Simple and Precise Quantification of Iron Catalyst Content in Carbon Nanotubes Using UV/Visible Spectroscopy

Iron catalysts have been used widely for the mass production of carbon nanotubes (CNTs) with high yield. In this study, UV/visible spectroscopy was used to determine the Fe catalyst content in CNTs using a colorimetric technique. Fe ions in solution form red–orange complexes with 1,10-phenanthroline, producing an absorption peak at λ=510 nm, the intensity of which is proportional to the solution Fe concentration. A series of standard Fe solutions were formulated to establish the relationship between optical absorbance and Fe concentration. Many Fe catalysts were microscopically observed to be encased by graphitic layers, thus preventing their extraction. Fe catalyst dissolution from CNTs was investigated with various single and mixed acids, and Fe concentration was found to be highest with CNTs being held at reflux in HClO₄/HNO₃ and H₂SO₄/HNO₃ mixtures. This novel colorimetric method to measure Fe concentrations by UV/Vis spectroscopy was validated by inductively coupled plasma optical emission spectroscopy, indicating its reliability and applicability to asses Fe content in CNTs.     

<Emphasis Type="Italic">FCC/BCC</Emphasis> competition and enhancement of saturation magnetization in nanocrystalline Co-Ni-Fe films

The structure, chemical composition, and magnetic properties of electrochemically deposited nanocrystalline Co-Ni-Fe films were investigated using a number of techniques. A high saturation magnetic induction up to B _s = 21 kG was attained. An enhancement of the saturation magnetization compared to the ideal anticipated one was revealed, which correlated with the nonlinear behavior of the structural phase composition and lattice parameters with the change of the composition. The text was submitted by the authors in English.     

Forecasting call frequency at a financial services call centre

A forecasting model is developed for the number of daily applications for loans at a financial services telephone call centre. The purpose of the forecasts and the associated prediction intervals is to provide effective staffing policies within the call centre. The model building process is constrained by the availability of only 2 years and 7 months of data. The distinctive feature of the data is that demand is driven in the main by advertising. The analysis given focuses on applications stimulated by press advertising. Unlike previous analyses of broadly similar data, where ARIMA models were used, a model with a dynamic level, multiplicative calendar effects and a multiplicative advertising response is developed and shown to be effective.     

Quadratic data envelopment analysis

Data Envelopment Analysis (DEA) offers a piece-wise linear approximation of the production frontier. The approximation tends to be poor if the true frontier is not concave, eg in case of economies of scale or of specialisation. To improve the flexibility of the DEA frontier and to gain in empirical fit, we propose to extend DEA towards a more general piece-wise quadratic approximation, called Quadratic Data Envelopment Analysis (QDEA). We show that QDEA gives statistically consistent estimates for all production frontiers with bounded Hessian eigenvalues. Our Monte-Carlo simulations suggest that QDEA can substantially improve efficiency estimation in finite samples relative to standard DEA models.