Plasmonic photocatalysts of supported gold nanoparticles for organic conversions

This thesis is a comprehensive study of plasmonic gold photocatalysts for organic conversions. It presents the advantages of plasmonic gold photocatalysts in the selective oxidation, reduction, and acetalisation. It is discovered that plasmonic gold photocatalysts exhibit better catalytic performance (higher selectivity or activity) in these organic conversions. The study in this thesis highlights the capacity of plasmonic gold photocatalysts in harvesting solar energy for converting organic raw materials to value-added chemicals, and the great potential of gold photocatalysts in chemical production.

LCADesign : an integrated approach to automatic eco-efficiency assessment of commercial buildings

Buildings consume resources and energy, contribute to pollution of our air, water and soil, impact the health and well-being of populations and constitute an important part of the built environment in which we live. The ability to assess their design with a view to reducing that impact automatically from their 3D CAD representations enables building design professionals to make informed decisions on the environmental impact of building structures. Contemporary 3D object-oriented CAD files contain a wealth of building information. LCADesign has been designed as a fully integrated approach for automated eco-efficiency assessment of commercial buildings direct from 3D CAD. LCADesign accesses the 3D CAD detail through Industry Foundation Classes (IFCs) - the international standard file format for defining architectural and constructional CAD graphic data as 3D real-world objects - to permit construction professionals to interrogate these intelligent drawing objects for analysis of the performance of a design. The automated take-off provides quantities of all building components whose specific production processes, logistics and raw material inputs, where necessary, are identified to calculate a complete list of quantities for all products such as concrete, steel, timber, plastic etc and combines this information with the life cycle inventory database, to estimate key internationally recognised environmental indicators such as CML, EPS and Eco-indicator 99. This paper outlines the key modules of LCADesign and their role in delivering an automated eco-efficiency assessment for commercial buildings.

Preparation and characterisation of tri-calcium phosphate scaffolds with tunnel-like macro-pores for bone tissue engineering

Calcium Phosphate ceramics have been widely used in tissue engineering due to their excellent biocompatibility and biodegradability. In the physiological environment, they are able to gradually degrade, absorbed and promote bone growth. Ultimately, they are capable of replacing damaged bone with new tissue. However, their low mechanical properties limit calcium phosphate ceramics in load-bearing applications. To obtain sufficient mechanical properties as well as high biocompatibility is one of the main focuses in biomaterials research. Therefore, the current project focuses on the preparation and characterization of porous tri-calcium phosphate (TCP) ceramic scaffolds. Hydroxapatite (HA) was used as the raw material, and normal calcium phosphate bioglass was added to adjust the ratio between calcium and phosphate. It was found that when 20% bioglass was added to HA and sintered at 1400oC for 3 hours, the TCP scaffold was obtained and this was confirmed by X-ray diffraction (XRD) analysis. Test results have shown that by applying this method, TCP scaffolds have significantly higher compressive strength (9.98MPa) than those made via TCP powder (<3MPa). Moreover, in order to further increase the compressive strength of TCP scaffolds, the samples were then coated with bioglass. For normal bioglass coated TCP scaffold, compressive strength was 16.69±0.5MPa; the compressive strength for single layer mesoporous bioglass coated scaffolds was 15.03±0.63MPa. In addition, this project has also concentrated on sizes and shapes effects; it was found that the cylinder scaffolds have more mechanical property than the club ones. In addition, this project performed cell culture within scaffold to assess biocompatibility. The cells were well distributed in the scaffold, and the cytotoxicity test was performed by 3-(4,5)-dimethylthiahiazo(-z-y1)-3,5-di- phenytetrazoliumromide (MTT) assay. The Alkaline Phosphatase (Alp) activity of human bone marrow mesenchymal stem cell system (hBMSCs) seeded on scaffold expressed higher in vitro than that in the positive control groups in osteogenic medium, which indicated that the scaffolds were both osteoconductive and osteoinductive, showing potential value in bone tissue engineering.

