Expanded coprime array for DOA estimation: augmented consecutive co-array and reduced mutual coupling

Multidimensional Systems and Signal Processing - Generalized coprime structure decomposes the interleaved subarrays in the conventional coprime array by introducing a displacement and the resulting...     

Two-dimensional DOA estimation for acoustic vector-sensor array using a successive MUSIC

This paper discusses the problem of two-dimensional (2D) direction of arrival (DOA) estimation for acoustic vector-sensor array, and derives a successive multiple signal classification (MUSIC) algorithm therein. The proposed algorithm obtains initial estimations of the azimuth and elevation angles obtained from the signal subspace, and uses successively one-dimensional local searches to achieve the joint estimation of 2D-DOA. The proposed algorithm, which requires the one-dimension local searches, can avoid the high computational cost within 2D-MUSIC algorithm. The proposed algorithm can obtain automatically-paired 2D-DOA estimation for acoustic vector-sensor array, and it has better DOA estimation performance than propagator method, estimation of signal parameters via rotational invariance technique algorithm and trilinear decomposition algorithm. Meanwhile, it has very close angle estimation to 2D-MUSIC algorithm. Furthermore, it is suitable for non-uniform linear arrays, works well for the sources with the same azimuth angle, and imposes less constraint on the sensor spacing, which does not have to be restricted within half-wavelength. We have also derived the mean-square error of DOA estimation of the proposed algorithm and the Cramer-Rao bound of DOA estimation. Simulation results verify the usefulness of the proposed algorithm.     

Reduced-Dimensional ESPRIT for Direction Finding in Monostatic MIMO Radar with Double Parallel Uniform Linear Arrays

In this paper, the issue of two-dimensional direction of arrival estimation in monostatic multiple-input–multiple-output (MIMO) radar with double parallel uniform linear arrays is studied, and an algorithm based on estimation of signal parameters via rotational invariance techniques (ESPRIT) is proposed. Through a series of reduced-dimensional transformations, the proposed algorithm has very low complexity due to the low dimension. Meanwhile, the estimation performance of the proposed algorithm is slightly improved compared to the conventional ESPRIT, especially in low signal-to-noise ratio. Furthermore, the algorithm can estimate azimuth and elevation angles without additional pair matching in monostatic MIMO radar. Error analysis of the angle estimation and Cramér–Rao bound are derived. Simulation results verify the usefulness of our algorithm.     

Ni3N–CeO2 Heterostructure Bifunctional Catalysts for Electrochemical Water Splitting

Developing low-cost and high-efficient bifunctional catalysts for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is greatly significant for water electrolysis. Here, Ni₃N-CeO₂/NF heterostructure is synthesized on the nickel foam, and it exhibits excellent HER and OER performance. As a result, the water electrolyzer based on Ni₃N-CeO₂/NF bifunctional catalyst only needs 1.515 V@10 mA cm⁻², significantly better than that of Pt/C||IrO₂ catalysts. In situ characterizations unveil that CeO₂ plays completely different roles in HER and OER processes. In situ infrared spectroscopy and density functional theory calculations indicate that the introduction of CeO₂ can optimizes the structure of interface water, and the synergistic effect of Ni₃N and CeO₂ improve the HER activity significantly, while the in situ Raman spectra reveal that CeO₂ accelerates the reconstruction of O_V (oxygen vacancy)-rich NiOOH for boosting OER. This study clearly unlocks the different catalytic mechanisms of CeO₂ for boosting the HER and OER activity of Ni₃N for water splitting, which provides the useful guidance for designing the high-performance bifunctional catalysts for water splitting.     

High-rate Decoupled Water Electrolysis System Integrated with α-MoO3 as a Redox Mediator with Fast Anhydrous Proton Kinetics

Hydrogen is a promising alternative to fossil fuels that can reduce greenhouse gas emissions. Decoupled water electrolysis system using a reversible proton storage redox mediator, where the oxygen evolution reaction and hydrogen evolution reaction are separated in time and space, is an effective approach to producing hydrogen gas with high purity, high flexibility, and low cost. To realize fast hydrogen production in such a system, a redox mediator capable of releasing protons rapidly is required. Herein, α-MoO₃, with an ultrafast proton transfer property that can be explained by a dense hydrogen bond network in the lattice oxygen arrays of HxMoO₃, is examined as a high-rate redox mediator for fast hydrogen production in acidic electrolytes. The α-MoO₃ redox mediator shows both a large capacity of 204 mAh g⁻¹ and fast hydrogen production at a current rate of 10 A cm⁻²(≈153 A g⁻¹), outperforming most of the previously reported solid-state redox mediators.     

