Bio-inspired carbon electro-catalysis for the oxygen reduction reaction

We report the synthesis, characterisation and catalytic performance of two nature-inspired biomass-derived electro-catalysts for the oxygen reduction reaction in fuel cells. The catalysts were prepared via pyrolysis of a real food waste (lobster shells) or by mimicking the composition of lobster shells using chitin and CaCO3 particles followed by acid washing. The simplified model of artificial lobster was prepared for better reproducibility. The calcium carbonate in both samples acts as a pore agent, creating increased surface area and pore volume, though considerably higher in artificial lobster samples due to the better homogeneity of the components. Various characterisation techniques revealed the presence of a considerable amount of hydroxyapatite left in the real lobster samples after acid washing and a low content of carbon (23%), nitrogen and sulphur (<1%), limiting the surface area to 23 m2/g, and consequently resulting in rather poor catalytic activity. However, artificial lobster samples, with a surface area of ≈200 m2/g and a nitrogen doping of 2%, showed a promising onset potential, very similar to a commercially available platinum catalyst, with better methanol tolerance, though with lower stability in long time testing over 10,000 s.

Optimization of facility location-allocation problem in customer-driven supply chain

This paper develops and applies an integrated multiple criteria decision making approach to optimize the facility location-allocation problem in the contemporary customer-driven supply chain. Unlike the traditional optimization techniques, the proposed approach, combining the analytic hierarchy process (AHP) and the goal programming (GP) model, considers both quantitative and qualitative factors, and also aims at maximizing the benefits of deliverer and customers. In the integrated approach, the AHP is used first to determine the relative importance weightings or priorities of alternative locations with respect to both deliverer oriented and customer oriented criteria. Then, the GP model, incorporating the constraints of system, resource, and AHP priority is formulated to select the best locations for setting up the warehouses without exceeding the limited available resources. In this paper, a real case study is used to demonstrate how the integrated approach can be applied to deal with the facility location-allocation problem, and it is proved that the integrated approach outperforms the traditional costbased approach.

Multiple criteria optimization of contemporary logistics distribution network problems

In the contemporary customer-driven supply chain, maximization of customer service plays an equally important role as minimization of costs for a company to retain and increase its competitiveness. This article develops a multiple-criteria optimization approach, combining the analytic hierarchy process (AHP) and an integer linear programming (ILP) model, to aid the design of an optimal logistics distribution network. The proposed approach outperforms traditional cost-based optimization techniques because it considers both quantitative and qualitative factors and also aims at maximizing the benefits of deliverer and customers. In the approach, the AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to some critical customer-oriented criteria. The results of AHP prioritization are utilized as the input of the ILP model, the objective of which is to select the best warehouses at the lowest possible cost. In this article, two commercial packages are used: including Expert Choice and LINDO.

DFIG machine design for maximizing power output based on surrogate optimization algorithm

This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine's previous operational performance, the DFIG's stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.

Multi-criteria logistics distribution network design using SAS/OR

This paper explores the use of the optimization procedures in SAS/OR software with application to the contemporary logistics distribution network design using an integrated multiple criteria decision making approach. Unlike the traditional optimization techniques, the proposed approach, combining analytic hierarchy process (AHP) and goal programming (GP), considers both quantitative and qualitative factors. In the integrated approach, AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to both deliverer oriented and customer oriented criteria. Then, a GP model incorporating the constraints of system, resource, and AHP priority is formulated to select the best set of warehouses without exceeding the limited available resources. To facilitate the use of integrated multiple criteria decision making approach by SAS users, an ORMCDM code was implemented in the SAS programming language. The SAS macro developed in this paper selects the chosen variables from a SAS data file and constructs sets of linear programming models based on the selected GP model. An example is given to illustrate how one could use the code to design the logistics distribution network.

A fuzzy AHP based integer linear programming model for the multi-criteria transshipment problem

