气相分子吸收光谱法测定水中硝酸盐氮

硝酸盐氮是水环境质量重点监测项目之一,建立节省人力、高效快捷、抗干扰能力强的测试水中硝酸盐氮的分析方法十分必要。本文从载气类型、载气流量、定量方式、加热温度、载流液配比等方面系统的优化气相分子吸收光谱法测定水中硝酸盐氮的仪器条件。在优化的仪器条件下,工作曲线相关系数为0.9995;检出限为0.006 mg/L,测定下限为0.024 mg/L;标准物质测定的相对误差范围在0.0%~0.6%,实际样品测定的相对标准偏差范围在0.5%~5.5%;实际样品加标回收率范围在89.0%~102%。方法的检出限、精密度和准确度良好,适用于水质硝酸盐氮的测定。     

Plasmonic properties of graphene on uniaxially anisotropic substrates

Most of the current graphene plasmonic researches are based on the substrates with isotropic dielectric constant such as silicon.In this work,we investigate optical properties of graphene nanoribbon arrays placed on a uniaxially anisotropic substrate,where the anisotropy provides an additional freedom to tune the behaviors of graphene plasmons,and its effect can be described by a simple effective formula.In practice,the substrates of semi-infinite and finite thickness are discussed by using both the formula and full wave simulations.Particularly,the dielectric constants ε|| and ε⊥ approaching zero are intensively studied,which show different impacts on the transverse magnetic(TM) surface modes.In reality,the hexagonal boron nitride(hBN) can be chosen as the anisotropic substrate,which is also a hyperbolic material in nature.     

基于径向基函数神经网络的磨粒识别系统

应用磨粒形状特征参数、颜色特征参数和表面纹理特征参数对磨粒形态进行量化表征，并以此为输入矢量，引入径向基函数神经网络对磨损微粒进行自动分类识别，建立了适用于磨粒识别的径向基函数神经网络模型，并给出了具体算法．应用实例表明，径向基函数神经网络的收敛速度和识别率优于传统的BP神经网络．