Microwave-Assisted Derivatization of Cellulose in an Ionic Liquid: An Efficient, Expedient Synthesis of Simple and Mixed Carboxylic Esters

Microwave (MW)-assisted cellulose dissolution in ionic liquids (ILs) has routinely led either to incomplete biopolymer solubilization, or its degradation. We show that these problems can be avoided by use of low-energy MW heating, coupled with efficient stirring. Dissolution of microcrystalline cellulose in the IL 1-allyl-3-methylimidazolium chloride has been achieved without changing its degree of polymerization; regenerated cellulose showed pronounced changes in its index of crystallinity, surface area, and morphology. MW-assisted functionalization of MCC by ethanoic, propanoic, butanoic, pentanoic, and hexanoic anhydrides has been studied. Compared with conventional heating, MW irradiation has resulted in considerable decrease in dissolution and reaction times. The value of the degree of substitution (DS) was found to be DS(ethanoate) > DS(propanoate) > DS(butanoate). The values of DS(pentanoate) and DS(hexanoate) were found to be slightly higher than DS(ethanoate). This surprising dependence on the chain length of the acylating agent has been reported before, but not rationalized. On the basis of the rate constants and activation parameters of the hydrolysis of ethanoic, butanoic, and hexanoic anhydrides in aqueous acetonitrile (a model acyl transfer reaction), we suggest that this result may be attributed to the balance between two opposing effects, namely, steric crowding and (cooperative) hydrophobic interactions between the anhydride and the cellulosic surface, whose lipophilicity has increased, due to its partial acylation. Four ethanoate-based mixed esters were synthesized by the reaction with a mixture of the two anhydrides; the ethanoate moiety predominated in all products. The DS is reproducible and the IL is easily recycled. (C) 2009 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 48: 134-143, 2010

Luminescence enhancement of the Tb(III) ion with the thenoyltrifluoroacetonate ligand acting as an efficient sensitizer

The synthesis, structural investigation, and photophysical properties of the complex [Tb(TTA)(2)(NO(3)) (TPPO)(2)] are reported. Unlike the analog tris-diketonate complex [Tb(TTA)(3)(TPPO)(2)], the new complex presents abnormally high luminescence intensity centered on the terbium ion. Our results clearly suggest a higher energy transfer efficiency from the TEA antenna ligand to the Tb(III) ion in the bis-diketonate complex compared with that in the tris-diketonate complex. A mechanism involving the increasing of triplet state energy when one TTA ligand is replaced by the NO(3)(-) group in the first coordination sphere is suggested and experimentally investigated to explain the anomalous luminescence properties of the new complex [Tb(TTA)(2)(NO(3))(TPPO)(2)]. (C) 2010 Elsevier B.V. All rights reserved.

Using autonomous mobile agents for efficient data collection in sensor networks

Sensor networks are emerging as the new frontier in sensing technology, however there are still issues that need to be addressed. Two such issues are data collection and energy conservation. We consider a mobile robot, or a mobile agent, traveling the network collecting information from the sensors themselves before their onboard memory storage buffers are full. A novel algorithm is presented that is an adaptation of a local search algorithm for a special case of the Asymmetric Traveling Salesman Problem with Time-windows (ATSPTW) for solving the dynamic scheduling problem of what nodes are to be visited so that the information collected is not lost. Our algorithms are given and compared to other work.

Maintaining optimal co-channel interference for power efficient wireless communication

Maintaining QoS (quality of service) guaranteed communication links, and improving the energy consumption; are two aspects that received a significant consideration in the modern wireless sensor network research. This paper formulates a transmission power control problem which satisfies both considerations mentioned above. Moreover, a class of functions for an iterative controller was introduced and analyzed for its convergence. The experimental evaluation of the controller justifies the theoretical assertions as well as the applicability of the control scheme in wireless nodes with minimum measurement capabilities.

