A techno-economic review of biomass gasification for production of chemicals

Gasification is a thermochemical process which can be used as a low-emission and highly efficient method to produce syngas and chemicals such as biomethanol and dimethyl ether (DME). In this paper, a review of technologies and methods for economic production of chemicals through gasification of biomass and other fuels has been carried out. A variety of techno-economic studies and analysis have been proposed in order to better understand the technical and economic assessments during the biomass gasification. Results showed that the methanol production cost for biomass (wood) is from 195 to 935 €/t, for waste residues is from 200 to 930 €/t, for coal is from 160 to 480 €/t, and for natural gas is from 90 to 290 €/t. It also concluded that fuel (wood) cost has positive linear relationship with ethanol production cost, meaning as the feedstock cost increases from 30 to 50 $/day-ton, the ethanol production cost enhances from 1.66 to 1.95 $/gal.     

A comprehensive review of renewable energy resources for electricity generation in Australia

Recently, renewable energy resources and their impacts have sparked a heated debate to resolve the Australian energy crisis. There are many projects launched throughout the country to improve network security and reliability. This paper aims to review the current status of different renewable energy resources along with their impacts on society and the environment. Besides, it provides for the first time the statistics of the documents published in the field of renewable energy in Australia. The statistics include information such as the rate of papers published, possible journals for finding relative paper, types of documents published, top authors, and the most prevalent keywords in the field of renewable energy in Australia. It will focus on solar, wind, biomass, geothermal and hydropower technologies and will investigate the social and environmental impacts of these technologies.     

On the prediction of solubility of alkane in carbon dioxide using the LSSVM algorithm

The increasing global energy demand and declination of oil reservoir in recent years cause the researchers attention focus on the enhancement of oil recovery approaches. One of the extensive applicable methods for enhancement of oil recovery, which has great efficiency and environmental benefits, is carbon dioxide injection. The CO₂ injection has various effects on the reservoir fluid, which causes enhancement of recovery. One of these effects is extraction of lighter components of crude oil, which straightly depends on solubility of hydrocarbons in carbon dioxide. In order to better understand of this parameter, in this study, Least squares support vector machine (LSSVM) algorithm was developed as a novel predictive tool to estimate solubility of alkane in CO₂ as function of carbon number of alkane, carbon dioxide density, pressure, and temperature. The predicting model outputs were compared with the extracted experimental solubility from literature statistically and graphically. The comparison showed the great ability and high accuracy of developed model in prediction of solubility.     

Using the red-near infrared spectral to estimate ground cover based on vegetative indices

Rapid and accurate estimation of Ground Cover (GC) at regional and global scales for agricultural management application is only possible by using remote sensing (RS). In this study, two Vegetation Indices (VIs) including the Perpendicular Vegetation Index (PVI) and Normalized Difference Vegetation Index (NDVI) were used for estimating GC. Since the parameters of the bare soil line have an important role in calculating GC based on PVI, this line was extracted based on the red-NIRmin (minimum near infrared) method with different intervals (0.0001, 0.0005, and 0.0010). In addition to traditional statistics such as Root Mean Square Error (RMSE), the sensitivity analysis (S) was also used to sharpen the accuracy of the models' estimations. The results indicated that the PVI-based method, in contrast to the NDVI-based approach, had a better performance in estimating GC of wheat. The highest correlation between the observed GC and the estimated GC based on PVI method was achieved in interval length of 0.0005 (R2 = 0.91) with RMSE equal to 8.82. This regression line (GCEST = -3.47 + 0.96 GCOBS) was not significantly different from the 1:1 line. As expected, the best estimation was achieved when the sensitivity of estimated GC based on PVI (length of the interval: 0.0005) was almost constant and low compared to the other models.     

Fabrication and characterization of highly efficient three component CuBTC/graphene oxide/PSF membrane for gas separation application

Metal organic frameworks (MOFs) with marvelous properties have aroused enormous attention for different application especially gas adsorption and separation. In this regard, fabrication of MOF hybrids with carbon based materials is new strategy to upgrade MOF performance. In this study CuBTC (Copper benzene-1,3,5-tricarboxylic acid)/graphene oxide (GO) composite was synthesized and characterized by BET, SEM, TGA, XRD and FT-IR techniques. Then CuBTC and CuBTC/GO composite were incorporated into polysulfone (PSF) polymer to construct mixed matrix membranes (MMMs). The obtained membranes were characterized by SEM, TGA, XRD and tensile tests and their gas permeability was measured. The results were compared to those of CuBTC/PSF MMMs. It was revealed that CuBTC/GO composite as filler showed superior performance relative to CuBTC. For instance, 15 wt% loading of CuBTC/GO in PSF represented outstanding gas separation behavior while the same loading of CuBTC in PSF deteriorated performance of MMM. Well particle dispersion and favorable polymer-filler interaction were responsible for such observed difference. A high H₂/CH₄ and H₂/N₂ selectivity of 80.03 and 70.46 were recorded for CuBTC/GO in PSF (15 wt%) compared to 44.56 and 40.92 for CuBTC in PSF (15 wt%).     

