Optimized microwave absorption properties by tailoring the morphology of carbon coated TiC nanoparticles by N2 pressure

Increasing the dielectric loss capacity plays an important role in enhancing the electromagnetic absorption performance of materials. It remains a challenge to simultaneously introduce multiple types of dielectric losses in the material. In this work, we show that the atomic and interfacial dipole polarizations can be simultaneously enhanced by substituting N species into both carbon coating layers and bulk TiC lattices of a core-shell TiC@C material. Additionally, substitution of N species results more exposed TiC(111) facets and refines the TiC grain sizes in the bulk material, which is beneficial for enhancing the scattering of the external electromagnetic waves. The maximum reflection loss of the N substituted TiC@C material is measured as ?47.1 dB with an effective absorbing bandwidth of 4.83 GHz at 1.9 mm, which illustrates a valuable way to further tuning the electromagnetic absorption performance of this type of materials.     

Effect of LiTFSI and LiFSI on Cycling Performance of Lithium Metal Batteries Using Thermoplastic Polyurethane/Halloysite Nanotubes Solid Electrolyte

All-solid-state lithium batteries(ASSLB) are promising candidates for next-generation energy storage devices.Nevertheless,the large-scale commercial application of high energy density AS S LB with the polymer electrolyte still faces challenges.In this study,a thin solid polymer composite electrolyte(SPCE) is prepared through a facile and cost-effective strategy with an infiltration of thermoplastic polyurethane(TPU),lithium salt(LiTFSI or LiFSI),and halloysite nanotubes(HNTs) in a porous framework of polyethylene separator(PE)(TPU-HNTs-LiTFSI-PE or TPU-HNTs-LiFSI-PE).The composition,electrochemical performance,and especially the effect of anions(TFSI~-and FSI~-) on cycling performance are investigated.The results reveal that the flexible TPU-HNTs-LiTFSI-PE and TPU-HNTs-LiFSI-PE with a thickness of 34 μm exhibit wide electrochemical windows of 4.9 and 5.1 V(vs.Li+/Li) at 60℃,respectively.Reduction in FSI~-tends to form more LiF and sulfur compounds at the interface between TPU-HNTs-LiFSI-PE and Li metal anode,thus enhancing the interfacial stability.As a result,cell composed of TPU-HNTs-LiFSI-PE exhibits a smaller increase in interfacial resistance of solid electrolyte interphase(SEI) with a distinct decrease in charge-transfer resistance during cycling.Li|Li symmetric cell with TPU-HNTs-LiFSI-PE could keep its stable overpotential profile for nearly 1300 h with a low hysteresis of approximately39 mV at a current density of 0.1 mA cm~(-2),while a sudden voltage rise with internal cell impedance-surge signals was observed within 600 h for cell composed of TPU-HNTs-LiTFSI-PE.The initial capacities of NCMITPU-HNTs-LiTFSIPEILi and NCMITPU-HNTs-LiFSI-PEILi cells were 149 and 114 mAh g~(-1),with capacity retention rates of 83.52% and89.99% after 300 cycles at 0.5 C,respectively.This study provides a valuable guideline for designing flexible SPCE,which shows great application prospect in the practice of ASSLB.     

Transmission line detection in aerial images: An instance segmentation approach based on multitask neural networks

Camera-based transmission line detection (TLD) is a fundamental and crucial task for automatically patrolling powerlines by aircraft. Motivated by instance segmentation, a TLD algorithm is proposed in this paper with a novel deep neural network, i.e., CableNet. The network structure is designed based on fully convolutional networks (FCNs) with two major improvements, considering the specific appearance characteristics of transmission lines. First, overlaying dilated convolutional layers and spatial convolutional layers are configured to better represent continuous long and thin cable shapes. Second, two branches of outputs are arranged to generate multidimensional feature maps for instance segmentation. Thus, cable pixels can be detected and assigned cable IDs simultaneously. Multiple experiments are conducted on aerial images, and the results show that the proposed algorithm obtains reliable detection performance and is superior to traditional TLD methods. Meanwhile, segmented pixels can be accurately identified as cable instances, contributing to line fitting for further applications.     

Enhanced electrochemical performance of LiNi0.8Co0.1Mn0.1O2 via titanium and boron co-doping

Titanium and boron are simultaneously introduced into LiNi_0.8Co_0.1Mn_0.1O₂ to improve the structural stability and electrochemical performance of the material. X-ray diffraction studies reveal that Ti⁴⁺ ion replaces Li⁺ ion and reduces the cation mixing; B³⁺ ion enters the tetrahedron of the transition metal layers and enlarges the distance of the [LiO₆] layers. The co-doped sample has spherical secondary particles with elongated and enlarged primary particles, in which Ti and B elements distribute uniformly. Electrochemical studies reveal the co-doped sample has improved rate performance (183.1 mAh·g^-1 at 1 C and 155.5 mAh·g^-1 at 10 C) and cycle stability (capacity retention of 94.7% after 100 cycles at 1 C). EIS and CV disclose that Ti and B co-doping reduces charge transfer impedance and suppresses phase change of LiNi_0.8Co_0.1Mn_0.1O_2.     

