Competing Magnetic Orderings and Tunable Topological States in Two-Dimensional Hexagonal Organometallic Lattices

The exploration of topological states is of significant fundamental and practical importance in contemporary condensed matter physics, for which the extension to two-dimensional (2D) organometallic systems is particularly attractive. Using first-principles calculations, we show that a 2D hexagonal triphenyl-lead lattice composed of only main group elements is susceptible to a magnetic instability, characterized by a considerably more stable antiferromagnetic (AFM) insulating state rather than the topologically nontrivial quantum spin Hall state proposed recently. Even though this AFM phase is topologically trivial, it possesses an intricate emergent degree of freedom, defined by the product of spin and valley indices, leading to Berry curvature-induced spin and valley currents under electron or hole doping. Furthermore, such a trivial band insulator can be tuned into a topologically nontrivial matter by the application of an out-of-plane electric field, which destroys the AFM order, favoring instead ferrimagnetic spin ordering and a quantum anomalous Hall state with a non-zero topological invariant. These findings further enrich our understanding of 2D hexagonal organometallic lattices for potential applications in spintronics and valleytronics.Comment: 9 pages, 8 figure

Dynamical Evolution of Anisotropic Response in Black Phosphorus under Ultrafast Photoexcitation

Black phosphorus has recently emerged as a promising material for high performance electronic and optoelectronic device for its high mobility, tunable mid-infrared bandgap and anisotropic electronic properties. Dynamical evolution of photo excited carriers and its induced change of transient electronic properties are critical for materials' high field performance, but remains to be explored for black phosphorus. In this work, we perform angle resolved transient reflection spectroscopy to study the dynamical evolution of anisotropic properties of black phosphorus under photo excitation. We find that the anisotropy of reflectivity is enhanced in the pump induced quasi-equilibrium state, suggesting an extraordinary enhancement of the anisotropy in dynamical conductivity in hot carrier dominated regime. These results raise enormous possibilities of creating high field, angle sensitive electronic, optoelectronic and remote sensing devices exploiting the dynamical electronic anisotropic with black phosphorus.Comment: 22 pages,10 figure

Experimental investigation of liquid film cooling in hypersonic flow

Film cooling is generally considered as a promising active cooling technology for developing thermal protection systems of hypersonic vehicles; however, most of experimental and numerical studies of film cooling mainly concentrated on gaseous film cooling. Since the phase change of liquid coolants can absorb a large amount of latent heat, liquid film cooling should have more potential advantages, especially for severe environments accompanied by hypersonic flight To address this issue, the film cooling using water as a coolant was experimentally investigated in hypersonic flow. Experiments were carried out in a detonation tunnel, at a hypersonic Mach number of 6 using a 25 degrees apex-angle wedge. Characteristic physical quantities, such as surface temperature rise, shock wave structure, film thickness, and cover area, are measured by thermocouples, schlieren, and a specially devised liquid film measurement system. The experimental results verify that the liquid film cooling is feasible in hypersonic flow and also indicate that it is featured with maintaining aerodynamic performances due to the weak effect on the main flow caused by coolant injection. Inspired by these results, liquid film flow characteristics and its influencing factors including mass flow rate, dynamic pressure, coolant injection direction, and surface tension are investigated to guide the design of a thermal protection system. Published under license by AIP Publishing

Multidimensional Feature-Based Graph Attention Networks and Dynamic Learning for Electricity Load Forecasting

Electricity load forecasting is of great significance for the overall operation of the power system and the orderly use of electricity at a later stage. However, traditional load forecasting does not consider the change in load quantity at each time point, while the information on the time difference of the load data can reflect the dynamic evolution information of the load data, which is a very important factor for load forecasting. In addition, the research topics in recent years mainly focus on the learning of the complex relationships of load sequences in time latitude by graph neural networks. The relationships between different variables of load sequences are not explicitly captured. In this paper, we propose a model that combines a differential learning network and a multidimensional feature graph attention layer, it can model the time dependence and dynamic evolution of load sequences by learning the amount of load variation at different time points, while representing the correlation of different variable features of load sequences through the graph attention layer. Comparative experiments show that the prediction errors of the proposed model have decreased by 5–26% compared to other advanced methods in the UC Irvine Machine Learning Repository Electricity Load Chart public dataset

Noise reduction for temperature-sensitive paint measurement contaminated by strong background radiation in a high enthalpy hypersonic tunnel

The strong background radiation in high enthalpy hypersonic shock tunnels has posed severe challenges for measurement using luminescent coatings. We proposed a solution for reducing background radiation from time-resolved temperature-sensitive paint (TSP) measurement in a hypersonic flow with Ma = 6.5 and T-0 = 3525 K. The TSP was applied on an inlet ramp model, and the images were taken by a high-speed camera at 2 kHz under a modulated excitation. The strong background radiation led to a low signal-to-noise ratio and significant errors for the first half of the 130-ms test duration. Accordingly, three noise reduction methods were developed and evaluated based on temporal reconstruction, spatial reconstruction and robust principal component analysis (RPCA), respectively. The RPCA method showed the best performance that successfully recovered high-quality TSP data for a majority of test duration (t >= 40 ms)

Dietary phenylalanine level could improve growth performance, glucose metabolism and insulin and mTOR signaling pathways of juvenile swimming crabs, Portunus trituberculatus

An 8-week feeding trial was conducted to determine the optimal dietary phenylalanine requirement of juvenile swimming crab (Portunus trituberculatus). Six experimental diets (45.0% crude protein and 8.0% crude lipid) were formulated to contain 0.89%, 1.15%, 1.41%, 1.64%, 1.90% and 2.18% phenylalanine, respectively. Each diet was randomly divided into triplicate groups with 30 juvenile swimming crabs (initial weight 22.87 ± 0.03 g). The highest percent weight gain (PWG) and feed efficiency (FE) were presented in crabs fed with 1.64% phenylalanine diet, and the lowest PWG and FE were observed in crabs fed diet with 0.89% phenylalanine (P  0.05). Crabs fed the diet containing 0.89% phenylalanine had the lowest content of crude lipid in hepatopancreas among all treatments (P < 0.05). Hematological parameters related to glucose and lipids metabolism and enzyme activities involved in glycolysis and gluconeogenesis were significantly affected by dietary phenylalanine levels (P < 0.05). The contents of saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), n-6 polyunsaturated fatty acids (n-6 PUFAs) and n-3 polyunsaturated fatty acids (n-3 PUFAs) in the hepatopancreas were notably affected by the dietary phenylalanine levels (P < 0.05). The enzyme activities related to glycolysis, gluconeogenesis and glycogen content in hepatopancreas were significantly influenced by dietary phenylalanine levels (P < 0.05). The mRNA levels of genes related to glycolysis and gluconeogenesis in the hepatopancreas were significantly affected by dietary phenylalanine levels (P < 0.05). Moreover, the insulin and mammalian target of rapamycin (mTOR) signaling pathway were notably activated by dietary phenylalanine levels (P < 0.05). Based on two slope broken-line regression analysis of PWG against the dietary phenylalanine levels, the optimal dietary phenylalanine requirement was estimated to be 1.60% dry matter (3.55% dietary protein) for juvenile swimming crab