A novel method for purification of low grade diatomite powders in centrifugal fields

This study presented a novel method for purification of three different grades of diatomite from China by scrubbing technique using sodiumhexametaphosphate (SHMP) as dispersant combinedwith centrifugation. Effects of pH value and dispersant amount on the grade of purified diatomitewere studied and the optimumexperimental conditions were obtained. The characterizations of original diatomite and derived products after purification were determined by scanning electron microscopy (SEM), X-ray diffraction (XRD), infrared spectroscopy (IR) and specific surface area analyzer (BET). The results indicated that the pore size distribution, impurity content and bulk density of purified diatomite were improved significantly. The dispersive effect of pH and SHMP on the separation of diatomite from clay minerals was discussed systematically through zeta potential test. Additionally, a possible purification mechanism was proposed in the light of the obtained experimental results.

Purification of particles of subterranean clover red leaf virus using an industrial-grade cellulase

Particles of two isolates of subterranean clover red leaf virus were purified by a method in which infected plant tissue was digested with an industrial-grade cellulase, Celluclast® 2.0 L type X. The yields of virus particles using this enzyme were comparable with those obtained using either of two laboratory-grade cellulases, Cellulase type 1 (Sigma) and Driselase®. However, the specific infectivity or aphid transmissibility of the particles purified using Celluclast® was 10-100 times greater than those of preparations obtained using laboratory-grade cellulases or no enzyme. The main advantage of using Celluclast® is that at present in Australia its cost is only ca. 1% of laboratory-grade cellulases.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. 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 was 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 absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

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.

Evaluation of a pilot-scale oil extraction from microalgae for biodiesel production

Biodiesel derived from microalgae is one of a suite of potential solutions to meet the increasing demand for a renewable, carbon-neutral energy source. However, there are numerous challenges that must be addressed before algae biodiesel can become commercially viable. These challenges include the economic feasibility of harvesting and dewatering the biomass and the extraction of lipids and their conversion into biodiesel. Therefore, it is essential to find a suitable extraction process given these processes presently contribute significantly to the total production costs which, at this stage, inhibit the ability of biodiesel to compete financially with petroleum diesel. This study focuses on pilot-scale (100 kg dried microalgae) solvent extraction of lipids from microalgae and subsequent transesterification to biodiesel. Three different solvents (hexane, isopropanol (IPA) and hexane + IPA (1:1)) were used with two different extraction methods (static and Soxhlet) at bench-scale to find the most suitable solvent extraction process for the pilot-scale. The Soxhlet method extracted only 4.2% more lipid compared to the static method. However, the fatty acid profiles of different extraction methods with different solvents are similar, suggesting that none of the solvents or extraction processes were biased for extraction of particular fatty acids. Considering the cost and availability of the solvents, hexane was chosen for pilot-scale extraction using static extraction. At pilot-scale the lipid yield was found to be 20.3% of total biomass which is 2.5% less than from bench scale. Extracted fatty acids were dominated by polyunsaturated fatty acids (PUFAs) (68.94±0.17%) including 47.7±0.43 and 17.86±0.42% being docosahexaenoic acid (DHA) (C22:6) and docosapentaenoic acid (DPA) (C22:5, ω-3), respectively. These high amounts of long chain poly unsaturated fatty acids are unique to some marine microalgae and protists and vary with environmental conditions, culture age and nutrient status, as well as with cultivation process. Calculated physical and chemical properties of density, viscosity of transesterified fatty acid methyl esters (FAMEs) were within the limits of the biodiesel standard specifications as per ASTM D6751-2012 and EN 14214. The calculated cetane number was, however, significantly lower (17.8~18.6) compared to ASTM D6751-2012 or EN 14214-specified minimal requirements. We conclude that the obtained microalgal biodiesel would likely only be suitable for blending with petroleum diesel to a maximum of 5 to 20%.