Transesterification of fish oil to produce fatty acid ethyl esters using ultrasonic energy

This study evaluated the production of fatty acid ethyl esters from fish oil using ultrasonic energy and alkaline catalysts dissolved in ethanol. The feasibility of fatty acid ethyl ester production was determined using an ultrasonic bath and probe, and between 0.5 and 1% KOH (added to the fish oil). Furthermore, factors such as ultrasonic device (bath and probe), catalyst (KOH and C2H5ONa), temperature (20 and 60 °C), and duration of exposure (10–90 min) were assessed. Sodium ethoxide was found to be a more efficient catalyst than KOH when transesterifying fish oil. Ultrasonic energy applied for greater than 30 min at 60 °C using 0.8% of C2H5ONa as a catalyst transesterified over 98% fish oil triglycerides to fatty acid ethyl esters. It is reasonable to conclude that the yield of fatty acid ethyl esters produced by applying ultrasonic energy to fish oil is related to the sonication time. Due to increases in the surface area contact between the reactants and the catalyst, ultrasonic energy has the potential to reduce the production time required by a conventional large-scale commercial transesterification method that uses agitation as a way of mixing.

Adaptive cruise control look-ahead system for energy management of vehicles

Cruise control in motor vehicles enhances safe and efficient driving by maintaining a constant speed at a preset level. Adaptive Cruise Control (ACC) is the latest development in cruise control. It controls engine throttle position and braking to maintain a safe distance behind a vehicle in front by responding to the speed of this vehicle, thus providing a safer and more relaxing driving environment. ACC can be further developed by including the look-ahead method of predicting environmental factors such as wind speed and road slope. The conventional analytical control methods for adaptive cruise control can generate good results; however they are difficult to design and computationally expensive. In order to achieve a robust, less computationally expensive, and at the same time more natural human-like speed control, intelligent control techniques can be used. This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS) based on ACC systems that reduces the energy consumption of the vehicle and improves its efficiency. The Adaptive Cruise Control Look-Ahead (ACC-LA) system works as follows: It calculates the energy consumption of the vehicle under combined dynamic loads like wind drag, slope, kinetic energy and rolling friction using road data, and it includes a look-ahead strategy to predict the future road slope. The cruise control system adaptively controls the vehicle speed based on the preset speed and the predicted future slope information. By using the ANFIS method, the ACC-LA is made adaptive under different road conditions (slope angle and wind direction and speed). The vehicle was tested using the adaptive cruise control look-ahead energy management system, the results compared with the vehicle running the same test but without the adaptive cruise control look-ahead energy management system. The evaluation outcome indicates that the vehicle speed was efficiently controlled through the look-ahead methodology based upon the driving cycle, and that the average fuel consumption was reduced by 3%.

Effect of noise factors in energy management of series plug-in hybrid electric vehicles

It has been demonstrated that charge depletion (CD) energy management strategies are more efficient choices for energy management of plug-in hybrid electric vehicles (PHEVs). The knowledge of drive cycle as a priori can improve the performance of CD energy management in PHEVs. However, there are many noise factors which affect both drivetrain power demand and vehicle performance even in identical drive cycles. In this research, the effect of each noise factor is investigated by introducing the concept of power cycle instead of drive cycle for a journey. Based on the nature of the noise factors, a practical solution for developing a power-cycle library is introduced. Investigating the predicted power cycle, an energy management strategy is developed which considers the influence of temperature noise factor on engine performance. The effect of different environmental and geographic conditions, driver behavior, aging of battery and other components are considered. Simulation results for a modelled series PHEV similar to GM Volt show that the suggested energy management strategy based on the driver power cycle library improves both vehicle fuel economy and battery health by reducing battery load and temperature.

