Theoretical study on a kind of cyclization mechanism of boron trichloride and hexamethyldisilazane to form the borazine ring for SiBCN ceramics precursor

Borazine rings act as a pivotal part in siliconboroncarbonitride ceramics (SiBCN) for high-temperature stability and great resistance to crystallization. A detailed investigation of the ring formation mechanism will guide the design and synthesis of SiBCN to meet application requirements under extreme conditions. Boron trichloride (BCl₃) and hexamethyldisilazane (HN(SiMe₃)₂) are common raw materials for the synthesis of precursors for SiBCN. In this paper, quantum chemical calculation was used to study the cyclization reaction mechanism between BCl₃ and HN(SiMe₃)₂ to form trichloroborazine (TCBZ) at the MP2/6-31G (d,p) level of theory. We discussed the structure properties, reaction pathways, energy barriers, reaction rates, and other aspects in detail. The results show that BCl₃ and HN(SiMe₃)₂ alternately participate in the reaction process, accompanied by the release of trimethylchlorosilane (TMCS), and that the entire reaction shows an absolute advantage in terms of energy. In the Step by step reaction, lower reaction barriers are formed due to the introduction of BCl₃ with more heat released compared to that for the introduction of HN(SiMe₃)₂. The final single-molecule cyclization and TMCS elimination steps are found to be faster compared to all previous bimolecular reactions.     

增材制造技术在超高膨胀封隔器中的应用

石油和天然气行业不断关注增材制造技术在航空航天和汽车行业的应用发展。研发了利用增材制造技术的超高膨胀封隔器,该封隔器的支承环系统由增材制造。增材制造设计大幅减少了支承系统的构件数量,同时显著提高了膨胀能力和额定压力。密封元件系统与增材制造支承环安装在一起,提供了极端膨胀比、零挤压间隙和对不规则孔的良好适应性。分析和测试结果表明:直径膨胀比高达111%,与常规封隔器相比,提高50%以上; 至少涵盖5种线重的套管(外径相同); 在148.89 ℃的温度下,密封元件能够保持压力68.95 MPa。介绍了增材制造技术、增材制造支承环概念、增材制造材料力学性能、密封元件系统优化和测试情况,以期给我国的完井作业提供借鉴。     

内燃机活塞环表面处理技术

活塞环在内燃机中有着支撑、密闭、储油、导热的作用,内燃机活塞环制备材料应该具备优良的加工性能、耐高温、耐腐蚀、导热性好且具有良好的强韧性,较好的与气缸材料表面的磨合性能。球墨铸铁和专用钢材已经成为制备内燃机活塞环的基础材料,目前国内外采用多种表面处理技术比如:镀铬、氮化、PVD与CVD镀膜、喷钼、喷涂陶瓷层等表面处理工艺进行表面改性,提高内燃机活塞环的使用寿命和使用性能。需要不断研究和开发新的内燃机活塞环的表面处理技术来满足实际生产和应用中内燃机越来越高的要求。     

A Student's t-based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results.     

门架式堆取料机在铜冶炼中的生产实践

针对铜冶炼工艺的特点,从门架式堆取料机对前后工序衔接、结构、原理出发,介绍了其在熔炼炉系统和吹炼炉系统中的应用情况。经过试生产期的生产实践证明,门架式堆取料机具有场地利用率高、取料量大,自动化程度高和安全环保等优点。     

Simulation studies on a rotating ring disk electrode: Effects of ionic migration with kinetic complication-disk results

In continuation to my previous work (Guha S. AIChE J. 2013;59(4):1390-1399), in this work, effects of ionic migration are evaluated for disk region of a rotating ring disk electrode system by numerically solving complex differential equations, developed for mass transfer along with kinetic complication in presence of ionic migration under limiting current condition. The system for simulation is 0.01 M Fe₂(SO₄)₃ solution with H₂SO₄ as supporting electrolyte. Simulation cases are presence and absence of ionic migration with kinetic complication (oxidation of Fe²⁺ to Fe³⁺ under O₂ pressure). Results show that concentration boundary layer thickness of reactant Fe³⁺ reduces appreciably and steady-state disk current reduces substantially in presence of migration. Simulated steady-state disk current in absence of migration case agrees well with published data. Results indicate higher Fe²⁺ concentration in presence of migration and thereby higher rate of oxidation of Fe²⁺ to Fe³⁺ at all rate constant values.     

基于多尺度双线性卷积神经网络的多角度下车型精细识别

针对多角度下车辆出现一定的尺度变化和形变导致很难被准确识别的问题，提出基于多尺度双线性卷积神经网络（MS-B-CNN）的车型精细识别模型。首先，对双线性卷积神经网络（B-CNN）算法进行改进，提出MS-B-CNN算法对不同卷积层的特征进行了多尺度融合，以提高特征表达能力；此外，还采用基于中心损失函数与Softmax损失函数联合学习的策略，在Softmax损失函数基础上分别对训练集每个类别在特征空间维护一个类中心，在训练过程中新增加样本时，网络会约束样本的分类中心距离，以提高多角度情况下的车型识别的能力。实验结果显示，该车型识别模型在CompCars数据集上的正确率达到了93.63%，验证了模型在多角度情况下的准确性和鲁棒性。     

结合优化支持向量机与K-means++的工控系统入侵检测方法

针对工业控制系统传统单一检测算法模型对不同攻击类型检测率和检测速度不佳的问题，提出一种优化支持向量机和K-means++算法结合的入侵检测模型。首先利用主成分分析法（PCA）对原始数据集进行预处理，消除其相关性；其次在粒子群优化（PSO）算法的基础上加入自适应变异过程避免在训练的过程中陷入局部最优解；然后利用自适应变异粒子群优化（AMPSO）算法优化支持向量机的核函数和惩罚参数；最后利用密度中心法改进K-means算法与优化后的支持向量机组合成入侵检测模型，从而实现工业控制系统的异常检测。实验结果表明，所提方法在检测速度和对各类攻击的检测率上得到明显提升。