Particle agglomeration study in rf silane plasmas: In situ study by polarization-sensitive laser light scattering

To determine self‐consistently the time evolution of particle size and their number density in situ multi‐angle polarization‐sensitive laser light scattering was used. Cross‐polarization intensities (incident and scattered light intensities with opposite polarization) measured at 135° and ex situ transmission electronic microscopy analysis demonstrate the existence of nonspherical agglomerates during the early phase of agglomeration. Later in the particle time development both techniques reveal spherical particles again. The presence of strong cross‐polarization intensities is accompanied by low‐frequency instabilities detected on the scattered light intensities and plasma emission. It is found that the particle radius and particle number density during the agglomeration phase can be well described by the Brownian free molecule coagulation model. Application of this neutral particle coagulation model is justified by calculation of the particle charge whereby it is shown that particles of a few tens of nanometer can be considered as neutral under our experimental conditions. The measured particle dispersion can be well described by a Brownian free molecule coagulation model including a log‐normal particle size distribution.

Liquid-liquid phase transition for soft-core attractive potential

Using event-driven molecular dynamics simulations, we study a three-dimensional one-component system of spherical particles interacting via a discontinuous potential combining a repulsive square soft core and an attractive square well. In the case of a narrow attractive well, it has been shown that this potential has two metastable gas-liquid critical points. Here we systematically investigate how the changes of the parameters of this potential affect the phase diagram of the system. We find a broad range of potential parameters for which the system has both a gas-liquid critical point C1 and a liquid-liquid critical point C2. For the liquid-gas critical point we find that the derivatives of the critical temperature and pressure, with respect to the parameters of the potential, have the same signs: they are positive for increasing width of the attractive well and negative for increasing width and repulsive energy of the soft core. This result resembles the behavior of the liquid-gas critical point for standard liquids. In contrast, for the liquid-liquid critical point the critical pressure decreases as the critical temperature increases. As a consequence, the liquid-liquid critical point exists at positive pressures only in a finite range of parameters. We present a modified van der Waals equation which qualitatively reproduces the behavior of both critical points within some range of parameters, and gives us insight on the mechanisms ruling the dependence of the two critical points on the potential¿s parameters. The soft-core potential studied here resembles model potentials used for colloids, proteins, and potentials that have been related to liquid metals, raising an interesting possibility that a liquid-liquid phase transition may be present in some systems where it has not yet been observed.

Learning form Nature to improve the heat generation of iron-oxide nanoparticles for magnetic hyperthermia applications.

The performance of magnetic nanoparticles is intimately entwined with their structure, mean size and magnetic anisotropy. Besides, ensembles offer a unique way of engineering the magnetic response by modifying the strength of the dipolar interactions between particles. Here we report on an experimental and theoretical analysis of magnetic hyperthermia, a rapidly developing technique in medical research and oncology. Experimentally, we demonstrate that single-domain cubic iron oxide particles resembling bacterial magnetosomes have superior magnetic heating efficiency compared to spherical particles of similar sizes. Monte Carlo simulations at the atomic level corroborate the larger anisotropy of the cubic particles in comparison with the spherical ones, thus evidencing the beneficial role of surface anisotropy in the improved heating power. Moreover we establish a quantitative link between the particle assembling, the interactions and the heating properties. This knowledge opens new perspectives for improved hyperthermia, an alternative to conventional cancer therapies.

Monte Carlo study of the finite-size effects on the magnetization of maghemite small particles

Monte Carlo simulations of a model for gamma-Fe2O3 (maghemite) single particle of spherical shape are presented aiming at the elucidation of the specific role played by the finite size and the surface on the anomalous magnetic behavior observed in small particle systems at low temperature. The influence of the finite-size effects on the equilibrium properties of extensive magnitudes, field coolings, and hysteresis loops is studied and compared to the results for periodic boundaries. It is shown that for the smallest sizes the thermal demagnetization of the surface completely dominates the magnetization while the behavior of the core is similar to that of the periodic boundary case, independently of D. The change in shape of the hysteresis loops with D demonstrates that the reversal mode is strongly influenced by the presence of broken links and disorder at the surface

Effects of nutrients and turbulence on the production of transparent exopolymer particles: a mesocosm study

