环戊烯催化氧化合成戊二醛及其动力学

对在非水溶剂存在下过氧化氢一步催化氧化环戊烯制备戊二醛过程中的催化体系进行了研究。考察了具有脱水功能的Ｂ２Ｏ３的作用及用量，确立了具有优良催化性能的催化体系ＷＯ３－Ｂ２Ｏ３；实验测定了反应动力学数据，采用非线性回归Ｐｏｗｅｌ共扼法求得了反应动力学方程。在推荐的催化剂体系和工艺条件下，环戊烯转化率６７％，戊二醛收率６３％，选择性９１％。     

聚丙烯交联技术发展现状

交联聚丙烯具有优异的机械性能和热性能。本文就当前聚丙烯的几种交联技术进行了总结与分类,并介绍了各自的反应机理。着重讨论了最常见的几种PP的交联工艺及其特性,包括有机过氧化物交联、硅烷接枝交联、辐射交联等。     

Characteristics of electrical responsive chitosan/polyallylamine interpenetrating polymer network hydrogel

An interpenetrating polymer network (IPN) hydrogel composed of chitosan and polyallylamine exhibited electric‐sensitive behavior. The chitosan/polyallylamine IPN hydrogel was synthesized by radical polymerization using 2,2‐dimethoxy‐2‐phenylacetophenone (DMPAP) and methylene bisacrylicamide (MBAAm) as initiator and crosslinker, respectively. The swelling behavior of the IPN was studied by immersion of the gel samples in aqueous NaCl solutions at various concentrations and pHs. The swelling ratio decreased with increasing concentration and pH of electrolyte solution. The stimuli response of the IPN hydrogel in electric fields was also investigated. When a swollen the IPN was placed between a pair of electrodes, the IPN exhibited bending behavior in response to the applied electric field. The IPN also showed stepwise bending behavior depending on the electric stimulus. In addition, thermal properties of the IPN were investigated by differential scanning calorimetry (DSC) and dielectric analysis (DEA). © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 2290–2295, 2002     

Pb2+ binding by polyaspartyl polymers and their application to Pb2+ removal from glycyrrhizin

Polyaspartate is an excellent Pb²⁺‐binding agent in comparison with some polyaspartamide derivatives with different side chains, in that it possesses a higher Pb²⁺ uptake and a lower Pb²⁺ equilibrium concentration. Equilibrium sorption data for Pb²⁺ on polyaspartate can be well fitted with the Freundlich and Langmuir models. Experimental results show that a crosslinked polyaspartate hydrogel is superior to poly(acrylic acid)‐based resins and polystyrene‐based chelating resins. IR spectra and X‐ray photoelectron spectra reveal that the polyaspartate hydrogel binds Pb²⁺ by both an ion‐exchange mechanism and a chelating mechanism. The polyaspartate hydrogel is also an effective agent for the removal of Pb²⁺ from glycyrrhizin. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 2215–2220, 2005     

Miscibility and morphology in crystalline/amorphous blends of poly(caprolactone)/poly(4-vinylphenol) as studied by DSC, FTIR, and C solid state NMR

The miscibility and morphology of poly(caprolactone) (PCL) and poly (4-vinylphenol) (PVPh) blends were investigated by using differential scanning calorimetry (DSC), Fourier transform infrared (FTIR) spectroscopy and ¹³C solid state nuclear magnetic resonance (NMR) spectroscopy. The DSC results indicate that PCL is miscible with PVPh. FTIR studies reveal that hydrogen bonding exists between the hydroxyl groups of PVPh and the carbonyl groups of PCL. ¹³C cross polarization (CP)/magic angle spinning (MAS)/dipolar decoupling (DD) spectra of the blends show a 1 ppm downfield shifting of ¹³C resonance of PVPh hydroxyl-substituted carbons and PCL carbonyl carbons with increasing PCL content. Both FTIR and NMR give evidence of inter-molecular hydrogen bonding within the blends. The proton spin-lattice relaxation in the laboratory frame, T₁(H), and in the rotating frame, T_1ρ(H), were studied as a function of the blend composition. The T₁(H) results are in good agreement with thermal analysis; i.e. the blends are completely homogeneous on the scale of 50-80 nm. The T_1ρ(H) results indicate that PCL in the blends has both crystalline and amorphous phases. The amorphous PCL phase is miscible with PVPh, but the PCL crystal domain size is probably larger than the spin-diffusion path length within the T_1ρ(H) time-frame, i.e. larger than 2-4 nm. The mobility differences between the crystalline and amorphous phases of PCL are clearly visible from the T_1ρ(H) data.     

