A New Electrolyte Formulation for Securing High Temperature Cycling and Storage Performances of Na‐Ion Batteries

The Na‐ion battery is recognized as a possible alternative to the Li‐ion battery for applications where power and cost override energy density performance. However, the increasing instability of their electrolyte with temperature is still problematic. Thus, a central question remains how to design Na‐based electrolytes. Here, the discovery of a Na‐based electrolyte formulation is reported which enlists four additives (vinylene carbonate, succinonitrile, 1,3‐propane sultone, and sodium difluoro(oxalate)borate) in proper quantities that synergistically combine their positive attributes to enable a stable solid electrolyte interphase at both negative and positive electrodes surface at 55 °C. Moreover, the role of each additive that consists in producing specific NaF coatings, thin elastomers, sulfate‐based deposits, and so on via combined impedance and X‐ray photoelectron spectroscopy is rationalized. It is demonstrated that empirical electrolyte design rules previously established for Li‐ion technology together with theoretical guidance is vital in the quest for better Na‐based electrolytes that can be extended to other chemistries. Overall, this finding, which is implemented to 18 650 cells, widens the route to the rapid development of the Na‐ion technology based on Na₃V₂(PO₄)₂F₃/C chemistry.     

Zwitterions for Organic/Perovskite Solar Cells,Light‐Emitting Devices,and Lithium Ion Batteries: Recent Progress and Perspectives

Zwitterions, a class of materials that contain covalently bonded cations and anions, have been extensively studied in the past decades owing to their special features, such as excellent solubility in polar solvents, for solution processing and dipole formation for the transfer of carriers and ions. Recently, zwitterions have been developed as electrode modifiers for organic solar cells (OSCs), perovskite solar cells (PVSCs), and organic light‐emitting devices (OLEDs), as well as electrolyte additives for lithium ion batteries (LIBs). With the rapid advances of zwitterionic materials, high‐performance devices have been constructed with enhanced efficiencies by introducing them as interface layers and electrolyte additives. In this review, recent progress in OSCs, PVSCs, OLEDs, and LIBs by using zwitterions is highlighted. The authors also elaborate the role of various zwitterionic materials as interfacial layers and additives for highly efficient OSCs, PVSCs, OLEDs, and LIBs. This article presents an overview of device performance of zwitterionic materials. The structure–property relationship is also discussed. Finally, the prospects of zwitterion materials are also addressed.     

Space use and genetic structure do not maintain color polymorphism in a species with alternative behavioral strategies

Space use including territoriality and spatial arrangement within a population can reveal important information on the nature, dynamics, and evolutionary maintenance of alternative strategies in color polymorphic species. Despite the prevalence of color polymorphic species as model systems in evolutionary biology, the interaction between space use and genetic structuring of morphs within populations has rarely been examined. Here, we assess the spatial and genetic structure of male throat color morphs within a population of the tawny dragon lizard, Ctenophorus decresii. Male color morphs do not differ in morphology but differ in aggressive and antipredator behaviors as well as androgen levels. Despite these behavioral and endocrine differences, we find that color morphs do not differ in territory size, with their spatial arrangement being essentially random with respect to each other. There were no differences in genetic diversity or relatedness between morphs; however, there was significant, albeit weak, genetic differentiation between morphs, which was unrelated to geographic distance between individuals. Our results indicate potential weak barriers to gene flow between some morphs, potentially due to nonrandom pre‐ or postcopulatory mate choice or postzygotic genetic incompatibilities. However, space use, spatial structure, and nonrandom mating do not appear to be primary mechanisms maintaining color polymorphism in this system, highlighting the complexity and variation in alternative strategies associated with color polymorphism.     

Activity of salivary glands in secreting honey‐elaborating enzymes in two subspecies of honeybee (Apis mellifera L)

The activity of invertase, glucose oxidase and amylase in the cephalic (post‐cerebral) and thoracic salivary glands is determined in Egyptian and Carniolan honeybees (Apis mellifera L). For this purpose, three ages of worker bees are selected for enzyme assays. The results show that the three target enzymes are detected in the two glands during the three worker ages, except invertase, which cannot be detected in the cephalic gland of newly emerged bees of both subspecies. In both glands, the secretion of invertase is highest, followed by amylase and then glucose oxidase. In Carniolan bees, invertase secretion of the cephalic and thoracic glands increases gradually with age. In Egyptian bees, invertase increases with age only in the cephalic gland, whereas, in the thoracic gland, the highest secretion activity is detected in 10–15‐day‐old bees. The highest amounts of glucose oxidase and amylase in the cephalic gland are detected in newly emerged individuals of both Egyptian and Carniolan bees. In the thoracic gland, however, the highest activity of both enzymes is recorded only in newly emerged Egyptian bees. The results are discussed in the light of bee management and biological aspects of the two subspecies.     

Theoretical calculation of the sugar concentrations during enzymatic production of fructooligosaccharides

Summary In a batch production of fructooligosaccharides from sucrose, the concentrations of residual sucrose, glucose and fructooligosaccharides at a given reaction time(t) and initial sucrose concentration(S₀) were theoretically calculated by the following correlation equations: Glucose(t) = 0.0653 S₀ × ln(t); Fructooligosaccharides(t) = 0.1636 S₀ × ln(t); Sucrose(t)=S₀ - Glucose(t) + FOS(t).