•Carbonization with liquid water produced a hydrochar with an HHV of 27.66MJkg−1.•Liquid water carbonization required 1/3 the heating energy compared to water vapor.•Vapor water produced a 42% ...increase in ash content compared to liquid water.•Liquid water carbonization reduced potassium content of corn husk by 90%.•Liquid water treated hydrochar produced the most coal-like combustion performance.
The effect of the phase during the hydrothermal carbonization (HTC) of corn husks was studied to determine whether liquid water or water vapor was the more suitable reaction medium, as well as if the HTC process could produce a solid fuel (hydrochar) from green corn husks that was comparable to coal. Using liquid water for the HTC process produced a hydrochar with an increased heating value (27.66MJkg−1) compared to using water vapor (25.46MJkg−1). HTC using liquid water removed 90% of the potassium contained in raw corn husk, whereas the water vapor HTC treatment removed 58%. The liquid water treated hydrochar contained a 29% decrease in ash content compared to the water vapor hydrochar. Using a TGA-FTIR analysis the liquid treated hydrochar demonstrated a more coal-like combustion in terms of mass loss and heat production, compared to the vapor treated hydrochar.
Solid hydrochar (HC) produced by hydrothermal carbonization (HTC) of tomato plant biomass from a greenhouse (GH) was assessed for different inhouse applications, including fuel, seed germination, and ...leached GH nutrient feed (GNF) wastewater treatment. Completed experiments showed encouraging results. HC was revealed to be an efficient renewable fuel, having peat-like characteristics with high heating value of about 26.0 MJ/kg and very low clinker forming potential. This would allow the use of HC as fuel for GH heating as a substitute to costly natural gas, or it could be commercialized after pelletizing. Experiments with soil application showed substantial potential for the produced HC in better seed germination of tomato plants. Another benefit from use of the produced HC is as a soil additive, which would also contribute to environmental emission reduction. Results suggest that the generated HC can remove about 6–30% of nutrients from leached-GNF wastewater. This would be an essential treatment in the reduction of nutrients from leached water from GH operations, and thus could prevent/reduce eutrophication. The exhausted HC after treatment application could then be reused for soil remediation. Overall, the paper highlights the potential applications of hydrothermal treatment in valorization of low-valued GH TPB waste, resulting in a circular economy.
Iron-based industries are one of the main contributors to greenhouse gas (GHG) emissions. Partial substitution of fossil carbon with renewable biocarbon (biomass) into the blast furnace (BF) process ...can be a sustainable approach to mitigating GHG emissions from the ironmaking process. However, the main barriers of using biomass for this purpose are the inherent high alkaline and phosphorous contents in ash, resulting in fouling, slagging, and scaling on the BF surface. Furthermore, the carbon content of the biomass is considerably lower than coal. To address these barriers, this research proposed an innovative approach of combining two thermochemical conversion methods, namely hydrothermal carbonization (HTC) and slow pyrolysis, for converting biomass into suitable biocarbon for the ironmaking process. Miscanthus, which is one of the most abundant herbaceous biomass sources, was first treated by HTC to obtain the lowest possible ash content mainly due to reduction in alkali matter and phosphorous contents, and then subjected to slow pyrolysis to increase the carbon content. Design expert 11 was used to plan the number of the required experiments and to find the optimal condition for HTC and pyrolysis steps. It was found that the biocarbon obtained from HTC at 199 °C for 28 min and consecutively pyrolyzed at 400 °C for 30 min showed similar properties to pulverized coal injection (PCI) which is currently used in BFs due to its low ash content (0.19%) and high carbon content (79.67%).
Recovery and reuse of valuable chemicals from hydrothermal carbonization process liquid (HTC-PL) from tomato plant biomass (TPB) was conducted. Different HTC-PLs were characterized with FTIR and ...Py-GC-MS analyses revealing the presence of low molecular weight linear, cyclic, and aromatics compounds in the HTC-PL. Separation of these valuable chemicals by fractional distillation resulted in eutectic constrains. Solvent extraction separation followed by solvent recovery and reuse provided encouraging results. The non-polar portion of HTC-PLs were extracted by using n-hexane (C6H14), and diethyl ether (C2H5)2O solvents with 8.5 and 4.3% recoveries, respectively. Characterization by FTIR and Py-GC-MS revealed petrol fuel like materials in the extracts of C6H14 and (C2H5)2O, irrespective of higher boiling components. Blends of both non-polar extracts were flame tested revealing good burning characteristics with minimal smoke and residue. Bench scale spirit lamp tests showed the blend would be very useful for greenhouse winter heating. The polar extracts using methylene chloride (CH2Cl2) resulted in about 55% recovery. Py-GC-MS analysis revealed acetic acid and 5-Hydroxymethyl furfural (5HMF) majors in the extract along with related derivatives. 5HMF is a valued chemical and demonstrated to be a useful building block for many industrial applications, and flatform chemical for various synthesis. Other identified minor components of HTC-PL were vanillin, divinyl terephthalate, and syringol. After the extractions of polar and non-polar components in three steps, the HTC-PL residue was applied as nutrient source after maintaining pH (5.6) and concentration (TOC, 100–200 mg/L) to typical greenhouse plants. Plant growth was encouraging. The paper discusses all the potential valued reuse applications of HTC-PL in greenhouses without discharges, which contributes to environmental protection and economic benefits.