Electrochemical performance of in situ LiFePO4 modified by N-doped graphene for Li-ion batteries

LiFePO₄ modified by N-doped graphene (NG) with a three-dimensional conductive network structure was synthesized via a one-step in situ hydrothermal method. The effects of N amount of NG on the phase structure, morphology, and electrochemical properties of LiFePO₄ are investigated in this study. X-ray diffraction (XRD) results show that doping suitable N amounts in NG do not alter the crystal structure of LiFePO_4, and scanning electron microscopy (SEM) images show that NG can slightly reduce the particle size of LiFePO₄. The high-resolution transmission electron microscopy (HRTEM) results show that the LiFePO₄ particles are well covered and connected by NG. The electrochemical performance confirms that LiFePO₄ modified by 20% N-doped graphene (named LFP/NG-4) displays a perfect specific capacity of 166.6 mAh·g^?1 at a rate of 0.2C and can reach 125 mAh·g^?1 at a rate of 5 C. Electrochemical impedance spectroscopy (EIS) results illustrate that the charge transfer resistance value of the LFP/NG-4 composite is only 58.6 Ω, which is very low compared with LiFePO₄. Cyclic voltammetry (CV) tests indicate that the addition of 20% N-doped graphene can effectively reduce electrode polarization and improve reversibility. The LFP/NG-4 composite with a three-dimensional conductive network structure can be regarded as a promising cathode material for Li-ion batteries.     

Speciation of copper in high chloride concentrations,in the context of corrosion of copper canisters

Canisters with a cast iron insert for mechanical strength and a 50-mm thick copper shell as corrosion protection are planned to be used for disposal of spent nuclear fuel in Sweden and Finland. Chloride can be considered “beneficial”, as it promotes active dissolution of copper rather than passivation (which might result in pitting), but a high concentration of chloride in solution would increase the driving force for corrosion through the formation of soluble copper chloro complexes. Thermodynamic calculations are performed in this study with the PHREEQC software and three of its accompanying databases, and a comparison with experimental data is performed to select the database to be used when evaluating repository performance. The activity coefficient models are given special attention. For the assessment of chloride-assisted corrosion of a KBS-3 canister, chloride concentrations pessimistically up to 5 mol/kg are used (in Finland and Sweden, the groundwater and bentonite porewater chloride concentrations are not expected to exceed 1 mol/kg). The resulting copper solubilities are then considered in different mass transport cases.     

防气窜固井技术研究

从气窜机理、气窜预测方法、提高水泥浆防气窜性能、防气窜固井工艺技术四个方面进行研究,为固井防气窜提供理论依据,进而提升防气窜固井技术。     

Energy conversion performances during biomass air gasification process under microwave irradiation

Biomass gasification technology under microwave irradiation is a new and novel method, and the energy conversion performances during the process play a guiding role in improving the energy conversion efficiencies and developing the gasification simulation models. In order to improve the energy utilization efficiency of microwave biomass gasification system, this study investigated and presented the energy conversion performances during biomass gasification process under microwave irradiation, and these were materialized through detailing (a) the energy conversion performance in the microwave heating stage, and (b) the energy conversion performance in the microwave assisted biomass gasification stage. Different forms of energies in the biomass microwave gasification process were calculated by the method given in this study based on the experimental data. The results showed that the useful energy (energy in silicon carbide (SiC), 18.73 kJ) accounted for 31.22% of the total energy input (electrical energy, 60.00 kJ) in the heating stage, and the useful energy (energy in the products, 758.55 kJ) accounted for 63.41% of the total energy input (electrical and biomass energy, 1196.28 kJ) in the gasification stage. During the whole biomass gasification process under microwave irradiation, the useful energy output (energy in the products, 758.55 kJ) accounted for 60.38% of the total energy input (electrical and biomass energy, 1256.28 kJ), and the energy in the gas (523.40 kJ) product played a dominate role in product energy (758.55 kJ). The energy loss mainly included the heat loss in the gas flow (89.20 kJ), magnetron loss (191.80 kJ) and microwave dissipation loss (198.00 kJ), which accounted for 7.10%, 15.27% and 15.76% of the total energy, respectively. The contents detailed in this study not only presented the energy conversion performances during microwave assisted gasification process but also supplied important data for developing gasification simulation models.     

基于NR-Transformer的集群作业运行时间预测

高性能集群的作业调度通常使用作业调度系统来实现，准确填写作业运行时间能在很大程度上提升作业调度效率。现有的研究通常使用机器学习的预测方式，在预测精度和实用性上还存在一定的提升空间。为了进一步提高集群作业运行时间预测的准确率，考虑先对集群作业日志进行聚类，将作业类别信息添加到作业特征中，再使用基于注意力机制的NR-Transformer网络对作业日志数据建模和预测。在数据处理上，根据与预测目标的相关性、特征的完整性和数据的有效性，从历史日志数据集中筛选出7维特征，并按作业运行时间的长度将其划分为多个作业集，再对各作业集分别进行训练和预测。实验结果表明，相比于传统机器学习和BP神经网络，时序神经网络结构有更好的预测性能，其中NR-Transformer在各作业集上都有较好的性能。