Control and diagnostics of inductively coupled plasmas for chemical vapour deposition of nanocomposite carbon nitride-based films

Control and diagnostics of low-frequency (∼ 500 kHz) inductively coupled plasmas for chemical vapor deposition (CVD) of nano-composite carbon nitride-based films is reported. Relation between the discharge control parameters, plasma electron energy distribution/probability functions (EEDF/EEPF), and elemental composition in the deposited C-N based thin films is investigated. Langmuir probe technique is employed to monitor the plasma density and potential, effective electron temperature, and EEDFs/EEPFs in Ar + N2 + CH4 discharges. It is revealed that varying RF power and gas composition/pressure one can engineer the EEDFs/EEPFs to enhance the desired plasma-chemical gas-phase reactions thus controlling the film chemical structure. Auxiliary diagnostic tools for study of the RF power deposition, plasma composition, stability, and optical emission are discussed as well.

A novel approach for numerical simulation of plant tissue shrinkage during drying

Drying is a key processing techniques used in food engineering which demands continual developments on advanced analysis techniques in order to optimize the product and the process. In this regard, plant based materials are a frequent subject of interest where microstructural studies can provide a clearer understanding on the fundamental physical mechanisms involved. In this context, considering numerous challenges of using conventional numerical grid-based modelling techniques, a meshfree particle based model was developed to simulate extreme deformations of plant microstructure during drying. The proposed technique is based on a particle based meshfree method: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). A tissue model was developed by aggrading individual cells modelled with SPH-DEM coupled approach by initializing the cells as hexagons and aggregating them to form a tissue. The model also involves a middle lamella resembling real tissues. Using the model, different dried tissue states were simulated with different moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model is capable of simulating plant tissues at lower moisture contents which results in excessive shrinkage and cell wall wrinkling. Model predictions were compared with experimental findings and a fairly good agreement was observed both qualitatively and quantitatively.

Experimental evidences in bearing diagnostics for traction system of high speed trains

Rolling element bearings are the most critical components in the traction system of high speed trains. Monitoring their integrity is a fundamental operation in order to avoid catastrophic failures and to implement effective condition based maintenance strategies. Generally, diagnostics of rolling element bearings is usually performed by analyzing vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. Several papers have been published on this subject in the last two decades, mainly devoted to the development and assessment of signal processing techniques for diagnostics. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in specific industrial applications, particularly in rail industry, remains scarcely investigated. This paper is aimed at filling this knowledge gap, by addressing the diagnostics of bearings taken from the service after a long term operation on the traction system of a high speed train. Moreover, in order to test the effectiveness of the diagnostic procedures in the environmental conditions peculiar to the rail application, a specific test-rig has been built, consisting of a complete full-scale train traction system, able to reproduce the effects of wheeltrack interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is proposed, in order to limit their number.

Plasma-enhanced chemical vapor deposition of graphene nanostructures

Graphene has received great interest from researchers all over the world owing to its unique properties. Much of the excitement surrounding graphene is due to its remarkable properties and inherent quantum effects. These effects and properties make it a desirable material for the fabrication of new devices. Graphene has a plethora of potential uses including gas and molecular sensors, electronics, spintronics and optics [1-7]. Interestingly, some of these properties have been known about since before the material was even isolated due to a considerable amount of theoretical work and simulations. The material was to some extent a condensed matter modelers "toy" as it was used as a benchmark 2D material Graphene had been used for a long time as the fundamental building block of many other carbon structures...

Effect of plasma environment on synthesis of vertically aligned carbon nanofibers in plasma-enhanced chemical vapor deposition

We present a theoretical model describing a plasma-assisted growth of carbon nanofibers (CNFs), which involves two competing channels of carbon incorporation into stacked graphene sheets: via surface diffusion and through the bulk of the catalyst particle (on the top of the nanofiber), accounting for a range of ion- and radical-assisted processes on the catalyst surface. Using this model, it is found that at low surface temperatures, Ts, the CNF growth is indeed controlled by surface diffusion, thus quantifying the semiempirical conclusions of earlier experiments. On the other hand, both the surface and bulk diffusion channels provide a comparable supply of carbon atoms to the stacked graphene sheets at elevated synthesis temperatures. It is also shown that at low Ts, insufficient for effective catalytic precursor decomposition, the plasma ions play a key role in the production of carbon atoms on the catalyst surface. The model is used to compute the growth rates for the two extreme cases of thermal and plasma-enhanced chemical vapor deposition of CNFs. More importantly, these results quantify and explain a number of observations and semiempirical conclusions of earlier experiments.

