农药沉积利用率喷雾指示剂诱惑红的酶标仪测定方法

诱惑红是一种水溶性染料,近年来被用作农药沉积利用率测定的指示剂。诱惑红的检测方法为高效液相色谱法和分光光度法。高效液相色谱法需要专门的分析仪器,且价格昂贵,可见分光光度计法操作繁琐,试剂用量大,耗时长,均不适宜田间快速高效测定。笔者发展了诱惑红的酶标仪测定方法,简单高效,可批量检测多个样品,且准确度和精密度高,线性关系良好,514 nm检测波长下不受其他农药影响,并应用于玉米无人飞机喷雾场景下农药雾滴在玉米冠层的沉积利用率测定。     

基于Matlab的量子激光雷达稳频通信模拟系统设计

传统通信模拟系统设计较为复杂,导致模拟过程消耗能量较大,不能准确模拟稳频通信质量。因此,提出基于Matlab的量子激光雷达稳频通信模拟系统。由于振荡器是雷达形成初始信号源的基础,通过分析振荡电路与相位噪声,获得相位噪声函数与通信频率存在的关系;为确保通信过程的稳定,将准确性与稳定性作为信号质量的评价指标,并采用锁频环稳频技术计算频率偏移程度,根据PID控制算法控制频率,量子激光雷达稳频通信;利用Matlab确定激光器、探测器等硬件组成结构,通过时序与数字阵列的设置完成模拟系统设计。仿真结果表明所提系统结构简便、性能稳定,能够真实模拟出稳频通信的信号质量。     

磁性硅铁载铜吸附Hg0动力学机制及密度泛函研究

采用粉末冶金法将纳米单质铜(Cu⁰)、硅铁(FeSi)、四氧化三铁硅涂层(Fe₃O₄@SiO₂)混合煅烧并制备出新型磁性硅铁载铜吸附剂MagFeSi-Cu⁰。实验研究不同烟气温度下MagFeSi-Cu⁰的汞吸附能力基础上,结合颗粒内扩散模型、准二阶动力学模型、Elovich模型及Bangham模型分析了MagFeSi-Cu⁰吸附Hg⁰过程的主要控制步骤。在此基础上,依据密度泛函理论(DFT)研究了不同反应温度下FeSi表面Cu⁰原子与Hg⁰原子的汞齐作用机制。研究结果表明,Bangham模型的拟合值与MagFeSi-Cu⁰汞吸附实验值拟合度最高,MagFeSi-Cu⁰表面痕量Hg⁰吸附由汞的外扩散和表面铜汞齐吸附共同控制;通过密度泛函计算,发现Cu⁰颗粒表面Cu-Hg齐吸附能为-0.534 eV,当烟气温度从80℃上升至200℃时,Hg⁰原子与单质Cu原子的吸附自由能从-22.47 kJ/mol下降至-13.96 kJ/mol,这些结果为深入了解Hg⁰在Cu(111)表面的反应机理提供了理论基础。     

Dithizone,carminic acid and pyrocatechol violet dyes sensitized metal (Ho,Ba& Cd) doped TiO2/CdS nanocomposite as a photoanode in hybrid heterojunction solar cell

Considering the great importance of nanocomposite based photo-active nanomaterials for a variety of electronics, photonics and photovoltaics application, it is always worth considering to synthesize new hetreostructure. This paper describes the sol-gel and hydrothermal synthesis of metal (holmium, barium, and cadmium) doped TiO₂/CdS nanocomposites for photoanode applications. Various characterization techniques, including XRD, FTIR, UV–VIS, EDX, and SEM were used to examine the synthesized heterostructures. The band gap of pure TiO₂ NPs is 3.10 eV, which was effectively decreased to 2.16 eV by doping and coupling with CdS. The nanomaterial's crystallinity, crystallite size, morphology and elemental composition were determined by XRD, SEM and EDX, respectively. As sensitizers, the organic dyes dithizone, carminic acid, and pyrocatechol violet were used. FTIR was used to analyze the effective dye grafting on the surface of nanomaterials. In the presence of hole conducting P3HT polymer as solid state electrolyte, the sensitized materials were evaluated for solid state dye-sensitized solar cells. Compared to the reference device, Cd–TiO₂/CdS photosensitized using Pyrocatechol violet dye demonstrated the highest efficiency of 2.68% (0.82%). Other parameters of this device, including open circuit voltage (Voc) and short circuit current (Jsc), were determined to be 16.97 mA cm² and 0.41V, respectively.     

Weighted regularized extreme learning machine to model the discharge coefficient of side slots

In the current research, a modern learning machine algorithm named “Weighted Regularized Extreme Learning Machine (WRELM)" is implemented for the first time for the simulation of the coefficient of discharge of side slots. For this purpose, an effective variable on the coefficient of discharge of side slots is firstly introduced, then five distinctive WRELM models are produced by it for the estimation of the coefficient. In the next stage, a database is created for verification of WRELM results. it should be mentioned that 70% of the data are utilized for training the WRELM models, while the rest (i.e. 30%) for testing them. After that, the optimal number of hidden layer neurons as well as the best activation function of the WRELM algorithm are chosen. In addition, the best regularization parameter and also the weight function of the WRELM are achieved. By conducting a sensitivity analysis, the most effective variable for the simulation of the coefficient of discharge along with the WRELM superior model is introduced. The WRELM superior model estimates values of the coefficient of discharge with the maximum exactness and the highest correlation. For instance, the estimations of the correlation coefficient and scatter index for this model are computed to be 0.930 and 0.051, respectively. The sensitivity analysis shows that the ratio of the side slot crest height to its length and the Froude number should be considered as the most important input variables. A comparison between the WRELM with the ELM displays that the former works much better. Furthermore, an uncertainty analysis is executed for both models. Eventually, an equation is suggested for the estimation of the coefficient of discharge and a partial derivative sensitivity analysis is performed on it.     

