单电机驱动的带式输送机的传动控制

本文阐述了带式输送机传动的特点，分析了采用各种不同电机软起动控制方法-电压斜坡控制。电流闭环控制，转矩闭环控制和速度 闭环控制起动带式输送机的工作及皮带张力的变化。文章指出单电机驱动的带式输送机应该选用具有转矩闭环控制的固态软起动器或者转速反馈控制（例如美国BENSHAW的RSM系列）的固态软起动器，这样才能使带式输送机平滑起动，皮带中不会产生过大的张力，而采用转速反馈控制的固态软起动器是最佳方案。     

Hydrogels: From soft contact lenses and implants to self‐assembled nanomaterials

Hydrogels were the first biomaterials designed for clinical use. Their discovery and applications as soft contact lenses and implants are presented. This early hydrogel research served as a foundation for the expansion of biomedical polymers research into new directions: design of stimuli sensitive hydrogels that abruptly change their properties upon application of an external stimulus (pH, temperature, solvent, electrical field, biorecognition) and hydrogels as carriers for the delivery of drugs, peptides, and proteins. Finally, pathways to self‐assembly of block and graft copolymers into hydrogels of precise 3D structures are introduced. © 2009 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 47: 5929–5946, 2009     

The reduction of rotational ambiguity in soft-modeling by introducing hard models

Rotational ambiguity is a major problem in the application of soft-modeling analysis to a variety of multivariate mixture resolution problems and particularly important in the analysis of kinetic data. Soft-modeling analyses rely on constraints that restrict the concentration profiles and/or the spectral responses of all components. The main goal of this work is to demonstrate how a hard-modeling constraint on concentration profiles drastically decreases the extent of the rotational ambiguity. Therefore, in the present paper the discussion is focused on systems in which hard-modeling information is available. The results of simulated examples reveal that the utilized hard constraint decreases the rotational ambiguity in estimated concentration profile even components that do not take part in the explicit model. In addition, the rate constant of known reaction is determined in this method.     

Simultaneous 2nd Order Derivative Spectrophotometry Determination of Sorbic and Benzoic Acids in Soft Drinks

Abstract

A method is developed for the simultaneous 2nd order spectrophotometric determination of 1 to 7 μg.mL^?1 of each of benzoic and sorbic acids in non vegetal soft drinks, using a blank prepared from the same soft drink to be analyzed in order to avoid the interferece from other additives and colouring matter present.     

Dipole bands in nucleus ~(139)Pm

High-spin states in nucleus 139Pm have been studied using the reaction 116Cd(27Al,4n)139Pm.Two dipole cascades have been found.Spin and parity assignments were based on the Directional Correlation of Oriented Nuclei(DCO) ratios and systematic behavior in neighboring odd-proton nuclei.The level structures of 139Pm are compared with those of the N =78 isotone 141Eu in which two dipole bands have been confirmed as magnetic rotational bands.The close similarity between them suggests that the dipole bands in 139...     

木糖-软模板水热法制备硼掺杂分级多孔炭球及其电化学性能

以D-木糖为炭源,月桂酸钠为模板剂,硼酸为掺杂剂,通过水热炭化方法制得硼掺杂分级多孔炭球（BPC_S）。通过扫描电子显微镜（SEM）、透射电子显微镜（TEM）、N₂吸附-脱附测试、X射线光电子能谱（XPS）、顺磁共振波谱（EPR）、傅里叶红外光谱（FT-IR）、拉曼光谱（Raman）、X射线粉末衍射（XRD）、热重（TG）分析对样品进行表征。结果表明：月桂酸钠作为介孔造孔剂的同时,通过与D-木糖间的氢键作用使有机-有机自组装过程自发进行并形成窄尺寸分布（2~5 μm）规整炭球;硼酸在水热中催化炭源脱水降解,并以BC₃、BCO₂和BC₂O的形式掺杂在炭球上,掺硼后炭球与水表面接触角降低,润湿性提高。经CO₂活化、月桂酸钠高温分解以及胶质炭球的堆积分别产生微孔（0.5~1.2 nm）、介孔（3.14~35.00 nm）和大孔（60~146 nm）并形成分级结构。当硼酸加入量为0.927 5 g时多孔炭球（BPC_S-1）的电化学性能最佳,在6 mol·L^-1 KOH三电极体系中电流密度为0.5 A·g^-1时,比电容达287.12 F·g^-1;两电极体系中电流密度为0.5 A·g^-1时比电容达151.34 F·g^-1,能量密度达5.3 Wh·kg^-1;电流密度为5 A·g^-1时进行1 000次充放电循环,电容保持率仍达96.43%。     

