6 resultados para 030000 CHEMICAL SCIENCE

em Universidad de Alicante


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The presence of a highly tunable porous structure and surface chemistry makes metal–organic framework (MOF) materials excellent candidates for artificial methane hydrate formation under mild temperature and pressure conditions (2 °C and 3–5 MPa). Experimental results using MOFs with a different pore structure and chemical nature (MIL-100 (Fe) and ZIF-8) clearly show that the water–framework interactions play a crucial role in defining the extent and nature of the gas hydrates formed. Whereas the hydrophobic MOF promotes methane hydrate formation with a high yield, the hydrophilic one does not. The formation of these methane hydrates on MOFs has been identified for the first time using inelastic neutron scattering (INS) and synchrotron X-ray powder diffraction (SXRPD). The results described in this work pave the way towards the design of new MOF structures able to promote artificial methane hydrate formation upon request (confined or non-confined) and under milder conditions than in nature.

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The Global Experiment, Water: A Chemical Solution, was one of the flagship activities of the International Year of Chemistry (IYC). During the virtual colloquium of the spring 2012 online ConfChem conference, the main results of this year-long experiment were presented and discussed online for a week. Some of the main conclusions of the virtual conversations relate to the benefits of creating online communities of people sharing similar interests, the use of online educational platforms to gather massive amounts of data, and specific questions about the development of this IYC initiative. The activities of the global water experiment (GWE) were designed by a team of experts and the protocols are available online on the GWE Web site. The results were shown in one interactive world map that allowed students to learn about data visualization, validation, and interpretation. The feedback obtained from the participants of the GWE and later by the contributors of the virtual colloquium was very positive. Many participants asked specific and technical questions about the development of this experiment, while others excitedly endorsed the convenience of these large open-access activities to promote chemistry worldwide. The estimate is that over 2 million people took part in the GWE during the IYC. This communication summarizes one of the invited papers to the ConfChem online conference: A Virtual Colloquium to Sustain and Celebrate IYC 2011 Initiatives in Global Chemical Education, held from May 18 to June 29, 2012 and hosted by the ACS DivCHED Committee on Computers in Chemical Education and the IUPAC Committee on Chemistry Education.

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The main goal of this paper is to present the initial version of a Textile Chemical Ontology, to be used by textile professionals with the purpose of conceptualising and representing the banned and harmful chemical substances that are forbidden in this domain. After analysing different methodologies and determining that “Methontology” is the most appropriate for the purposes, this methodology is explored and applied to the domain. In this manner, an initial set of concepts are defined, together with their hierarchy and the relationships between them. This paper shows the benefits of using the ontology through a real use case in the context of Information Retrieval. The potentiality of the proposed ontology in this preliminary evaluation encourages extending the ontology with a higher number of concepts and relationships, and validating it within other Natural Language Processing applications.

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With advances in the synthesis and design of chemical processes there is an increasing need for more complex mathematical models with which to screen the alternatives that constitute accurate and reliable process models. Despite the wide availability of sophisticated tools for simulation, optimization and synthesis of chemical processes, the user is frequently interested in using the ‘best available model’. However, in practice, these models are usually little more than a black box with a rigid input–output structure. In this paper we propose to tackle all these models using generalized disjunctive programming to capture the numerical characteristics of each model (in equation form, modular, noisy, etc.) and to deal with each of them according to their individual characteristics. The result is a hybrid modular–equation based approach that allows synthesizing complex processes using different models in a robust and reliable way. The capabilities of the proposed approach are discussed with a case study: the design of a utility system power plant that has been decomposed into its constitutive elements, each treated differently numerically. And finally, numerical results and conclusions are presented.

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In this work, we analyze the effect of demand uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear program (MILP) with the unique feature of incorporating explicitly the demand uncertainty using scenarios with given probability of occurrence. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact.

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Over the past decade, a great effort has been made by the chemical community to improve the efficiency of organic transformations and allow sustainable processes. Merging the use of supported and recyclable organocatalysts and aqueous conditions for the asymmetric synthesis of valuable molecules, has led to outstanding contributions in the area of green chemistry. Recent progresses in the field include the implementation of these methodologies in the large scale production of chiral molecules using automated flow chemistry.