Chemical Bonding by the Chemical Orthogonal Space of Reactivity

The fashionable Parr–Pearson (PP) atoms-in-molecule/bonding (AIM/AIB) approach for determining the exchanged charge necessary for acquiring an equalized electronegativity within a chemical bond is refined and generalized here by introducing the concepts of chemical power within the chemical orthogonal space (COS) in terms of electronegativity and chemical hardness. Electronegativity and chemical hardness are conceptually orthogonal, since there are opposite tendencies in bonding, i.e., reactivity vs. stability or the HOMO-LUMO middy level vs. the HOMO-LUMO interval (gap). Thus, atoms-in-molecule/bond electronegativity and chemical hardness are provided for in orthogonal space (COS), along with a generalized analytical expression of the exchanged electrons in bonding. Moreover, the present formalism surpasses the earlier Parr–Pearson limitation to the context of hetero-bonding molecules so as to also include the important case of covalent homo-bonding. The connections of the present COS analysis with PP formalism is analytically revealed, while a numerical illustration regarding the patterning and fragmentation of chemical benchmarking bondings is also presented and fundamental open questions are critically discussed.     

多级深度还原法制备Ti6Al4V合金粉体的基础研究

目前Ti6Al4V合金粉体的生产方法主要有雾化法、机械合金法和氢化脱氢法,它们都以Kroll法生产海绵钛为基础。使用钛的氧化物作为原料的熔盐电解法和金属热还原法仍处于研究阶段。本文依据变价金属Ti和V的氧化物在还原过程中逐级还原的特性,提出使用金属氧化物(TiO₂, V₂O₅)作为原料的多级深度还原法制备Ti6Al4V合金粉体的新思路。首先计算了TiO₂-V₂O₅-Mg-Ca体系的吉布斯自由能变,结果表明先进行镁热自蔓延反应,后进行钙热深度还原反应制备Ti6Al4V合金粉体在热力学上具备可行性。然后通过实验进行了的验证。镁热自蔓延反应产物酸浸后除去MgO可得到氧含量为15.84%的多孔Ti-Al-V-O前驱体。配入金属Ca后进行深度脱氧可得到低氧Ti6Al4V合金粉体(Al: 6.2wt.%, V: 3.64wt.%, O: 0.24wt.%, Mg: 0.01wt.%, Ca: < 0.01wt.%)。     

Development of silicon wafer packaging technology for deep UV LED

This paper reports a deep‐ultraviolet LED (deep‐UV‐LED) package based on silicon MEMS process technology (Si‐PKG). The package consists of a cavity formed by silicon crystalline anisotropic etching, through‐silicon vias (TSVs) filled with electroplated Cu, bonding metals made of electroplated Ni/AuSn and a quartz lid for hermetic sealing. A deep‐UV LED die is directly mounted in the Si‐PKG by AuSn eutectic bonding without a submount. It has advantages in terms of size, heat dissipation, light utilization efficiency, productivity and cost over conventional AlN ceramic packages. We confirmed a light output of 30 mW and effective reflection on Si (111) cavity slopes in the Si‐PKG. Based on simulation, further improvement of the optical output is expected by optimizing DUV‐LED die mount condition.     

养老机构公共空间需求及影响因素研究——基于Kano模型分析

运用细分后的Kano模型甄别养老机构中老年人对公共空间需求的优先度排序及其影响因素的主次排序。首先通过规范、文献研究与访谈研究获取南京市养老机构中老年群体公共空间需求要素，并将得到的需求项进行层次归属划分。接着测算SI与DI系数量化各项需求对空间满意度的影响，得出公共空间需求优先度排序。最后利用多元线性回归对需求项的影响因素进行分析，探讨“自我”和“家庭”维度下影响因素的主次排序。得出养老机构公共空间的设计应首先满足老年人医疗保健空间层面的需求且空间需求受老年人“自我”维度下失能等级的影响程度最深。通过对需求重要度的排序，可以得出设计的优先满足策略，提升空间的利用效率及老年群体的满意度，为养老机构公共空间的投入侧重点提供理论依据。     

