Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Atomistic simulation of surface functionalization on the interfacial properties of graphene-polymer nanocomposites

Graphene has been increasingly used as nano sized fillers to create a broad range of nanocomposites with exceptional properties. The interfaces between fillers and matrix play a critical role in dictating the overall performance of a composite. However, the load transfer mechanism along graphene-polymer interface has not been well understood. In this study, we conducted molecular dynamics simulations to investigate the influence of surface functionalization and layer length on the interfacial load transfer in graphene polymer nanocomposites. The simulation results show that oxygen-functionalized graphene leads to larger interfacial shear force than hydrogen-functionalized and pristine ones during pull-out process. The increase of oxygen coverage and layer length enhances interfacial shear force. Further increase of oxygen coverage to about 7% leads to a saturated interfacial shear force. A model was also established to demonstrate that the mechanism of interfacial load transfer consists of two contributing parts, including the formation of new surface and relative sliding along the interface. These results are believed to be useful in development of new graphene-based nanocomposites with better interfacial properties.

Mechanochemical synthesis of aluminium nanoparticles and their deuterium sorption properties to 2 kbar

A mechanochemical synthesis process has been used to synthesise aluminium nanoparticles. The aluminium is synthesised via a solid state chemical reaction which is initiated inside a ball mill at room temperature between either lithium (Li) or sodium (Na) metal which act as reducing agents with unreduced aluminium chloride (AlCl3). The reaction product formed consists of aluminium nanoparticles embedded within a by-product salt phase (LiCl or NaCl, respectively). The LiCl is washed with a suitable solvent resulting in aluminium (Al) nanoparticles which are not oxidised and are separated from the byproduct phase. Synthesis and washing was confirmed using X-ray diffraction (XRD). Nanoparticles were found to be ∼25–100nm from transmission electron microscopy (TEM) and an average size of 55nm was determined fromsmall angle X-ray scattering (SAXS) measurements. As synthesised Al/NaCl composites, washed Al nanoparticles, and purchased Al nanoparticles were deuterium (D2) absorption tested up to 2 kbar at a variety of temperatures, with no absorption detected within system resolution.

Tensile properties of a boron/nitrogen-doped carbon nanotube–graphene hybrid structure

Doping is an effective approach that allows for the intrinsic modification of the electrical and chemical properties of nanomaterials. Recently, a graphene and carbon nanotube hybrid structure (GNHS) has been reported, which extends the excellent properties of carbon-based materials to three dimensions. In this paper, we carried out a first-time investigation on the tensile properties of the hybrid structures with different dopants. It is found that with the presence of dopants, the hybrid structures usually exhibit lower yield strength, Young’s modulus, and earlier yielding compared to that of a pristine hybrid structure. For dopant concentrations below 2.5% no significant reduction of Young’s modulus or yield strength could be observed. For all considered samples, the failure is found to initiate at the region where the nanotubes and graphene sheets are connected. After failure, monatomic chains are normally observed around the failure region. Dangling graphene layers without the separation of a residual CNT wall are found to adhere to each other after failure with a distance of about 3.4 Å. This study provides a fundamental understanding of the tensile properties of the doped graphene–nanotube hybrid structures, which will benefit the design and also the applications of graphene-based hybrid materials.

Numerical investigation of mechanical and thermal dynamic properties of the industrial transformer

Industrial transformer is one of the most critical assets in the power and heavy industry. Failures of transformers can cause enormous losses. The poor joints of the electrical circuit on transformers can cause overheating and results in stress concentration on the structure which is the major cause of catastrophic failure. Few researches have been focused on the mechanical properties of industrial transformers under overheating thermal conditions. In this paper, both mechanical and thermal properties of industrial transformers are jointly investigated using Finite Element Analysis (FEA). Dynamic response analysis is conducted on a modified transformer FEA model, and the computational results are compared with experimental results from literature to validate this simulation model. Based on the FEA model, thermal stress is calculated under different temperature conditions. These analysis results can provide insights to the understanding of the failure of transformers due to overheating, therefore are significant to assess winding fault, especially to the manufacturing and maintenance of large transformers.

Clinical dyslipidaemia is associated with changes in the lipid composition and inflammatory properties of apolipoprotein-B-containing lipoproteins from women with type 2 diabetes

