Effects of an inhomogeneous electron density distribution on the hydrogen distribution in TiZrTaNbAl multi-principal element alloys

A body-centered cubic equiatomic TiZrTaNbAl multi-principal element alloy (MPEA) with elemental fluctuations was investigated to further understand the relationship between the microstructure and hydrogen distribution. In this study, a composition dependence of the hydrogen distribution was observed in the TiZrTaNbAl MPEA. An inhomogeneous electron density distribution of the MPEA was revealed by advanced differential phase-contrast scanning electron microscopy (DPC-STEM) for the first time. The results showed that the electron density has a significant effect on the hydrogen distribution in TiZrTaNbAl MPEAs. This work provides new insight into the design of materials with high hydrogen storage capacity and high hydrogen embrittlement resistance.     

Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

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.     

The phosphorescence emission in undoped lead-halide Cs4PbBr6 single crystals at low temperature

Recently, all-inorganic cesium lead-halide perovskites have shown their promise for light emission applications, due to the excellent optical performance. Herein, we report that the initially nonphosphorescent undoped lead-halide Cs₄PbBr₆ single crystals (SCs) exhibit an ultralong phosphorescence emission under X-ray excitation at low temperatures. It is shown that the dramatic change has been taken place in radioluminescence spectra and the broad-band emission gradually appeared with the decrease of temperature. Below 210 K, the radioluminescence spectra can be deconvoluted into one narrow peak located at 530 nm and two broad peaks centered at 595 nm and 672 nm respectively. Subsequently, the time-dependent radioluminescence spectra in undoped lead-halide Cs₄PbBr₆ SCs were investigated. The ultralong phosphorescence emission can persist over 120 min at 70 K. We consider that ultralong phosphorescence originates from defect-related emission. To the best of our knowledge, our finding is the first time that undoped Cs₄PbBr₆ SCs exhibit the phosphorescence emission, which will offer a paradigm to motivate revolutionary applications on perovskite.     

High-temperature oxidation behavior of monolithic Zr3[Al(Si)]4C6 and its composite incorporating 30vol% ZrB2-SiC: Providing a basis for broadening the service temperature

To provide a basis for the high-temperature oxidation of ultra-high temperature ceramics (UHTCs), the oxidation behavior of Zr₃[Al(Si)]₄C₆ and a novel Zr₃[Al(Si)]₄C₆-ZrB₂-SiC composite at 1500 °C were investigated for the first time. From the calculation results, the oxidation kinetics of the two specimens follow the oxidation dynamic parabolic law. Zr₃[Al(Si)]₄C₆ exhibited a thinner oxide scale and lower oxidation rate than those of the composite under the same conditions. The oxide scale of Zr₃[Al(Si)]₄C₆ exhibited a two-layer structure, while that of the composite exhibited a three-layer structure. Owing to the volatilization of B₂O₃ and the active oxidation of SiC, a porous oxide layer formed in the oxide scale of the composite, resulting in the degradation of its oxidation performance. Furthermore, the cracks and defects in the oxide scale of the composite indicate that the reliability of the oxide scale was poor. The results support the service temperature of the obtained ceramics.     

Essential (Mg,Fe, Zn and Cu) and Non-Essential (Cd and Pb) Elements in Predatory Insects (Vespa crabro and Vespa velutina): A Molecular Perspective

The recent introduction of the Asian yellow-legged hornet, Vespa velutina, into Europe has raised concern regarding the threat to honeybees and the competition with the European hornet, Vespa crabro. The aim of this study was to investigated essential (Mg, Fe, Zn, Cu) and non-essential (Cd and Pb) elements in these two species. Element concentrations were determined in the whole body and separately in the head, thorax and abdomen using atomic absorption spectrometry (AAS). The changes in essential element concentration and speciation during metamorphosis were also studied using size exclusion chromatography followed by AAS and proteomic analysis. In both species, the essential elements were more concentrated in the abdomen due to the presence of fat bodies. Magnesium, Fe and Zn concentrations were significantly higher in V. crabro than in V. velutina and could have been related to the higher aerobic energy demand of the former species required to sustain foraging flight. Low concentrations of Cd and Pb were indicative of low environmental exposure. The concentration and speciation of essential elements, particularly Fe, varied among the developmental stages, indicating a modification of ligand preferences during metamorphosis. Overall, the results in the present study provide a better understanding of the hornet metal metabolism and a foundation for additional studies.     

Superradiant Emission from Coherent Excitons in van Der Waals Heterostructures

Recent advancements in isolation and stacking of layered van der Waals materials have created an unprecedented paradigm for demonstrating varieties of 2D quantum materials. Rationally designed van der Waals heterostructures composed of monolayer transition-metal dichalcogenides (TMDs) and few-layer hBN show several unique optoelectronic features driven by correlations. However, entangled superradiant excitonic species in such systems have not been observed before. In this report, it is demonstrated that strong suppression of phonon population at low temperature results in a formation of a coherent excitonic-dipoles ensemble in the heterostructure, and the collective oscillation of those dipoles stimulates a robust phase synchronized ultra-narrow band superradiant emission even at extremely low pumping intensity. Such emitters are in high demand for a multitude of applications, including fundamental research on many-body correlations and other state-of-the-art technologies. This timely demonstration paves the way for further exploration of ultralow-threshold quantum-emitting devices with unmatched design freedom and spectral tunability.     

Research and development of liquid hydrogen (LH2) temperature monitoring system for marine applications

Monitoring the temperature in liquid hydrogen (LH₂) storage tanks on ships is important for the safety of maritime navigation. In addition, accurate temperature measurement is also required for commercial transactions. Temperature and pressure define the density of liquid hydrogen, which is directly linked to trading interests. In this study, we developed and tested a liquid hydrogen temperature monitoring system that uses platinum resistance sensors with a nominal electrical resistance of approximately 1000 Ω at room temperature, PT-1000, for marine applications. The temperature measurements were carried out using a newly developed temperature monitoring system under different pressure conditions. The measured values are compared with a calibrated reference PT-1000 resistance thermometer. We confirm a measurement accuracy of ±50 mK in a pressure range of 0.1 MPa–0.5 MPa.     

Effect of support and reduction temperature in the hydrogenation of CO2 over the Cu–Pd bimetallic catalyst with high Cu/Pd ratio

Metal-support interaction and catalyst pretreatment are important for industrial catalysis. This work investigated the effect of supports (SiO₂, CeO₂, TiO₂ and ZrO₂) for Cu–Pd catalyst with high Cu/Pd ratio (Cu/Pd = 33.5) regarding catalyst cost, and the reduction temperatures of 350 °C and 550 °C were compared. The activity based on catalyst weight follows the order of Si > Ce > Zr > Ti when reduced at 350 °C. The reduction temperature leads to the surface reconstruction over the SiO₂, CeO₂ and TiO₂ catalysts, while results in phase transition over Cu–Pd/ZrO₂. The effect of reduction temperature on catalytic performance is prominent for the SiO₂ and ZrO₂ supported catalysts but not for the CeO₂ and TiO₂ ones. Among the investigated catalysts, Zr-350 exhibits the highest methanol yield. This work reveals the importance of the supports and pretreatment conditions on the physical-chemical properties and the catalytic performance of the Cu–Pd bimetallic catalysts.