Purpose – The purpose of this research is to develop a holistic approach to maximize the customer service level while minimizing the logistics cost by using an integrated multiple criteria decision making (MCDM) method for the contemporary transshipment problem. Unlike the prevalent optimization techniques, this paper proposes an integrated approach which considers both quantitative and qualitative factors in order to maximize the benefits of service deliverers and customers under uncertain environments. Design/methodology/approach – This paper proposes a fuzzy-based integer linear programming model, based on the existing literature and validated with an example case. The model integrates the developed fuzzy modification of the analytic hierarchy process (FAHP), and solves the multi-criteria transshipment problem. Findings – This paper provides several novel insights about how to transform a company from a cost-based model to a service-dominated model by using an integrated MCDM method. It suggests that the contemporary customer-driven supply chain remains and increases its competitiveness from two aspects: optimizing the cost and providing the best service simultaneously. Research limitations/implications – This research used one illustrative industry case to exemplify the developed method. Considering the generalization of the research findings and the complexity of the transshipment service network, more cases across multiple industries are necessary to further enhance the validity of the research output. Practical implications – The paper includes implications for the evaluation and selection of transshipment service suppliers, the construction of optimal transshipment network as well as managing the network. Originality/value – The major advantages of this generic approach are that both quantitative and qualitative factors under fuzzy environment are considered simultaneously and also the viewpoints of service deliverers and customers are focused. Therefore, it is believed that it is useful and applicable for the transshipment service network design.

Optimal image colour extraction by differential evolution

Differential evolution is an optimisation technique that has been successfully employed in various applications. In this paper, we apply differential evolution to the problem of extracting the optimal colours of a colour map for quantised images. The choice of entries in the colour map is crucial for the resulting image quality as it forms a look-up table that is used for all pixels in the image. We show that differential evolution can be effectively employed as a method for deriving the entries in the map. In order to optimise the image quality, our differential evolution approach is combined with a local search method that is guaranteed to find the local optimal colour map. This hybrid approach is shown to outperform various commonly used colour quantisation algorithms on a set of standard images. Copyright © 2010 Inderscience Enterprises Ltd.

The development and optimisation of a fast pyrolysis process for bio-oil production

A two-tier study is presented in this thesis. The first involves the commissioning of an extant but at the time, unproven bubbling fluidised bed fast pyrolysis unit. The unit was designed for an intended nominal throughput of 300 g/h of biomass. The unit came complete with solids separation, pyrolysis vapour quenching and oil collection systems. Modifications were carried out on various sections of the system including the reactor heating, quenching and liquid collection systems. The modifications allowed for fast pyrolysis experiments to be carried out at the appropriate temperatures. Bio-oil was generated using conventional biomass feedstocks including Willow, beechwood, Pine and Miscanthus. Results from this phase of the research showed however, that although the rig was capable of processing biomass to bio-oil, it was characterised by low mass balance closures and recurrent operational problems. The problems included blockages, poor reactor hydrodynamics and reduced organic liquid yields. The less than optimal performance of individual sections, particularly the feed and reactor systems of the rig, culminated in a poor overall performance of the system. The second phase of this research involved the redesign of two key components of the unit. An alternative feeding system was commissioned for the unit. The feed system included an off the shelf gravimetric system for accurate metering and efficient delivery of biomass. Similarly, a new bubbling fluidised bed reactor with an intended nominal throughput of 500g/h of biomass was designed and constructed. The design leveraged on experience from the initial commissioning phase with proven kinetic and hydrodynamic studies. These units were commissioned as part of the optimisation phase of the study. Also as part of this study, two varieties each, of previously unreported feedstocks namely Jatropha curcas and Moringa olifiera oil seed press cakes were characterised to determine their suitability as feedstocks for liquid fuel production via fast pyrolysis. Consequently, the feedstocks were used for the production of pyrolysis liquids. The quality of the pyrolysis liquids from the feedstocks were then investigated via a number of analytical techniques. The oils from the press cakes showed high levels of stability and reduced pH values. The improvements to the design of the fast pyrolysis unit led to higher mass balance closures and increased organic liquid yields. The maximum liquid yield obtained from the press cakes was from African Jatropha press cake at 66 wt% on a dry basis.

Analytical techniques for the study of soft contact lens spoilation

Soft contact lens wear has become a common phenomenon in recent times. The contact lens when placed in the eye rapidly undergoes change. A film of biological material builds up on and in the lens matrix. The long term wear characteristics of the lens ultimately depend on this process. With time distinct structures made up of biological material have been found to build up on the lens. A fuller understanding of this process and how it relates to the lens chemistry could lead to contact lenses that are better tolerated by the eye. The tear film is a complex biological fluid, it is this fluid that bathes the lens during wear. It is reasonable to suppose that it is material derived from this source that accumulates on the lens. To understand this phenomenon it was decided to investigate the make up and conformation of the protein species that are found on and in the lens. As inter individual variations in tear fluid composition have been found it is important to be able to study the proteins on a single lens. Many of the analytical techniques used in bio research are not suitable for this study because of the lack of sensitivity. Work with poly acrylamide electrophoresis showed the possibility of analyzing the proteins extracted from a single lens. The development of a biotin avidin electro-blot and an enzyme linked aniibody electro-blot, lead to the high sensitivity detection and identification of the proteins present. The extraction of proteins from a lens is always incomplete. A method that analyses the proteins in situ would be a great advancement. Fourier transform infra red microscopy was developed to a point where a thin section of a contact lens could yield information about the proteins present and their conformation. The three dimensional structure of the gross macroscopic structures termed white spots was investigated using confocal laser microscopy.

