Synthesis and slurry spray coating of barium strontium alumino silicate on SiC substrate

Barium strontium alumino silicate (BSAS); (Ba_0.6Sr_0.4Al₂Si₂O₈) was synthesized through solid state reaction between BaCO₃, SrCO₃, Al₂O₃ and SiO₂ subjected to wet milling in isopropanol for about 24 h. The sequence of the solid state reaction was studied by subjecting to DG/DTG from room temperature to 1550 °C. The crystallographic phase evolution was confirmed by X-ray diffraction of the powders calcined in the range 1000 to 1300 °C for 2 h. The monoclinic celsian phase obtained at 1300 °C, pelletized through uniaxial pressing was sinterable to 67 to 78% density in the temperature range of 1300 to 1500 °C. The density improved to 75 to 94% after ball milling for 76 h, while ZrO₂ addition further improved the density by 2%. The celcian phase of BSAS was dispersed in isopropyl alcohol, milled for about 24 h and spray coated on to plain SiC and mullite precoated SiC substrates. Sintering of coated samples and characterization for weight gain/loss, microstructure, scratch test prove that mullite + BSAS coating is more effective than single layer coating of BSAS on SiC substrates.     

High performance H2 sensor based on rGO-wrapped SnO2–Pd porous hollow spheres

Hydrogen (H₂) sensors based on metal oxide semiconductors (MOS) are promising for many applications such as a rocket propellant, industrial gas and the safety of storage. However, poor selectivity at low analyte concentrations, and independent response on high humidity limit the practical applications. Herein, we designed rGO-wrapped SnO₂–Pd porous hollow spheres composite (SnO₂–Pd@rGO) for high performance H₂ sensor. The porous hollow structure was from the carbon sphere template. The rGO wrapping was via self-assembly of GO on SnO₂-based spheres with subsequent thermal reduction in H₂ ambient. This sensor exhibited excellently selective H₂ sensing performances at 390 °C, linear response over a broad concentration range (0.1–1000 ppm) with recovery time of only 3 s, a high response of ～8 to 0.1 ppm H₂ in a minute, and acceptable stability under high humidity conditions (e. g. 80%). The calculated detection limit of 16.5 ppb opened up the possibility of trace H₂ monitoring. Furthermore, this sensor demonstrated certain response to H₂ at the minimum concentration of 50 ppm at 130 °C. These performances mainly benefited from the special hollow porous structure with abundant heterojunctions, the catalysis of the doped-PdO_x, the relative hydrophobic surface from rGO, and the deoxygenation after H₂ reduction.     

消防战勤保障体系建设的思考

随着经济的发展,消防救援队伍承担的任务越来越繁重.重大灾害事故的发生,对消防战勤保障方面提出了更高的要求.文章主要从消防战勤保障的主要任务职能、消防战勤的任务分类以及消防战勤保障体系建设存在的问题与建议等几个方面进行了详细的阐述,以期消防战勤保障得到更好的发展.     

钻井机器人的连续油管钻压和钻速控制模型

连续油管钻井机器人利用机身内外的钻井液压力差作为动力源，可在牵引连续油管的同时加载钻压。以钻井机器人为基础，建立连续油管钻柱动力学模型，并推导出通过钻井液排量控制钻压和钻速的单参数控制数学模型；对钻井机器人引入调速回路，建立具有调速功能的钻柱动力学模型；在溢流阀调定压力大于机身内外压差时，推导出利用钻井液排量和节流阀流通面积两种参数控制钻压、钻速的数学模型，在溢流阀调定压力小于机身内外压差时，推导出利用钻井液排量、节流阀流通面积和溢流阀调定压力3种参数控制钻压、钻速的数学模型；以11.43 cm（4.5英寸）井眼为例，对上述3种数学模型进行了分析。分析结果表明：钻压、钻速随钻井液排量的增加基本呈线性增加，在钻井液排量大于0.005 m³/s时，钻井机器人能够向前爬行，在钻井液排量大于0.005 7 m³/s时，钻头能够正常钻进；调节节流阀流通面积和溢流阀调定压力，可以在一定范围内无级调钻压和钻速；3种控制方法相结合，可以实现小排量、大钻压，及大排量、小钻压等钻井参数的控制。以控制模型为基础，针对不同井下工况建立钻进工艺的专家数据库，以钻井机器人为"大脑"，结合井下随钻测量数据就能够实现闭环控制，自动钻进。     

