172 research outputs found
Distributed Reasoning in a Peer-to-Peer Setting: Application to the Semantic Web
In a peer-to-peer inference system, each peer can reason locally but can also
solicit some of its acquaintances, which are peers sharing part of its
vocabulary. In this paper, we consider peer-to-peer inference systems in which
the local theory of each peer is a set of propositional clauses defined upon a
local vocabulary. An important characteristic of peer-to-peer inference systems
is that the global theory (the union of all peer theories) is not known (as
opposed to partition-based reasoning systems). The main contribution of this
paper is to provide the first consequence finding algorithm in a peer-to-peer
setting: DeCA. It is anytime and computes consequences gradually from the
solicited peer to peers that are more and more distant. We exhibit a sufficient
condition on the acquaintance graph of the peer-to-peer inference system for
guaranteeing the completeness of this algorithm. Another important contribution
is to apply this general distributed reasoning setting to the setting of the
Semantic Web through the Somewhere semantic peer-to-peer data management
system. The last contribution of this paper is to provide an experimental
analysis of the scalability of the peer-to-peer infrastructure that we propose,
on large networks of 1000 peers
Towards the 3D Modelling of the Effective Conductivity of Solid Oxide Fuel Cell Electrodes - Validation against experimental measurements and prediction of electrochemical performance
© 2015 Elsevier Ltd. All rights reserved.The effective conductivity of thick-film solid oxide fuel cell (SOFC) electrodes plays a key role in their performance. It determines the ability of the electrode to transport charge to/from reaction sites to the current collector and electrolyte. In this paper, the validity of the recently proposed 3D resistor network model for the prediction of effective conductivity, the ResNet model, is investigated by comparison to experimental data. The 3D microstructures of Ni/10ScSZ anodes are reconstructed using tomography through the focused ion beam and scanning electron microscopy (FIB-SEM) technique. This is used as geometric input to the ResNet model to predict the effective conductivities, which are then compared against the experimentally measured values on the same electrodes. Good agreement is observed, supporting the validity of the ResNet model for predicting the effective conductivity of SOFC electrodes. The ResNet model is then combined with the volume-of-fluid (VOF) method to integrate the description of the local conductivity (electronic and ionic) in the prediction of electrochemical performance. The results show that the electrochemical performance is in particular sensitive to the ionic conductivity of the electrode microstructure, highlighting the importance of an accurate description of the local ionic conductivity
Predictive models for the phase behaviour and solution properties of weak electrolytes: nitric, sulfuric and carbonic acid
The distribution of ionic species in electrolyte systems is important in many fields of science and engineering, ranging from the study of degradation mechanisms to the design of systems for electrochemical energy storage. Often, other phenomena closely related to the ionic speciation, such as ion pairing, clustering and hydrogen bonding, which are difficult to investigate experimentally, are also of interest. Here, we develop an accurate molecular approach, accounting for reactions as well as association and ion pairing, to deliver a predictive framework that helps validate experiment and guides future modelling of speciation phenomena of weak electrolytes. We extend the SAFT-VRE Mie equation of state [D. K. Eriksen et al., Mol. Phys., 2016, 114, 2724–2749] to study aqueous solutions of nitric, sulphuric and carbonic acid, considering complete and partially dissociated models. In order to incorporate the dissociation equilibria, correlations to experimental data for the relevant thermodynamic equilibrium constants of the dissociation reactions are taken from the literature and are imposed as a boundary condition in the calculations. The models for water, the hydronium ion, and carbon dioxide are treated as transferable and are taken from our previous work. Here we present new molecular models for nitric acid, and the nitrate, bisulfate, sulfate, and bicarbonate anions. The resulting framework is used to predict a range of phase behaviour and solution properties of the aqueous acids over wide ranges of concentration and temperature, including the degree of dissociation, as well as the activity coefficients of the ionic species, and the activity of water and osmotic coefficient, density, and vapour pressure of the solutions. The SAFT-VRE Mie models obtained in this manner provide a means of elucidating the mechanisms of association and ion pairing in the systems studied, complementing the experimental observations reported in the literature
Solvent effects on Grubbs’ pre-catalyst initiation rates