The production of transparent exopolymer particles (TEP) in response to several environmental variables was studied in 2 mesocosm experiments. The first (Expt 1) examined a gradient of 4 nutrient levels; the second (Expt 2) examined different conditions of silicate availability and zooplankton presence. Tanks were separated in 2 series, one subjected to turbulence and the other not influenced by turbulence. In tanks with nutrient addition, TEP were rapidly formed, with net apparent production rates closely linked to chl a growth rates, suggesting that phytoplankton cells were actively exuding TEP precursors. High nutrient availability increased the absolute concentration of TEP; however, the relative quantity of TEP produced was found to be lower, as TEP concentration per unit of phytoplankton biomass was inversely related to the initial nitrate dose. In Expt 1, an increase in TEP volume (3 to 48 µm equivalent spherical diameter) with nutrient dose was observed; in Expt 2, both silicate addition and turbulence enhanced TEP production and favored aggregation to larger TEP (>48 µm). The presence of zooplankton lowered TEP concentration and changed the size distribution of TEP, presumably by grazing on TEP or phytoplankton. For lower nutrient concentrations, the ratio of particulate organic carbon (POC) to particulate organic nitrogen (PON) followed the Redfield ratio. At higher nutrient conditions, when nutrients were exhausted during the post-bloom, a decoupling of carbon and nitrogen dynamics occurred and was correlated to TEP formation, with a large flow of carbon channeled toward the TEP pool in turbulent tanks. TEP accounted for an increase in POC concentration of 50% in high-nutrient and turbulent conditions. The study of TEP dynamics is crucial to understanding the biogeochemical response of the aquatic system to forcing variables such as nutrient availability and turbulence intensity.

Particle shape and orientation in laser diffraction and static image analysis size distribution analysis of micrometer sized rectangular particles

Laser diffraction (LD) and static image analysis (SIA) of rectangular particles [United States Pharmacopeia, USP30-NF25, General Chapter <776>, Optical Miroscopy.] have been systematically studied. To rule out sample dispersion and particle orientation as the root cause of differences in size distribution profiles, we immobilize powder samples on a glass plate by means of a dry disperser. For a defined region of the glass plate, we measure the diffraction pattern as induced by the dispersed particles, and the 2D dimensions of the individual particles using LD and optical microscopy, respectively. We demonstrate a correlation between LD and SIA, with the scattering intensity of the individual particles as the dominant factor. In theory, the scattering intensity is related to the square of the projected area of both spherical and rectangular particles. In traditional LD the size distribution profile is dominated by the maximum projected area of the particles (A). The diffraction diameters of a rectangular particle with length L and breadth B as measured by the LD instrument approximately correspond to spheres of diameter ØL and ØB respectively. Differences in the scattering intensity between spherical and rectangular particles suggest that the contribution made to the overall LD volume probability distribution by each rectangular particle is proportional to A2/L and A2/B. Accordingly, for rectangular particles the scattering intensity weighted diffraction diameter (SIWDD) explains an overestimation of their shortest dimension and an underestimation of their longest dimension. This study analyzes various samples of particles whose length ranges from approximately 10 to 1000 μm. The correlation we demonstrate between LD and SIA can be used to improve validation of LD methods based on SIA data for a variety of pharmaceutical powders all with a different rectangular particle size and shape.

Estimation of dynamic latent variable models using simulated nonparametric moments

Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Since conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. Monte Carlo results show that the estimator performs well in comparison to other estimators that have been proposed for estimation of general DLV models.

Estimation of dynamic latent variable models using simulated nonparametric moments

Abstract. Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Because conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. It is shown that as the number of simulations diverges, the estimator is consistent and a higher-order expansion reveals the stochastic difference between the infeasible GMM estimator based on the same moment conditions and the simulated version. In particular, we show how to adjust standard errors to account for the simulations. Monte Carlo results show how the estimator may be applied to a range of dynamic latent variable (DLV) models, and that it performs well in comparison to several other estimators that have been proposed for DLV models.