Caveolin-1 orchestrates the balance between glucose and lipid-dependent energy metabolism : implications for liver regeneration

Caveolin-1 (CAV1) is a structural protein of caveolae involved in lipid homeostasis and endocytosis. Using newly generated pure Balb/C CAV1 null (Balb/CCAV1−/−) mice, CAV1−/− mice from Jackson Laboratories (JAXCAV1−/−), and CAV1−/− mice developed in the Kurzchalia Laboratory (KCAV1−/−), we show that under physiological conditions CAV1 expression in mouse tissues is necessary to guarantee an efficient progression of liver regeneration and mouse survival after partial hepatectomy. Absence of CAV1 in mouse tissues is compensated by the development of a carbohydrate-dependent anabolic adaptation. These results were supported by extracellular flux analysis of cellular glycolytic metabolism in CAV1-knockdown AML12 hepatocytes, suggesting cell autonomous effects of CAV1 loss in hepatic glycolysis. Unlike in KCAV1−/− livers, in JAXCAV1−/− livers CAV1 deficiency is compensated by activation of anabolic metabolism (pentose phosphate pathway and lipogenesis) allowing liver regeneration. Administration of 2-deoxy-glucose in JAXCAV1−/− mice indicated that liver regeneration in JAXCAV1−/− mice is strictly dependent on hepatic carbohydrate metabolism. Moreover, with the exception of regenerating JAXCAV1−/− livers, expression of CAV1 in mice is required for efficient hepatic lipid storage during fasting, liver regeneration, and diet-induced steatosis in the three CAV1−/− mouse strains. Furthermore, under these conditions CAV1 accumulates in the lipid droplet fraction in wildtype mouse hepatocytes. Conclusion: Our data demonstrate that lack of CAV1 alters hepatocyte energy metabolism homeostasis under physiological and pathological conditions.

Stochastic models of road geometry and wind condition for vehicle energy management and control

Modeling and simulation is commonly used to improve vehicle performance, to optimize vehicle system design, and to reduce vehicle development time. Vehicle performances can be affected by environmental conditions and driver behavior factors, which are often uncertain and immeasurable. To incorporate the role of environmental conditions in the modeling and simulation of vehicle systems, both real and artificial data are used. Often, real data are unavailable or inadequate for extensive investigations. Hence, it is important to be able to construct artificial environmental data whose characteristics resemble those of the real data for modeling and simulation purposes. However, to produce credible vehicle simulation results, the simulated environment must be realistic and validated using accepted practices. This paper proposes a stochastic model that is capable of creating artificial environmental factors such as road geometry and wind conditions. In addition, road geometric design principles are employed to modify the created road data, making it consistent with the real-road geometry. Two sets of real-road geometry and wind condition data are employed to propose probability models. To justify the distribution goodness of fit, Pearson's chi-square and correlation statistics have been used. Finally, the stochastic models of road geometry and wind conditions (SMRWs) are developed to produce realistic road and wind data. SMRW can be used to predict vehicle performance, energy management, and control strategies over multiple driving cycles and to assist in developing fuel-efficient vehicles.

Design and analysis of efficient rectifiers for wireless power harvesting in DBS devices

This paper presents an analysis of optimum rectifier circuits for wireless energy harvesting in deep brain stimulation (DBS) devices. Since DBS demands compact and low power consumption devices, small, high conversion efficient, and high output voltage rectifiers need to be developed. The investigation that is presented in this paper is analytical and simulated based. Analysis on a variety of circuit configurations brings more evidence to improve the performance of rectifiers. Analytical parameters influencing the output DC voltage and the efficiency of the rectifiers are described. The operating frequency of the 915 MHz industrial, scientific and medical (ISM) radio band is used in this study. The maximum conversion efficiency of the LC matched half wave rectifier, the Greinacher voltage doubler, the Delon doubler, and the 2-stage voltage multiplier is obtained as 56.34%, 74.45%, 71.48%, and 31.44%, respectively, at the 30 dBm input power level. The corresponding maximum output DC voltages are 6.27 V, 16.83 V, 13.36 V, and 9.20 V. Thus the Greinacher voltage doubler is deemed as the best configuration according to the conversion efficiency and the output voltage measurements.

