Designing Optimal Perovskite Structure for High Ionic Conduction

Solid-oxide fuel/electrolyzer cells are limited by a dearth of electrolyte materials with low ohmic loss and an incomplete understanding of the structure–property relationships that would enable the rational design of better materials. Here, using epitaxial thin-film growth, synchrotron radiation, impedance spectroscopy, and density-functional theory, the impact of structural parameters (i.e., unit-cell volume and octahedral rotations) on ionic conductivity is delineated in La_0.9Sr_0.1Ga_0.95Mg_0.05O_3–δ. As compared to the zero-strain state, compressive strain reduces the unit-cell volume while maintaining large octahedral rotations, resulting in a strong reduction of ionic conductivity, while tensile strain increases the unit-cell volume while quenching octahedral rotations, resulting in a negligible effect on the ionic conductivity. Calculations reveal that larger unit-cell volumes and octahedral rotations decrease migration barriers and create low-energy migration pathways, respectively. The desired combination of large unit-cell volume and octahedral rotations is normally contraindicated, but through the creation of superlattice structures both expanded unit-cell volume and large octahedral rotations are experimentally realized, which result in an enhancement of the ionic conductivity. All told, the potential to tune ionic conductivity with structure alone by a factor of ≈2.5 at around 600 °C is observed, which sheds new light on the rational design of ion-conducting perovskite electrolytes.     

Camel milk composition by breed,season, publication year,and country: A global systematic review,meta-analysis,and meta-regression

Camel milk consists of an essential macro/micronutrient for human nutrition in the arid and urban regions. This review study aimed to use meta-analysis statistical techniques for assessment and correction of publication bias, exploration of heterogeneity between studies, and detailed assessment of the effect of a comprehensive set of moderators including breed, season, country, year of publication, and the interaction between composition elements. This could provide a single synthesis of the camel milk composition to warrant strong generalizability of results, examine variability between available studies, and analyze differences in camel milk composition among different exposures. Such a finding will aid future researchers and health professionals in acquiring a more precise understanding of camel milk composition and drawing more clinical implications. Six searching databases and bibliographic were used including PubMed/MEDLINE, ScienceDirect, Springer, EBSCOhost, Scopus, and Web of Science from January 1980 to December 2021. The DerSimonian–Laird estimator was used to create the current random-effects meta-analysis. This systematic review and meta-analysis included a total of 7298 camel milk samples from 23 countries. This review comprises 79 studies published in the English language on or after 1980, including a subgroup of 117 analyses consisting of seasons, sub-breeds, and countries. The contents of macro/micronutrients in camel milk were identified as follows: protein, 3.17%; fat, 3.47%; lactose, 4.28%; ash, 0.78%; and total solids, 11.31%; calcium, 112.93 mg/100 g; iron, 0.45 mg/100 g; potassium, 116.13 mg/100 g; magnesium, 9.65 mg/100 g; sodium, 53.10 mg/100 g; zinc, 1.68 mg/100 g; vitamin C, 5.38 mg/100 g; vitamin A, 0.36 mg/100 g; vitamin B₁,0.05 mg/100 g; vitamin B₂, 0.13 mg/100 g; vitamin B₃, 0.51 mg/100 g; vitamin B₆, 0.09 mg/100 g; and vitamin B₁₂, 0.0039 mg/100 g. Our meta-regression analysis found that fat and total solids were statistically significant moderators of protein; moreover, total solids content is a statistically significant moderator of fat. Discrepancies observed in camel milk profiles are dependent upon several factors, including number of included studies, number of samples, different analytical techniques, feeding patterns, camel's breeds, geographical locations, and seasonal variations.     

A model-driven approach for vulnerability evaluation of modern physical protection systems

Software and Systems Modeling - Modern physical protection systems integrate a number of security systems (including procedures, equipments, and personnel) into a single interface to ensure an...     

Fire Behaviour of a Prestressed Thin-Walled Concrete V-Beam

Fire Technology - The present work investigates the fire behaviour of a prestressed thin-walled concrete V-beam with variable cross section along its longitudinal axis. In particular, the results...     

Position-Controlled Functionalization of Vacancies in Silicon by Single-Ion Implanted Germanium Atoms

Special point defects in semiconductors have been envisioned as suitable components for quantum-information technology. The identification of new deep centers in silicon that can be easily activated and controlled is a main target of the research in the field. Vacancy-related complexes are suitable to provide deep electronic levels but they are hard to control spatially. With the spirit of investigating solid state devices with intentional vacancy-related defects at controlled position, the functionalization of silicon vacancies is reported on here by implanting Ge atoms through single-ion implantation, producing Ge-vacancy (GeV) complexes. The quantum transport through an array of GeV complexes in a silicon-based transistor is investigated. By exploiting a model based on an extended Hubbard Hamiltonian derived from ab initio results, anomalous activation energy values of the thermally activated conductance of both quasi-localized and delocalized many-body states are obtained, compared to conventional dopants. Such states are identified, forming the upper Hubbard band, as responsible for the experimental sub-threshold transport across the transistor. The combination of the model with the single-ion implantation method enables future research for the engineering of GeV complexes toward the creation of spatially controllable individual defects in silicon for applications in quantum information technology.