Diffusiophoresis in suspensions of highly charged soft particles

Diffusiophoresis phenomenon of aoft particles suspended in binary electrolyte solutions is explored theoretically in this study based on the spherical cell model, focusing on the chemiphoresis component in absence of diffusion potential. Both the electrostatic and hydrodynamic aspects of the boundary confinement, or steric effect, due to the presence of neighboring particles are examined extensively under various electrokinetic conditions. Significant local extrema are found in mobility profiles expressed as functions of the Debye length in general, synchronized with the strength of the motion-inducing double layer polarization. Moreover, a seemingly peculiar phenomenon is observed that the soft particles may move faster in more concentrated suspensions. The competition between the simultaneous enhancement of the motion-inducing electric driving force and the motion-retarding hydrodynamic drag force from the boundary confinement effect of the neighboring particles is found to be responsible for it. The above findings are also demonstrated experimentally in a very recent study on the diffusiophoretic motion of soft particles through porous collagen hydrogels. The results presented here are useful in various practical applications of soft particles like drug delivery.     

Actuating Shape Memory Polymer for Thermoresponsive Soft Robotic Gripper and Programmable Materials

For soft robotics and programmable metamaterials, novel approaches are required enabling the design of highly integrated thermoresponsive actuating systems. In the concept presented here, the necessary functional component was obtained by polymer syntheses. First, poly(1,10-decylene adipate) diol (PDA) with a number average molecular weight M_n of 3290 g·mol⁻¹ was synthesized from 1,10-decanediol and adipic acid. Afterward, the PDA was brought to reaction with 4,4′-diphenylmethane diisocyanate and 1,4-butanediol. The resulting polyester urethane (PEU) was processed to the filament, and samples were additively manufactured by fused-filament fabrication. After thermomechanical treatment, the PEU reliably actuated under stress-free conditions by expanding on cooling and shrinking on heating with a maximum thermoreversible strain of 16.1%. Actuation stabilized at 12.2%, as verified in a measurement comprising 100 heating-cooling cycles. By adding an actuator element to a gripper system, a hen’s egg could be picked up, safely transported and deposited. Finally, one actuator element each was built into two types of unit cells for programmable materials, thus enabling the design of temperature-dependent behavior. The approaches are expected to open up new opportunities, e.g., in the fields of soft robotics and shape morphing.     

Mathematical Analysis of Reaction–Diffusion Equations Modeling the Michaelis–Menten Kinetics in a Micro-Disk Biosensor

In this study, we have investigated the mathematical model of an immobilized enzyme system that follows the Michaelis–Menten (MM) kinetics for a micro-disk biosensor. The film reaction model under steady state conditions is transformed into a couple differential equations which are based on dimensionless concentration of hydrogen peroxide with enzyme reaction (H) and substrate (S) within the biosensor. The model is based on a reaction–diffusion equation which contains highly non-linear terms related to MM kinetics of the enzymatic reaction. Further, to calculate the effect of variations in parameters on the dimensionless concentration of substrate and hydrogen peroxide, we have strengthened the computational ability of neural network (NN) architecture by using a backpropagated Levenberg–Marquardt training (LMT) algorithm. NNs–LMT algorithm is a supervised machine learning for which the initial data set is generated by using MATLAB built in function known as “pdex4”. Furthermore, the data set is validated by the processing of the NNs–LMT algorithm to find the approximate solutions for different scenarios and cases of mathematical model of micro-disk biosensors. Absolute errors, curve fitting, error histograms, regression and complexity analysis further validate the accuracy and robustness of the technique.