基于XPS对硫铁矿去除SeO2-3的机理研究

硒是动植物及人体生长必需的十五种微量元素之一，具有清除体内自由基、抗氧化、增强免疫力等功能，但其安全剂量的范围却很窄。利用扫描电子显微镜（SEM）和X射线衍射仪（XRD）对湿法球磨制备的硫铁矿形貌进行了表征。SEM观测发现加乙醇助磨后的硫铁矿为粒径大小较均匀的球形颗粒团聚体，粒径范围在17～200 nm之间，平均粒径138 nm。XRD衍射图谱中的特征峰与FeS₂衍射图谱中各峰位置基本一致，因此判定硫铁矿中主要化学组分为FeS₂，且图谱中基本没有杂峰，表明制备过程中并未混入杂质，样品纯度较高。实验结果表明，该法制备的硫铁矿具有颗粒粒径小、比表面积大、反应活性高等优点。研究中利用X射线光电子能谱仪（XPS）对硫铁矿去除水体中SeO2-₃的机理进行了研究。研究结果表明, （1）在较为广泛的实验pH范围（pH 2.2～11.5），硫铁矿均能有效去除水体中SeO2-₃，去除效率（除pH值7.8以外）均达到90%以上；（2）硫铁矿与SeO2-₃发生反应后，其主要组成元素的XPS特征峰结合能有所减小，表明硫铁矿表面发生了一定化学变化；（3）酸碱环境下硫铁矿去除SeO2-₃的机理不完全相同，酸性环境下，硫铁矿对SeO2-₃的去除是单纯的氧化还原过程，即硫铁矿中被酸活化的S2-₂将SeO2-₃还原为单质Se(0)，并且酸性越强，SeO2-₃去除效果越好；碱性环境下，SeO2-₃的去除过程中氧化还原与络合反应并存，硫铁矿表面有络合态Fe(OH)SeO₃和单质Se(0)两种存在形态，且碱性越强，络合态Fe(OH)SeO₃含量越高。以上研究结果为硫铁矿去除固定水体和土壤中以SeO2-₃为代表的可变价金属阴离子提供重要理论依据和应用基础。     

Chiral Interlocked Corrole Dimers Directly Linked at Inner Carbon Atoms of Confused Pyrrole Rings

A facile synthetic strategy towards conformationally stable chiral chromophores based on dimeric porphyrinoids has been established. A peculiar class of face-to-face intramolecularly interlocked corrole dimers were formed by the oxidative C−C coupling linked at the inner carbon sites upon simple treatment of copper(II) ions. Their intrinsic electronic structures were modulated by the peripheral corrole ring annulations, which lead to distinct optical properties and redox profiles. The stereogenic carbon centers implemented in the confused corrole skeleton provided a rationale for designing novel chiral materials.     

Spontaneous magnetization of the Ising model on a 4–8 lattice

The spontaneous magnetization of the Ising model on a 4–8 lattice with six different coupling constants and two different magnetic moments is studied. A formula for the spontaneous magnetization is proposed. The result agrees with the exact low-temperature series expansions up to the 12th order.     

镧系金属一氢化物有效芯势研究

采用Cundari和Stevens等推导的有效芯势对镧系金属一氢化物进行了理论计算，以探讨镧系金属元素与氢的相互作用。结果表明所有镧系金属一氢化物基态时理论上是稳定的，最稳定的是SmH,最不稳定的是DyH;键长计算结果显示，基态时镧系金属一招兵买马花物有独立王国 收缩现象发生；红外振动频率理论计算值与实验结果一致；成键轨道中，金属原子轨道的贡献主要是s轨道和d轨道：从CeH至ErH(GdH)例外）随着外层电子的增加s轨道成分逐渐增大d轨道成分逐渐减小；从TmH和LuH（包括GdH)，成键轨道中金属原子轨道的贡献主要是d轨道，约为90％；约大多数镧系金属一氧化物的成键轨道中金属原子轨道f成分小于1％。     

Stability Properties of Feynman's Operational Calculus for Exponential Functions of Noncommuting Operators

Stability properties of Feynman's operational calculus are addressed in the setting of exponential functions of noncommuting operators. Applications of some of the stability results are presented. In particular, the time-dependent perturbation theory of nonrelativistic quantum mechanics is presented in the setting of the operational calculus and application of the stability results of this paper to the perturbation theory are discussed.     

High-temperature expansions to fifteenth order

High-temperature series expansions of the susceptibility and second moment to 15th order are calculated for zero external field on the linear chain (LC), plane square (PSQ), simple cubic (SC), and body-centered cubic (BCC) lattices. Checks for specific models against pertinent work in the literature are detailed.     

夫琅禾费衍射公式的一般形式

从不同的途径导出了大角度情形下亦成立的夫琅禾费衍射积分的一般形式，指出此一般形式公式是求解夫琅禾费衍射的基本公式．并通过对夫琅禾费衍射公式的级数形式的推导，揭示了傅里叶光学中“夫琅禾费衍射公式”与一般形式公式存在的差别，以及消除这种差别的措施．此外，还较详细地讨论了倾斜因子对衍射花样的影响．这对于衍射测量及深入理解夫琅禾费衍射的本质有一定的指导意义．     

级数小于1的亚纯函数的Borel例外值

证明了当超越亚纯函数的级小于1时，其Norel例外值最多只有一个．由于存在任何级的整函数，因此一个例外值总可达到，故所得结果不能再改进。     

Time Series Prediction Based on Chaotic Attractor

A new prediction technique is proposed for chaotic time series. The usefulness of the technique is thatit can kick off some false neighbor points which are not suitable for the local estimation of the dynamics systems. Atime-delayed embedding is used to reconstruct the underlying attractor, and the prediction model is based on the timeevolution of the topological neighboring in the phase space. We use a feedforward neural network to approximate thelocal dominant Lyapunov exponent, and choose the spatial neighbors by the Lyapunov exponent. The model is testedfor the Mackey-Glass equation and the convection amplitude of lorenz systems. The results indicate that this predictiontechnique can improve the prediction of chaotic time series.