The aim of this study was to use lipidomics to determine if the lipid composition of apolipoprotein-B-containing lipoproteins is modified by dyslipidaemia in type 2 diabetes and if any of the identified changes potentially have biological relevance in the pathophysiology of type 2 diabetes. VLDL and LDL from normolipidaemic and dyslipidaemic type 2 diabetic women and controls were isolated and quantified with HPLC and mass spectrometry. A detailed molecular characterisation of VLDL triacylglycerols (TAG) was also performed using the novel ozone-induced dissociation method, which allowed us to distinguish vaccenic acid (C18:1 n-7) from oleic acid (C18:1 n-9) in specific TAG species. Lipid class composition was very similar in VLDL and LDL from normolipidaemic type 2 diabetic and control participants. By contrast, dyslipidaemia was associated with significant changes in both lipid classes (e.g. increased diacylglycerols) and lipid species (e.g. increased C16:1 and C20:3 in phosphatidylcholine and cholesteryl ester and increased C16:0 [palmitic acid] and vaccenic acid in TAG). Levels of palmitic acid in VLDL and LDL TAG correlated with insulin resistance, and VLDL TAG enriched in palmitic acid promoted increased secretion of proinflammatory mediators from human smooth muscle cells. We showed that dyslipidaemia is associated with major changes in both lipid class and lipid species composition in VLDL and LDL from women with type 2 diabetes. In addition, we identified specific molecular lipid species that both correlate with clinical variables and are proinflammatory. Our study thus shows the potential of advanced lipidomic methods to further understand the pathophysiology of type 2 diabetes.

Effect of strong acids on red mud structural and fluoride adsorption properties

The removal of fluoride using red mud has been improved by acidifying red mud with hydrochloric, nitric and sulphuric acid. This investigation shows that the removal of fluoride using red mud is significantly improved if red mud is initially acidified. The acidification of red mud causes sodalite and cancrinite phases to dissociate, confirmed by the release of sodium and aluminium into solution as well as the disappearance of sodalite bands and peaks in infrared and X-ray diffraction data. The dissolution of these mineral phases increases the amount of available iron and aluminium oxide/hydroxide sites that are accessible for the adsorption of fluoride. The removal of fluoride is dependent on the charge of iron and aluminium oxide/hydroxides on the surface of red mud. Acidifying red mud with hydrochloric, nitric and sulphuric acid resulted in surface sites of the form ≡ SOH2+ and ≡ SOH. Optimum removal is obtained when the majority of surface sites are in the form ≡ SOH2+ as the substitution of a fluoride ion doesn’t cause a significant increase in pH. This investigation shows the importance of having a low and consistent pH for the removal of fluoride from aqueous solutions using red mud.

Tuneable resonance properties of graphene by nitrogen-dopant

Doping as one of the popular methods to manipulate the properties of nanomaterials has received extensive application in deriving different types of graphene derivates, while the understanding of the resonance properties of dopant graphene is still lacking in literature. Based on the large-scale molecular dynamics simulation, reactive empirical bond order potential, as well as the tersoff potential, the resonance properties of N-doped graphene were studied. The studied samples were established according to previous experiments with the N atom’s percentage ranging from 0.43%-2.98%, including three types of N dopant locations, i.e., graphitic N, pyrrolic N and pyridinic N. It is found that different percentages of N-dopant exert different influence to the resonance properties of the graphene, while the amount of N-dopant is not the only factor that determines its impact. For all the considered cases, a relative large percentage of N-dopant (2.98% graphitic N-dopant) is observed to introduce significant influence to the profile of the external energy, and thus lead to an extremely low Q-factor comparing with that of the pristine graphene. The most striking finding is that, the natural frequency of the defective graphene with N-dopant appears uniformly larger than that of the pristine defective graphene. While for the perfect graphene, the N-dopant shows less influence to its natural frequency. This study will enrich the current understanding of the influence of dopants on graphene, which will eventually shed lights on the design of different molecules-doped graphene sheet.

Reinforced insulation properties of epoxy resin/SiO2 nanocomposites by atmospheric pressure plasma modification

Nanocomposite dielectrics hold a promising future for the next generation of insulation materials because of their excellent physical, chemical, and dielectric properties. In the presented study, we investigate the use of plasma processing technology to further enhance the dielectric performance of epoxy resin/SiO2 nanocomposite materials. The SiO2 nanoparticles are treated with atmospheric-pressure non-equilibrium plasma prior to being added into the epoxy resin host. Fourier transform infrared spectroscopy (FTIR) results reveal the effects of the plasma process on the surface functional groups of the treated nanoparticles. Scanning electron microscopy (SEM) results show that the plasma treatment appreciably improves the dispersion uniformity of nanoparticles in the host polymer. With respect to insulation performance, the epoxy/plasma-treated SiO2 specimen shows a 29% longer endurance time than the epoxy/untreated SiO2 nanocomposite under electrical aging. The Weibull plots of the dielectric breakdown field intensity suggest that the breakdown strength of the nanocomposite with the plasma pre-treatment on the nanoparticles is improved by 23.3%.

