Regional development gaps in Argentina: A multidimensional approach to identify the location of policy priorities

Spatial inequalities within Latin American countries have historically attracted the interest ofacademics, policy-makers, and international agencies. This article aims to provide amultidimensional diagnosis of provincial development gaps in Argentina, in order to identifythe location of policy priorities. Therefore, we built a large database, which covers sevendevelopment dimensions, and applied multivariate analysis techniques to overcome someanalytical limitations of previous studies. Results show the stability of provincial developmentgaps between 2003 and 2013 and some heterogeneity within geographic regions. Instead,cluster analysis offers a better classification of Argentine provinces according to theirdevelopment gaps, which can help the government to prioritize the places wheredevelopment policies are strategic.Fil: Niembro, Andrés Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina. Universidad Nacional de Río Negro; ArgentinaFil: Sarmiento, Jesica Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina. Universidad Nacional de Río Negro; Argentin

Quantitative structure-property relationship approach to predicting xylene separation with diverse exchanged faujasites

International audienceStreamlining the xylene separation process on faujasites is a promising way to design innovative adsorbents for this application. For this purpose, we present herein an original quantitative structure–property relationship (QSPR) approach. It deals with the development of a multi-linear predictive model correlating the separation properties with a set of structural descriptors for the adsorbents. The implementation of such an approach makes it necessary to (i) set an appropriate design of experiment (DOE), (ii) prepare an adsorbent database, (iii) test the adsorbent database for xylene separation and (iv) compute a set of relevant descriptors. The selected descriptors essentially characterize the nature of the confinement in the faujasite supercage, i.e., the size of the cations localized in adsorption sites II, as well as the occupancy ratio of both adsorption sites II and III. Two different statistical methods were applied to develop a structure–property relationship model linking experimental selectivity and the set of descriptors. A multiple linear regression model enables the prediction of para/meta-xylene selectivity with a correlation coefficient R2 of 0.78, while a linear discriminant analysis predicts the assignment of the adsorbents to four identified classes with a total prediction percentage of 76%

Enhanced CO₂ Solubility in Hybrid Adsorbents: Optimization of Solid Support and Solvent Properties for CO₂ Capture

In this study, we optimize the CO₂ adsorption performance of hybrid adsorbents prepared by confining physical solvents in porous solid supports. A number of prospective solid supports and physical solvents are chosen to prepare hybrid adsorbents, and are subsequently evaluated in CO₂ adsorption experiments. Generally, all the hybrid adsorbents show an enhancement of CO₂ solubility compared to the bulk physical solvent. However, not all the adsorbents positively display an improvement in the CO₂ adsorption performance as compared with the original solids after confining the physical solvent into the solids’ pore. The micropore blocking effect is observed in the impregnated forms of zeolite, activated carbon, silicagel, and cecagel. Furthermore, we have obtained certain requisites for a good solid support, as efficient structures should be mesoporous with large surface area. In addition, there is an optimized solvent’s size to achieve an optimized enhanced solubility. As a result, among the candidates, <i>N</i>-methyl-2-pyrrolidone confined in MCM-41 and alumina are identified as the most suitable hybrid adsorbents for an effective CO₂-removal application

Generic Postfunctionalization Route from Amino-Derived Metal-Organic Frameworks

Savonnet, Marie Bazer-Bachi, Delphine Bats, Nicolas Perez-Pellitero, Javier Jeanneau, Erwann Lecocq, Vincent Pinel, Catherine Farrusseng, DavidThis study deals with the development of a soft, generic, one-pot postfunctionalization method for metal-organic frameworks (MOFs) starting from compounds with an amino group on the linker. The first step consists of transforming the amino group into azide (N-3) by an unconventional route using tBuONO and TMSN3. In the same vessel, the desired functionalized MOF then is obtained by the Huisgen 1,3-dipolar cycloaddition of azides to alkynes, otherwise known as the "click" reaction. The method was applied to DMOF-NH2 and MIL-68(In)-NH2, which represent two distinct and important classes of MOF. For both, the functionalization was complete (>90% grafting) and the crystallinity was maintained. Thanks to the large diversity and availability of cyano- and acetylene-based chemicals, this method opens the door to tailor-made functionalized MOFs

Accurate model for predicting adsorption of olefins and paraffins on MOFs with open metal sites

Metal–organic frameworks (MOFs) have shown tremendous potential for challenging gas separation applications, an example of which is the separation of olefins from paraffins. Some of the most promising MOFs show enhanced selectivity for the olefins due to the presence of coordinatively unsaturated metal sites, but accurate predictive models for such systems are still lacking. In this paper, we present results of a combined experimental and theoretical study on adsorption of propane, propylene, ethane, and ethylene in CuBTC, a MOF with open metal sites. We first propose a simple procedure to correct for impurities present in real materials, which in most cases makes experimental data from different sources consistent with each other and with molecular simulation results. By applying a novel molecular modeling approach based on a combination of quantum mechanical density functional theory and classical grand canonical Monte Carlo simulations, we are able to achieve excellent predictions of olefin adsorption, in much better agreement with experiment than traditional, mostly empirical, molecular models. Such an improvement in predictive ability relies on a correct representation of the attractive energy of the unsaturated metal for the carbon–carbon double bond present in alkenes. This approach has the potential to be generally applicable to other gas separations that involve specific coordination-type bonds between adsorbates and adsorbents