Hydrochar was produced from neutral sulfite semi-chemical (NSSC) red liquor as a possible bio-based solid fuel for use in power generation facilities. Hydrothermal conversion (HTC) experiments were ...conducted using a fixed liquor-to-water volume ratio of 1:8 and reaction time of 3 h. Solutions were processed using different chemical additives, pH and temperature conditions to determine the optimum conditions required for producing a high energy content solid fuel. The hydrochar samples produced were analyzed by ultimate, thermogravimetric (TGA) and Fourier transform infrared spectroscopy (FTIR) analyses to determine physicochemical properties that are important for utilization as a fuel. The residual process liquids were also analyzed to better understand the effect of HTC process conditions on their properties. It was determined that the optimum conditions for producing a solid fuel was at a reaction temperature of 250 degree C, in the presence of acetic acid at pH 3. The maximum energy content (HHV) of the hydrochar produced from red liquor at this condition was 29.87 MJ/kg, and its ash content was 1.12 wt.%. This result reflects the effect of increasing reaction temperature on the physicochemical characteristics of the hydrochar. The increase of HTC temperature significantly reduces the ash content of the hydrochar, leads to a significant increase in the carbon content of the hydrochar, and a reduction in both the oxygen and hydrogen content. These effects suggests an increase in the degree of condensation of the hydrochar products, and consequently the formation of a high energy content material. Based on TGA and FTIR analyses, hydrochars prepared at high HTC temperature showed lower adsorbed moisture, hemicellulose and cellulose contents, with enrichment in content of higher temperature volatiles, such as lignin.
Clustering of vertices in complex networks to detect communities is an open challenge due to its unknown and hidden properties and broad areas. Complex networks occur in various areas and ...interdisciplinary fields be it biological, social, chemical, electrical or any other. Numerous methods have been proposed with significant contributions to detect communities but still its nature of properties, throw us a challenge in detecting meaningful communities in real networks. Communities are built through nodes and each node has its own significance. Similarity among nodes through their neighbors suggests common interest of those nodes. The idea is to identify small groups of similar nodes locally and gradually built communities using global information. Moreover, we are not taking any seed nodes and consider each node an important player. The identification of local structures and demarcating their boundaries possess another challenge. Here, we propose Local Group Assimilation (LGA) algorithm that identifies clusters or communities in a network graph using both local and global structure information. The algorithm compares two adjacent nodes by neighborhood similarity measure and picks the highest value pair. The highest value pairs of nodes are grouped together in such a manner that it generates initial clusters of various sizes. The local groups are merged further in iterative manner that maximizes inter cluster edge density between them. Our algorithm detects small significant and relevant communities on real networks that assimilate into larger ones with promising results. We evaluated our algorithm in both real world networks and synthetic benchmark networks and compared it with most popular state-of-the-art community detection algorithms. Our experimental results show that the LGA algorithm detects significant communities in complex networks comparable to most popular algorithms and can be used in real networks to detect communities.
•Community detection through clustering nodes is proposed in three stages.•Neighborhood similarity and inter cluster edge density is taken as measures to group nodes.•Both local and global information of networks are used for detecting communities.•Our algorithm performs well in real world networks.
Experimental investigations on the technical viability of solid oxide fuel cells to replace internal combustion engines in automobiles have increased in recent years. However, the performance and ...stability of catalysts in the presence of carbon is key for the commercial success of fuel cell reformers. In this paper, finite element method was used to study the effect of coke deposition on heat and mass transfer during the catalytic partial oxidation of ethanol in a packed bed reactor. The properties of Ni/Al2O3 catalyst bed were investigated after being subjected to several hours of carbon buildup. Bed permeability, porosity, and temperature distribution were significantly affected after just 1500 s of reaction time. It was observed that void fraction and permeability became nonuniform across the bed. These two parameters decreased with axial position, and the difference became more pronounced with time. A decrease in bed porosity reduced the bed temperature due to an increase in effective thermal conductivity and ethanol conversion and hydrogen selectivity decreased as a result. Thus, it was concluded that heat transfer becomes a limiting factor in reforming reactions in the presence of carbon. Production distribution before deactivation was also studied, and it was observed that a maximum ethanol conversion of 100% was achieved at 600 °C and a C/O ratio of 1.0. Finally, results from the reactions were compared to that of a different study to validate the reaction mechanism and similar results were found in the literature.
