958 resultados para Enthalpy of mixture


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Molar heat capacities of n-butanol and the azeotropic mixture in the binary system [water (x=0.716) plus n-butanol (x=0.284)] were measured with an adiabatic calorimeter in a temperature range from 78 to 320 K. The functions of the heat capacity with respect to thermodynamic temperature were established for the azeotropic mixture. A glass transition was observed at (111.9 +/- 1.1) K. The phase transitions took place at (179.26 +/- 0.77) and (269.69 +/- 0.14) K corresponding to the solid-liquid phase transitions of. n-butanol and water, respectively. The phase-transition enthalpy and entropy of water were calculated. A thermodynamic function of excess molar heat capacity with respect to temperature was established, which took account of physical mixing, destructions of self-association and cross-association for n-butanol and water, respectively. The thermodynamic functions and the excess thermodynamic ones of the binary systems relative to 298.15 K were derived based on the relationships of the thermodynamic functions and the function of the measured heat capacity and the calculated excess heat capacity with respect to temperature.

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Organic solar cells based on bulk heterojunction between a conductive polymer and a carbon nanostructure offer potential advantages compared to conventional inorganic cells. Low cost, light weight, flexibility and high peak power per unit weight are all features that can be considered a reality for organic photovoltaics. Although polymer/carbon nanotubes solar cells have been proposed, only low power conversion efficiencies have been reached without addressing the mechanisms responsible for this poor performance. The purpose of this work is therefore to investigate the basic interaction between carbon nanotubes and poly(3-hexylthiophene) in order to demonstrate how this interaction affects the performance of photovoltaic devices. The outcomes of this study are the contributions made to the knowledge of the phenomena explaining the behaviour of electronic devices based on carbon nanotubes and poly(3-hexylthiophene). In this PhD, polymer thin films with the inclusion of uniformly distributed carbon nanotubes were deposited from solution and characterised. The bulk properties of the composites were studied with microscopy and spectroscopy techniques to provide evidence of higher degrees of polymer order when interacting with carbon nanotubes. Although bulk investigation techniques provided useful information about the interaction between the polymer and the nanotubes, clear evidence of the phenomena affecting the heterojunction formed between the two species was investigated at nanoscale. Identifying chirality-driven polymer assisted assembly on the carbon nanotube surface was one of the major achievements of this study. Moreover, the analysis of the electrical behaviour of the heterojunction between the polymer and the nanotube highlighted the charge transfer responsible for the low performance of photovoltaic devices. Polymer and carbon nanotube composite-based devices were fabricated and characterised in order to study their electronic properties. The carbon nanotube introduction in the polymer matrix evidenced a strong electrical conductivity enhancement but also a lower photoconductivity response. Moreover, the extension of pristine polymer device characterisation models to composites based devices evidenced the conduction mechanisms related to nanotubes. Finally, the introduction of carbon nanotubes in the polymer matrix was demonstrated to improve the pristine polymer solar cell performance and the spectral response even though the power conversion efficiency is still too low.

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In this paper, the goal of identifying disease subgroups based on differences in observed symptom profile is considered. Commonly referred to as phenotype identification, solutions to this task often involve the application of unsupervised clustering techniques. In this paper, we investigate the application of a Dirichlet Process mixture (DPM) model for this task. This model is defined by the placement of the Dirichlet Process (DP) on the unknown components of a mixture model, allowing for the expression of uncertainty about the partitioning of observed data into homogeneous subgroups. To exemplify this approach, an application to phenotype identification in Parkinson’s disease (PD) is considered, with symptom profiles collected using the Unified Parkinson’s Disease Rating Scale (UPDRS). Clustering, Dirichlet Process mixture, Parkinson’s disease, UPDRS.

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Autonomous navigation and picture compilation tasks require robust feature descriptions or models. Given the non Gaussian nature of sensor observations, it will be shown that Gaussian mixture models provide a general probabilistic representation allowing analytical solutions to the update and prediction operations in the general Bayesian filtering problem. Each operation in the Bayesian filter for Gaussian mixture models multiplicatively increases the number of parameters in the representation leading to the need for a re-parameterisation step. A computationally efficient re-parameterisation step will be demonstrated resulting in a compact and accurate estimate of the true distribution.

