Surfactant-mediated wetting and spreading: Recent advances and applications

Surfactant-mediated wetting and spreading are ubiquitous. Understanding of these phenomena in-depth allows precise tailoring of wetting performance which can contribute to global challenges in the food supply chain, healthcare, ecology and industrial processes. The first part of this review shows how surfactants can be used to improve the efficacy of fertilisers and pesticides in agriculture, enhanced oil recovery, treatment of lung diseases and extinguishing fires involving flammable liquids. The second part provides analysis of recent studies on wetting and spreading over solid substrates. It includes discussion on the effect of surfactants on the outcome of the impact of liquid drops, the wetting state after impact, autophobic effect and spreading kinetics for both partial and complete wetting, including superspreading. Perspectives of future development in the area of surfactant-assisted wetting and spreading on solid substrates are outlined.     

Discrimination of Beers by Cyclic Voltammetry Using a Single Carbon Screen-printed Electrode

A fast, simple and costless methodology without sample pre-treatment is proposed for the discrimination of beers. It is based on cyclic voltammetry (CV) using commercial carbon screen-printed electrodes (SPCE) and includes a correction of the signals measured with different SPCE units. Data are submitted to partial least squares discriminant analysis (PLS−DA) and support vector machine discriminant analysis (SVM−DA), which allow a reasonable classification of the beers. Also, CV data from beers can be used to predict their alcoholic degree by partial least squares (PLS) and artificial neural networks (ANN). In general, non-linear methods provide better results than linear ones.     

The Order of Automorphisms of Quasigroups

We prove quadratic upper bounds on the order of any autotopism of a quasigroup or Latin square, and hence also on the order of any automorphism of a Steiner triple system or 1‐factorization of a complete graph. A corollary is that a permutation σ chosen uniformly at random from the symmetric group will almost surely not be an automorphism of a Steiner triple system of order n, a quasigroup of order n or a 1‐factorization of the complete graph . Nor will σ be one component of an autotopism for any Latin square of order n. For groups of order n it is known that automorphisms must have order less than n, but we show that quasigroups of order n can have automorphisms of order greater than n. The smallest such quasigroup has order 7034. We also show that quasigroups of prime order can possess autotopisms that consist of three permutations with different cycle structures. Our results answer three questions originally posed by D.  Stones.     

Classification of Graeco‐Latin Cubes

A q‐ary code of length n, size M, and minimum distance d is called an code. An code with is said to be maximum distance separable (MDS). Here one‐error‐correcting () MDS codes are classified for small alphabets. In particular, it is shown that there are unique (5, 5³, 3)₅ and (5, 7³, 3)₇ codes and equivalence classes of (5, 8³, 3)₈ codes. The codes are equivalent to certain pairs of mutually orthogonal Latin cubes of order q, called Graeco‐Latin cubes.     

Ni/CeO2-SiO2催化剂的制备、表征及其甲烷部分氧化制合成气性能

以硝酸亚铈（Ce（NO₃）₃·6H₂O）和正硅酸四乙酯（C₈H₂₀O₄Si）为前驱体,采用溶胶-凝胶法合成了系列具有大比表面积的xCeO₂-（1-x）SiO₂（x = 0,0.25,0.50,0.75,1）复合氧化物载体,然后浸渍活性组分Ni制得用于甲烷部分氧化制合成气的Ni催化剂。运用N₂物理吸附-脱附、X射线粉末衍射、扫描电镜、紫外-可见漫反射光谱、氢程序升温还原、氨程序升温脱附和热重等手段对所得催化剂的组织结构、还原性、表面酸性和积炭行为等进行了表征;同时考察了催化剂的组成、焙烧温度和反应时间等对催化剂在甲烷部分氧化制合成气中催化性能的影响。表征结果表明,该系列Ni/CeO₂-SiO₂催化剂具有大比表面积,CeO₂晶粒较小,NiO的分散性好且易被还原,表面酸性弱,不容易积炭。当Ce/Si摩尔比为1：1,活性组分Ni的质量分数为10%,焙烧温度为700℃时,所制备的Ni/CeO₂-SiO₂催化剂表现出较好的稳定性、最高的CH₄转化率（~84%）和对产物CO及H₂的选择性（>87%）。     

基于光谱技术的杨梅汁品种快速鉴别方法的研究

为了实现杨梅汁品种的快速无损鉴别,提出了一种用可见和近红外光谱技术快速鉴别杨梅汁品种的新方法。首先采用偏最小二乘法进行模式特征分析,经过交互验证法判别,确定最佳主成分数为9。完成特征提取后,将这9个主成分作为神经网络的输入变量,建立了三层BP神经网络,实现类别预测的同时也完成了数学建模与优化分析工作。3个品种的杨梅汁样本数均为20,共计60个样本。在神经网络学习中,将其分成训练集样本51个和预测集样本9个。对9个未知样本进行预测,准确率为100％。说明本文提出的基于光谱技术和模式识别的方法具有很好的分类和鉴别能力。     

双层PLS算法及其在近红外光谱分析中的应用

针对近红外光谱数据局部效应显著,变量个数多,且彼此间常存在严重的复共线性,并与样品组分含量呈非线性关系,构建了一种双层非线性偏最小二乘回归 (DNPLSR)算法。它将非线性回归和偏最小二 乘(PLS)相结合,先在外层由PLS从样本数据中提取成分,并实现每对成分间的非线性映射,再在内层实施PLS算法,将外层因变量成分的拟合误差反馈计算转换权向量的增量,进一步修正转换权向量,以使外层所提取的成分对因变量具有更优的解释能力。最后,将该法应用于80个谷物样品的水组分含量与其近红外光谱的定量关系建模,效果良好,显示出很强的学习能力,所建模型的预报性能也优于其他方法。     

基于小波变换的图像融合新算法

针对现有图像融合技术中的尺度系数卷积法存在的边缘细节损失和对比度下降问题,提出了将Canny边缘检测算子等价于提取图像的小波变换模极大值点这一思想引入图像的低频分量融合规则以及用于高频子带融合的局部对比度结合方向方差方法.最后通过仿真试验以及熵值数据证明该算法有效改善了边缘细节的准确度,提高了分辨率,并使局部对比度信息得以保留,从而更加符合人类的视觉特性.     

偏最小二乘法结合傅里叶变换红外漫反射光谱快速测定煤质

发热量、挥发分和灰分等是衡量煤质的质量指标。通常,烟煤的发热量、挥发分和灰分是按行业标准方法[1]分别进行测定的,操作过程繁琐,速度慢,且费用高。随着化学计量学多元校正方法的发展与广泛应用,董庆年采用最小二乘法结合红外光谱成功测定了灰分[2];而应用偏最小二乘法[3](P     

部分水解聚丙烯酰胺弱凝胶交联动力学的流变学分析

用流变学方法对部分水解聚丙烯酰胺(HPAM)苯酚甲醛间苯二酚交联体系的弱凝胶化过程进行了研究,通过对基团转化率和高分子交联转化率的分析,发现凝胶化过程在接近凝胶点时,处于反应动力学的初期,这使得交联点增加的动力学是比较简单的.通过在不同聚合物浓度和交联剂浓度并在地层温度和矿化度条件下线性粘弹性行为的研究,得到了交联体系凝胶化动力学过程的完整数据,发现聚合物浓度与交联剂浓度对凝胶点与凝胶强度的影响比较类似,反映出交联点增加的共同动力学特征.复数粘度在一个诱导期后,是以指数上升的,类似一个一级反应的特征.产生交联的临界聚合物浓度约为250mg L左右.并提出了剪切粘度数学模型,可以描述凝胶化过程中流变性质的变化.