A systematic approach for selecting lean strategies and assessing leanness in manufacturing organizations

Lean strategies have been developed to eliminate or reduce manufacturing waste and thus improve operational efficiency in manufacturing processes. However, implementing lean strategies requires a large amount of resources and, in practice, manufacturers encounter difficulties in selecting appropriate lean strategies within their resource constraints. There is currently no systematic methodology available for selecting appropriate lean strategies within a manufacturer's resource constraints. In the lean transformation process, it is also critical to measure the current and desired leanness levels in order to clearly evaluate lean implementation efforts. Despite the fact that many lean strategies are utilized to reduce or eliminate manufacturing waste, little effort has been directed towards properly assessing the leanness of manufacturing organizations. In practice, a single or specific group of metrics (either qualitative or quantitative) will only partially measure the overall leanness. Existing leanness assessment methodologies do not offer a comprehensive evaluation method, integrating both quantitative and qualitative lean measures into a single quantitative value for measuring the overall leanness of an organization. This research aims to develop mathematical models and a systematic methodology for selecting appropriate lean strategies and evaluating the leanness levels in manufacturing organizations. Mathematical models were formulated and a methodology was developed for selecting appropriate lean strategies within manufacturers' limited amount of available resources to reduce their identified wastes. A leanness assessment model was developed by using the fuzzy concept to assess the leanness level and to recommend an optimum leanness value for a manufacturing organization. In the proposed leanness assessment model, both quantitative and qualitative input factors have been taken into account. Based on program developed in MATLAB and C#, a decision support tool (DST) was developed for decision makers to select lean strategies and evaluate the leanness value based on the proposed models and methodology hence sustain the lean implementation efforts. A case study was conducted to demonstrate the effectiveness of these proposed models and methodology. Case study results suggested that out of 10 wastes identified, the case organization (ABC Limited) is able to improve a maximum of six wastes from the selected workstation within their resource limitations. The selected wastes are: unnecessary motion, setup time, unnecessary transportation, inappropriate processing, work in process and raw material inventory and suggested lean strategies are: 5S, Just-In-Time, Kanban System, the Visual Management System (VMS), Cellular Manufacturing, Standard Work Process using method-time measurement (MTM), and Single Minute Exchange of Die (SMED). From the suggested lean strategies, the impact of 5S was demonstrated by measuring the leanness level of two different situations in ABC. After that, MTM was suggested as a standard work process for further improvement of the current leanness value. The initial status of the organization showed a leanness value of 0.12. By applying 5S, the leanness level significantly improved to reach 0.19 and the simulation of MTM as a standard work method shows the leanness value could be improved to 0.31. The optimum leanness value of ABC was calculated to be 0.64. These leanness values provided a quantitative indication of the impacts of improvement initiatives in terms of the overall leanness level to the case organization. Sensitivity analsysis and a t-test were also performed to validate the model proposed. This research advances the current knowledge base by developing mathematical models and methodologies to overcome lean strategy selection and leanness assessment problems. By selecting appropriate lean strategies, a manufacturer can better prioritize implementation efforts and resources to maximize the benefits of implementing lean strategies in their organization. The leanness index is used to evaluate an organization's current (before lean implementation) leanness state against the state after lean implementation and to establish benchmarking (the optimum leanness state). Hence, this research provides a continuous improvement tool for a lean manufacturing organization.

Fractal dimension of dried foods : a correlation between microstructure and porosity

The quality of dried food is affected by a number of factors including quality of raw material, initial microstructure, and drying conditions. The structure of the food materials goes through deformations due to the simultaneous effect of heat and mass transfer during the drying process. Shrinkage and changes in porosity, microstructure and appearance are some of the most remarkable features that directly influence overall product quality. Porosity and microstructure are the important material properties in relation to the quality attributes of dried foods. Fractal dimension (FD) is a quantitative approach of measuring surface, pore characteristics, and microstructural changes [1]. However, in the field of fractal analysis, there is a lack of research in developing relationship between porosity, shrinkage and microstructure of different solid food materials in different drying process and conditions [2-4]. Establishing a correlation between microstructure and porosity through fractal dimension during convective drying is the main objective of this work.