Optimization of protein crystallization:the OptiCryst project

Protein crystallization has gained a new strategic and commercial relevance in the postgenomic era due to its pivotal role in structural genomics. Producing high quality crystals has always been a bottleneck to efficient structure determination, and this problem is becoming increasingly acute. This is especially true for challenging, therapeutically important proteins that typically do not form suitable crystals. The OptiCryst consortium has focused on relieving this bottleneck by making a concerted effort to improve the crystallization techniques usually employed, designing new crystallization tools, and applying such developments to the optimization of target protein crystals. In particular, the focus has been on the novel application of dual polarization interferometry (DPI) to detect suitable nucleation; the application of in situ dynamic light scattering (DLS) to monitor and analyze the process of crystallization; the use of UV-fluorescence to differentiate protein crystals from salt; the design of novel nucleants and seeding technologies; and the development of kits for capillary counterdiffusion and crystal growth in gels. The consortium collectively handled 60 new target proteins that had not been crystallized previously. From these, we generated 39 crystals with improved diffraction properties. Fourteen of these 39 were only obtainable using OptiCryst methods. For the remaining 25, OptiCryst methods were used in combination with standard crystallization techniques. Eighteen structures have already been solved (30% success rate), with several more in the pipeline.

The development of a novel Bio-MEMS filtration chip for the separation of specific cells in fluid suspension

In the clinical/microbiological laboratory there are currently several ways of separating specific cells from a fluid suspension. Conventionally cells can be separated based on size, density, electrical charge, light-scattering properties, and antigenic surface properties. Separating cells using these parameters can require complex technologies and specialist equipment. This paper proposes new Bio-MEMS (microelectromechanical systems) filtration chips manufactured using deep reactive ion etching (DRIE) technology that, when used in conjunction with an optical microscope and a syringe, can filter and grade cells for size without the requirement for additional expensive equipment. These chips also offer great versatility in terms of design and their low cost allows them to be disposable, eliminating sample contamination. The pumping mechanism, unlike many other current filtration techniques, leaves samples mechanically and chemically undamaged. In this paper the principles behind harnessing passive pumping are explored, modelled, and validated against empirical data, and their integration into a microfluidic device to separate cells from a mixed population suspension is described. The design, means of manufacture, and results from preliminary tests are also presented. © IMechE 2007.

Multi-frequency segmental bio-impedance device:design, development and applications

Bio-impedance analysis (BIA) provides a rapid, non-invasive technique for body composition estimation. BIA offers a convenient alternative to standard techniques such as MRI, CT scan or DEXA scan for selected types of body composition analysis. The accuracy of BIA is limited because it is an indirect method of composition analysis. It relies on linear relationships between measured impedance and morphological parameters such as height and weight to derive estimates. To overcome these underlying limitations of BIA, a multi-frequency segmental bio-impedance device was constructed through a series of iterative enhancements and improvements of existing BIA instrumentation. Key features of the design included an easy to construct current-source and compact PCB design. The final device was trialled with 22 human volunteers and measured impedance was compared against body composition estimates obtained by DEXA scan. This enabled the development of newer techniques to make BIA predictions. To add a ‘visual aspect’ to BIA, volunteers were scanned in 3D using an inexpensive scattered light gadget (Xbox Kinect controller) and 3D volumes of their limbs were compared with BIA measurements to further improve BIA predictions. A three-stage digital filtering scheme was also implemented to enable extraction of heart-rate data from recorded bio-electrical signals. Additionally modifications have been introduced to measure change in bio-impedance with motion, this could be adapted to further improve accuracy and veracity for limb composition analysis. The findings in this thesis aim to give new direction to the prediction of body composition using BIA. The design development and refinement applied to BIA in this research programme suggest new opportunities to enhance the accuracy and clinical utility of BIA for the prediction of body composition analysis. In particular, the use of bio-impedance to predict limb volumes which would provide an additional metric for body composition measurement and help distinguish between fat and muscle content.