Carbon nanotube membranes with ultrahigh specific adsorption capacity for water desalination and purification

Development of technologies for water desalination and purification is critical to meet the global challenges of insufficient water supply and inadequate sanitation, especially for point-of-use applications. Conventional desalination methods are energy and operationally intensive, whereas adsorption-based techniques are simple and easy to use for point-of-use water purification, yet their capacity to remove salts is limited. Here we report that plasma-modified ultralong carbon nanotubes exhibit ultrahigh specific adsorption capacity for salt (exceeding 400% by weight) that is two orders of magnitude higher than that found in the current state-of-the-art activated carbon-based water treatment systems. We exploit this adsorption capacity in ultralong carbon nanotube-based membranes that can remove salt, as well as organic and metal contaminants. These ultralong carbon nanotube-based membranes may lead to next-generation rechargeable, point-of-use potable water purification appliances with superior desalination, disinfection and filtration properties. © 2013 Macmillan Publishers Limited.

Biodiesel production from non-edible beauty leaf (Calophyllum Inophyllum) oil : process optimization using response surface methodology (RSM)

In recent years, the beauty leaf plant (Calophyllum Inophyllum) is being considered as a potential 2nd generation biodiesel source due to high seed oil content, high fruit production rate, simple cultivation and ability to grow in a wide range of climate conditions. However, however, due to the high free fatty acid (FFA) content in this oil, the potential of this biodiesel feedstock is still unrealized, and little research has been undertaken on it. In this study, transesterification of beauty leaf oil to produce biodiesel has been investigated. A two-step biodiesel conversion method consisting of acid catalysed pre-esterification and alkali catalysed transesterification has been utilized. The three main factors that drive the biodiesel (fatty acid methyl ester (FAME)) conversion from vegetable oil (triglycerides) were studied using response surface methodology (RSM) based on a Box-Behnken experimental design. The factors considered in this study were catalyst concentration, methanol to oil molar ratio and reaction temperature. Linear and full quadratic regression models were developed to predict FFA and FAME concentration and to optimize the reaction conditions. The significance of these factors and their interaction in both stages was determined using analysis of variance (ANOVA). The reaction conditions for the largest reduction in FFA concentration for acid catalysed pre-esterification was 30:1 methanol to oil molar ratio, 10% (w/w) sulfuric acid catalyst loading and 75 °C reaction temperature. In the alkali catalysed transesterification process 7.5:1 methanol to oil molar ratio, 1% (w/w) sodium methoxide catalyst loading and 55 °C reaction temperature were found to result in the highest FAME conversion. The good agreement between model outputs and experimental results demonstrated that this methodology may be useful for industrial process optimization for biodiesel production from beauty leaf oil and possibly other industrial processes as well.

Microalgae: An alternative source of biodiesel for the compression ignition (CI) engine

This thesis is a comprehensive study of microalgae biodiesel for the compression ignition engine. It examines microalgae growing conditions, the extraction process and physiochemical properties with a wide range of microalgae species. It also evaluates microalgae biodiesel with regards to engine performance and emission characteristics and explains the difficulties and potentiality of microalgae as a biodiesel. In doing so, an extensive analysis of different extraction methods and engine testing was conducted and a comprehensive study on microalgae biodiesel is presented.

Technoeconomic analysis of an integrated microalgae photobioreactor, biodiesel and biogas production facility

As fossil fuel prices increase and environmental concerns gain prominence, the development of alternative fuels from biomass has become more important. Biodiesel produced from microalgae is becoming an attractive alternative to share the role of petroleum. Currently it appears that the production of microalgal biodiesel is not economically viable in current environment because it costs more than conventional fuels. Therefore, a new concept is introduced in this article as an option to reduce the total production cost of microalgal biodiesel. The integration of biodiesel production system with methane production via anaerobic digestion is proved in improving the economics and sustainability of overall biodiesel stages. Anaerobic digestion of microalgae produces methane and further be converted to generate electricity. The generated electricity can surrogate the consumption of energy that require in microalgal cultivation, dewatering, extraction and transesterification process. From theoretical calculations, the electricity generated from methane is able to power all of the biodiesel production stages and will substantially reduce the cost of biodiesel production (33% reduction). The carbon emissions of biodiesel production systems are also reduced by approximately 75% when utilizing biogas electricity compared to when the electricity is otherwise purchased from the Victorian grid. The overall findings from this study indicate that the approach of digesting microalgal waste to produce biogas will make the production of biodiesel from algae more viable by reducing the overall cost of production per unit of biodiesel and hence enable biodiesel to be more competitive with existing fuels.