A coupled SPH-DEM model for micro-scale structural deformations of plant cells during drying

A single plant cell was modeled with smoothed particle hydrodynamics (SPH) and a discrete element method (DEM) to study the basic micromechanics that govern the cellular structural deformations during drying. This two-dimensional particle-based model consists of two components: a cell fluid model and a cell wall model. The cell fluid was approximated to a highly viscous Newtonian fluid and modeled with SPH. The cell wall was treated as a stiff semi-permeable solid membrane with visco-elastic properties and modeled as a neo-Hookean solid material using a DEM. Compared to existing meshfree particle-based plant cell models, we have specifically introduced cell wall–fluid attraction forces and cell wall bending stiffness effects to address the critical shrinkage characteristics of the plant cells during drying. Also, a moisture domain-based novel approach was used to simulate drying mechanisms within the particle scheme. The model performance was found to be mainly influenced by the particle resolution, initial gap between the outermost fluid particles and wall particles and number of particles in the SPH influence domain. A higher order smoothing kernel was used with adaptive smoothing length to improve the stability and accuracy of the model. Cell deformations at different states of cell dryness were qualitatively and quantitatively compared with microscopic experimental findings on apple cells and a fairly good agreement was observed with some exceptions. The wall–fluid attraction forces and cell wall bending stiffness were found to be significantly improving the model predictions. A detailed sensitivity analysis was also done to further investigate the influence of wall–fluid attraction forces, cell wall bending stiffness, cell wall stiffness and the particle resolution. This novel meshfree based modeling approach is highly applicable for cellular level deformation studies of plant food materials during drying, which characterize large deformations.

Social licence to operate and the coal seam gas industry : lessons from social issues in established mining operations?

The recent growth of the coal seam gas industry has increased pressure on regional communities. Debate surrounding the industry is intense and a social licence to operate has yet to be granted to the industry in its entirety. This article presents an analysis of social issues surrounding the coal seam gas industry, making comparisons between two case studies: the Ranger and Jabiluka mines and the Yandicoogina mine. It presents the results of a desktop study, focussed on three topics: community identity; procedural justice and distributive justice, which provides a means for comparison and draws attention to central concerns. It is found that: power imbalances; changing community identities; potentially inequitable distributions of long term benefits and the process to distribute those benefits and negative perceptions of the industry as a whole serve to undermine the provision of a social licence to operate by communities and has the potential to impose significant negative impacts on companies within the industry.

Three dimensional digitisation of plant leaves

Realistic plant models are important for leaf area and plant volume estimation, reconstruction of growth canopies, structure generation of the plant, reconstruction of leaf surfaces and agrichemical spray droplet modelling. This article investigates several different scanning devices for obtaining a three dimensional digitisation of plant leaves with a point cloud resolution of 200-500μm. The devices tested were a Roland mdx-20, Microsoft Kinect, Roland lpx-250, Picoscan and Artec S. The applicability of each of these devices for scanning plant leaves is discussed. The most suitable tested digitisation device for scanning plant leaves is the Artec S scanner.

Calculation of the oxygen isotope discrimination factor for studying plant respiration

Measurement of discrimination against 18O during dark respiration in plants is currently accepted as the only reliable method of estimating the partitioning of electrons between the cytochrome and alternative pathways. In this paper, we review the theory of the technique and its application to a gas-phase system. We extend it to include sampling effects and show that the isotope discrimination factor, D, is calculated as –dln(1 + δ)/dlnO*, where δ is isotopic composition of the substrate oxygen and O*=[O2]/[N2] in a closed chamber containing tissue respiring in the dark. It is not necessary to integrate the expression but, if the integrated form is used, the resultant regression should not be constrained through the origin. This is important since any error in D will have significant effects on the estimation of the flux of electrons through the two pathways.

