Metal separation from mixed types of batteries using selective precipitation and liquid-liquid extraction techniques

The purpose of this paper is to study metal separation from a sample composed of a mixture of the main types of spent household batteries, using a hydrometallurgical route, comparing selective precipitation and liquid-liquid extraction separation techniques. The preparation of the solution consisted of: grinding the waste of mixed batteries, reduction and volatile metals elimination using electric furnace and acid leaching. From this solution two different routes were studied: selective precipitation with sodium hydroxide and liquid-liquid extraction using Cyanex 272 [bis(2,4,4-trimethylpentyl) phosphoric acid] as extracting agent. The best results were obtained from liquid-liquid extraction in which Zn had a 99% extraction rate at pH 2.5. More than 95% Fe was extracted at pH 7.0, the same pH at which more than 90% Ce was extracted. About 88% Mn, Cr and Co was extracted at this pH. At pH 3.0, more than 85% Ni was extracted, and at pH 3.5 more than 80% of Cd and La was extracted. (C) 2010 Elsevier Ltd. All rights reserved.

Characterisation of Leucaena condensed tannins by size and protein precipitation capacity

The ability of differently sized condensed tannins from the genus Leucaena, a fodder tree-legume, to bind protein at different pH values was evaluated to characterise their potential biological effects. Two factors affecting the ability of condensed tannin to bind protein, its major biological activity, have been purported to be the condensed tannin size and the pH of the reaction environment. To test these hypotheses, the protein-precipitating capacities of condensed tannin extracted from four Leucaena genotypes, L leucocephala (UHK636), L pallida (CQ3439), L trichandra (CP146568) and L collinsii (OFI52/88), were assessed. Condensed tannin from L leucocephala had approximately 50% of the ability to precipitate protein on a gg(-1) basis than L pallida or L trichandra, while L collinsii gave no measurable ability to precipitate protein (reaction environment pH 5.0). Increasing or decreasing the pH of the reaction solution away from pH 5.0 (approximately the isoelectric point of the protein) reduced the ability of condensed tannin from all the species to precipitate protein, the decrease being higher at pH 2.5 than at pH 7.5. Condensed tannins from each Leucaena species were also separated by size exclusion chromatography, and the fractions examined for protein-precipitating capacity. In general, it was found that the larger-sized condensed tannin of the accessions L pallida and L trichandra could precipitate more protein than the smaller-sized condensed tannin. This pattern was not found for L leucocephala. (C) 2001 Society of Chemical Industry.

Precipitation hardening of Cu-Fe-Cr alloys - Part I - Mechanical and electrical properties

This research is part of a project whose scope was to investigate the engineering properties of new non-commercial alloy formulations based on the Cu rich corner of the Cu-Fe-Cr ternary system with the primary aim of exploring the development of a new cost-effective high-strength, high-conductivity copper alloy. The literature indicated that Cu rich Cu-Cr and Cu-Fe alloys have been thoroughly investigated. A number of commercial alloys have been developed and these are used for a variety of applications requiring combinations of high-strength, high-conductivity and resistance to softening. Little evidence was found in the literature that the Cu rich corner of the Cu-Fe-Cr system had previously been investigated for the purpose of developing high-strength, high-conductivity copper alloys resistant to softening. The aim of these present investigations was to explore the possibility that new alloys could be developed that combined the properties of both sets of alloys, ie large precipitation hardening response combined with the ability to stabilise cold worked microstructures to high temperatures while at the same maintain high electrical conductivity. To assess the feasibility of this goal the following alloys were chosen for investigation: Cu-0.7wt%Cr-0.3wt%Fe, Cu-0.7wt%Cr-0.8wt%Fe, Cu-0.7wt%Cr-2.0wt%Fe. This paper reports on the mechanical property investigation which indicated that the Cu-0.7wt%Cr-0.3wt%Fe, and Cu-0.7wt%Cr-2.0wt%Fe alloys were worthy of further investigation. (C) 2001 Kluwer Academic Publishers.

