Synthesis of Monomeric Fe(II) and Ru(II) Complexes of Tetradentate Phosphines

rac-Bis[{(diphenylphosphino)ethyl}-phenylphosphino]methane (DPPEPM) reacts with iron(II) and ruthenium(II) halides to generate complexes with folded DPPEPM coordination. The paramagnetic, five-coordinate Fe(DPPEPM)Cl2 (1) in CD2Cl2 features a tridentate binding mode as established by 31P{1H} NMR spectroscopy. Crystal structure analysis of the analogous bromo complex, Fe(DPPEPM)Br2 (2) revealed a pseudo-octahedral, cis-α geometry at iron with DPPEPM coordinated in a tetradentate fashion. However, in CD2Cl2solution, the coordination of DPPEPM in 2 is similar to that of 1 in that one of the external phosphorus atoms is dissociated resulting in a mixture of three tridentate complexes. The chloro ruthenium complex cis-Ru(κ4-DPPEPM)Cl2 (3) is obtained from rac-DPPEPM and either [RuCl2(COD)]2 [COD = 1,5-cyclooctadiene] or RuCl2(PPh3)4. The structure of 3 in both the solid state and in CD2Cl2 solution features a folded κ4-DPPEPM. This binding mode was also observed in cis-[Fe(κ4-DPPEPM)(CH3CN)2](CF3SO3)2 (4). Addition of an excess of CO to a methanolic solution of 1 results in the replacement of one of the chloride ions by CO to yieldcis-[Fe(κ4-DPPEPM)Cl(CO)](Cl) (5). The same reaction in CH2Cl2 produces a mixture of 5and [Fe(κ3-DPPEPM)Cl2(CO)] (6) in which one of the internal phosphines has been substituted by CO. Complexes 2, 3, 4, and 5 appear to be the first structurally characterized monometallic complexes of κ4-DPPEPM

A Partial Backlogging Inventory Model for Deteriorating Item under Fuzzy Inflation and Discounting over Random Planning Horizon: A Fuzzy Genetic Algorithm Approach

An inventory model for deteriorating item is considered in a random planning horizon under inflation and time value money. The model is described in two different environments: random and fuzzy random. The proposed model allows stock-dependent consumption rate and shortages with partial backlogging. In the fuzzy stochastic model, possibility chance constraints are used for defuzzification of imprecise expected total profit. Finally, genetic algorithm (GA) and fuzzy simulation-based genetic algorithm (FSGA) are used to make decisions for the above inventory models. The models are illustrated with some numerical data. Sensitivity analysis on expected profit function is also presented. Scope and Purpose. The traditional inventory model considers the ideal case in which depletion of inventory is caused by a constant demand rate. However, to keep sales higher, the inventory level would need to remain high. Of course, this would also result in higher holding or procurement cost. Also, in many real situations, during a longer-shortage period some of the customers may refuse the management. For instance, for fashionable commodities and hightech products with short product life cycle, the willingness for a customer to wait for backlogging is diminishing with the length of the waiting time. Most of the classical inventory models did not take into account the effects of inflation and time value of money. But in the past, the economic situation of most of the countries has changed to such an extent due to large-scale inflation and consequent sharp decline in the purchasing power of money. So, it has not been possible to ignore the effects of inflation and time value of money any more. The purpose of this paper is to maximize the expected profit in the random planning horizon

A Partial Backlogging Inventory Model for Deteriorating Item under Fuzzy Inflation and Discounting over Random Planning Horizon: A Fuzzy Genetic Algorithm Approach

An inventory model for deteriorating item is considered in a random planning horizon under inflation and time value money. The model is described in two different environments: random and fuzzy random. The proposed model allows stock-dependent consumption rate and shortages with partial backlogging. In the fuzzy stochastic model, possibility chance constraints are used for defuzzification of imprecise expected total profit. Finally, genetic algorithm (GA) and fuzzy simulation-based genetic algorithm (FSGA) are used to make decisions for the above inventory models. The models are illustrated with some numerical data. Sensitivity analysis on expected profit function is also presented. Scope and Purpose. The traditional inventory model considers the ideal case in which depletion of inventory is caused by a constant demand rate. However, to keep sales higher, the inventory level would need to remain high. Of course, this would also result in higher holding or procurement cost. Also, in many real situations, during a longer-shortage period some of the customers may refuse the management. For instance, for fashionable commodities and high-tech products with short product life cycle, the willingness for a customer to wait for backlogging is diminishing with the length of the waiting time. Most of the classical inventory models did not take into account the effects of inflation and time value of money. But in the past, the economic situation of most of the countries has changed to such an extent due to large-scale inflation and consequent sharp decline in the purchasing power of money. So, it has not been possible to ignore the effects of inflation and time value of money any more. The purpose of this paper is to maximize the expected profit in the random planning horizon

Utilizing Reduced Graphene Oxide-Iron Nanoparticles Composite to Enhance and Accelerate the Removal of Methyl Blue Organic Dye in Wastewater

