An EQCM Investigation of Electrochemical Precipitation of Mn(OH)(2) and Its Capacitance Behavior

Electrochemical quartz crystal microbalance (EQCM) has been used to study the electrochemical precipitation of Mn(OH)(2) on a Au crystal and its capacitance properties. From the EQCM data, it is inferred that NO3- ions get adsorbed on the Au crystal and then undergo reduction, resulting in an increase in pH near the electrode surface. Precipitation of Mn2+ occurs as Mn(OH)(2), with an increase in mass of the Au crystal. Mn(OH)(2) undergoes oxidation to MnO2, which exhibits electrochemical supercapacitor behavior on subjecting to electrochemical cycling in a Na2SO4 electrolyte. EQCM data indicate mass variations corresponding to surface insertion/extraction of Na+ ions during discharge/charge cycling. (C) 2010 The Electrochemical Society. DOI: 10.1149/1.3479665] All rights reserved.

Sensitivity of the simulated precipitation to changes in convective relaxation time scale

The paper describes the sensitivity of the simulated precipitation to changes in convective relaxation time scale (TAU) of Zhang and McFarlane (ZM) cumulus parameterization, in NCAR-Community Atmosphere Model version 3 (CAM3). In the default configuration of the model, the prescribed value of TAU, a characteristic time scale with which convective available potential energy (CAPE) is removed at an exponential rate by convection, is assumed to be 1 h. However, some recent observational findings suggest that, it is larger by around one order of magnitude. In order to explore the sensitivity of the model simulation to TAU, two model frameworks have been used, namely, aqua-planet and actual-planet configurations. Numerical integrations have been carried out by using different values of TAU, and its effect on simulated precipitation has been analyzed. The aqua-planet simulations reveal that when TAU increases, rate of deep convective precipitation (DCP) decreases and this leads to an accumulation of convective instability in the atmosphere. Consequently, the moisture content in the lower-and mid-troposphere increases. On the other hand, the shallow convective precipitation (SCP) and large-scale precipitation (LSP) intensify, predominantly the SCP, and thus capping the accumulation of convective instability in the atmosphere. The total precipitation (TP) remains approximately constant, but the proportion of the three components changes significantly, which in turn alters the vertical distribution of total precipitation production. The vertical structure of moist heating changes from a vertically extended profile to a bottom heavy profile, with the increase of TAU. Altitude of the maximum vertical velocity shifts from upper troposphere to lower troposphere. Similar response was seen in the actual-planet simulations. With an increase in TAU from 1 h to 8 h, there was a significant improvement in the simulation of the seasonal mean precipitation. The fraction of deep convective precipitation was in much better agreement with satellite observations.

Precipitation in small systems-I. stochastic analysis

Precipitation in small droplets involving emulsions, microemulsions or vesicles is important for Producing multicomponent ceramics and nanoparticles. Because of the random nature of nucleation and the small number of particles in a droplet, the use of a deterministic population balance equation for predicting the number density of particles may lead to erroneous results even for evaluating the mean behavior of such systems. A comparison between the predictions made through stochastic simulation and deterministic population balance involving small droplets has been made for two simple systems, one involving crystallization and the other a single-component precipitation. The two approaches have been found to yield quite different results under a variety of conditions. Contrary to expectation, the smallness of the population alone does not cause these deviations. Thus, if fluctuation in supersaturation is negligible, the population balance and simulation predictions concur. However, for large fluctuations in supersaturation, the predictions differ significantly, indicating the need to take the stochastic nature of the phenomenon into account. This paper describes the stochastic treatment of populations, which involves a sequence of so-called product density equations and forms an appropriate framework for handling small systems.

Why is there a short-term increase in global precipitation in response to diminished CO2 forcing?

Recently, it was found that a reduction in atmospheric CO2 concentration leads to a temporary increase in global precipitation. We use the Hadley Center coupled atmosphere-ocean model, HadCM3L, to demonstrate that this precipitation increase is a consequence of precipitation sensitivity to changes in atmospheric CO2 concentrations through fast tropospheric adjustment processes. Slow ocean cooling explains the longer-term decrease in precipitation. Increased CO2 tends to suppress evaporation/precipitation whereas increased temperatures tend to increase evaporation/precipitation. When the enhanced CO2 forcing is removed, global precipitation increases temporarily, but this increase is not observed when a similar negative radiative forcing is applied as a reduction of solar intensity. Therefore, transient precipitation increase following a reduction in CO2-radiative forcing is a consequence of the specific character of CO2 forcing and is not a general feature associated with decreases in radiative forcing. Citation: Cao, L., G. Bala, and K. Caldeira (2011), Why is there a short-term increase in global precipitation in response to diminished CO2 forcing?, Geophys. Res. Lett., 38, L06703, doi:10.1029/2011GL046713.