Priority threat management of invasive plant species in the Lake Eyre Basin

This project is led by scientists in conservation decision appraisal and brings together a group of experts working across the Lake Eyre Basin (LEB). The LEB covers a sixth of Australia, with an array of globally significant natural values that are threatened by invasive plants, among other things. Managers at various levels are investing in attempts to control, contain and eradicate these invasive plant species, under severe time and resources limitations. To date there has been no basin-wide assessment of which weed management strategies and locations provide the best investments for maximising outcomes for biodiversity per unit cost. Further, there has been no assessment of the extent of ecosystem intactness that may be lost without effective invasive plant species management strategies. Given that there are insufficient resources to manage all invasive plant species everywhere, this information has the potential to improve current investment decisions. Here, we provide a prioritisation of invasive plant management strategies in the LEB. Prioritisation was based on cost-effectiveness for biodiversity benefits. We identify the key invasive plant species to target to protect ecosystem intactness across the bioregions of the LEB, the level of investment required and the likely reduction in invasive species dominance gained per dollar spent on each strategy. Our focus is on strategies that are technically and socially feasible and reduce the likelihood that high impact invasive plant species will dominate native ecosystems, and therefore change their form and function. The outputs of this work are designed to help guide decision-making and further planning and investment in weed management for the Basin. Experts in weed management, policy-making, community engagement, biodiversity and natural values of the Basin, attended a workshop and agreed upon 12 strategies to manage invasive plants. The strategies focused primarily on 10 weeds which were considered to have a high potential for broad, significant impacts on natural ecosystems in the next 50 years and for which feasible management strategies could be defined. Each strategy consisted of one or more supporting actions, many of which were spatially linked to IBRA (Interim Biogeographical Regionalisation of Australia) bioregions. The first strategy was an over-arching recommendation for improved mapping, information sharing, education and extension efforts in order to facilitate the more specific weed management strategies. The 10 more specific weed management strategies targeted the control and/or eradication of the following high-impact exotic plants: mesquite, parkinsonia, rubber vine, bellyache bush, cacti, mother of millions, chinee apple, athel pine and prickly acacia, as well as a separate strategy for eradicating all invasive plants from one key threatened ecological community, the GAB (Great Artesian Basin dependant) mound springs. Experts estimated the expected biodiversity benefit of each strategy as the reduction in area that an invasive plant species is likely to dominate in over a 50-year period, where dominance was defined as more than 30% coverage at a site. Costs were estimated in present day terms over 50 years largely during follow up discussions post workshop. Cost-effectiveness was then calculated for each strategy in each bioregion by dividing the average expected benefit by the average annual costs. Overall, the total cost of managing 12 invasive plant strategies over the next 50 years was estimated at $1.7 billion. It was estimated that implementation of these strategies would result in a reduction of invasive plant dominance by 17 million ha (a potential 32% reduction), roughly 14% of the LEB. If only targeting Weeds of National Significance (WONS), the total cost was estimated to be $113 million over the next 50 years. Over the next 50 years, $2.3 million was estimated to eradicate all invasive plant species from the Great Artesian Basin Mound Springs threatened ecological community. Prevention and awareness programs were another key strategy targeted across the Basin and estimated at $17.5 million in total over 50 years. The cost of controlling, eradicating and containing buffel grass were the most expensive, over $1.5 billion over 50 years; this strategy was estimated to result in a reduction in buffel grass dominance of a million ha in areas where this species is identified as an environmental problem. Buffel grass has been deliberately planted across the Basin for pasture production and is by far the most widely distributed exotic species. Its management is contentious, having economic value to many graziers while posing serious threats to biodiversity and sites of high cultural and conservation interest. The strategy for containing and locally eradicating buffel grass was a challenge to cost based on expert knowledge, possibly because of the dual nature of this species as a valued pastoral grass and environmental weed. Based on our conversations with experts, it appears that control and eradication programs for this species, in conservation areas, are growing rapidly and that information on the most cost-effective strategies for this species will continue to develop over time. The top five most cost-effective strategies for the entire LEB were for the management of: 1) parkinsonia, 2) chinee apple, 3) mesquite, 4) rubber vine and 5) bellyache bush. Chinee apple and mother of millions are not WONS and have comparatively small populations within the semi-arid bioregions of Queensland. Experts felt that there was an opportunity to eradicate these species before they had the chance to develop into high-impact species within the LEB. Prickly acacia was estimated to have one of the highest benefits, but the costs of this strategy were high, therefore it was ranked 7th overall. The buffel grass strategy was ranked the lowest (10th) in terms of cost effectiveness. The top five most cost-effective strategies within and across the bioregions were the management of: 1) parkinsonia in the Channel Country, 2) parkinsonia in the Desert Uplands, 3) mesquite in the Mitchell Grass Downs, 4) parkinsonia in the Mitchell Grass Downs, and 5) mother of millions in the Desert Uplands. Although actions for several invasive plant species like parkinsonia and prickly acacia were concentrated in the Queensland part of the LEB, the actions involved investing in containment zones to prevent the spread of these species into other states. In the NT and SA bioregions of the LEB, the management of athel pine, parkinsonia and cacti were the main strategies. While outside the scientific research goals of study, this work highlighted a number of important incidental findings that led us to make the following recommendations for future research and implementation of weed management in the Basin: • Ongoing stakeholder engagement, extension and participation is required to ensure this prioritisation effort has a positive impact in affecting on-ground decision making and planning. • Short term funding for weed management was identified as a major reason for failure of current efforts, hence future funding needs to be secure and ongoing. • Improved mapping and information sharing is essential to implement effective weed management. • Due to uncertainties in the outcomes and impacts of management options, strategies should be implemented as part of an adaptive management program. The information provided in this report can be used to guide investment for controlling high-impact invasive plant species for the benefits of biodiversity conservation. We do not present a final prioritisation of invasive plant strategies for the LEB, and we have not addressed the cultural, socio-economic or spatial components necessary for an implementation plan. Cost-effectiveness depends on the objectives used; in our case we used the intactness of ecosystems as a surrogate for expected biodiversity benefits, measured by the extent that each invasive plant species is likely to dominate in a bioregion. When other relevant factors for implementation are considered the priorities may change and some actions may not be appropriate in some locations. We present the costs, ecological benefits and cost-effectiveness of preventing, containing, reducing and eradicating the dominance of high impact invasive plants through realistic management actions over the next 50 years. In doing so, we are able to estimate the size of the weed management problem in the LEB and provide expert-based estimates of the likely outcomes and benefits of implementing weed management strategies. The priorities resulting from this work provide a prospectus for guiding further investment in management and in improving information availability.

