Tb0.3Dy0.7(Fe0.9T0.1)1.95合金的结构、自旋重取向和穆斯堡尔谱

系统研究了室温下Tb_0.3Dy_0.7(Fe_0.9T_0.1)_1.95(过渡金属元素T=Mn，Fe，Co，B，Al，Ga)合金中ⅢA族金属和过渡金属元素T替代Fe对结构、自旋重取向和穆斯堡尔谱的影响.结果发现，不同金属T替代Fe，Tb_0.3Dy_0.7(Fe_0.9T_0.1)_1.95，合金具有相同的MgCu₂型立方Laves相结构；Al，Ga替代使Tb_0.3Dy_0.7(Fe_0.9T_0.1)_1.95合金的易磁化方向在{110}面逐渐偏离了立方晶体的主对称轴，即自旋重取向，B，Mn，Co替代未使易磁化轴发生明显转动；Al，Ga元素替代使超精细场H_hf略有下降，B，Mn替代对超精细场H_hf的影响不大，而Co元素替代使超精细场H_hf有较大增加；所有元素替代使同质异能移IS有所增加；B，Al，Ga和Mn替代使四极劈裂Q_s增加，而Co替代使四极劈裂Q_s下降. 关键词： 立方Laves相 自旋重取向 穆斯堡尔谱     

Simultaneous estimation of the temperature and heat rate distributions within the combustion region by a new inverse radiation analysis

A new inverse radiation analysis is presented for estimating the heat rate and temperature distributions in the combustion region from the information of the temperature and heat flux profiles of wall elements in the system. The Monte Carlo method is employed to solve the radiative heat transfer equation. The inverse radiation problem is posed as a minimization problem of the least squares criterion, which is solved by the conjugate gradient method. The performance of the present technique of inverse analysis is evaluated and the effects of the errors of the absorption coefficient, emissivity and convective heat transfer coefficient on the inverse analysis are investigated. The results show that the present technique is robust and yields accurate estimation even with noisy measurement.     

“J—646”新型光学光敏胶胶合工艺简介

“J—646”光敏胶具有透光率好,收缩率小,粘接强度适中,耐老化,毒性小和成本低廉等特点。本文简要介绍了该胶的胶合工艺。     

不同激发密度下CdS晶体的光致发光和受激发射

本文主要研究在77-111K温度范围内、不同激发密度的N2激光器的337.1nm谱线激发下,激子-激子(Ex-Ex)、激子-载流子(Ex-e)的相互作用和发射一个LO声子(Ex-1LO)、两个LO声子(Ex-2LO)的自由激子的辐射复合行为.并在77K温度下观测到由Ex-Ex发射产生的受激发射.     

Impact of Extracellular Polymeric Substance in the Inactivation of Harmful Algae by Ag2O/g-C3N4 under Visible Light

Photocatalysis has attracted much attention as an emerging algae removal technology, but the inactivation performance is inevitably affected by the extracellular polymeric substance (EPS) produced by algae. In this study, a photocatalyst (Ag₂O/g-C₃N₄) with efficient algae inactivation is adopted to investigate the interactions with EPS, and the impact of EPS on photocatalytic algae removal is studied. The results show that EPS can adhere to the surface of Ag₂O/g-C₃N₄ by electrostatic force. The interaction with EPS decreases the surface zeta potential of the Ag₂O/g-C₃N₄ from 7.71 to −22.3 mV with the increase in EPS concentration, and the maximum ratio of particle size increases from 825 to 1281 nm. In addition, the interaction with EPS inhibits the release of Ag⁺ in Ag₂O/g-C₃N₄ by half, thus, the toxicity of metal ions will be alleviated. Meanwhile, EPS can also be degraded by Ag₂O/g-C₃N₄, indicating that EPS can work as a radical scavenger to protect the algae cells. Without the protection of EPS, 97.8% of algae cells are inactivated after 5 h photocatalysis. Therefore, more attention should be given to the interaction between EPS and photocatalyst to promote the design and application of the photocatalytic.     

HL-2M 装置运行控制技术初步研究

重点介绍了 HL-2M 装置的运行技术和初步的等离子体控制实验结果,包括等离子体放电方案设计、 线圈电流控制、击穿阶段零场匹配和等离子体电流以及位移的控制。为了降低放电运行风险,HL-2M 装置初始放 电采用了简化的放电方案,通过整定 PID 参数实现了线圈电流控制,在击穿阶段获得了 10V 以上的环电压和较大 范围的零场区域,成功实现等离子体击穿。最后,投入了等离子体电流和水平位移反馈控制算法,成功将等离子 体放电脉宽提升至 200ms 以上,且维持 I_p≥100kA 的时间超过了 100ms,上述结果表明 HL-2M 装置运行控制技术 得到了初步的检验。      