Optimal asymptotic bounds for spherical designs

"Vegeu el resum a l'inici del document del fitxer adjunt"

Solving Large Location-Allocation problems by Clustering and Simulated Annealing

Globalization involves several facility location problems that need to be handled at large scale. Location Allocation (LA) is a combinatorial problem in which the distance among points in the data space matter. Precisely, taking advantage of the distance property of the domain we exploit the capability of clustering techniques to partition the data space in order to convert an initial large LA problem into several simpler LA problems. Particularly, our motivation problem involves a huge geographical area that can be partitioned under overall conditions. We present different types of clustering techniques and then we perform a cluster analysis over our dataset in order to partition it. After that, we solve the LA problem applying simulated annealing algorithm to the clustered and non-clustered data in order to work out how profitable is the clustering and which of the presented methods is the most suitable

Conjugation of genetically-engineered protein phosphatases to magnetic particles for okadaic acid detection

This work presents the functional characterisation of a protein phosphatase 2A (PP2A) catalytic subunit obtained by genetic engineering and its conjugation to magnetic particles (MPs) via metal coordination chemistry for the subsequent development of assays for diarrheic lipophilic marine toxins. Colorimetric assays with free enzyme have allowed the determination of the best enzyme activity stabiliser, which is glycerol at 10%. They have also demonstrated that the recombinant enzyme can be as sensitive towards okadaic acid (OA) (LOD=2.3μg/L) and dinophysistoxin-1 (DTX-1) (LOD=15.2μg/L) as a commercial PP2A and, moreover, it has a higher operational stability, which makes possible to perform the protein phosphatase inhibition assay (PPIA) with a lower enzyme amount. Once conjugated to MPs, the PP2A catalytic subunit still retains its enzyme activity and it can also be inhibited by OA (LOD=30.1μg/L).

Self-serving biases: Evidence from a simulated labor relationship

Previous studies have found evidence of a self-serving bias in bargaining and dispute resolution. We use experimental data to test for this effect in a simulated labor relatonship. We finda consistent discrepancy between employer beliefs and employee actions that can only be attributed to self-serving biases. This discrepancy is evident through stated beliefs, revealed satisfaction, and actual actions. We present evidenceand discuss implications.

Attribution and reciprocity in a simulated labor market: An experimental investigation

While papers such as Akerlof and Yellen (1990) and Rabin (1993) argue that psychological considerations such as fairness and reciprocity are important in individual decision-making, there is little explicit empirical evidence of reciprocal altruism in economic environments. This paper tests whether attribution of volition in choosing a wage has a significant effect on subsequent costly effort provision. An experiment was conducted in which subjects are first randomly divided into groups of employers and employees. Wages were selected and employees asked to choose an effort level, where increased effort is costly to the employee, but highly beneficial to the employer. The wage-determination process was common knowledge and wages were chosen either by the employer or by an external process. There is evidence for both distributional concerns and reciprocal altruism. The slope of the effort/wage profile is clearly positive in all cases, but is significantly higher when wages are chosen by the employer, offering support for the hypothesis of reciprocity. There are implications for models of utility and a critique of some current models is presented.

Experiencing simulated outcomes

Whereas much literature has documented difficulties in making probabilistic inferences, it hasalso emphasized the importance of task characteristics in determining judgmental accuracy.Noting that people exhibit remarkable efficiency in encoding frequency information sequentially,we construct tasks that exploit this ability by requiring people to experience the outcomes ofsequentially simulated data. We report two experiments. The first involved seven well-knownprobabilistic inference tasks. Participants differed in statistical sophistication and answered withand without experience obtained through sequentially simulated outcomes in a design thatpermitted both between- and within-subject analyses. The second experiment involvedinterpreting the outcomes of a regression analysis when making inferences for investmentdecisions. In both experiments, even the statistically naïve make accurate probabilistic inferencesafter experiencing sequentially simulated outcomes and many prefer this presentation format. Weconclude by discussing theoretical and practical implications.

Surface topography and mixed-pixel effects on the simulated L-band brightness temperatures.

The impact of topography and mixed pixels on L-band radiometric observations over land needs to be quantified to improve the accuracy of soil moisture retrievals. For this purpose, a series of simulations has been performed with an improved version of the soil moisture and ocean salinity (SMOS) end-to-end performance simulator (SEPS). The brightness temperature generator of SEPS has been modified to include a 100-m-resolution land cover map and a 30-m-resolution digital elevation map of Catalonia (northeast of Spain). This high-resolution generator allows the assessment of the errors in soil moisture retrieval algorithms due to limited spatial resolution and provides a basis for the development of pixel disaggregation techniques. Variation of the local incidence angle, shadowing, and atmospheric effects (up- and downwelling radiation) due to surface topography has been analyzed. Results are compared to brightness temperatures that are computed under the assumption of an ellipsoidal Earth.