Initiation rates for Grubbs and Grubbs-Hoveyda second generation pre-catalysts have been measured accurately in a range of solvents. Solvatochromic fitting reveals different dependencies on key solvent parameters for the two pre-catalysts, consistent with different mechanisms by which the Grubbs and Grubbs-Hoveyda pre-catalysts initiate
Systems thinking for the transition to zero pollution
Systems approaches are vital for coordinating decision-making in the face of complex issues because they provide the whole picture view needed to avoid negative unintended consequences and to generate genuine benefits. This paper explains how systems thinking can be used to address environmental pollution and support decision-makers in finding solutions
Toward a simulation approach for alkene ring-closing metathesis : scope and limitations of a model for RCM
A published model for revealing solvent effects on the ring-closing metathesis (RCM) reaction of di-Et diallylmalonate 7 has been evaluated over a wider range of conditions, to assess its suitability for new applications. Unfortunately, the model is too flexible and the published rate consts. do not agree with exptl. studies in the literature. However, by fixing the values of important rate consts. and restricting the concn. ranges studied, useful conclusions can be drawn about the relative rates of RCM of different substrates, precatalyst concn. can be simulated accurately and the effect of precatalyst loading can be anticipated. Progress has also been made toward applying the model to precatalyst evaluation, but further modifications to the model are necessary to achieve much broader aims
Predicting enhanced absorption of light gases in polyethylene using simplified PC-SAFT and SAFT-VR
International audienceAbsorption of light gases in polyethylene (PE) is studied using two versions of the Statistical Associating Fluid Theory (SAFT): SAFT for chain molecules with attractive potentials of variable range (VR) and simplified perturbed-chain (PC) SAFT. Emphasis is placed on the light gases typically present during ethylene polymerisation in the gas-phase reactor (GPR) process. The two approaches are validated using experimental binary-mixture data for gas absorbed in PE, and predictions are made for mixtures of more components. For most cases studied both SAFT versions perform equally well. For the case of ternary mixtures of two gases with PE, it is predicted that the less-volatile of the two gases acts to enhance the absorption of the more-volatile gas, while the more-volatile gas inhibits the absorption of the less-volatile gas. This general behaviour is also predicted in mixtures containing more gases, such as typical reactor mixtures. The magnitude of the effect may vary considerably, depending on the relative proximity of the gas-mixture saturation pressure to the reactor pressure; for example it is predicted that the absorption of ethylene may be approximately doubled if diluent gases, propane or nitrogen, are partially or completely replaced by less-volatile butane or pentane for a reactor pressure similar to 2 MPa. In the case of a co-polymerisation reaction, it is predicted that increases in absorption of both co-monomers may be obtained in roughly equal proportion. Our findings cast light on the so-called co-monomer effect, in which substantial increases in the rate of ethylene polymerisation are observed in the presence of hexene co-monomer, while suggesting that the effect is more general and not restricted to co-monomer. For example, similar rate increases may be expected in the presence of, e.g., pentane instead of hexene, but without the change in the branch structure of the produced polymer that is inevitable when the amount of co-monomer is increased
Predicting the solvation of organic compounds in aqueous environments: from alkanes and alcohols to pharmaceuticals
The development of accurate models to predict the solvation, solubility, and partitioning of nonpolar and amphiphilic compounds in aqueous environments remains an important challenge. We develop state-of-the-art group-interaction models that deliver an accurate description of the thermodynamic properties of alkanes and alcohols in aqueous solution. The group-contribution formulation of the statistical associating fluid theory based on potentials with a variable Mie form (SAFT-γ Mie) is shown to provide accurate predictions of the phase equilibria, including liquid–liquid equilibria, solubility, free energies of solvation, and other infinite-dilution properties. The transferability of the model is further exemplified with predictions of octanol–water partitioning and solubility for a range of organic and pharmaceutically relevant compounds. Our SAFT-γ Mie platform is reliable for the prediction of challenging properties such as mutual solubilities of water and organic compounds which can span over 10 orders of magnitude, while remaining generic in its applicability to a wide range of compounds and thermodynamic conditions. Our work sheds light on contradictory findings related to alkane–water solubility data and the suitability of models that do not account explicitly for polarity
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