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.

Productive inefficiency analysis and toxic chemical substances in US and Japanese manufacturing sectors

Corporate social responsibility is imperative for manufacturing companies to achieve sustainable development. Under a strong environmental information disclosure system, polluting companies are disadvantaged in terms of market competitiveness, because they lack an environmentally friendly image. The objective of this study is to analyze productive inefficiency change in relation to toxic chemical substance emissions for the United States and Japan and their corresponding policies. We apply the weighted Russell directional distance model to measure companies productive inefficiency, which represents their production technology. The data encompass 330 US manufacturing firms observed from 1999 to 2007, and 466 Japanese manufacturing firms observed from 2001 to 2008. The article focuses on nine high-pollution industries (rubber and plastics; chemicals and allied products; paper and pulp; steel and non-ferrous metal; fabricated metal; industrial machinery; electrical products; transportation equipment; precision instruments) categorized into two industry groups: basic materials industries and processing and assembly industries. The results show that productive inefficiency decreased in all industrial sectors in the United States and Japan from 2001 to 2007. In particular, that of the electrical products industry decreased rapidly after 2002 for both countries, possibly because of the enforcement of strict environmental regulations for electrical products exported to European markets.

Decomposition of toxic chemical substance management in three U.S. manufacturing sectors from 1991 to 2008

This study analyzes toxic chemical substance management in three U.S. manufacturing sectors from 1991 to 2008. Decomposition analysis applying the logarithmic mean Divisia index is used to analyze changes in toxic chemical substance emissions by the following five factors: cleaner production, end-of-pipe treatment, transfer for further management, mixing of intermediate materials, and production scale. Based on our results, the chemical manufacturing sector reduced toxic chemical substance emissions mainly via end-of-pipe treatment. In the meantime, transfer for further management contributed to the reduction of toxic chemical substance emissions in the metal fabrication industry. This occurred because the environmental business market expanded in the 1990s, and the infrastructure for the recycling of metal and other wastes became more efficient. Cleaner production is the main contributor to toxic chemical reduction in the electrical product industry. This implies that the electrical product industry is successful in developing a more environmentally friendly product design and production process.

Determinants of plant performance dynamics : empirical analysis of the manufacturing sector in Indonesia, 1990-2000

We identify determinants of plant dynamics and find their differences before, during, and after the Asian financial crisis. The results show that the distinction of the crisis is important and the effects of the crisis do not seem to persist after 1998. Furthermore, we reject Gibrat's law as the right functional form to describe plant growth. We are not able to support empirically the theoretical results that smaller and efficient plants tend to grow faster than larger and inefficient plants with the exception of the crisis period. The results reflect that there was a trickle down effect of economic development.

miRPlant : an integrated tool for identification of plant miRNA from RNA sequencing data

Background Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction. Result We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram. Conclusions We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.