Composition-dependent structural and electronic properties of α-(Si1−xCx)3N4

The highly unusual structural and electronic properties of the α-phase of (Si1-xCx)3N4 are determined by density functional theory (DFT) calculations using the Generalized Gradient Approximation (GGA). The electronic properties of α-(Si 1-xCx)3N4 are found to be very close to those of α-C3N4. The bandgap of α-(Si 1-xCx)3N4 significantly decreases as C atoms are substituted by Si atoms (in most cases, smaller than that of either α-Si3N4 or α-C3N4) and attains a minimum when the ratio of C to Si is close to 2. On the other hand, the bulk modulus of α-(Si1-xCx)3N 4 is found to be closer to that of α-Si3N 4 than of α-C3N4. Plasma-assisted synthesis experiments of CNx and SiCN films are performed to verify the accuracy of the DFT calculations. TEM measurements confirm the calculated lattice constants, and FT-IR/XPS analysis confirms the formation and lengths of C-N and Si-N bonds. The results of DFT calculations are also in a remarkable agreement with the experiments of other authors.

Structural, electronic, and optical properties of wurtzite and rocksalt InN under pressure

Structural stability, electronic, and optical properties of InN under high pressure are studied using the first-principles calculations. The lattice constants and electronic band structure are found consistent with the available experimental and theoretical values. The pressure of the wurtzite-to-rocksalt structural transition is 13.4 GPa, which is in an excellent agreement with the most recent experimental values. The optical characteristics reproduce the experimental data thus justifying the feasibility of our theoretical predictions of the optical properties of InN at high pressures.

Effect of doping with Co and/or Cu on electronic structure and optical properties of ZnO

This paper reports on ab initio numerical simulations of the effect of Co and Cu dopings on the electronic structure and optical properties of ZnO, pursued to develop diluted magnetic semiconductors vitally needed for spintronic applications. The simulations are based upon the Perdew-Burke-Enzerh generalized gradient approximation on the density functional theory. It is revealed that the electrons with energies close to the Fermi level effectively transfer only between Cu and Co ions which substitute Zn atoms, and are located in the neighbor sites connected by an O ion. The simulation results are consistent with the experimental observations that addition of Cu helps achieve stable ferromagnetism of Co-doped ZnO. It is shown that simultaneous insertion of Co and Cu atoms leads to smaller energy band gap, redshift of the optical absorption edge, as well as significant changes in the reflectivity, dielectric function, refractive index, and electron energy loss function of ZnO as compared to the doping with either Co or Cu atoms. These highly unusual optical properties are explained in terms of the computed electronic structure and are promising for the development of the next-generation room-temperature ferromagnetic semiconductors for future spintronic devices on the existing semiconductor micromanufacturing platform.

Mechanical model and superelastic properties of carbon microcoils with circular cross-section

Here we report on an unconventional Ni-P alloy-catalyzed, high-throughput, highly reproducible chemical vapor deposition of ultralong carbon microcoils using acetylene precursor in the temperature range 700-750 °C. Scanning electron microscopy analysis reveals that the carbon microcoils have a unique double-helix structure and a uniform circular cross-section. It is shown that double-helix carbon microcoils have outstanding superelastic properties. The microcoils can be extended up to 10-20 times of their original coil length, and quickly recover the original state after releasing the force. A mechanical model of the carbon coils with a large spring index is developed to describe their extension and contraction. Given the initial coil parameters, this mechanical model can successfully account for the geometric nonlinearity of the spring constants for carbon micro- and nanocoils, and is found in a good agreement with the experimental data in the whole stretching process.

Low-frequency dispersion properties of plasmas with variable-charge impurities

A theory of low-frequency dust-acoustic waves in low-temperature collisional plasmas containing variable-charge impurities is presented. Physical processes such as dust-charge relaxation, ionization-recombination of the electrons and ions, electron and ion elastic collisions with neutrals and dusts, as well as charging collisions with the dusts, are taken into account. Inclusion of these processes allows a balance of the plasma particles and thus a self-consistent determination of the stationary state of the unperturbed plasma. The generalized dispersion relation describing the propagation and damping of the dust acoustic waves is derived and analyzed. © 2000 American Institute of Physics.

A general approach to tune the vibration properties of the mounting system in the high-speed and heavy-duty engine

Majority of the current research on the mounting system has emphasised on the low/medium power engine, rare work has been reported for the high-speed and heavy-duty engine, the vibration characteristics of which exhibits significantly increased complexity and uncertainty. In this work, a general dynamics model was firstly established to describe the dynamic properties of a mounting system with various numbers of mounts. Then, this model was employed for the optimization of the mounting system. A modified Powell conjugate direction method was developed to improve the optimization efficiency. Basing on the optimization results obtained from the theoretical model, a mounting system was constructed for a V6 diesel engine. The experimental measurement of the vibration intensity of the mounting systems shows excellent agreement with the theoretical calculations, indicating the validity of the model. This dynamics model opens a new avenue in assessing and designing the mounting system for a high-speed and heavy-duty engine. On the other hand, the delineated dynamics model, and the optimization algorithm should find wide applications for other mounting systems, such as the power transmission system which usually has various uncertain mounts.