Characteristics and applications of energy storage system to power network - A review

Maintaining reliability and stability of a power systems in transmission and distribution level becomes a big challenge in present scenario. Grid operators are always responsible to maintain equilibrium between available power generation and demand of end users. Maintaining grid balance is a bigger issue, in case of any unexpected generation shortage or grid disturbance or integration of any renewable energy sources like wind and solar power in the energy mix. In order to compensate such imbalance and to facilitate more renewable energy sources with the grid, energy storage system (ESS) started to be playing an important role with the advancement of the state of the art technology. ESS can also help to get reduction in greenhouse gas (GHG) emission by means of integrating more renewable energy sources to the grid. There are various types of Energy Storage (ES) technologies which are being used in power systems network from large scale (above 50MW) to small scale (up to 100KW). Based on the characteristics, each storage technology has their own merits and demerits. This paper carried out extensive review study and verifies merits and demerits of each storage technology and identifies the suitable technology for the future. This paper also has conducted feasibility study with the aid of E-SelectTM tool for various ES technologies in applications point of view at different grid locations. This review study helps to evaluate feasible ES technology for a particular electrical application and also helps to develop smart hybrid storage system for grid applications in efficient way.

Efficient simulations of the aqueous bio-interface of graphitic nanostructures with a polarisable model.

To fully harness the enormous potential offered by interfaces between graphitic nanostructures and biomolecules, detailed connections between adsorbed conformations and adsorption behaviour are needed. To elucidate these links, a key approach, in partnership with experimental techniques, is molecular simulation. For this, a force-field (FF) that can appropriately capture the relevant physics and chemistry of these complex bio-interfaces, while allowing extensive conformational sampling, and also supporting inter-operability with known biological FFs, is a pivotal requirement. Here, we present and apply such a force-field, GRAPPA, designed to work with the CHARMM FF. GRAPPA is an efficiently implemented polarisable force-field, informed by extensive plane-wave DFT calculations using the revPBE-vdW-DF functional. GRAPPA adequately recovers the spatial and orientational structuring of the aqueous interface of graphene and carbon nanotubes, compared with more sophisticated approaches. We apply GRAPPA to determine the free energy of adsorption for a range of amino acids, identifying Trp, Tyr and Arg to have the strongest binding affinity and Asp to be a weak binder. The GRAPPA FF can be readily incorporated into mainstream simulation packages, and will enable large-scale polarisable biointerfacial simulations at graphitic interfaces, that will aid the development of biomolecule-mediated, solution-based graphene processing and self-assembly strategies.

Adaptive intelligent energy management system of plug-in hybrid electric vehicle

Efficient energy management in hybrid vehicles is the key for reducing fuel consumption and emissions. To capitalize on the benefits of using PHEVs (Plug-in Hybrid Electric Vehicles), an intelligent energy management system is developed and evaluated in this paper. Models of vehicle engine, air conditioning, powertrain, and hybrid electric drive system are first developed. The effect of road parameters such as bend direction and road slope angle as well as environmental factors such as wind (direction and speed) and thermal conditions are also modeled. Due to the nonlinear and complex nature of the interactions between PHEV-Environment-Driver components, a soft computing based intelligent management system is developed using three fuzzy logic controllers. The crucial fuzzy engine controller within the intelligent energy management system is made adaptive by using a hybrid multi-layer adaptive neuro-fuzzy inference system with genetic algorithm optimization. For adaptive learning, a number of datasets were created for different road conditions and a hybrid learning algorithm based on the least squared error estimate using the gradient descent method was proposed. The proposed adaptive intelligent energy management system can learn while it is running and makes proper adjustments during its operation. It is shown that the proposed intelligent energy management system is improving the performance of other existing systems. © 2014 Elsevier Ltd.