Thermal Stability of Polymer Additives: Comparison of Decomposition Models Including Oxidative Pyrolysis

The thermo‐oxidative stability of widely used polymer additives has been investigated. A comparative analytical approach with classic and innovative decomposition models for polymer additives was conducted and the results supported using quantum‐chemical calculations. Unique pyrolysis products of the analytes were compiled utilizing pyrolysis online coupled to gas chromatography followed by mass spectrometric detection (Pyr‐GC–MS). The pyrolysis was either performed under inert conditions or in an oxygen‐containing atmosphere. Squalane was applied as polymer‐mimicking liquid next to low density polyethylene (LDPE) and polyamide 6 (PA 6) as matrices for 10 selected additives. The additives included in this study range from antioxidants and plasticizers to processing aids. These were selected to address a range of application in consumer products and to cover different chemical classes. The toxicological relevance of additives and potential breakdown products was considered. Consequently, degradation of sterically hindered antioxidants, diarylamines, and a trimellitic acid derivative was investigated. The findings were used to predict the behavior of consumer products made of polymeric materials entailing additives. The level of Antioxidant 2246 [2‐tert‐butyl‐6‐[(3‐tert‐butyl‐2‐hydroxy‐5‐methylphenyl)methyl]‐4‐methylphenol] and one of its predicted decomposition products was determined in baby bottle nipples made of natural rubber [2‐tert‐butyl‐4‐methylphenol] utilizing the complementary technique of gas chromatography coupled to tandem mass spectrometry (GC–MS/MS). This study provides a comprehensive characterization of important polymer additives and enables the prioritization of degradation products for further risk assessment. J. VINYL ADDIT. TECHNOL., 25:E12–E27, 2019. © 2018 The Authors. Journal of Vinyl and Additive Technology published by Wiley Periodicals, Inc. on behalf of Society of Plastics Engineers     

Enzyme activity and partial characterization of proteases obtained from Bromelia karatas fruit and compared with Bromelia pinguin proteases

Food Science and Biotechnology - The enzymatic activity and partial characterization of proteases from Bromelia karatas fruits were evaluated and compared with Bromelia pinguin proteases. The...     

On the problem of hydrogen removal during heat treatment of large forgings

The solutions to a differential equation for the problem of heating of a cylinder in a medium with a fixed temperature are used to obtain equations for estimating the change in the hydrogen concentration in forgings from data on the hydrogen concentration at the cylinder axis or on the average bulk hydrogen concentration. Similar equations are also obtained for forgings having square cross sections. The calculation demonstrates that, for the case of a twofold decrease in the hydrogen concentration in a forging, the calculated times of annealing of a cylindrical forging differ by three times.     

Robust nonlinear feedback–feedforward control of a coupled kinetic Monte Carlo–finite difference simulation

Robust nonlinear feedforward–feedback controllers are designed for a multiscale system that dynamically couples kinetic Monte Carlo (KMC) and finite difference (FD) simulation codes. The coupled codes simulate the copper electrodeposition process for manufacturing on-chip copper interconnects in electronic devices. The control objective is to regulate the current density subject to the condition that the steady-state fluctuation of the overpotential remains bounded within ±0.01 V. The controller designs incorporate a low-order stochastic model that captures the input–output behavior of the coupled KMC–FD code. The controllers achieve the objectives and the closed-loop responses implemented on the low-order model and the coupled KMC–FD code match well within stochastic variations. The nonlinear feedforward control reduces the rise time of the controller response while the feedback control ensures robustness in the presence of model uncertainty.     

Vacuum degassing of chromium-nickel-molybdenum steel at the Magnitogorsk Metallurgical Combine

The Magnitogorsk Metallurgical Combine has conducted a study of the effect of technological factors on the hydrogen content of chromium-nickel-molybdenum steel after vacuum degassing. It was established that the most important factor is the hydrogen content of the steel before the degassing operation. The study also determined the effects of the circulation coefficient, the duration of the degassing operation, and the vacuum used in the treatment. __________ Translated from Metallurg, No. 7, pp. 68–69, July, 2006.     

Assessing the Market Stability of Chemical Industry Enterprises

Breakdown of a company is examined and the concept of its stability is given. A system of indexes for characterizing the market position of an enterprise in the chemical industry and predicting its dynamics is proposed. An integral index can be an effective tool in the hands of managers in making managerial decisions related to effectively reacting to changes in the company's market position.     

Comparison of Two Statistical Models for the Calculation of Collisions of Particles in Isotropic Turbulence

Two models are given for determining the collision rate of inertial particles in a homogeneous isotropic turbulence. The advantages and disadvantages of the known models of particle collisions are discussed. One of the models suggested by us is based on the assumption that the joint probability density function of gas and particle velocities is a Gaussian distribution. The second model follows from the kinetic equation for the probability density of the relative velocity of two particles. These two models are compared with each other and with the available data of direct numerical simulation.     

基于交会图和多元统计法的神经网络技术在火山岩识别中的应用

针对火山岩储层的特殊性(复杂性、离散性和随机性),应用BP神经网络技术对火山岩测井解释中岩性识别问题进行了研究。该方法的技术关键是样本集和初始权重的建立,以及模型的优选。本文提出了一种基于交会图和多元统计法的学习样本生成方法,即根据取心岩样的地球化学和岩石学研究,用交会图技术建立样本集,采用聚类分析和距离判别法确定初始权重。将研究方法应用在松辽盆地杏山地区火山岩岩性识别问题中,取得了很好的效果,岩性解释符合率高于90%。文中通过四种岩性识别处理模式的对比研究,表明赋权重处理模式为最优处理模型。在神经网络模型预测过程中,需充分利用已有的地质经验和测井曲线信息建立典型可靠的样本文件,同时考虑神经网络方法中各种因素的影响,优选模型和计算参数才能使预测结果符合实际情况。