The harnessing of peptide-monolith constructs for single step plasmid DNA purification

The availability of synthetic peptides has paved the way for their use in tailor-made interactions with biomolecules. In this study, a 16mer LacI-based peptide was used as an affinity ligand to examine the scale up feasibility for plasmid DNA purification. First, the peptide was designed and characterized for the affinity purification of lacO containing plasmid DNA, to be employed as a high affinity ligand for the potential capturing of plasmid DNA in a single unit operation. It was found there were no discernible interactions with a control plasmid that did not encode the lacO nucleotide sequence. The dissociation equilibrium constant of the binding between the 16mer peptide and target pUC19 was 5.0 ± 0.5 × 10-8 M as assessed by surface plasmon resonance. This selectivity and moderated affinity indicate that the 16mer is suitable for the adsorption and chromatographic purification of plasmid DNA. The suitability of this peptide was then evaluated using a chromatography system with the 16mer peptide immobilized to a customized monolith to purify plasmid DNA, obtaining preferential purification of supercoiled pUC19. The results demonstrate the applicability of peptide-monolith supports to scale up the purification process for plasmid DNA using designed ligands via a biomimetic approach.

Versatility of polymethacrylate monoliths for chromatographic purification of biomolecules

Polymethacrylate monoliths, specifically poly(glycidyl methacrylate-co-ethylene dimethacrylate) or poly(GMA-co-EDMA) monoliths, are a new generation of chromatographic supports and are significantly different from conventional particle-based adsorbents, membranes, and other monolithic supports for biomolecule purification. Similar to other monoliths, polymethacrylate monoliths possess large pores which allow convective flow of mobile phase and result in high flow rates at reduced pressure drop, unlike particulate supports. The simplicity of the adsorbent synthesis, pH resistance, and the ease and flexibility of tailoring their pore size to that of the target biomolecule are the key properties which differentiate polymethacrylate monoliths from other monoliths. Polymethacrylate monoliths are endowed with reactive epoxy groups for easy functionalization (with anion-exchange, hydrophobic, and affinity ligands) and high ligand retention. In this review, the structure and performance of polymethacrylate monoliths for chromatographic purification of biomolecules are evaluated and compared to those of other supports. The development and use of polymethacrylate monoliths for research applications have grown rapidly in recent times and have enabled the achievement of high through-put biomolecule purification on semi-preparative and preparative scales.

Dewatering of microalgal culture for biodiesel production : exploring polymer flocculation and tangential flow filtration

Background: Conventional biodiesel production relies on trans-esterification of lipids extracted from vegetable crops. However, the use of valuable vegetable food stocks as raw material for biodiesel production makes it an unfeasibly expensive process. Used cooking oil is a finite resource and requires extra downstream processing, which affects the amount of biodiesel that can be produced and the economics of the process. Lipids extracted from microalgae are considered an alternative raw material for biodiesel production. This is primarily due to the fast growth rate of these species in a simple aquaculture environment. However, the dilute nature of microalgae culture puts a huge economic burden on the dewatering process especially on an industrial scale. This current study explores the performance and economic viability of chemical flocculation and tangential flow filtration (TFF) for the dewatering of Tetraselmis suecicamicroalgae culture. Results: Results show that TFF concentrates the microalgae feedstock up to 148 times by consuming 2.06 kWh m-3 of energy while flocculation consumes 14.81 kWhm-3 to concentrate the microalgae up to 357 times. Economic evaluation demonstrates that even though TFF has higher initial capital investment than polymer flocculation, the payback period for TFF at the upper extreme ofmicroalgae revenue is ∼1.5 years while that of flocculation is ∼3 years. Conclusion: These results illustrate that improved dewatering levels can be achieved more economically by employing TFF. The performances of these two techniques are also compared with other dewatering techniques.

Single step purification of plasmid DNA using peptide ligand affinity chromatography

Single step affinity chromatography was employed for the purification of plasmid DNA (pDNA), thus eliminating several steps compared with current commercial purification methods for pDNA. Significant reduction in pDNA production time and cost was obtained. This chromatographic operation employed a peptide-monolith construct to isolate pDNA from Escherichia coli (E. coli) impurities present in a clarified lysate feedstock. Mild conditions were applied to avoid any degradation of pDNA. The effect of some important parameters on pDNA yield was also evaluated with the aim of optimising the affinity purification of pDNA. The results demonstrate that 81% of pDNA was recovered and contaminating gDNA, RNA and protein were removed below detectable levels. © 2008 Elsevier B.V. All rights reserved.