Synthesis of polyacrylonitrile via reverse atom transfer radical polymerization catalyzed by FeCl3/isophthalic acid

FeCl₃ coordinated by isophthalic acid was first used as a catalyst in the azobisisobutyronitrile‐initiated reverse atom transfer radical polymerization of acrylonitrile. N,N‐Dimethylformamide was used as a solvent to improve the solubility of the ligand. An FeCl₃‐to‐isophthalic acid ratio of 0.5 not only gave the best control of the molecular weight and its distribution but also provided rather a rapid reaction rate. The effects of different solvents on the polymerization of acrylonitrile were also investigated. The rate of the polymerization in N,N‐dimethylformamide was faster than that in propylene carbonate and toluene. The molecular weight of polyacrylonitrile agreed reasonably well with the theoretical molecular weight in N,N‐dimethylformamide. The rate of polymerization increased with increasing polymerization temperature, and the apparent activation energy was calculated to be 59.9 kJ mol^?1. Reverse atom transfer radical polymerization was first used to successfully synthesize acrylonitrile polymers with a molecular weight higher than 80,000 and a narrow polydispersity as low as 1.22. © 2005 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 219–225, 2006     

Mathematical modeling of crystallization analysis fractionation (Crystaf) of polyethylene

Four polyethylene samples (PE) with different molecular weight distributions (MWD) were analyzed by crystallization analysis fractionation (Crystaf) at several cooling rates to investigate the effect of MWD and cooling rate on their Crystaf profiles. Using these results, we developed a mathematical model for Crystaf that considers crystallization kinetic effects, which are ignored in all previous Crystaf models. The Crystaf model we proposed can fit the experimental Crystaf profiles of the 4 polyethylene resins very well. © 2006 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 44: 2749–2759, 2006     

Synthesis of Surface-Modified Nanoparticles via Cycloaddition-Reactions

Summary. The surface modification of nanoparticles via azide/alkine-1,3-dipolar cycloaddition-reactions is described. Ligand exchange onto various nanoparticles was monitored by ¹H NMR spectroscopy and formed the basis for the attachment of ligands onto the nanoparticles and their subsequent modification by dipolar cycloaddition reactions. Nanoparticle-surfaces were monitored by binding onto self-assembled monolayers derivatized with matching supramolecular interactions after derivatization.     

加权增量卡尔曼滤波法在ICP－AES中的应用

卡尔曼滤波法用于ＩＣＰ－ＡＥＳ分析时，在白色噪音情况下能给出准确的分析结果，当试样的某些组分未知时，测量噪音将不是白色的，分析结果将不准确。本文提出了一种加权增量卡尔曼滤波法来解决这个问题。     

Identification of chlorinated sulfur compounds in pulp mill effluents by GC-MS and GC-AED

Summary Three chlorinated dimethyl sulfones and five chlorinated thiophenes have been identified in the alkaline extraction liquor from a bleach plant by gas chromatography with atomic emission detection (GC-AED) and with mass spectrometry (GC-MS). The information on elemental content obtained by GC-AED enabled a rapid screening of the sulfur compounds and provided important structural information complementary to the mass spectral data. Quantitation was accomplished by GC-AED based on universal calibration.     

高纯氧化钆中14种稀土杂质元素的柱色谱分离ICP-AES法测定

用Ｐ５０７萃淋树脂柱色谱法分离高纯氧化钆基体与稀土杂质。用ＩＣＰ－ＡＥＳ法测定高纯氧化钆中微量稀土杂质。选择了柱色谱分离的合适条件。优化了仪器测定参数。使本方法测定稀土总量下限小于１×１０－５％。可以满足９９．９９９９％高纯氧化钆的测定。此方法回收率在８５％－１１０％之间。相对标准偏差小于１８％。     

原子吸收光谱法测定铬基合金中钒

本文研究了用原子吸收光谱法，在笑气－乙炔火焰中，测定钒的最佳条件，不用任何分离手段，以铝盐做干扰抑制剂，消除铬，镍对测定钒的干扰，西方法用于铬基合金中钒的测定，方法简单准确，具有实用意义。     