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This paper evaluates the operational activities of Chinese hydroelectric power companies over the period 2000-2010 using a finite mixture model that controls for unobserved heterogeneity. In so doing, a stochastic frontier latent class model, which allows for the existence of different technologies, is adopted to estimate cost frontiers. This procedure not only enables us to identify different groups among the hydro-power companies analysed, but also permits the analysis of their cost efficiency. The main result is that three groups are identified in the sample, each equipped with different technologies, suggesting that distinct business strategies need to be adapted to the characteristics of China's hydro-power companies. Some managerial implications are developed. © 2012 Elsevier B.V.

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This paper proposes solutions to three issues pertaining to the estimation of finite mixture models with an unknown number of components: the non-identifiability induced by overfitting the number of components, the mixing limitations of standard Markov Chain Monte Carlo (MCMC) sampling techniques, and the related label switching problem. An overfitting approach is used to estimate the number of components in a finite mixture model via a Zmix algorithm. Zmix provides a bridge between multidimensional samplers and test based estimation methods, whereby priors are chosen to encourage extra groups to have weights approaching zero. MCMC sampling is made possible by the implementation of prior parallel tempering, an extension of parallel tempering. Zmix can accurately estimate the number of components, posterior parameter estimates and allocation probabilities given a sufficiently large sample size. The results will reflect uncertainty in the final model and will report the range of possible candidate models and their respective estimated probabilities from a single run. Label switching is resolved with a computationally light-weight method, Zswitch, developed for overfitted mixtures by exploiting the intuitiveness of allocation-based relabelling algorithms and the precision of label-invariant loss functions. Four simulation studies are included to illustrate Zmix and Zswitch, as well as three case studies from the literature. All methods are available as part of the R package Zmix, which can currently be applied to univariate Gaussian mixture models.

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A binary mixture of ammonium perchlorate-sodium nitrate in molar proportion undergoes partial fusion at 223°C and the transformation of the mixture to sodium perchlorate-ammonium nitrate occurs in the broad endothermic region. The mixture was heated and quenched at various temperatures in a differential thermal analysis assembly. Thermogravimetric analysis, X-ray diffraction, and infrared spectroscopic techniques were used to determine the composition of the quenched sample in order to explain the overall thermal phenomenon. Visual observations of the morphological changes that occur during the course of heating were made using a hot-stage microscope, 30–350°C.

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In this study, reduction and desorption of oxides of nitrogen (NOx) were conducted using an electrical discharge plasma technique. The study was carried out using a simulated gas mixture to explore the possibility of re-generation of used adsorbents by a nonthermal plasma desorption technique. Three different types of corona electrodes, namely, pipe, helical wire, and straight wire, were used for analyzing their effectiveness in NOx reduction/desorption. The pipe-type corona electrode exhibited a nitric oxide (NO) conversion of 50%, which is 1.5 times that of the straight-wire-type electrode at an energy density of 175J/L. The helical-wire-type corona electrode exhibited a NOx desorption efficiency almost 4 times that of the pipe-type electrode,indicating the possibility that corona-generated species play a crucial role in desorption.

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Dairy farms in subtropical Australia use irrigated, annually sown short-term ryegrass (Lolium multiflorum) or mixtures of short-term ryegrass and white (Trifolium repens) and Persian (shaftal) (T. resupinatum) clover during the winter-spring period in all-year-round milk production systems. A series of small plot cutting experiments was conducted in 3 dairying regions (tropical upland, north Queensland, and subtropical southeast Queensland and northern New South Wales) to determine the most effective rate and frequency of application of nitrogen (N) fertiliser. The experiments were not grazed, nor was harvested material returned to the plots, after sampling. Rates up to 100 kg N/ha.month (as urea or calcium ammonium nitrate) and up to 200 kg N/ha every 2 months (as urea) were applied to pure stands of ryegrass in 1991. In 1993 and 1994, urea, at rates up to 150 kg N/ha.month and to 200 kg N/ha every 2 months, was applied to pure stands of ryegrass; urea, at rates up to 50 kg N/ha.month, was also applied to ryegrass-clover mixtures. The results indicate that applications of 50-85 kg N/ha.month can be recommended for short-term ryegrass pastures throughout the subtropics and tropical uplands of eastern Australia, irrespective of soil type. At this rate, dry matter yields will reach about 90% of their potential, forage nitrogen concentration will be increased, there is minimal risk to stock from nitrate poisoning and there will be no substantial increase in soil N. The rate of N for ryegrass-clover pastures is slightly higher than for pure ryegrass but, at these rates, the clover component will be suppressed. However, increased ryegrass yields and higher forage nitrogen concentrations will compensate for the reduced clover component. At application rates up to 100 kg N/ha.month, build-up of NO3--N and NH4+-N in soil was generally restricted to the surface layers (0-20 cm) of the soil, but there was a substantial increase throughout the soil profile at 150 kg N/ha.month. The build-up of NO3--N and NH4+-N was greater and was found at lower rates on the lighter soil compared with heavy clays. Generally, most of the soil N was in the NO3--N form and most was in the top 20 cm.

