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Interfacial resistance at electrode‐high Li+ conductive solid electrolytes must be reduced well to develop high‐power all‐solid‐state batteries using oxide‐based solid electrolytes (Ox‐SSBs). Herein, crystalline electrode films of LiCoO2 (LCO) are formed on a high Li+ conductive crystalline‐glass solid electrolyte sheet, Li1.3Al0.3Ti2(PO4)3 (LATP) (σ25 °C = 1 × 10−4 S cm−1), at room temperature by aerosol deposition (AD), and the effects of the annealing temperature on the interfacial resistivities (Rint) at the LCO/LATP are investigated. The Rint visibly increases by annealing over 500 °C with the growth of Co3O4 as a reactant. In contrast, Rint is reduced to ≈100 Ω cm2 by low‐temperature annealing at 250–350 °C due to superior contact through the structural rearrangement of an artificial metastable interface formed by the AD. These results are applied to bulk‐type Ox‐SSB, Li/Li7La3Zr2O12(LLZ)/LCO–LATP, and our best Ox‐SSB delivers a discharge capacity of 100 mA cm−2 at 100 °C.

Abstract The anodic polarization behaviour of iron whisker crystals was investigated in a neutral solution with or without the presence of chloride ion, with special attention to the role played by surface defects in the dissolution, the passivation and the pitting of iron. The grown whisker used was substantially dislocation-free and the defect density was varied by twisting of whisker. With increase in the angle of twisting, the anodic dissolution current increased in a chloride-free solution, whereas it decreased in a chloride-containing solution. The defect density in the substrate had no remarkable effect on passivation but the thickness of the passive film was slightly increased on twisted whiskers. The anodic polarization curve of a grown whisker in a chloride-containing solution did not exhibit a distinct pitting potential. By twisting of whisker, however, a current rise due to pitting appeared on the polarization curve and the apparent pitting potential shifted in the negative direction with increasing angle of twisting. Potentiostatic polarization experiments in a chloride-containing solution showed the emergence of random current pulses due to the breakdown of passive film and to repassivation. It is highly probable that the breakdown of the passive film occurs at the physical or chemical inhomogeneities in the passive film not associated with dislocation termini but that pitting occurs only when the breakdown occurs at emergent dislocation sites.

AbstractCumulus‐intact and ‐denuded unfertilized oocytes from two mouse strains were exposed to 1.5 m ethanol (EtOH) or two cryoproteclant solutions, 1.5 M propanediol (PROH) or 1.5 M dimethylsulfoxide (DMSO), for 4.5 min at 27°C, and the proportion of activating or degenerating oocytes studied. Exposure to DMSO did not significantly increase activation above that of oocytes not exposed to DMSO. Treatment of oocytes in PROH resulted in the activation of up to 87% of viable oocytes. This was significantly higher (P <01) than in control oocytes and comparable to the rate of activation after treatment with EtOH (59–96% activation). In solutions at 1°C, 47% of control oocytes were activated, which was not significantly different from the rate of activation in EtOH (36%) or PROH (50%) at 1°C. Following treatment with PROH, up to 87% of oocytes degenerated within a period of 6 h in vitro. The age of the oocytes (h post hCG) and the time of cumulus removal with the enzyme hyaluronidase, relative to the time of exposure to the chemicals, influenced the level of degeneration in most groups. Significantly fewer oocytes degenerated when cumulus cells were removed before treatment (0–31%) than when the cumulus was left intact throughout the treatment and 6 h culture period (10–87%). Exposure to PROH at 1°C reduced oocyte degeneration to 5%. We conclude that PROH causes significantly greater losses of oocytes as a result of parthenogenetic activation and degeneration than of exposure to DMSO.

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.

In order to exploit renewable energies from tidal stream, tandem propellers of a unique counter-rotating type horizontal-axis tidal turbine was firstly designed based on the blade element momentum (BEM) theory. And then a multi-objective numerical optimization method coupled the response surface method (RSM) with the genetic algorithm (GA) was employed to obtain desirable blade profiles. The front blade pitch angle distribution was taken as optimization variable in this paper, as it plays an important role in affecting the inlet conditions of the rear blade. The numerical results show that both optimization objectives of power coefficient and thrust coefficient can be significantly improved. It was verified that the performance of the power unit with the optimized blades increases obviously by optimizing the pitch angle.