Transcript and metabolite profiling for the evaluation of tobacco tree and poplar as feedstock for the bio-based industry

The global demand for food, feed, energy and water poses extraordinary challenges for future generations. It is evident that robust platforms for the exploration of renewable resources are necessary to overcome these challenges. Within the multinational framework MultiBioPro we are developing biorefinery pipelines to maximize the use of plant biomass. More specifically, we use poplar and tobacco tree (Nicotiana glauca) as target crop species for improving saccharification, isoprenoid, long chain hydrocarbon contents, fiber quality, and suberin and lignin contents. The methods used to obtain these outputs include GC-MS, LC-MS and RNA sequencing platforms. The metabolite pipelines are well established tools to generate these types of data, but also have the limitations in that only well characterized metabolites can be used. The deep sequencing will allow us to include all transcripts present during the developmental stages of the tobacco tree leaf, but has to be mapped back to the sequence of Nicotiana tabacum. With these set-ups, we aim at a basic understanding for underlying processes and at establishing an industrial framework to exploit the outcomes. In a more long term perspective, we believe that data generated here will provide means for a sustainable biorefinery process using poplar and tobacco tree as raw material. To date the basal level of metabolites in the samples have been analyzed and the protocols utilized are provided in this article.

Encapsulation of Hydrocortisone and Mesalazine in Zein Microparticles

Zein was investigated for use as an oral-drug delivery system by loading prednisolone into zein microparticles using coacervation. To investigate the adaptability of this method to other drugs, zein microparticles were loaded with hydrocortisone, which is structurally related to prednisolone; or mesalazine, which is structurally different having a smaller LogP and ionizable functional groups. Investigations into the in vitro digestibility, and the electrophoretic profile of zein, and zein microparticles were conducted to shed further insight on using this protein as a drug delivery system. Hydrocortisone loading into zein microparticles was comparable with that reported for prednisolone, but mesalazine loading was highly variable. Depending on the starting quantities of hydrocortisone and zein, the average amount of microparticles equivalent to 4 mg hydrocortisone, (a clinically used dose), ranged from 60-115 mg, which is realistic and practical for oral dosing. Comparatively, an average of 2.5 g of microparticles was required to deliver 250 mg of mesalazine (a clinically used dose), so alternate encapsulation methods that can produce higher and more precise mesalazine loading are required. In vitro protein digestibility revealed that zein microparticles were more resistant to digestion compared to the zein raw material, and that individual zein peptides are not preferentially coacervated into the microparticles. In combination, these results suggest that there is potential to formulate a delivery system based on zein microparticles made using specific subunits of zein that is more resistant to digestion as starting material, to deliver drugs to the lower gastrointestinal tract.

Auto-tune, and why we shouldn't be surprised that Britney can't sing

Put Britney Spears into a YouTube search and the third auto-fill on the list is “Britney Spears without Autotune”. Auto-Tune has become the music industry equivalent of doping in the Tour de France circa 2005; we know everyone’s doing it, but we still have a sense of surprise and outrage when it becomes public. In the last week or so a video has surfaced of the pop singer Britney Spears – with examples of her vocal before and after processing. Whether or not the “before” version is actually the raw material for the “after” version is difficult to say. What’s not difficult to say is that the “before” vocal is distinctly lacking in a demonstrable ability to sing in tune.

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.

Charged-controlled separation of nitrogen from natural gas using boron nitride fullerene

Natural gas (the main component is methane) has been widely used as a fuel and raw material in industry. Removal of nitrogen (N2) from methane (CH4) can reduce the cost of natural gas transport and improve its efficiency. However, their extremely similar size increases the difficulty of separating N2 from CH4. In this study, we have performed a comprehensive investigation of N2 and CH4 adsorption on different charge states of boron nitride (BN) nanocage fullerene, B36N36, by using a density functional theory approach. The calculational results indicate that B36N36 in the negatively charged state has high selectivity in separating N2 from CH4. Moreover, once the extra electron is removed from the BN nanocage, the N2 will be released from the material. This study demonstrates that the B36N36 fullerene can be used as a highly selective and reusable material for the separation of N2 from CH4. The study also provides a clue to experimental design and application of BN nanomaterials for natural gas purification.