Precipitation hardening of Cu-Fe-Cr alloys - Part II - Microstructural characterisation

This research is part of a project whose scope was to investigate the engineering properties of new non-commercial alloy formulations based on the Cu rich corner of the Cu-Fe-Cr ternary system with the primary aim of exploring the development of a new cost-effective high-strength, high-conductivity copper alloy. Promising properties have been measured for the following alloys: Cu-0.7wt%Cr-0.3wt%Fe and Cu-0.7wt%Cr-2.0wt%Fe. This paper reports on the microstructural characterisation of these alloys and discusses the mechanical and electrical properties of these alloys in terms of their microstructure, particularly the formation of precipitates. These alloys have evinced properties that warrant further investigation. Cost modelling has shown that Cu-0.7wt%Cr-0.3wt%Fe is approximately 25% cheaper to produce than commercial Cu-1%Cr. It has also been shown to be more cost efficient on a yield stress and % IACS per dollar basis. The reason for the cost saving is that the Cu-0.7%Cr-0.3%Fe alloy can be made with low carbon ferro-chrome additions as the source of chromium rather than the more expensive Cu-Cr master-alloy. For applications in which cost is one of the primary materials selection criteria, it is envisaged that there would be numerous applications in both cast and wrought form, where the Cu-0.7%Cr-0.3%Fe alloy would be more suitable than Cu-1%Cr. (C) 2001 Kluwer Academic Publishers.

Moisture recycling in the Iberian Peninsula from a regional climate simulation: spatiotemporal analysis and impact on the precipitation regime

The contribution of the evapotranspiration from a certain region to the precipitation over the same area is referred to as water recycling. In this paper, we explore the spatiotemporal links between the recycling mechanism and the Iberian rainfall regime. We use a 9 km resolution Weather Research and Forecasting simulation of 18 years (1990-2007) to compute local and regional recycling ratios over Iberia, at the monthly scale, through both an analytical and a numerical recycling model. In contrast to coastal areas, the interior of Iberia experiences a relative maximum of precipitation in spring, suggesting a prominent role of land-atmosphere interactions on the inland precipitation regime during this period of the year. Local recycling ratios are the highest in spring and early summer, coinciding with those areas where this spring peak of rainfall represents the absolute maximum in the annual cycle. This confirms that recycling processes are crucial to explain the Iberian spring precipitation, particularly over the eastern and northeastern sectors. Average monthly recycling values range from 0.04 in December to 0.14 in June according to the numerical model and from 0.03 in December to 0.07 in May according to the analytical procedure. Our analysis shows that the highest values of recycling are limited by the coexistence of two necessary mechanisms: (1) the availability of sufficient soil moisture and (2) the occurrence of appropriate synoptic configurations favoring the development of convective regimes. The analyzed surplus of rainfall in spring has a critical impact on agriculture over large semiarid regions of the interior of Iberia.

Assessment of the ensembles regional climate models in the representation of precipitation variability and extremes over Portugal

A new data set of daily gridded observations of precipitation, computed from over 400 stations in Portugal, is used to assess the performance of 12 regional climate models at 25 km resolution, from the ENSEMBLES set, all forced by ERA-40 boundary conditions, for the 1961-2000 period. Standard point error statistics, calculated from grid point and basin aggregated data, and precipitation related climate indices are used to analyze the performance of the different models in representing the main spatial and temporal features of the regional climate, and its extreme events. As a whole, the ENSEMBLES models are found to achieve a good representation of those features, with good spatial correlations with observations. There is a small but relevant negative bias in precipitation, especially in the driest months, leading to systematic errors in related climate indices. The underprediction of precipitation occurs in most percentiles, although this deficiency is partially corrected at the basin level. Interestingly, some of the conclusions concerning the performance of the models are different of what has been found for the contiguous territory of Spain; in particular, ENSEMBLES models appear too dry over Portugal and too wet over Spain. Finally, models behave quite differently in the simulation of some important aspects of local climate, from the mean climatology to high precipitation regimes in localized mountain ranges and in the subsequent drier regions.