矿井钻孔测井分析仪在云冈矿上覆采空区积水探放中的应用

通过分析云冈矿12号层410盘区81010回采工作面上覆采空区情况,发现上覆3号层、7号层采空区中均存在积水,为消除该水患对回采工作的影响,须先行探放。文章结合81010回采工作面探放水实践,介绍了YCJ90/360矿用钻孔测井分析仪对钻孔轨迹的指导意义,以及测井技术对成孔准确性和可靠性的保障作用,证明其对采空区探放水钻孔施工具有必不可少的保障作用。     

泥鳅多糖的研究进展

近年来随着泥鳅养殖及产业化的快速发展, 泥鳅资源的开发和高值化利用已成为研究热点。泥鳅是一种含有丰富优质蛋白、脂肪酸以及微量元素的营养健康食品, 具备多种保健功能和药用价值, 其中泥鳅多糖是从泥鳅中提取得到的一种游离中性多糖, 具有耐缺氧、抗肿瘤、抗氧化、调节免疫、降血糖、抗炎等功能。本文主要综述了泥鳅多糖的制备方法、分离提纯方法、结构表征、生物活性、精深加工等方面的研究进展,旨在为泥鳅多糖的高值化利用提供一些理论基础, 为泥鳅产业链的快速发展提供新的发展方向。     

Using deep learning to combine static and dynamic power analyses of cryptographic circuits

Side-channel attacks have shown to be efficient tools in breaking cryptographic hardware. Many conventional algorithms have been proposed to perform side-channel attacks exploiting the dynamic power leakage. In recent years, with the development of processing technology, static power has emerged as a new potential source for side-channel leakage. Both types of power leakage have their advantages and disadvantages. In this work, we propose to use the deep neural network technique to combine the benefits of both static and dynamic power. This approach replaces the classifier in template attacks with our proposed long short-term memory network schemes. Hence, instead of deriving a specific probability density model for one particular type of power leakage, we gain the ability of combining different leakage sources using a structural algorithm. In this paper, we propose three schemes to combine the static and dynamic power leakage. The performance of these schemes is compared using simulated test circuits designed with a 45-nm library.     

镁质熔剂性球团矿相的多重分形谱

 球团矿相微观结构决定其冶金物理化学性能，为透视球团矿微观结构与其宏观冶金物理化学性能之间的依赖关系，需要解决的首要关键问题是矿相微观视觉特征的提取与定量表征。以镁质熔剂性球团微观矿相为研究对象，在直观分析矿相视觉特征的基础上，采用多重分形谱分析方法，提取矿相的微观多重分形谱定量表征值f（α），并分别深度挖掘由f（α）衍生出的对称度特征值Δf、谱宽特征值Δα、容量维特征值D（0）随碱度变化的迁移规律和随矿相检测位置变化的迁移规律。研究结果表明，矿相微观视觉特征在HSV颜色空间上呈现的颜色特征未在碱度变化和位置变化上存在显著差异性；矿相微观多重分形谱分析中，Δf、Δα、D（0） 3个特征值在碱度变化和位置变化上有显著的差异性，可以很好地表征碱度迁移规律和位置迁移规律。     

退火炉内罩中气体流动及钢卷传热的数值模拟

摘要：轧制力预报一直是热连轧过程控制模型的核心，浅层神经网络对复杂函数的表示能力有限，而深度学习模型通过学习一种深层非线性网络结构，实现复杂函数逼近。利用深度学习框架TensorFlow，构建了一种深度前馈神经网络轧制力模型，采用BP算法计算网络损失函数的梯度，运用融入Mini batch策略的Adam优化算法进行参数寻优，采用Early stopping、参数惩罚和Dropout正则化策略提高模型的泛化能力。基于上述建模策略，针对宝钢1880热连轧精轧机组的大量轧制历史数据进行了建模实验，对比分析了4种不同结构的前馈网络预测精度。结果表明，相比于传统SIMS轧制力模型，深度神经网络可实现轧制力的高精度预测，针对所有机架的预测精度平均提升21.11%。