In this work, a nano-composite is used to remove dye from wastewater of different industries. For this purpose, thesynthesis of a magnetic 1:1 composite made of iron nanoparticles (NPs) using reduced graphene oxide is a novel techniqueand tested for Methyl Blue (MB) dye adsorption from aqueous solution. In this study Fe nanoparticles in reduced Graphenecomposite (FGOC) has been prepared using Graphene Oxide (GO). X-ray diffraction, FTIR spectroscopy and Ramanspectroscopy, are used to identify the structures. Many methods have been developed for MB removal in wastewater. One ofthe most popular methods is adsorption because it is simple and high-efficiency, and the adsorbent is crucial. It reached amaximum MB adsorption at pH 7. The kinetic study indicated that the adsorption of MB process was fitted well to thequasi-first-order and quasi-second-order kinetic models. The isotherm study revealed that the MB adsorption process obeyedthe Langmuir and Freundlich adsorption Isotherms models. The GO adding content and absorption conditions on the methylblue removal efficiencies were investigated. This adsorbent is easily recovered by an external magnetic field from thetreated wastewater and has high reusability

Development and applications of a relaxation-inducing cluster expansion theory for treating strong relaxation and differential correlation effects

We present in this paper a multi-reference coupled cluster (MRCC) formulation for energy differences which treats orbital relaxation and correlation effects on the same footing, by invoking a novel cluster ansatz of the valence portion of the wave operator Ωv. Unlike in the traditional normal-ordered exponential representation of Ωv, our new relaxation-inducing ansatz, represented symbolically as E r(S), allows contractions between the spectator lines and also certain other special contractions. By an extensive theoretical analysis, taking as an example the case of one-hole model space (the IP problem), we demonstrate that our ansatz incorporates in a manifestly spin-free form the orbital relaxation to all orders. The traditional Thouless-type of exponential transformation via one-body excitations can induce the same effect, as is done in the valence-specific or the quasi-valence-specific MRCC formalisms, but they have to be done in the spin-orbital basis - making the spin adaptation of the problem a complicated exercise. In contrast, we use a spin-free representation of the cluster operators right from start, but expand the rank of the cluster operators by involving spectator orbitals to distinguish the various spin possibilities. The combinatorial factors entering the contracted power series in E r(S) are chosen in such a way that they correspond to what we would have obtained if we had used a Thouless-like transformation to induce the orbital relaxation. Our working equations generally have only finite powers of the cluster operators S, resulting in a very compact formulation of the relaxation problem. Pilot numerical applications for the IP computations of HF and H2O in the core, the inner valence and the outer valence regions show very good performance of the method vis-a-vis those obtained using the traditional normal ordered ansatz for Ωv. The improvement in the core IP value is particularly impressive, although even for the valence regions there is an overall improvement of the IP values

Constrained FC 4D MITPs for Damageable Substitutable and Complementary Items in Rough Environments

Very often items that are substitutable and complementary to each other are sent from suppliers to retailers for business. In this paper, for these types of items, fixed charge (FC) four-dimensional (4D) multi-item transportation problems (MITPs) are formulated with both space and budget constraints under crisp and rough environments. These items are damageable/breakable. The rates of damageability of the items depend on the quantity transported and the distance of travel i.e., path. A fixed charge is applied to each of the routes (independent of items). There are some depots/warehouses (origins) from which the items are transported to the sales counters (destinations) through different conveyances and routes. In proposed FC 4D-MITP models, per unit selling prices, per unit purchasing prices, per unit transportation expenditures, fixed charges, availabilities at the sources, demands at the destinations, conveyance capacities, total available space and budget are expressed by rough intervals, where the transported items are substitutable and complementary in nature. In this business, the demands for the items at the destinations are directly related to their substitutability and complementary natures and prices. The suggested rough model is converted into a deterministic one using lower and upper approximation intervals following Hamzehee et al. as well as Expected Value Techniques. The converted model is optimized through the Generalized Reduced Gradient (GRG) techniques using LINGO 14 software . Finally, numerical examples are presented to illustrate the preciseness of the proposed model. As particular cases, different models such as 2D, 3D FCMITPs for two substitute items, one item with its complement and two non substitute non complementary items are derived and results are presented

FCSTP with possibility and expected value approaches in hybrid uncertain environments

The objective of this investigation is to formulate a fixed charge (FC) solid transportation problem (STP) under a hybrid uncertain environment where both fuzziness and roughness coexist. A fuzzy rough STP model is developed by integrating the classical STP, fuzzy set theory, and rough set theory, which apparently provides a way to accommodate the uncertainty. For solving the problem, we apply the fuzzy rough expected value operator and propose the possibility based STP model with fuzzy rough parameters on a rough space. At the end, a mathematical illustration is provided to describe the fuzzy rough approach using LINGO 14.0 optimization software. As particular cases, the proposed model is also solved for single impreciseness. Finally, a graphical presentation is also shown to describe the comparison between two proposed approaches. In a particular case, the expressions of an earlier investigator have been derived from the present expressions. Important managerial decisions are made after observation of optimal results.Publisher's Versio