2D MoN1.2-rGO Stacked Heterostructures Enabled Water State Modification for Highly Efficient Interfacial Solar Evaporation

Improving interfacial solar evaporation performance is crucial for the practical application of this technology in solar-driven seawater desalination. Lowering evaporation enthalpy is one of the most promising and effective strategies to significantly improve solar evaporation rate. In this study, a new pathway to lower vaporization enthalpy by introducing heterogeneous interactions between hydrophilic hybrid materials and water molecules is developed. 2D MoN_1.2 nanosheets are synthesized and integrated with rGO nanosheets to form stacked MoN_1.2-rGO heterostructures with massive junction interfaces for interfacial solar evaporation. Molecular dynamics simulation confirms that atomic thick 2D MoN_1.2 and rGO in the MoN_1.2-rGO heterostructures simultaneously interact with water molecules, while the interactions are remarkably different. These heterogeneous interactions cause an imbalanced water state, which easily breaks the hydrogen bonds between water molecules, leading to dramatically lowered vaporization enthalpy and improved solar evaporation rate (2.6 kg m⁻² h⁻¹). This study provides a promising strategy for designing 2D-2D heterostructures to regulate evaporation enthalpy to improve solar evaporate rate for clean water production.     

Nested planar array: configuration design,optimal array and DOA estimation

Nested array enables to enhance localisation resolution and achieve under-determined direction of arrival (DOA) estimation. In this paper, we improve the traditional nested planar array to achieve more degrees of freedom (DOFs) and better angle estimation performance. The closed-form expressions for sensor positions of the improved array are given and the optimal array configuration for largest available DOFs is derived. Meanwhile, a computationally efficient DOA estimation algorithm is proposed. Specifically, we utilise two dimensional Discrete Fourier Transform (2D DFT) method to obtain the coarse DOA estimates; Subsequently, we achieve the fine DOA estimates by 2D spatial smoothing multiple signals classification (SS-MUSIC) algorithm. The proposed algorithm enjoys the same estimation accuracy as SS-MUSIC algorithm but with lower complexity because the coarse DOA estimates enable to shrink the range of spectral search. In addition, estimation of the number of signals is not required by 2D DFT method. Extensive simulation results testify the effectiveness of the proposed algorithm.     

Biodegradation characteristics of heavy oil and correlation with group composition and carbon isotopes

Shallow heavy oil is abundant but seriously biodegraded in Chepaizi Uplift and many biomarkers cannot be used effectively. Therefore, some new parameters and methods are used to analyze the biodegradation extent, classification, and oil–source of heavy oil samples. The acid value and group compositions are used to evaluate the biodegradation extent. Carbon isotopes are not only used to calculate the percentage of complex combined oil, but also to correlate oil–source in Chepaizi Uplift. δ¹³C of oil is used together with biomarkers that can bear serious degradation, such as pregnanes, tricyclic terpanes, and gammacerane. The crossplots of δ¹³C and biomarkers are effective correlation tools, such as the crossplot of δ¹³C and C₂₁/C₂₃ tricyclic terpanes. δ¹³C in different group compositions also show excellent oil–source correlation results. These methods to study biodegraded heavy oil are not only helpful to clarify the biodegradation extent of shallow heavy oil in an extensive area, but also effective to classify heavy oil and correlate oil–source.     

二维卡尔曼─中值混合自适应滤波

本文提出了能同时抑制加性噪声，脉冲噪声干扰和点扩展函数模糊，又能保护图象边缘及细节信息的新型滤波方法—“二维Kalman－Median混合自适应滤波”，并成功地应用于统计图象恢复，取得了满意的效果。     

Performance of SBR-Modified Asphalt Yufeng Cong

A dose of SBR modifier added to asphalt can improve asphalt's performance in stability, permanence, viscosity, and resistance to aging. Better application performances of asphalt pavement are affected directly by proper SBR modifying. This paper shows some investigations that confirm the relationship between the addition of SBR with the structure and the properties of SBR-modified asphalt. This paper also discusses the modified asphalt high temperature property, low temperature ductility, and mechanism of SBR-modified asphalt. The addition of SBR modifier showed an increase in viscosity, softening point, and elastic recovery of modified asphalt with rising temperature. When the temperature rises, the improvement of SBR-modified asphalt in softening point, elastic recovery, and visco-toughness result from SBR cross-linking. Although the lengths of low temperature ductility of SBR-modified asphalt are increased, the viscosities of modified asphalt increase; however, the softening point between the upper layer and lower layer were about 1.8°C after the isolated experiment.