The life cycle (LC) of ethanol extracted from Miscanthus has been evaluated to identify the potential location for the Miscanthus-based ethanol industry in Ontario, Canada to mitigate greenhouse gas ...(GHG) emissions and minimize the production cost of ethanol. Four scenarios are established considering the land classes, land use, and cropping patterns in Ontario, Canada. The net energy consumption, emissions, and cost of ethanol are observed to be dependent on the processing plant location and scenarios. The net energy consumption, emissions, and cost vary from 12.9 MJ/L to 13.4 MJ/L, 0.79 $/L to 0.84 $/L, and 0.45 kg-CO2e/L to 1.32 kg-CO2e/L, respectively, which are reliant on the scenarios. Eastern Ontario has emerged as the best option. This study reveals that Miscanthus is a potential feedstock for the ethanol industries in Ontario, even if it is cultivated on marginal land. This study also highlights the contribution of energy crops (Miscanthus) to avoid the potential technical and economic constraints of lignocellulosic biomass for the renewable energy industry. Miscanthus may help avoid competition with food crops for prime land (higher quality land that is suitable for food crops), avoid the food versus fuel debate, help meet the ethanol demand, and achieve the GHG emissions abatement target of Canada.
The influential spreaders play a significant role in maximizing or controlling any spreading process in a network. In the literature, many methods have been proposed to identify influential ...spreaders. In this article, we classify all the methods mainly into four categories, such as local centrality, global centrality, semi-global centrality and hybrid centrality. Among them, we have found semi-global centrality based methods have immense potential in identifying the influential spreaders from various types of network structures. However, we have observed that the existing semi-global centrality methods can identify the spreaders from the periphery of a network, where the nodes in the periphery are loosely coupled and the collective influence in the peripheral region of a spreading process will be nominal. We propose a new indexing method “semi-global triangular centrality”, which does not consider the best spreaders from the periphery. The proposed method maximizes the total collective influence of a spreading process by selecting the best spreaders from the dense part of a network. We have examined the performance of the proposed method using the Susceptible–Infected–Recovered epidemic model and applied to nine real-networks. The experimental result reveals that the proposed method performs better than the other centrality methods in terms of spreading dynamics.
•Proposes a semi-global triangular centrality based on triangle pattern of a network.•The proposed method identifies the best spreaders from dense part of a network.•The proposed method yields a significant spreading performance.•The method is applicable in different scales and varieties of networks.
•A single ranking method will not yield best performance for all varieties of network.•It is a difficult task to measure the percentage completeness of a network structure.•We propose a new ranking ...method “Weighted kshell degree neighborhood method”.•The proposed method is applicable to different varieties and large-scale networks.
Due to the fast and worldwide growth of the social network, it has become a potent platform for broadcasting any information. Through the network, people can easily reach to a mass, can easily propagate a piece of information within a short time. Considering the advantages, especially to accelerate the information spreading or controlling the spreading, the organizations want to exploit the social network to its best. However, as we know, the network is formed by connecting one node (i.e., user) to another node, and it is not that all the nodes will be effective equally in spreading. Because it depends on many factors and one of them is their topological position in the network. Automatically finding the effective nodes (the influential spreaders) from a network is a real challenge. In the literature, kshell decomposition and degree centrality are the two popular measures for identifying the influential spreaders from a network. Moreover, it is more challenging in identifying the influential spreaders when network connectivity structure varies from network to network. It has been found that the kshell decomposition method works better in the complete global network connectivity structures and neighbors’ degree method in the incomplete global network connectivity structures. But the degree of completeness of the network connectivity structures also vary. Under this circumstance, only the kshell method or only the neighbors’ degree method will not be able to obtain the best influential spreaders. To overcome this problem, this article proposes an indexing method weighted kshell degree neighborhood which is a composition of kshell and degree through tunable parameters. We have evaluated the effectiveness of the proposed method using different real networks and the Susceptible-Infected-Recovered (SIR) spreading epidemic model. The results show that the proposed method can significantly obtain the best spreading dynamics from different varieties of network connectivity structures and outperforms the other existing indexing methods.
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