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In the subtropics of Australia, the ryegrass component of irrigated perennial ryegrass (Lolium perenne) - white clover (Trifolium repens) pastures declines by approximately 40% in the summer following establishment, being replaced by summer-active C4 grasses. Tall fescue (Festuca arundinacea) is more persistent than perennial ryegrass and might resist this invasion, although tall fescue does not compete vigorously as a seedling. This series of experiments investigated the influence of ryegrass and tall fescue genotype, sowing time and sowing mixture as a means of improving tall fescue establishment and the productivity and persistence of tall fescue, ryegrass and white clover-based mixtures in a subtropical environment. Tall fescue frequency at the end of the establishment year decreased as the number of companion species sown in the mixture increased. Neither sowing mixture combinations nor sowing rates influenced overall pasture yield (of around 14 t/ha) in the establishment year but had a significant effect on botanical composition and component yields. Perennial ryegrass was less competitive than short-rotation ryegrass, increasing first-year yields of tall fescue by 40% in one experiment and by 10% in another but total yield was unaffected. The higher establishment-year yield (3.5 t/ha) allowed Dovey tall fescue to compete more successfully with the remaining pasture components than Vulcan (1.4 t/ha). Sowing 2 ryegrass cultivars in the mixture reduced tall fescue yields by 30% compared with a single ryegrass (1.6 t/ha), although tall fescue alone achieved higher yields (7.1 t/ha). Component sowing rate had little influence on composition or yield. Oversowing the ryegrass component into a 6-week-old sward of tall fescue and white clover improved tall fescue, white clover and overall yields in the establishment year by 83, 17 and 11%, respectively, but reduced ryegrass yields by 40%. The inclusion of red (T. pratense) and Persian (T. resupinatum) clovers and chicory (Cichorium intybus) increased first-year yields by 25% but suppressed perennial grass and clover components. Yields were generally maintained at around 12 t/ha/yr in the second and third years, with tall fescue becoming dominant in all 3 experiments. The lower tall fescue seeding rate used in the first experiment resulted in tall fescue dominance in the second year following establishment, whereas in Experiments 2 and 3 dominance occurred by the end of the first year. Invasion by the C4 grasses was relatively minor (<10%) even in the third year. As ryegrass plants died, tall fescue and, to a lesser extent, white clover increased as a proportion of the total sward. Treatment effects continued into the second, but rarely the third, year and mostly affected the yield of one of the components rather than total cumulative yield. Once tall fescue became dominant, it was difficult to re-introduce other pasture components, even following removal of foliage and moderate renovation. Severe renovation (reducing the tall fescue population by at least 30%) seems a possible option for redressing this situation.

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A binary mixture of ammonium perchlorate-sodium nitrate in molar proportion undergoes partial fusion at 223°C and the transformation of the mixture to sodium perchlorate-ammonium nitrate occurs in the broad endothermic region. The mixture was heated and quenched at various temperatures in a differential thermal analysis assembly. Thermogravimetric analysis, X-ray diffraction, and infrared spectroscopic techniques were used to determine the composition of the quenched sample in order to explain the overall thermal phenomenon. Visual observations of the morphological changes that occur during the course of heating were made using a hot-stage microscope, 30–350°C.

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Presented in this letter is a critical discussion of a recent paper on experimental investigation of the enthalpy, entropy and free energy of formation of gallium nitride (GaN) published in this journal [T.J. Peshek, J.C. Angus, K. Kash, J. Cryst. Growth 311 (2008) 185-189]. It is shown that the experimental technique employed detects neither the equilibrium partial pressure of N-2 corresponding to the equilibrium between Ga and GaN at fixed temperatures nor the equilibrium temperature at constant pressure of N-2. The results of Peshek et al. are discussed in the light of other information on the Gibbs energy of formation available in the literature. Entropy of GaN is derived from heat-capacity measurements. Based on a critical analysis of all thermodynamic information now available, a set of optimized parameters is identified and a table of thermodynamic data for GaN developed from 298.15 to 1400 K.