High-rate removal of As(Ⅲ) from aqueous system with sulfhydryl magnetic biological bamboo charcoal nanocomposites prepared by chemical co-precipitation method

Sulfhydryl magnetic biological bamboo charcoal nanocomposite(BBC@nFe-SH)was prepared by chemical co-precipitation method for the robust capture of As(Ⅲ)from aqueous solutions.The novel BBC@nFe-SH shows favorable magnetic field strength(83376 A/m),which enables BBC@nFe-SH to be quickly recovered from aqueous solution.The maximum As(Ⅲ)adsorption capacity is as high as 98.63 mg/g at pH 5.0 and 40°C,reaching reaction equilibrium within 120 min.Various characterizations(e.g.,SEM,FTIR,VSM and XPS)suggest that As(Ⅲ)prefers to coordinate with surface oxygen groups bonded to the surface.BBC@nFe-SH displayed high stability and recyclability throughout the removal process,which could be easily activated by 1 mol/L NaOH after usage.Thus,the novel BBC@nFe-SH has promising applications for As(Ⅲ)treatment.

基于可见/近红外光谱技术的板栗产地识别

采用可见/近红外光谱分析技术对河北和安徽两个产地的板栗进行检测分级,获得板栗样品在600~1100 nm波长区间的可见/近红外光谱,采用偏最小二乘判别分析(PLSDA)进行建模,比较不同预处理方法和波长范围对PLSDA模型精度的影响。结果显示,不同预处理方法对模型性能影响较大,一阶导数预处理在全波长范围所建PLSDA模型性能最优,校正集和验证集的决定系数分别为0.884和0.863,均方根误差分别为0.170和0.191。不同波长范围也会影响模型的预测和识别性能,在波长区间为750~1000 nm的光谱所建立的PLSDA模型性能要高于全波长光谱所建立的模型性能,其中经过Savitzky-Golay平滑预处理后,模型性能的提高最为明显,且其与原始光谱在校正集和验证集的敏感性和特异性均达到最优,即识别率均可达到100%。因此,可见/近红外光谱分析技术能够对板栗产地进行鉴别。