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Based on the previous work conducted by Fujii et al., NdBaInO4 compounds present modest oxide-ion conductivities. Therefore, it has been an attractive system of significant interest. In this study, we attempted to partially substitute Ca for Nd and the total electrical conductivity was successfully improved due to the generation of oxygen vacancies. The synthesis, crystal structure, density, surface topography, and electrical properties of NdBaInO4 and Ca-doped NdBaInO4 have been studied, respectively. NdBaInO4 and 10% and 20% molar fractions of Ca-doped NdBaInO4 were synthesized through solid-state reactions. The crystal structure of them was obtained from Le Bail refinement of the XRD pattern, giving the result of the monoclinic structure, which belongs to P21/c space group. The highest total electrical conductivity of 4.91 × 10−3 S cm−1 was obtained in the Nd0.9Ca0.1BaInO3.95 sample at a temperature of 760 °C in the dry atmosphere and the activation energy was reduced from 0.68 eV to 0.58 eV when the temperature was above 464 °C (737 K) after doping the NdBaInO4 with a 0.1 molar fraction of Ca2+. Moreover, the total conductivity of Nd0.9Ca0.1BaInO3.95 in the wet atmosphere at moderate temperature was relatively higher than that in the dry atmosphere, which suggests that potential proton conduction may exist in wet atmospheres. In addition, the oxygen diffusion coefficients of Nd0.9Ca0.1BaInO3.95 (D* = 1.82 × 10−8 cm2/s, 850 °C) was about two times higher than that of Nd0.8Ca0.2BaInO3.90 (D* = 7.95 × 10−9 cm2/s, 850 °C) and was increased significantly by two orders of magnitude when compared with the oxygen diffusion coefficient of the undoped NdBaInO4 (D* = 8.25 × 10−11 cm2/s, 850 °C). [ABSTRACT FROM AUTHOR]

Microalgae is a promising metabolism microorganism for the fixation of CO2 from industrial gas while accumulating microalgae biomass. The process of CO2 fixation by microalgae is able to be significantly improved by the regulation of phytohormones. However, the complex metabolic mechanism of microalgae regulated by phytohormones and abiotic stress on CO2 fixation deserves to be explored. To systematically understand the existing status and establish a foundation for promoting the technology, this paper reviews investigations on the metabolic mechanism of microalgae regulated by phytohormones. The influences of nitrogen stress, light intensity stress, heavy metal stress, and salinity stress on CO2 fixation and lipid production are summarized. In addition, a comprehensive overview of the multistage regulation of phytohormones and abiotic stress on CO2 fixation and lipid production through microalgae is presented. The recent advances in CO2 transfer reinforcement and light transmission reinforcement in photobioreactors are discussed. This review provides an insight into the enhancement of CO2 fixation by microalgae regulated by phytohormones, abiotic stress, and mass transfer in multistage photobioreactors. [ABSTRACT FROM AUTHOR]

In some cases, the oil shale deposited in shallow lakes may be genetically associated with the coal-bearing successions. Although paleovegetation is an important controlling factor for the formation of oil shale- and coal-bearing successions, few studies have focused on their joint characterization. In this study, a total of twenty-one oil shale and coal samples were collected from the upper member of the Lower Cretaceous Muling Formation (K1ml2) in the Laoheishan Basin, and investigated for their bulk geochemical, maceral, palynological, and terpenoid biomarker characteristics, in order to reconstruct the paleovegetation and reveal its influence on the formation of oil shale and coal. The K1ml2 is subdivided into lower, middle, and upper units. The studied oil shale samples from the lower and upper units display a high ash yield (Ad), low total organic carbon (TOC) and sulfur (S) contents, and limited hydrocarbon generation potential. The studied coal samples from the middle unit are characterized by low Ad, and high TOC and low S values, and show significant hydrocarbon generation potential. The paleovegetation during the formation of the lower unit was dominated by mire vegetation, such as shrubs (e.g., Lygodiaceae, Schizaeaceae), tree ferns (e.g., Dicksoniaceae/Cyatheaceae), and coniferous trees (e.g., Podocarpaceae). In the middle unit interval, the paleovegetation was represented by highland vegetation (Pinaceae and Araucariaceae) and peat-forming coniferous plants (e.g., Podocarpaceae, Cupressaceae/Taxodiaceae). Various vegetation, such as herbs (e.g., Osmundaceae), shrubs (e.g., Schizaeaceae), and coniferous trees (e.g., Podocarpaceae) was prosperous during the upper unit interval. Coniferous trees could provide abundant hydrogen-rich materials (e.g., resins) to the mire/lake, which may elevate the hydrogen content in peat/lake sediments, and finally result in higher hydrocarbon generation potential in the coal than in the oil shale. Therefore, the influence of paleovegetation on the formation of oil shale and coal should be fully considered when studying oil shale- and coal-bearing successions. The results also provide guidance for further exploration studies on oil shale and coal in northeast China. [ABSTRACT FROM AUTHOR]

Electrolytes are involved in the thermal runaway (TR) process of cells, which is a potential hazard in lithium-ion batteries (LIBs). Therefore, the effects of different mass ratio of carbonate solvents (ethylene carbonate (EC)/propylene carbonate (PC)/ethyl methyl carbonate (EMC)) with LiBF4 and different environmental pressure on the combustion characteristics of electrolyte such as flame centerline temperature, mass loss rate (MLR) and heat release rate (HRR) were analyzed. The combustion process could be divided into four stages: ignition, stable combustion stage, stable combustion with flame color change stage and extinguishing; with the decrease of pressure, the MLR of electrolyte declined and the combustion time prolonged, while the temperature of flame centerline increased. [ABSTRACT FROM AUTHOR]

Condition monitoring is used to assess the reliability and equipment efficiency of wind turbines. Feature extraction is an essential preprocessing step to achieve a high level of performance in condition monitoring. However, the fluctuating conditions of wind turbines usually cause sudden variations in the monitored features, which may lead to an inaccurate prediction and maintenance schedule. In this scenario, this article proposed a novel methodology to detect the multiple levels of faults of rolling bearings in variable operating conditions. First, signal decomposition was carried out by variational mode decomposition (VMD). Second, the statistical features were calculated and extracted in the time domain. Meanwhile, a permutation entropy analysis was conducted to estimate the complexity of the vibrational signal in the time series. Next, feature selection techniques were applied to achieve improved identification accuracy and reduce the computational burden. Finally, the ranked feature vectors were fed into machine learning algorithms for the classification of the bearing defect status. In particular, the proposed method was performed over a wide range of working regions to simulate the operational conditions of wind turbines. Comprehensive experimental investigations were employed to evaluate the performance and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]