991 resultados para optimize
Resumo:
Unnatural amino acids are a growing class of intermediates required for pharmaceuticals, agrochemicals and other industrial products. However, no single method has proven sufficiently versatile to prepare these compounds broadly at scale. To address this need, we have developed a general chemoenzymatic process to prepare enantiomerically pure L- and D-amino acids in high yield by deracemization of racemic starting materials. This method involves the concerted action of an enantioselective oxidase biocatalyst and a non-selective chemical reducing agent to effect the stereoinversion of one enantiomer and can result in an enantiomeric excess of >99% from the starting racemate, and product yields of over 90%. This approach compares very favourably with resolution processes, which have a maximum single-pass yield of 50%. We have developed efficient methods to adapt the process towards new target compounds and to optimize key factors that influence process efficiency and offer competitive economics at scale.
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Two varieties of grapes, white grape and red grape grown in the Campania region of Italy were selected for the study of drying characteristics, moisture diffusion, quality changes (colour) and shrinkage behaviour. Comparisons were made with treated and untreated grapes under constant drying condition of 50o C in a conventional drying system. This temperature was selected to represent farm drying conditions. Grapes were purchased from a local market from the same supplier to maintain the same size of grapes and same properties. An abrasive physical treatment was used as pretreatment. The drying curves were constructed and drying kinetics was calculated using several commonly available models. It was found that treated samples shows better drying characteristics than untreated samples. The objective of this study is to obtain drying kinetics which can be used to optimize the drying operations in grape drying.
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OBJECTIVE Although the survival outcomes among women diagnosed with endometrial cancer are very favorable, little is known about the long-term impact of their cancer experience. This study identifies the extent of positive and negative impacts of cancer and factors associated with this, amongst long-term survivors of endometrial cancer. METHODS Australian women diagnosed with endometrial cancer (N=632) were sent questionnaires at the time of diagnosis and 3-5 years later. Hierarchical multiple regression models were used to examine whether a range of variables at diagnosis/treatment predicted subsequent scores on the Impact of Cancer Scale, which examines positive (e.g. health awareness) and negative (e.g. appearance concerns) impacts amongst cancer survivors. RESULTS Overall, women had a higher mean score for the positive than negative impact scales (M=3.5 versus M=2.5, respectively). An intermediate grade of endometrial cancer, a prior diagnosis of cancer and lower levels of education were significant, but weak, predictors of higher scores on the positive impact scale. Higher scores on the negative impact scale were predicted by a higher grade of cancer, poor physical and mental health, a younger age, being single or having lower levels of education. CONCLUSIONS The study demonstrates that factors that predict positive impact in cancer survivors differ to those that predict negative impact, suggesting that interventions to optimize cancer survivors' quality of life will need to be multi-dimensional, and this supports the need for tailored intervention.
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Fundamental understanding on microscopic physical changes of plant materials is vital to optimize product quality and processing techniques, particularly in food engineering. Although grid-based numerical modelling can assist in this regard, it becomes quite challenging to overcome the inherited complexities of these biological materials especially when such materials undergo critical processing conditions such as drying, where the cellular structure undergoes extreme deformations. In this context, a meshfree particle based model was developed which is fundamentally capable of handling extreme deformations of plant tissues during drying. The model is built by coupling a particle based meshfree technique: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). Plant cells were initiated as hexagons and aggregated to form a tissue which also accounts for the characteristics of the middle lamella. In each cell, SPH was used to model cell protoplasm and DEM was used to model the cell wall. Drying was incorporated by varying the 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 can be used to simulate tissues under excessive moisture content reductions incorporating cell wall wrinkling. Also, compared to the state of the art SPH-DEM tissue models, the proposed model better replicates real tissues and the cell-cell interactions used ensure efficient computations. Model predictions showed good agreement both qualitatively and quantitatively with experimental findings on dried plant tissues. The proposed modelling approach is fundamentally flexible to study different cellular structures for their microscale morphological changes at dehydration.
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This paper introduces an integral approach to the study of plasma-surface interactions during the catalytic growth of selected nanostructures (NSs). This approach involves basic understanding of the plasma-specific effects in NS nucleation and growth, theoretical modelling, numerical simulations, plasma diagnostics, and surface microanalysis. Using an example of plasma-assisted growth of surface-supported single-walled carbon nanotubes, we discuss how the combination of these techniques may help improve the outcomes of the growth process. A specific focus here is on the effects of nanoscale plasma-surface interactions on the NS growth and how the available techniques may be used, both in situ and ex situ to optimize the growth process and structural parameters of NSs.
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This review focuses on one of the fundamental phenomena that occur upon application of sufficiently strong electric fields to gases, namely the formation and propagation of ionization waves-streamers. The dynamics of streamers is controlled by strongly nonlinear coupling, in localized streamer tip regions, between enhanced (due to charge separation) electric field and ionization and transport of charged species in the enhanced field. Streamers appear in nature (as initial stages of sparks and lightning, as huge structures-sprites above thunderclouds), and are also found in numerous technological applications of electrical discharges. Here we discuss the fundamental physics of the guided streamer-like structures-plasma bullets which are produced in cold atmospheric-pressure plasma jets. Plasma bullets are guided ionization waves moving in a thin column of a jet of plasma forming gases (e.g.,He or Ar) expanding into ambient air. In contrast to streamers in a free (unbounded) space that propagate in a stochastic manner and often branch, guided ionization waves are repetitive and highly-reproducible and propagate along the same path-the jet axis. This property of guided streamers, in comparison with streamers in a free space, enables many advanced time-resolved experimental studies of ionization waves with nanosecond precision. In particular, experimental studies on manipulation of streamers by external electric fields and streamer interactions are critically examined. This review also introduces the basic theories and recent advances on the experimental and computational studies of guided streamers, in particular related to the propagation dynamics of ionization waves and the various parameters of relevance to plasma streamers. This knowledge is very useful to optimize the efficacy of applications of plasma streamer discharges in various fields ranging from health care and medicine to materials science and nanotechnology.