AbstractIf the energy‐density of prey bodies is not uniform, predators usually should maximize their rate of energy intake while foraging by selectively consuming energy‐rich regions of their prey and discarding other parts. In this study, the hypothesis of selective body‐part consumption was tested using two species of dasyurid marsupials, Sminthopsis youngsoni and Ningaui ridei, and their invertebrate prey in arid central Australia. Energy‐densities were similar for several divergent types of prey, including whole insects, centipedes, and spiders (20.2 ± 2.19 (sd) J/mg ash‐free dry mass), but there were marked differences in energy‐density among orders of insects and also between different body regions of invertebrates. In captivity, the two dasyurid species consumed different body regions of prey in the same way. For beetles and cockroaches, the rank order for selection of body parts was abdomen, thorax, head, then legs; for centipedes it was body, then head + legs; and for spiders it was opisthosoma, prosoma and then legs. Selection of prey body regions by the marsupials correlated closely with the energy‐densities of these regions, and also with the rates of energy intake that they yielded. In the field, selection of body parts of arthropod prey by dasyurids probably occurs primarily when prey is abundant. This selection should allow maximization of rates of energy intake in favourable periods and should, in turn, allow dasyurid predators to effectively exploit pulses of prey resources in the temporally variable desert environment.

This paper presents a multi-objective optimization model for a long-term generation mix in Indonesia. The objective of this work is to assess the economic, environment, and adequacy of local energy sources. The model includes two competing objective functions to seek the lowest cost of generation and the lowest CO2 emissions while considering technology diffusion. The scenarios include the use of fossil reserves with or without the constraints of the reserve to production ratio and exports. The results indicate that Indonesia should develop all renewable energy and requires imported coal and natural gas. If all fossil resources were upgraded to reserves, electricity demand in 2050 could be met by domestic energy sources. The maximum share of renewable energy that can be achieved in 2050 is 33% with and 80% without technology diffusion. The least cost optimization produces lower generation costs than the least CO2 emissions, as well as the combined scenario. Total CO2 emissions in 2050 are five to six times as large as current emissions. The least CO2 emissions scenario can reduce almost half of the CO2 emissions of the least cost scenario by 2050. The proposed multi-objective optimization model leads some optimal solutions for a more sustainable electricity system.

Microgrids are increasingly being used as a platform to integrate distributed generation such as renewable energy sources and (RESs) conventional sources in both grid-connected and isolated power systems. Due to the inherent intermittent nature of RESs, energy storage systems (ESSs) that can absorb fluctuations have become inevitable. Nevertheless, large capacities of ESSs increase the initial cost while small capacities lead to instabilities and increase in the cost of conventional fuels. Therefore, finding the optimal size of the ESS for a given application is essential for the reliable, efficient and economical operation of a microgrid. Once the battery size is decided, maintaining its energy at appropriate levels is essential to ensure stable and safe operation of the microgrid. This paper presents a novel expert fuzzy system - grey wolf optimization (FL-GWO) based intelligent meta-heuristic method for battery sizing and energy management. The proposed energy management operation is carried out by a Grey Wolf Optimiser (GWO) that is helped to set the membership functions and rules of the fuzzy logic expert system. The unit commitment (UC) issue, which is essential for the proper operation of the isolated microgrid, has been additionally considered in this paper. To verify the performance of the proposed method, results are compared with the rules-based method and traditional GWO algorithm. It has been proven from the results that the FL-GWO has a significant convergence property and capability to minimize the Levelized Cost Of Electricity (LCOE) by 14.13% and 24.15% compared with conventional GWO algorithm and rules-based method, respectively. The weather conditions for different climates is used to verify the performance of the intelligent energy management method under different operating scenarios. The results show that the intelligent online multi-objective energy management strategy is capable of managing a smooth power flow with the same optimal configuration in the isolated microgrid, minimising the fossil fuel utilisation and reducing the CO2 emission level.