P213 BN: a novel large-cell boron nitride polymorph

A new boron nitride polymorph, P2₁3 BN (space group: P2₁3), is investigated by first-principles calculations, including its structural properties, stability, elastic properties, anisotropy and electronic properties. It is found that the new boron nitride polymorph P2₁3 BN is mechanically, dynamically and thermodynamically stable. The bulk modulus (B), shear modulus (G) and Young's modulus of P2₁3 BN are 91 GPa, 41 GPa and 107 GPa, respectively, all of which are larger than that of Y carbon and TY carbon. By comparing with c-BN, the Young's modulus, shear modulus and Poisson's ratio of P2₁3 BN show tiny anisotropy in the (001), (010), (100) and (111) planes. At the same time, in contrast with most boron nitride polymorphs, P2₁3 BN is a semiconductor material with a smaller band gap of 1.826 eV. The Debye temperature and the anisotropic sound velocities of P2₁3 BN are also investigated in this work.     

Nearby source interpretation of differences among light and medium composition spectra in cosmic rays

Recently the AMS-02 reported the precise measurements of the energy spectra of medium-mass compositions (Neon, Magnesium, Silicon) of primary cosmic rays, which reveal different properties from those of light compositions (Helium, Carbon, Oxygen). Here we propose a nearby source scenario, together with the background source contribution, to explain the newly measured spectra of cosmic ray Ne, Mg, Si, and particularly their differences from that of He, C, O. Their differences at high energies can be naturally accounted for by the element abundance of the nearby source. Specifically, the abundance ratio of the nearby source to the background of the Ne, Mg, Si elements is lower by a factor of ∼ 1.7 than that of the He, C, O elements. Such a difference could be due to the abundance difference of the stellar evolution of the progenitor star or the acceleration process/environment, of the nearby source. This scenario can simultaneously explain the high-energy spectral softening features of cosmic ray spectra revealed recently by CREAM/NUCLEON/DAMPE, as well as the energy-dependent behaviors of the large-scale anisotropies. It is predicted that the dipole anisotropy amplitudes below PeV energies of the Ne, Mg, Si group are smaller than that of the He, C, O group, which can be tested with future measurements.     

FTRLIM: Distributed Instance Matching Framework for Large-Scale Knowledge Graph Fusion

Instance matching is a key task in knowledge graph fusion, and it is critical to improving the efficiency of instance matching, given the increasing scale of knowledge graphs. Blocking algorithms selecting candidate instance pairs for comparison is one of the effective methods to achieve the goal. In this paper, we propose a novel blocking algorithm named MultiObJ, which constructs indexes for instances based on the Ordered Joint of Multiple Objects’ features to limit the number of candidate instance pairs. Based on MultiObJ, we further propose a distributed framework named Follow-the-Regular-Leader Instance Matching (FTRLIM), which matches instances between large-scale knowledge graphs with approximately linear time complexity. FTRLIM has participated in OAEI 2019 and achieved the best matching quality with significantly efficiency. In this research, we construct three data collections based on a real-world large-scale knowledge graph. Experiment results on the constructed data collections and two real-world datasets indicate that MultiObJ and FTRLIM outperform other state-of-the-art methods.     

A Fast Approach to Removing Muscle Artifacts for EEG with Signal Serialization Based Ensemble Empirical Mode Decomposition

An electroencephalogram (EEG) is an electrophysiological signal reflecting the functional state of the brain. As the control signal of the brain–computer interface (BCI), EEG may build a bridge between humans and computers to improve the life quality for patients with movement disorders. The collected EEG signals are extremely susceptible to the contamination of electromyography (EMG) artifacts, affecting their original characteristics. Therefore, EEG denoising is an essential preprocessing step in any BCI system. Previous studies have confirmed that the combination of ensemble empirical mode decomposition (EEMD) and canonical correlation analysis (CCA) can effectively suppress EMG artifacts. However, the time-consuming iterative process of EEMD may limit the application of the EEMD-CCA method in real-time monitoring of BCI. Compared with the existing EEMD, the recently proposed signal serialization based EEMD (sEEMD) is a good choice to provide effective signal analysis and fast mode decomposition. In this study, an EMG denoising method based on sEEMD and CCA is discussed. All of the analyses are carried out on semi-simulated data. The results show that, in terms of frequency and amplitude, the intrinsic mode functions (IMFs) decomposed by sEEMD are consistent with the IMFs obtained by EEMD. There is no significant difference in the ability to separate EMG artifacts from EEG signals between the sEEMD-CCA method and the EEMD-CCA method (p > 0.05). Even in the case of heavy contamination (signal-to-noise ratio is less than 2 dB), the relative root mean squared error is about 0.3, and the average correlation coefficient remains above 0.9. The running speed of the sEEMD-CCA method to remove EMG artifacts is significantly improved in comparison with that of EEMD-CCA method (p < 0.05). The running time of the sEEMD-CCA method for three lengths of semi-simulated data is shortened by more than 50%. This indicates that sEEMD-CCA is a promising tool for EMG artifact removal in real-time BCI systems.