On the isotopic composition of precipitation in tropical stations (*).

Some of the trends and characteristics of the isotopic composition oh precipitation in tropical stations are discussed. Stations in small Pacific islands show a variation with latitude, with lower 8-values between 15°N and 1S°S and higher values at higher. Inland stations are depleted in heavy isotopes with respect to coastal stations but sometimes this continental effect is rather complex, as f,or instance in África. Mean monthly 8-values show a remarkable correlation with the amount of precipitation, but the slope variations do not show a clear dependence on the mean long term 8-value,as should be expected theoretically. In Southern American stations the seasonal variations of the meanmonthly 5-values are correlated and they are greater in inland stations due to con-tinentaly. The possible effects of recycling of water vapour by evapotranspiration are also discussed.

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.

Parallelization of kinetic Monte Carlo algorithm to simulate AL3Sc precipitation

The present paper reports the precipitation process of Al3Sc structures in an aluminum scandium alloy, which has been simulated with a synchronous parallel kinetic Monte Carlo (spkMC) algorithm. The spkMC implementation is based on the vacancy diffusion mechanism. To filter the raw data generated by the spkMC simulations, the density-based clustering with noise (DBSCAN) method has been employed. spkMC and DBSCAN algorithms were implemented in the C language and using MPI library. The simulations were conducted in the SeARCH cluster located at the University of Minho. The Al3Sc precipitation was successfully simulated at the atomistic scale with the spkMC. DBSCAN proved to be a valuable aid to identify the precipitates by performing a cluster analysis of the simulation results. The achieved simulations results are in good agreement with those reported in the literature under sequential kinetic Monte Carlo simulations (kMC). The parallel implementation of kMC has provided a 4x speedup over the sequential version.

Continuous-flow precipitation as a route to prepare highly controlled nanohydroxyapatite

[Excerpt] Hydroxyapatite Ca10(PO4)6(OH)2 (HAp) has been widely used for biomedical purposes because of its exceptional biocompatibility, bioactivity and osteoconductivity [1]. As these properties are directly related to HAp particles characteristics (size, morphology and purity), a very good control of the reaction conditions is required to obtain particles with the desired properties. Usually, HAp is synthesized by wet chemical precipitation in stirred tank batch reactors that often lead to inconsistencies in product specifications due to their low mixing efficiency [2]. (...)

A design of experiments to assess phosphorous removal and crystal properties in struvite precipitation of source separated urine using different Mg sources

Supplementary data associated with this article can be found, in the online version, at: http://dx.doi.org/10.1016/j.cej.2016.03.148.

Precipitation of barium sulphate nanoparticles in microemulsion : experiments and modelling

Nanopartikel, BaSO4, Mikroemulsion, Fällung, Modellierung

Precipitation of barium sulfate in a semi-batch stirred tank reactor : influence of feeding policy on particle size and morphology

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2012

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

Exploration of alpine orographic precipitation patterns with radar image processing and clustering techniques

A methodology of exploratory data analysis investigating the phenomenon of orographic precipitation enhancement is proposed. The precipitation observations obtained from three Swiss Doppler weather radars are analysed for the major precipitation event of August 2005 in the Alps. Image processing techniques are used to detect significant precipitation cells/pixels from radar images while filtering out spurious effects due to ground clutter. The contribution of topography to precipitation patterns is described by an extensive set of topographical descriptors computed from the digital elevation model at multiple spatial scales. Additionally, the motion vector field is derived from subsequent radar images and integrated into a set of topographic features to highlight the slopes exposed to main flows. Following the exploratory data analysis with a recent algorithm of spectral clustering, it is shown that orographic precipitation cells are generated under specific flow and topographic conditions. Repeatability of precipitation patterns in particular spatial locations is found to be linked to specific local terrain shapes, e.g. at the top of hills and on the upwind side of the mountains. This methodology and our empirical findings for the Alpine region provide a basis for building computational data-driven models of orographic enhancement and triggering of precipitation. Copyright (C) 2011 Royal Meteorological Society .