Monitoring process variation using modified EWMA

A new control chart, namely, modified exponentially weighted moving average (EWMA) control chart, for monitoring the process variance is introduced in this work by following the recommendations of Khan et al.¹⁵ The proposed control chart deduces the existing charts to be its special cases. The necessary coefficients, which are required for the construction of modified EWMA chart, are determined for various choices of sample sizes and smoothing constants. The performance of the proposed modified EWMA is evaluated in terms of its run length (RL) characteristics such as average RL and standard deviation of RL. The efficiency of the modified EWMA chart is investigated and compared with some existing control charts. The comparison reveals the superiority of proposal as compared with other control charts in terms of early detection of shift in process variation. The application of the proposal is also demonstrated using a real-life dataset.     

Modeling dynamic viscosity of n-alkanes using LSSVM technique

One of the important thermophysical properties is viscosity which expresses the resistance of fluid to flow. The least squares support vector machine (LSSVM) algorithm is proposed as a novel method for prediction of dynamic viscosity of different normal alkanes in a wide range of pressure and temperature. As this study is purely computational, 228 experimental data points were gathered from literature for training and validation of the model. The outcomes of the LSSVM algorithm were compared with the actual data with acceptable average absolute relative deviation and the coefficient of determination (R²) of 1.014 and 0.9968, respectively. The comparisons showed that the predicting model has the potential of prediction of n-alkane dynamic viscosity in terms of pressure, temperature, and carbon number of n-alkane, so this strategy can be used as a simple tool for predicting the behavior of reservoir fluids.     

Controlled release of fluorouracil (5-FU) from chitosan-co-poly(ethylene glycol)/ poly(glycerol sebacate)-co-poly(ethylene glycol)-coated iron oxide

A blend of polyglycerol sebacate-poly ethylene glygol/chitosan-poly ethylene glycol-coated iron oxide (PGS-PEG/CS-PEG@Fe₃O₄) nanoparticles for 5FU delivery was prepared by reverse ultrasonic emulsification method. To enhance polymers’ solubility, PEG was grafted. Chemical characterization was performed through Fourier transformed infrared and proton nuclear magnetic resonance spectra. In vitro assay revealed that release profile of 5FU-loaded PGS-PEG/CS-PEG@Fe₃O₄ is sustained. Moreover, cytotoxicity was analyzed on HT29 cell line at the presence of external magnetic field using the lactate dehydrogenase and Alamar Blue. Results illustrate that (PGS-PEG/CS-PEG@Fe₃O₄) is promising to use as a carrier for 5FU anticancer agent with sustained tailored release.     

Salt-assisted solution combustion synthesis of NiFe2O4: Effect of salt type

The effects of three types of salt including NaF, KCl, and NaCl on the properties of NiFe₂O₄ nanoparticles using salt-assisted solution combustion synthesis (SSCS) have been investigated. The synthesized powders were evaluated by SEM, TEM, FTIR, XRD, and VSM analysis. Also, the specific surface area (SSA), as well as size distribution and volume of the porosities of NiFe₂O₄ powders were determined by the BET apparatus. The visual observations showed that the intensity and time of combustion synthesis of nanoparticles have been severely influenced by the type of salt. The highest crystallinity was observed in the synthesized powder using NaCl. The SSA has also been correlated completely to the type of salt. The quantities of SSA was achieved about 91.62, 64.88, and 47.22 m²g^-1 for the powders synthesized by KCl, NaCl, and NaF respectively. Although the magnetic hysteresis loops showed the soft ferromagnetic behavior of the NiFe₂O₄ nanoparticles in all conditions, KCl salt could produce the particles with the least coercivity and remanent magnetization. Based on the present study, the salt type is a key parameter in the SSCS process for the preparation of spinel ferrites. Thermodynamic evaluation also showed that the melting point and heat capacity are important parameters for the proper selection of the salt.     

Effect of fuel type on structural and physicochemical properties of solution combustion synthesized CoCr2O4 ceramic pigment nanoparticles

Due to importance and wide applications, CoCr₂O₄ ceramic pigment nanoparticles were synthesized via low-temperature solution combustion route by different fuels including ethylenediamine/oxalic acid, ethylenediamine/citric acid, oxalic acid/citric acid and ethylenediamine/oxalic acid/citric acid. Physicochemical properties of the synthesized samples were determined by different techniques such as fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM) and energy dispersive X-ray spectroscopy (EDX) and color/optical properties were evaluated based on CIELAB system by spectrophotometer. Moreover, thermodynamic considerations of combustion reactions for CoCr₂O₄ nanopigments formation in terms of calculated adiabatic flame temperature and enthalpy of combustion reaction were studied. The Comparison of results and data showed that cobalt chromite pigment nanoparticles synthesized by using ethylenediamine/citric acid and ethylenediamine/oxalic acid/citric acid fuels exhibited higher purity, smaller crystallite size and lower degree agglomeration.