On generating optimal signal probabilities for random tests: A genetic approach

Genetic Algorithms are robust search and optimization techniques. A Genetic Algorithm based approach for determining the optimal input distributions for generating random test vectors is proposed in the paper. A cost function based on the COP testability measure for determining the efficacy of the input distributions is discussed, A brief overview of Genetic Algorithms (GAs) and the specific details of our implementation are described. Experimental results based on ISCAS-85 benchmark circuits are presented. The performance pf our GA-based approach is compared with previous results. While the GA generates more efficient input distributions than the previous methods which are based on gradient descent search, the overheads of the GA in computing the input distributions are larger. To account for the relatively quick convergence of the gradient descent methods, we analyze the landscape of the COP-based cost function. We prove that the cost function is unimodal in the search space. This feature makes the cost function amenable to optimization by gradient-descent techniques as compared to random search methods such as Genetic Algorithms.

Some Basic Aspects of Reaction Engineering of Precipitation Processes

Analysis of precipitation reactions is extremely important in the technology of production of fine particles from the liquid phase. The control of composition and particle size in precipitation processes requires careful analysis of the several reactions that comprise the precipitation system. Since precipitation systems involve several, rapid ionic dissociation reactions among other slower ones, the faster reactions may be assumed to be nearly at equilibrium. However, the elimination of species, and the consequent reduction of the system of equations, is an aspect of analysis fraught with the possibility of subtle errors related to the violation of conservation principles. This paper shows how such errors may be avoided systematically by relying on the methods of linear algebra. Applications are demonstrated by analyzing the reactions leading to the precipitation of calcium carbonate in a stirred tank reactor as well as in a single emulsion drop. Sample calculations show that supersaturation dynamics can assume forms that can lead to subsequent dissolution of particles that have once been precipitated.

Modeling of precipitation in reverse micellar systems

A model of the precipitation process in reverse micelles has been developed to calculate the size of fine particles obtained therein. While the method shares several features of particle nucleation and growth common to precipitation in large systems, complexities arise in describing the processes of nucleation, due to the extremely small size of a micelle and of particle growth caused by fusion among the micelles. Occupancy of micelles by solubilized molecules is governed by Poisson statistics, implying most of them are empty and cannot nucleate of its own. The model therefore specifies the minimum number of solubilized molecules required to form a nucleus which is used to calculate the homogeneous nucleation rate. Simultaneously, interaction between micelles is assumed to occur by Brownian collision and instantaneous fusion. Analysis of time scales of various events shows growth of particles to be very fast compared to other phenomena occurring. This implies that nonempty micelles either are supersaturated or contain a single precipitated particle and allows application of deterministic population balance equations to describe the evolution of the system with time. The model successfully predicts the experimental measurements of Kandori ct al.(3) on the size of precipitated CaCO3 particles, obtained by carbonation of reverse micelles containing aqueous Ca(OH)(2) solution.

Regionalization of precipitation in data sparse areas using large scale atmospheric variables - A fuzzy clustering approach

Delineation of homogeneous precipitation regions (regionalization) is necessary for investigating frequency and spatial distribution of meteorological droughts. The conventional methods of regionalization use statistics of precipitation as attributes to establish homogeneous regions. Therefore they cannot be used to form regions in ungauged areas, and they may not be useful to form meaningful regions in areas having sparse rain gauge density. Further, validation of the regions for homogeneity in precipitation is not possible, since the use of the precipitation statistics to form regions and subsequently to test the regional homogeneity is not appropriate. To alleviate this problem, an approach based on fuzzy cluster analysis is presented. It allows delineation of homogeneous precipitation regions in data sparse areas using large scale atmospheric variables (LSAV), which influence precipitation in the study area, as attributes. The LSAV, location parameters (latitude, longitude and altitude) and seasonality of precipitation are suggested as features for regionalization. The approach allows independent validation of the identified regions for homogeneity using statistics computed from the observed precipitation. Further it has the ability to form regions even in ungauged areas, owing to the use of attributes that can be reliably estimated even when no at-site precipitation data are available. The approach was applied to delineate homogeneous annual rainfall regions in India, and its effectiveness is illustrated by comparing the results with those obtained using rainfall statistics, regionalization based on hard cluster analysis, and meteorological sub-divisions in India. (C) 2011 Elsevier B.V. All rights reserved.

Large rapidity gaps survival probabilities at LHC

We calculate the probability of large rapidity gaps in high energy hadronic collisions using a model based on QCD mini-jets and soft gluon emission down into the infrared region. Comparing with other models we find a remarkable agreement among most predictions.