Good dielectric performance and broadband dielectric polarization in Ag,Nb co-doped TiO2

Due to the demand of miniaturization and integration for ceramic capacitors in electronic components market, TiO₂-based ceramics with colossal permittivity has become a research hotspot in recent years. In this work, we report that Ag⁺/Nb⁵⁺ co-doped (Ag_1/4Nb_3/4)_xTi_1−xO₂ (ANTOx) ceramics with colossal permittivity over a wide frequency and temperature range were successfully prepared by a traditional solid–state method. Notably, compositions of ANTO0.005 and ANTO0.01 respectively exhibit both low dielectric loss (0.040 and 0.050 at 1 kHz), high dielectric permittivity (9.2 × 10³ and 1.6 × 10⁴ at 1 kHz), and good thermal stability, which satisfy the requirements for the temperature range of application of X9R and X8R ceramic capacitors, respectively. The origin of the dielectric behavior was attributed to five dielectric relaxation phenomena, i.e., localized carriers' hopping, electron–pinned defect–dipoles, interfacial polarization, and oxygen vacancies ionization and diffusion, as suggested by dielectric temperature spectra and valence state analysis via XPS; wherein, electron-pinned defect–dipoles and internal barrier layer capacitance are believed to be the main causes for the giant dielectric permittivity in ANTOx ceramics.     

Design of Deep Convolution Neural Networks for categorical signature classification of raw panchromatic satellite images

Multimedia Tools and Applications - Remote Sensing categorical signature classification has gained significant implications on spatial resolution image analysis due to differences in the...     

Influence of Titanium Excess in a Ti–Si Reaction Mixture on the Synthesis of a Composite in a Combustion Wave

Theoretical Foundations of Chemical Engineering - On the basis of the classic concepts of the theory of solid-phase combustion, for the first time, a model with a detailed scheme of chemical...     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Effect of Drosophila suzukii on Blueberry VOCs: Chemical Cues for a Pupal Parasitoid,Trichopria anastrephae

Journal of Chemical Ecology - Biocontrol agents such as parasitic wasps use long-range volatiles and host-associated cues from lower trophic levels to find their hosts. However, this chemical...     

Influence of Continuous Wave Interference on the Efficiency of the Non-Threshold Search Procedure for a Noise-Like Signal by Delay Time with Transition to the Frequency Domain

Journal of Communications Technology and Electronics - A statistical study of the effectiveness of the non-threshold search procedure for a noise-like phase-shift keyed signal by the delay time is...     

A novel strategy based on salp swarm algorithm for extracting the maximum power of proton exchange membrane fuel cell

Cell temperature and water content of the membrane have a significant effect on the performance of fuel cells. The current-power curve of the fuel cell has a maximum power point (MPP) that is needed to be tracked. This study presents a novel strategy based on a salp swarm algorithm (SSA) for extracting the maximum power of proton-exchange membrane fuel cell (PEMFC). At first, a new formula is derived to estimate the optimal voltage of PEMFC corresponding to MPP. Then the error between the estimated voltage at MPP and the actual terminal voltage of the fuel cell is fed to a proportional-integral-derivative controller (PID). The output of the PID controller tunes the duty cycle of a boost converter to maximize the harvested power from the PEMFC. SSA determines the optimal gains of PID. Sensitivity analysis is performed with the operating fuel cell at different cell temperature and water content of the membrane. The obtained results through the proposed strategy are compared with other programmed approaches of incremental resistance method, Fuzzy-Logic, grey antlion optimizer, wolf optimizer, and mine-blast algorithm. The obtained results demonstrated high reliability and efficiency of the proposed strategy in extracting the maximum power of the PEMFC.     

Influence of α′‐/α‐crystal polymorphism on properties of poly(l‐lactic acid)

Poly(l ‐lactic acid) (PLLA) is a biodegradable and biocompatible thermoplastic polyester produced from renewable sources, widely used for biomedical devices, in food packaging and in agriculture. It is a semicrystalline polymer, and as such its properties are strongly affected by the developed semicrystalline morphology. As a function of the crystallization temperature, PLLA can form different crystal modifications, namely α′‐crystals below about 120 °C and α‐crystals at higher temperatures. The α′ modification is therefore of special importance as it may be the preferred polymorph developing at processing‐relevant conditions. It is a metastable modification which typically transforms into the more stable α‐crystals on annealing at elevated temperature. The structure, kinetics of formation and thermodynamics of α′‐ and α‐crystals of PLLA are reviewed in this contribution, together with the effect of α′‐/α‐crystal polymorphism on the properties of PLLA. © 2018 Society of Chemical Industry     

Extraction and characterization of hydroxyapatite-based materials from grey triggerfish skin and black scabbardfish bones

The conversion of food industry by-products to compounds with high added value is nowadays a significant topic, for social, environmental, and economic reasons. In this paper, calcium phosphate-based materials were obtained from black scabbardfish (Aphanopus carbo) bones and grey triggerfish (Balistes capriscus) skin, which are two of the most abundant fish by-products of Madeira Island. Different calcination temperatures between 400 and 1000°C were employed. Materials obtained from calcination of bones of black scabbard fish were composed by homogeneous mixtures of hydroxyapatite (Ca₁₀(PO4)₆(OH)₂, HAp) and β-tricalcium phosphate (β-Ca₃(PO₄)₂, β-TCP). Because of the high biocompatibility of HAp and the good resorbability of β-TCP, these natural biphasic materials could be very relevant in the field of biomaterials, as bone grafts. The ratio between HAp and β-TCP in the biphasic compound was dependent on the calcination temperature. Differently, the material obtained from skin of grey triggerfish contained HAp as the main phase, together with small amounts of other mineral phases, such as halite and rhenanite, which are known to enhance osteogenesis when used as bone substitutes. In both cases, the increase of calcination temperature led to an increase in the particles size with a consequent decrease in their specific surface area. These results demonstrate that from the fish by-products of the most consumed fishes in Madeira Island it is possible to obtain bioceramic materials with tunable composition and particle morphology, which could be promising materials for the biomedical field.     

Lithiation MXene Derivative Skeletons for Wide-Temperature Lithium Metal Anodes

Lithium (Li) metal, as an appealing candidate for the next-generation of high-energy-density batteries, is plagued by its safety issue mainly caused by uncontrolled dendrite growth and infinite volume expansion. Developing new materials that can improve the performance of Li-metal anode is one of the urgent tasks. Herein, a new MXene derivative containing pure rutile TiO₂ and N-doped carbon prepared by heat-treating MXene under a mixing gas, exhibiting high chemical activity in molten Li, is reported. The lithiation MXene derivative with a hybrid of LiTiO₂-Li₃N-C and Li offers outstanding electrochemical properties. The symmetrical cell assembling lithiation MXene derivative hybrid anode exhibits an ultra-long cycle lifespan of 2000 h with an overpotential of ≈30 mV at 1 mA cm⁻², which overwhelms Li-based anodes reported so far. Additionally, long-term operations of 34, 350, and 500 h at 10 mA cm⁻² can be achieved in symmetrical cells at temperatures of −10, 25, and 50 °C, respectively. Both experimental tests and density functional theory calculations confirm that the LiTiO₂-Li₃N-C skeleton serves as a promising host for Li infusion by alleviating volume variation. Simultaneously, the superlithiophilic interphase of Li₃N guides Li deposition along the LiTiO₂-Li₃N-C skeleton to avoid dendrite growth.