Optimal Design of Novel Electromagnetic-Ring Active Balancing Actuator with Radial Excitation

Imbalance vibration is a typical failure mode of rotational machines and has significant negative effects on the effii-ciency,accuracy,and service life of equipment.To automatically reduce the imbalance vibration during the opera-tional process,different types of active balancing actuators have been designed and widely applied in actual produc-tion.However,the existing electromagnetic-ring active balancing actuator is designed based on an axial excitation structure which can cause structural instability and has low electromagnetic driving efficiency.In this paper,a novel radial excitation structure and the working principle of an electromagnetic-ring active balancing actuator with a combined driving strategy are presented in detail.Then,based on a finite element model,the performance param-eters of the actuator are analyzed,and reasonable design parameters are obtained.Self-locking torque measurements and comparative static and dynamic experiments are performed to validate the self-locking torque and driving effi-ciency of the actuator.The results indicate that this novel active balancing actuator has sufficient self-locking torque,achieves normal step rotation at 2000 r/min,and reduces the driving voltage by 12.5％.The proposed novel balancing actuator using radial excitation and a combination of permanent magnets and soft-iron blocks has improved electro-magnetic efficiency and a more stable and compact structure.     

基于C#持久蠕变强度外推功能的实现

持久蠕变强度外推是预测材料在高温高压环境下工作寿命的有效方法。目前常用的外推方法有等温法和参数法。这两种方法都是通过在实验室中采用较短时间的试验，获取试验数据后，通过Excel或者MATLAB等数据处理软件进行数据的拟合处理和外推计算。这些数据归纳统计和数学建模的过程有时需要耗费试验人员的大量精力。介绍了持久蠕变强度外推的软件实现方法，该功能包含在持久蠕变试验设备配备的软件中，试验完成后，软件直接根据试验结果进行数据拟合和持久蠕变强度的外推计算，无需试验数据的统计和建模，大大提高了持久蠕变强度外推计算的效率。     

Prediction models for multiphase-flow-induced corrosion of API X80 steel in CO2/H2S environment

In the offshore oil and gas industry, mainly focusing on the use of rigid or flexible pipes of subsea infrastructure applied to risers or flowlines, one of the greatest difficulties is the interpretation of the combined effects of the various correlated phenomena (hydrodynamic effects of intermittent flow, the effects of corrosivity of the environment in addition to variations in pressure, temperature, and dynamic loading). On the basis of this scenario, defining the degree of severity of each of the correlated system variables becomes of fundamental importance for establishing reliable criteria for selecting materials for subsea application. The established flow pattern directly affects the corrosion rate (or the pipe material mass loss), but the balance of other variables including possible changes in the physical and transported fluid chemical properties may increase the damage up to an order of magnitude, which is a piece of information normally not foreseen in design criteria. Therefore, to improve the understanding of the corrosion study influenced by multiphase flow, a testing loop was designed and assembled at the Corrosion and Protection Laboratory of the Institute for Technological Research, in which API X80 steel coupons were positioned in locations with a 0° and 45° inclinations. Tests were conducted by varying the partial pressure of the gaseous phase containing blends of CO₂ and H₂S with N₂ balance, mixed with the liquid phase containing light oil and heavy oil in water with salinity (NaCl)-simulating oil well conditions with 80% water cut. The main objective of this study is to establish models that can predict the corrosion intensity in conditions close to those obtained experimentally. To achieve results, the multiple regression and Box–Cox transformation methods were applied. These models will make possible damage prediction and optimization of matrix parameters for the multiphase-loop test.     

Molecular fingerprint and machine learning to accelerate design of high-performance homochiral metal–organic frameworks

Computational screening was employed to calculate the enantioseparation capabilities of 45 functionalized homochiral metal–organic frameworks (FHMOFs), and machine learning (ML) and molecular fingerprint (MF) techniques were used to find new FHMOFs with high performance. With increasing temperature, the enantioselectivities for (R,S)-1,3-dimethyl-1,2-propadiene are improved. The “glove effect” in the chiral pockets was proposed to explain the correlations between the steric effect of functional groups and performance of FHMOFs. Moreover, the neighborhood component analysis and RDKit/MACCS MFs show the highest predictive effect on enantioselectivities among the four ML classification algorithms with nine MFs that were tested. Based on the importance of MF, 85 new FHMOFs were designed, and a newly designed FHMOF, NO₂-NHOH-FHMOF, with high similarity to the optimal MFs achieved improved chiral separation performance, with enantioselectivities of 85%. The design principles and new chiral pockets obtained by ML and MFs could facilitate the development of new materials for chiral separation.