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Titanium dioxide thin films with a rutile crystallinite size around 20 nm were fabricated by pulsed laser deposition (PLD) aided with an electron cyclotron resonance (ECR) plasma. With annealing treatment, the crystal size of the rutile crystallinite increased to 100 nm. The apatite-forming ability of the films as deposited and after annealing was investigated in a kind of simulated body fluid with ion concentrations nearly equal to those of human blood plasma. The results indicate that ECR aided PLD is an effective way both to fabricate bioactive titanium dioxide thin films and to optimize the bioactivity of titanium dioxide, with both crystal size and defects of the film taken into account.
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Carbon nanotips have been synthesized from a thin carbon film deposited on silicon by bias-enhanced hot filament chemical vapor deposition under different process parameters. The results of scanning electron microscopy indicate that high-quality carbon nanotips can only be obtained under conditions when the ion flux is effectively drawn from the plasma sustained in a CH4 + NH3 + H2 gas mixture. It is shown that the morphology of the carbon nanotips can be controlled by varying the process parameters such as the applied bias, gas pressure, and the NH3 / H2 mass flow ratios. The nanotip formation process is examined through a model that accounts for surface diffusion, in addition to sputtering and deposition processes included in the existing models. This model makes it possible to explain the major difference in the morphologies of the carbon nanotips formed without and with the aid of the plasma as well as to interpret the changes of their aspect ratio caused by the variation in the ion/gas fluxes. Viable ways to optimize the plasma-based process parameters to synthesize high-quality carbon nanotips are suggested. The results are relevant to the development of advanced plasma-/ion-assisted methods of nanoscale synthesis and processing.
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Microscopic surface diffusivity theory based on atomic ionization energy concept is developed to explain the variations of the atomic and displacement polarizations with respect to the surface diffusion activation energy of adatoms in the process of self-assembly of quantum dots on plasma-exposed surfaces. These polarizations are derived classically, while the atomic polarization is quantized to obtain the microscopic atomic polarizability. The surface diffusivity equation is derived as a function of the ionization energy. The results of this work can be used to fine-tune the delivery rates of different adatoms onto nanostructure growth surfaces and optimize the low-temperature plasma based nanoscale synthesis processes.
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Understanding the generation of reactive species in a plasma is an important step towards creating reliable and robust plasma-aided nanofabrication processes. A two-dimensional fluid simulation of the number densities of surface preparation species in a low-temperature, low-pressure, non-equilibrium Ar+H2 plasma is conducted. The operating pressure and H2 partial pressure have been varied between 70-200 mTorr and 0.1-50%, respectively. An emphasis is placed on the application of these results to nanofabrication. A reasonable balance between operating pressures and H 2 partial pressures that would optimize the number densities of the two working units largely responsible for activation and passivation of surface dangling bonds (Ar+ and H respectively) in order to achieve acceptable rates of surface activation and passivation is obtained. It is found that higher operating pressures (150-200 mTorr) and lower H2 partial pressures (∼5%) are required in order to ensure high number densities of Ar+ and H species. This paper contributes to the improvement of the controllability and predictability of plasma-based nanoassembly processes.
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The results of two-dimensional fluid simulation of number densities and fluxes of the main building blocks and surface preparation species involved in nanoassembly of carbon-based nanopatterns in Ar+H2+C2H2 reactive plasmas are reported. It is shown that the process parameters and non-uniformity of surface fluxes of each particular species may affect the targeted nanopattern quality. The results can be used to improve predictability of plasma-aided nanofabrication processes and optimize the parameters of plasma nanotools.KGaA, Weinheim.
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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.
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The influence of ion current density on the thickness of coatings deposited in a vacuum arc setup has been investigated to optimize the coating porosity. A planar probe was used to measure the ion current density distribution across plasma flux. A current density from 20 to 50 A/m2 was obtained, depending on the probe position relative to the substrate center. TiN coatings were deposited onto the cutting inserts placed at different locations on the substrate, and SEM was used to characterize the surfaces of the coatings. It was found that lowdensity coatings were formed at the decreased ion current density. A quantitative dependence of the coating thickness on the ion current density in the range of 20-50 A/m2 were obtained for the films deposited at substrate bias of 200 V and nitrogen pressure 0.1 Pa, and the coating porosity was calculated. The coated cutting inserts were tested by lathe machining of the martensitic stainless steel AISI 431. The results may be useful for controlling ion flux distribution over large industrial-scale substrates.
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This article analyses ‘performance government’ as an emergent form of rule in advanced liberal democracies. It discloses how teachers and school leaders in Australia are being governed by the practices of performance government which centre on the recently established Australian Institute for Teaching and School Leadership (AITSL) and are given direction by two major strategies implicit within the exercise of this form of power: activation and regulation. Through an ‘analytics of government’ of these practices, the article unravels the new configurations of corporatized expert and academic knowledge—and their attendant methods of application—by which the self-governing capacities of teachers and school leaders are being activated and regulated in ways that seek to optimize the performance of these professionals. The article concludes by outlining some of the dangers of performance government for the professional freedom of educators and school leaders.
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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.