed model over other solutions which considered individual decision making models.

Keywords: AHP, fuzzy set theory, multi-criteria decision making, multi-objective integer linear programming, TOPSIS

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1222 Catalytic and Non-Catalytic Pyrolysis of Walnut Shell Waste to Biofuel: Characterisation of Catalytic Biochar and Biooil

Authors: Saimatun Nisa

Abstract:

Walnut is an important export product from the Union Territory of Jammy and Kashmir. After extraction of the kernel, the walnut shell forms a solid waste that needs to be managed. Pyrolysis is one interesting option for the utilization of this walnut waste. In this study microwave pyrolysis reactor is used to convert the walnut shell biomass into its value-added products. Catalytic and non-catalytic conversion of walnut shell waste to oil, gas and char was evaluated using a Co-based catalyst. The catalyst was characterized using XPS and SEM analysis. Pyrolysis temperature, reaction time, particle size and sweeping gas (N₂) flow rate were set in the ranges of 400–600 °C, 40 min, <0.6mm to < 4.75mm and 300 ml min−1, respectively. The heating rate was fixed at 40 °C min−1. Maximum gas yield was obtained at 600 °C, 40 min, particle size range 1.18-2.36, 0.5 molar catalytic as 45.2%. The liquid product catalytic and non-catalytic was characterized by GC–MS analyses. In addition, the solid product was analyzed by means of FTIR & SEM.

Keywords: walnut shell, biooil, biochar, microwave pyrolysis

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1221 Performance of Bimetallic Catalyst in the Oxidation of Volatile Organic Compounds

Authors: Faezeh Aghazadeh

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The catalytic activity of Pt/γ-Al₂O₃ and Pt-Fe/γ-Al₂O₃ catalysts was investigated to bring about the complete oxidation of 2-Propanol. Among them, Pt-Fe/γ-Al₂O₃ was found to be the most promising catalyst based on activity. The catalysts were characterized by (XRD), (SEM), (TEM) and ICP-AES techniques. Iron loadings on Pt/γ-Al₂O₃ had a great effect on catalytic activity, and Pt-Fe/γ-Al₂O₃ (1.75 wt% Fe) catalyst at calcination temperature 300°C was observed to be the most active, which might be contributed to the favorable synergetic effects between Pt and Fe, high activity and the well-dispersed bimetallic phase. The combustion of 2-Propanol in the vapor phase was carried out in a conventional flow U-shape glass reactor used in the differential mode at atmospheric pressure. 2-Propanol was analyzed by a gas chromatograph VARIAN 3800 CX equipped with an FID. As observed, better performance and activity were observed for Pt-Fe/Al₂O₃ bimetallic catalyst. These results indicate that the high dispersion on support gives a positive effect on catalytic activity.

Keywords: volatile organic compounds, bimetallic catalyst, catalytic activity, low temperature

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1220 Investigation of Parameters Affecting Copper Recovery from Brass Melting Dross

Authors: Sercan Basit, Muhlis N. Sarıdede

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Metal amounts of copper based compounds in the various wastes have been recovered successfully by hydrometallurgical treatment methods in the literature. X-ray diffraction pattern of the brass melting slag demonstrates that it contains sufficient amount of recoverable copper. Recovery of copper from brass melting dross by sulfuric acid leaching and the effect of temperature and acid and oxidant concentration on recovery rate of copper have been investigated in this study. Experiments were performed in a temperature-controlled reactor in sulfuric acid solution in different molarities using solid liquid ratio of 100 g/L, with leaching time of 300 min. Temperature was changed between 25 °C and 80 °C and molarity was between 0.5 and 3M. The results obtained showed that temperature has important positive effect on recovery whereas it decreases with time. Also copper was recovered in larger amounts from brass dross in the presence of H2O2 as an oxidant according to the case that oxidant was not used.

Keywords: brass dross, copper recovery, hydrogen peroxide, leaching

Procedia PDF Downloads 334
1219 Development and Analysis of SFR Control Rod Design

Authors: Lenka Dujčíková, Laurent Buiron, Ján Haščík

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The study is dedicated to safety management of SFR CAPRA core with CFV design improvements. In the case of CAPRA core, demands for reactivity control are higher than for reference core. There are two possible ways how to ensure the certain amount of negative reactivity. One option is to boost control rods worth. The Greater part of the study is aimed at the proposal of appropriate control rod design. At first, the European Fast Reactor (EFR) control rod design with high-enriched boron carbide B4C as absorber material was tested. Considering costly and difficult enrichment process, usage of natural boron carbide absorbator is desired. Obviously, the use of natural boron leads to CR worth reduction. In order to increase it to required value, moderator material was inserted inside the control rod. Various materials and geometric configurations were examined to find optimal solution corresponding with EFR based CR worth value.

Keywords: boron carbide, CAPRA core, control rod design, low void effect design, melting temperature, moderator material

Procedia PDF Downloads 505
1218 Recovery of Boron as Homogeneous Perborate Particles from Synthetic Wastewater by Integrating Chemical Oxo-Precipitation with Fluidized-Bed Homogeneous Granulation

Authors: Chiung-Chin Huang, Jui-Yen Lin, Yao-Hui Huang

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Among current techniques of boron removal from wastewater with high boron concentration, chemical oxo-precipitation (COP) is one of the promising methods due to its milder condition. COP uses H2O2 to transform boric acid to perborates which can easily precipitate with barium ions at room temperature. However, the generation of the waste sludge that requires sludge/water separation and sludge dewatering is troublesome. This work presents an innovative technology which integrates chemical oxo-precipitation (COP) with fluidized-bed homogeneous granulation (FBHG) to reclaim boron as homogeneous perborate particles. By conducting COP in a fluidized-bed reactor, the barium perborate can be granulated to form homogeneous particles (>1.0 mm) with low water content (< 10%). Under the suitable condition, more than 70% of boron can be recovered from 600 ppm of boron solution and the residual boron is lower than 100 ppm.

Keywords: barium, perborate, chemical oxo-precipitation, boron removal, fluidized-bed, granulation

Procedia PDF Downloads 324