Exergoeconomic analysis of a thermochemical copper–chlorine cycle for hydrogen production using specific exergy cost (SPECO) method

The manner is investigated in which exergy-related parameters can be used to minimize the cost of a copper–chlorine (Cu–Cl) thermochemical cycle for hydrogen production. The iterative optimization technique presented requires a minimum of available data and provides effective assistance in optimizing thermal systems, particularly in dealing with complex systems and/or cases where conventional optimization techniques cannot be applied. The principles of thermoeconomics, as embodied in the specific exergy cost (SPECO) method, are used here to determine changes in the design parameters of the cycle that improve the cost effectiveness of the overall system. The methodology provides a reasonable approach for improving the cost effectiveness of the Cu–Cl cycle, despite the fact that it is still in development. It is found that the cost rate of exergy destruction varies between $1 and $15 per kilogram of hydrogen and the exergoeconomic factor between 0.5 and 0.02 as the cost of hydrogen rises from $20 to $140 per GJ of hydrogen energy. The hydrogen cost is inversely related to the exergoeconomic factor, plant capacity and exergy efficiency. The results are expected to assist ongoing efforts to increase the economic viability and to reduce product costs of potential commercial versions of this process. The impact of the results are anticipated to be significant since thermochemical water splitting with a copper–chlorine cycle is a promising process that could be linked with nuclear reactors to produce hydrogen with no greenhouse gases emissions, and thereby help mitigate numerous energy and environment concerns.     

The beautiful cell: high-content screening in drug discovery

The term “high-content screening” has become synonymous with imaging screens using automated microscopes and automated image analysis. The term was coined a little over 10 years ago. Since then the technology has evolved considerably and has established itself firmly in the drug discovery and development industry. Both the instruments and the software controlling the instruments and analyzing the data have come to maturity, so the full benefits of high-content screening can now be realized. Those benefits are the capability of carrying out phenotypic multiparametric cellular assays in an unbiased, fully automated, and quantitative fashion. Automated microscopes and automated image analysis are being applied at all stages of the drug discovery and development pipeline. All major pharmaceutical companies have adopted the technology and it is in the process of being embraced broadly by the academic community. This review aims at describing the current capabilities and limits of the technology as well as highlighting necessary developments that are required to exploit fully the potential of high-content screening and analysis.     

Investigations providing a plausible mechanism in the hexamethyldisilazane-catalyzed trimerization of alkyl isocyanates

Using HMDS as catalyst for the trimerization of isocyanates presents many advantages as the expected isocyanurate is not contaminated by the catalyst or other side-products resulting from its degradation. In addition, HMDS presents a low toxicity, and is compatible with industrial applications. This article describes the hexamethyldisilazane (HMDS)-catalyzed trimerization of octylisocyanate. Experimental investigations and mechanistic considerations indicate that the true catalyst of the trimerization is trimethylsilyloctylamine, which results from the preliminary condensation of HMDS with octylisocyanate.     

A Large Deviations Principle Related to the Strong Arc-Sine Law

We show a large deviations principle for the family of random variables when t+, where B=(B _u ,u0) is a standard linear Brownian motion.     

The Entrance Laws of Self-Similar Markov Processes and Exponential Functionals of Lévy Processes

We consider the asymptotic behavior of semi-stable Markov processes valued in ]0,[ when the starting point tends to 0. The entrance distribution is expressed in terms of the exponential functional of the underlying Lévy process which appears in Lamperti's representation of a semi-stable Markov process.     

Quantitative Modelization of Hydrogen-Bonding in Polyoxometalate Chemistry

The PACHA (Partial Atomic Charges and Hardnesses Analysis) formalism is applied to polyoxometalate chemistry. Using the Ca₂(H₃O)₂[V₁₀O₂₈]16H₂O crystal structure, it was shown that the relative affinity for protons of the various oxygen sites may be quantitatively determined. The charge distribution was also found to be in good agreement with ¹⁷O and ⁵¹V NMR measurements. The H-bond energy in this kind of compound was found to be about –17 kJmol^–1, i.e., about 20% lower than in hexagonal ice. Finally, the 57 H-atom coordinates characterizing this structure were successfully recovered from a crystal structure optimization in the solid-state through electrostatic balance minimization. The importance of considering neutral clusters for a good modelization was demonstrated not only in the case of the decavanadate structure, but also in polysilicate chemistry. For the first time a clear picture emerges explaining the widespread occurrence of four- and five-membered rings in zeolite and silicate chemistry. The possibility of forming much larger polyanions with transition metal cations, is well explained using the crystal structure of the superfullerene keplerate [Mo₁₃₂O₃₇₂(HCO₂)₃₀(H₂O)₇₂]^42– as a benchmark compound. The possibility of performing an ab-initio retrosynthetic analysis of this cage is demonstrated.     

Polar,non-coordinating ionic liquids as solvents for the alternating copolymerization of styrene and CO catalyzed by cationic palladium catalysts

The palladium-catalyzed copolymerization of styrene and CO in an ionic liquid solvent, 1-hexylpyridinium bis(trifluoromethanesulfonyl)imide, gave improved yields and increased molecular weights compared to polymerizations run in methanol.