Separation of Triacylglycerol Species from Interesterified Oils by High-Performance Liquid Chromatography

Using a 1,3-regioselective lipase as a catalyst, soybean oil and olive oil were interesterified with the short-chain triacylglycerol tributyrin (1,2,3-tributyrylglycerol) to produce mixtures of structured triacylglycerols (SL-TAG). The SL-TAG were purified by column chromatography and analyzed by both normal-phase (silica column; NP_SIL) and reversed-phase [octadecyl silane (ODS) column] high-performance liquid chromatography (HPLC). Individual SL-TAG molecular species were detected by evaporative light-scattering detection, and characterized by mass spectrometry. NP_SIL HPLC successfully separated the newly synthesized SL-TAG into two groups of TAG: one composed of one butyryl group and two long-chain fatty acyl groups (from soybean or olive oil); the second was composed of two butyryl groups and one long-chain fatty acyl group. The SL-TAG species were further analyzed by reversed-phase HPLC which gave a more detailed separation of the TAG species present in the two SL-TAG.     

高温、高压、临氢设备设计分析

以高温、高压、临氢设备在恶劣的操作环境下引起氢损伤、硫化氢应力等腐蚀为引线,详细分析了引起腐蚀的原因,对临氢压力容器在设计选材、加工制造和操作维护等方面进行了较深入的阐述。     

互联网金融平台中高违约风险用户识别算法

在我国金融科技不断创新的背景下,互联网金融平台中通过网络分析技术开展用户风险识别已经成为当前的热点技术发展方向。以某互联网金融平台的用户交易数据为对象,通过分析其中借贷逾期违约的传播行为,提出通过传播特征构建模型算法识别互联网金融平台的高风险用户。在构建基于阈值传播和随机传播的SIS模型和SIR模型基础上,将模型转换为可评价用户风险值的算法,并进一步与实际违约数据进行验证对比。对比结果显示在前5%和10%高风险群体划分条件下,算法具有较高的召回率和良好的结构关联性。     

Synthesis and characterization of new functional poly(urethane‐imide) crosslinked networks

To synthesize new functional poly(urethane‐imide) crosslinked networks, soluble polyimide from 2,2′‐bis(3,4‐dicarboxyphenyl) hexafluoropropane dianhydride, 4,4′‐oxydianiline, and maleic anhydride and polyurethane prepolymer from polycaprolactone diol, tolylene 2,4‐diisocyanate and hydroxyl ethyl acrylate were prepared. Poly(urethane‐imide) thin films were finally prepared by the reaction between maleimide end‐capped soluble polyimide (PI) and acrylate end‐capped polyurethane (PU). The effect of polyurethane content on dielectric constant, residual stress, morphology, thermal property, and mechanical property was studied by FTIR, prism coupler, Thin Film Stress Analyzer (TFSA), XRD, TGA, DMTA, and Nano‐indentation. Dielectric constant of poly(urethane‐imide) thin films (2.39–2.45) was lower than that of pure polyimide (2.46). Especially, poly(urethane‐imide) thin films with 50% of PU showed lower dielectric constant than other poly(urethane‐imide) thin films did. Lower residual stress and slope in cooling curve were achieved in higher PU content. Compared to typical polyurethane, poly(urethane‐imide) thin films exhibited better thermal stability due to the presence of the imide groups. The glass transition temperature, modulus, and hardness decreased with increase in the flexible PU content even though elongation and thermal expansion coefficient increased. Finally, poly(urethane‐imide) thin films with low residual stress and dielectric constant, which are strongly affected by the morphological structure, chain mobility, and modulus, can be suggested to apply for electronic devices by variation of PU. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 113–123, 2006     

Artificial neural network approaches on composition-property relationships of jet fuels based on GC-MS

The relationships of composition-properties of 80 jet fuels concerning chemical compositions and several specification properties including density, flashpoint, freezing point, aniline point and net heat of combustion were studied. The chemical compositions of the jet fuels were determined by GC-MS, and grouped into eight classes of hydrocarbon compounds, including n-paraffins, isoparaffins, monocyclopraffins, dicyclopraffins, alkylbenzens, naphthalenes, tetralins, hydroaromatics. Several quantitative composition-property relationships were developed with three artificial neural network (ANN) approaches, including single-layer feedforward neural network (SLFNN), multiple layer feedforward neural network (MLFNN) and general regressed neural network (GRNN). It was found that SLFNNs are adequate to predict density, freezing point and net heat of combustion, while MLFNNs produce better results as far as the flash point and aniline point prediction are concerned. Comparisons with the multiple linear regression (MLR) correlations reported and the standard ASTM methods showed that ANN approaches of composition-property relationships are significant improvement on MLR correlations, and are comparable to the standard ASTM methods.