Compiler compatible 5.66 Mb/mm2 8T 1R1W register file in 14 nm FinFET technology

1-read/1-write (1R1W) register file (RF) is a popular memory configuration in modern feature rich SoCs requiring significant amount of embedded memory. A memory compiler is constructed using the 8T RF bitcell spanning a range of instances from 32 b to 72 Kb. An 8T low-leakage bitcell of 0.106 μm² is used in a 14 nm FinFET technology with a 70 nm contacted gate pitch for high-density (HD) two-port (TP) RF memory compiler which achieves 5.66 Mb/mm² array density for a 72 Kb array which is the highest reported density in 14 nm FinFET technology. The density improvement is achieved by using techniques such as leaf-cell optimization (eliminating transistors), better architectural planning, top level connectivity through leaf-cell abutment and minimizing the number of unique leaf-cells. These techniques are fully compatible with memory compiler usage over the required span. Leakage power is minimized by using power-switches without degrading the density mentioned above. Self-induced supply voltage collapse technique is applied for write and a four stack static keeper is used for read Vmin improvement. Fabricated test chips using 14 nm process have demonstrated 2.33 GHz performance at 1.1 V/25 °C operation. Overall V_min of 550 mV is achieved with this design at 25 °C. The inbuilt power-switch improves leakage power by 12x in simulation. Approximately 8% die area of a leading 14 nm SoC in commercialization is occupied by these compiled RF instances.     

不同苯乙烯工艺技术经济分析及建议

通过对国内外苯乙烯市场供需趋势的梳理,针对4种苯乙烯主要生产工艺,重点从原料可获性、产品质量、能耗物耗以及成本竞争力等方面对不同工艺主要技术经济指标进行了对比分析,并提出了行业可持续发展的有关建议。     

藕节多酚超声波辅助提取工艺优化及其抗油脂氧化能力研究

以藕节多酚得率为评价指标,超声时间、超声温度、料液比和乙醇体积分数为影响因素,通过单因素试验和Box-Behnken(BBD)试验设计优化藕节多酚的提取工艺条件,同时采用恒温箱热贮藏试验法研究藕节多酚的抗油脂氧化能力。结果表明:藕节多酚的最佳提取条件为超声时间34 min、超声温度50℃、料液比1∶20、乙醇体积分数70%,在此条件下藕节多酚得率为(7. 11±0. 14)%;藕节多酚能够明显减缓油脂过氧化值的升高趋势,对动植物油脂的自氧化均有明显的抑制作用,且具有一定的浓度依赖性。     

环氧丙烷产业现状及发展趋势

简述了全球及我国环氧丙烷产业的生产及供需现状;对环氧丙烷在聚醚多元醇、丙二醇/碳酸二甲酯、丙二醇醚及其酯类等领域的应用进行了分析;并对环氧丙烷生产技术进行了比较,提出了发展建议。     

High Accuracy Network Cardinalities Estimation by Step Sampling Revision on GPU

Host cardinality estimation is an important research field in network management and network security. The host cardinality estimation algorithm based on the linear estimator array is a common method. Existing algorithms do not take memory footprint into account when selecting the number of estimators used by each host. This paper analyzes the relationship between memory occupancy and estimation accuracy and compares the effects of different parameters on algorithm accuracy. The cardinality estimating algorithm is a kind of random algorithm, and there is a deviation between the estimated results and the actual cardinalities. The deviation is affected by some systematical factors, such as the random parameters inherent in linear estimator and the random functions used to map a host to different linear estimators. These random factors cannot be reduced by merging multiple estimators, and existing algorithms cannot remove the deviation caused by such factors. In this paper, we regard the estimation deviation as a random variable and proposed a sampling method, recorded as the linear estimator array step sampling algorithm (L2S), to reduce the influence of the random deviation. L2S improves the accuracy of the estimated cardinalities by evaluating and remove the expected value of random deviation. The cardinality estimation algorithm based on the estimator array is a computationally intensive algorithm, which takes a lot of time when processing high-speed network data in a serial environment. To solve this problem, a method is proposed to port the cardinality estimating algorithm based on the estimator array to the Graphics Processing Unit (GPU). Experiments on real-world highspeed network traffic show that L2S can reduce the absolute bias by more than 22% on average, and the extra time is less than 61 milliseconds on average.