A minimum average risk approach to shrinkage estimators of the normal mean

For the problem of estimating the normal mean based on a random sample X ₁,...,X _n when a prior value ₀ is available, a class of shrinkage estimators % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqdbaGafqiVd0MbaKaaaaGccaqGGaGaaiikaiaa% dUgacaGGPaGaeyypa0Jaam4AaiaacIcadaqfqaqabKqaahaacaqGUb% aaleqaneaacaqGubaaaOGaaiykaiaabccadaqfqaqabKqaahaacaWG% UbaaleqaneaaceqGybGbaebaaaGccaqGGaGaey4kaSIaaeiiaiaacI% cacaaIXaGaaeiiaiabgkHiTiaabccacaWGRbGaaiikamaavababeqc% baCaaiaab6gaaSqab0qaaiaabsfaaaGccaGGPaGaaiykamaavababe% qcbaCaaiaad6gaaSqab0qaaiabeY7aTbaaaaa!5615!\[\mathop {\hat \mu }\nolimits_n {\rm{ }}(k) = k(\mathop {\rm{T}}\nolimits_{\rm{n}} ){\rm{ }}\mathop {{\rm{\bar X}}}\nolimits_n {\rm{ }} + {\rm{ }}(1{\rm{ }} - {\rm{ }}k(\mathop {\rm{T}}\nolimits_{\rm{n}} ))\mathop \mu \nolimits_n \] is considered, where % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqcdawaaiaadsfaaaGccaqGGaGaaeypaiaabcca% caWGUbWaaWbaaSqabeaacaaIXaGaai4laiaaikdaaaGccaGGOaWaa0% aaaeaacaWGybaaamaaBaaajeaWbaGaamOBaaWcbeaakiaabccacqGH% sislcaqGGaWaaubeaeqajeaWbaGaaGimaaWcbeqdbaGaaeiVdaaaki% aacMcacaqGGaGaae4laiabeccaGiabeo8aZbaa!4C33!\[\mathop T\nolimits_n {\rm{ = }}n^{1/2} (\overline X _n {\rm{ }} - {\rm{ }}\mathop {\rm{\mu }}\nolimits_0 ){\rm{ /}} \sigma \] and k is a weight function. For certain choices of k, % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqdbaGafqiVd0MbaKaaaaGccaqGGaGaaiikaiaa% dUgacaGGPaaaaa!3CEE!\[\mathop {\hat \mu }\nolimits_n {\rm{ }}(k)\] coincides with previously studied preliminary test and shrinkage estimators. We consider choosing k from a natural non-parametric family of weight functions so as to minimize average risk relative to a specified prior p. We study how, by varying p, the MSE efficiency (relative to \-X) properties of % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqdbaGafqiVd0MbaKaaaaGccaqGGaGaaiikaiaa% dUgacaGGPaaaaa!3CEE!\[\mathop {\hat \mu }\nolimits_n {\rm{ }}(k)\] can be controlled. In the process, a certain robustness property of the usual family of posterior mean estimators, corresponding to the conjugate normal priors, is observed.     

电感耦合等离子体原子发射光谱分析中不同电离电位元素基体效应的比较研究

选择不同电离电位的基体元素K、Na、La、Y和Mg,比较研究了它们对分析元素谱线强度的影响,其影响程度与谱线激发电位及基体元素电离电位有定量的相关关系。碱金属基体(K、Na)和非碱金属基体(La、Y和Mg)对分析元素检出限、背景强度及其相对标准偏差的影响显著不同,后者的记忆效应也大于前者。La的电离电位与Na相差不大。但其基体效应与Y相似,表明墓体效应与基体元素的化学性质有关。     

α—甲基苯乙烯离子聚合体分子量分布

聚α-甲基苯乙烯-丁二烯-α-甲基苯乙烯嵌段共聚物是一种性能优异的热塑性弹性体。常温下,α-甲基苯乙烯的聚合是在极性添加剂存在下进行的,添加剂的种类,用量及聚合温度不仅影响聚合动力学,尚且影响聚合物分子量及其分布,控制α-甲基苯乙烯聚合速率、