Preparation and characterization of a set of IAEA reference air filters for quality control in air-pollution studies

Several sets of reference air filters were prepared as part of an IAEA evaluation of the performance of laboratories involved in air-pollution studies. Each set comprised three polycarbonate membrane filters, two of which were loaded with urban air particulate matter (APM) obtained in Vienna or Prague, and one unloaded filter. The filters were loaded by filtration of a suspension of the APM materials in water. The homogeneity both of bulk APM materials and of the loaded filters was evaluated and found suitable by determining several elements by instrumental neutron-activation analysis (INAA), proton-induced X-ray emission (PIXE), and micro-X-ray energy-dispersive fluorescence analysis (micro-EDXRF). After evaluation of the homogeneity, INAA, PIXE, EDXRF, atomic absorption spectrometry (AAS), inductively coupled plasma optical emission spectrometry (ICP-OES), and ICP mass spectrometry (ICP-MS) were used to characterize the filter materials and establish "target values" and their associated standard deviations for 15 elements. Problems encountered during the preparation of these unique, simulated air filters and the criteria for setting both the target values and standard deviations are presented.     

Some new methods for preparing 2,3- and 3,4-diaminopyridines

New methods of preparing 2,3-diaminopyridine ( 13 ) from 2-chloro-3-nitropyridine ( 11 ) and 3,4-diaminopy-ridine ( 8 ) from 4-ethoxy-3-nitropyridine hydrochloride ( 5 ) have been explored and evaluated.     

Win X-ray: a new Monte Carlo program that computes X-ray spectra obtained with a scanning electron microscope.

A new Monte Carlo program, Win X-ray, is presented that predicts X-ray spectra measured with an energy dispersive spectrometer (EDS) attached to a scanning electron microscope (SEM) operating between 10 and 40 keV. All the underlying equations of the Monte Carlo simulation model are included. By simulating X-ray spectra, it is possible to establish the optimum conditions to perform a specific analysis as well as establish detection limits or explore possible peak overlaps. Examples of simulations are also presented to demonstrate the utility of this new program. Although this article concentrates on the simulation of spectra obtained from what are considered conventional thick samples routinely explored by conventional microanalysis techniques, its real power will be in future refinements to address the analysis of sample classifications that include rough surfaces, fine structures, thin films, and inclined surfaces because many of these can be best characterized by Monte Carlo methods. The first step, however, is to develop, refine, and validate a viable Monte Carlo program for simulating spectra from conventional samples.