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Increased applications of fluorochemicals have prompted development of elemental methods for detection and quantitation of these compounds. However, high-sensitivity detection of fluorine is a challenge because of difficulties in excitation and ionization of this element. Recently, a new approach has emerged to detect F as a diatomic ion (BaF+) in inductively coupled plasma mass spectrometry (ICP-MS). However, formation of this species in the high-temperature plasma is inefficient, leading to low sensitivities. Here, we introduce a post-ICP chemical ionization approach to enhance analytical performance for F detection in liquid samples. Solutions of fluorochemicals are introduced into an ICP leading to formation of HF in the afterglow. Subsequently, reagent ions from nanospray of sodium acetate and barium acetate electrolytes are utilized to ionize HF to Na2F+ and BaF+, respectively, via post-plasma ion-neutral reactions. Both ions provide substantially better sensitivities compared to that of BaF+ formed inside the plasma in conventional ICP-MS methods. Notably, post-plasma BaF+ offers a sensitivity of 280 cps ppb−1 for F, near two orders of magnitude higher than that of conventional ICP-MS methods. Compound-independent response for F from structurally diverse organofluorines is confirmed by monitoring BaF+ and a limit of detection (LOD) of 8–11 ng mL−1 F is achieved. Importantly, isobaric interferences are substantially reduced in chemical ionization, leaving F background as the main factor in LOD determination. Insights into BaF+ formation via experimental and computational investigations suggest that BaNO2+ and Ba(H2O)n2+ serve as reagent ions while nonreactive BaCH3CO2+ is the dominant ion produced by nanospray. The facile development of effective post-plasma ionization chemistries using the presented approach offers a path for further improvements in F elemental analysis. [ABSTRACT FROM AUTHOR]

Elemental analysis of chlorine using inductively coupled plasma mass spectrometry (ICP-MS) is challenging because of poor ion formation efficiency of Cl+ in the argon plasma, and prevalence of isobaric interferences. To improve Cl detection, we have recently developed plasma assisted reaction chemical ionization (PARCI) in which an Ar-ICP is coupled to an atmospheric-pressure afterglow reaction tube, leading to high-sensitivity detection of Cl−. We have shown that introduction of sodium and methanol into the ICP improves Cl− sensitivity in PARCI-MS to levels better than those of conventional ICP-MS/MS. In this report, we probe the chloride ion formation mechanism in the ICP afterglow via examining the impact of the aerosol gas flow rate and torch box exhaust flow rate on Cl− detection. Specifically, we evaluate analyte breakdown in the ICP, sampling of plasma products into the afterglow reaction tube, and ion–neutral reactions in the atmospheric-pressure afterglow as major processes for chloride ion formation in PARCI. We find that aerosol carrier gas flow rates ≤ 2.2 L min−1 result in compound-independent response factors for Cl, indicating sufficient residence time in the plasma for efficient breakdown of analytes. Notably, we show that torch box exhaust flow rate has a drastic impact on Cl− sensitivity. This effect stems from its influence on plasma sampling efficiency and on ion–neutral reactions in the afterglow. Lastly, our results indicate that clusters formed in the afterglow reaction tube play critical roles in Cl− detection. Specifically, [NaClHCO2]− and [NaClNO2]− are identified as key species for Cl− detection from chlorinated compounds introduced into the ICP in conjunction with methanol and sodium. Ab initio calculations indicate thermodynamically favorable reactions for formation of these cluster ions, supporting the importance of cluster formation in the ICP afterglow for high-sensitivity chloride ion detection. [ABSTRACT FROM AUTHOR]

We report development of an atmospheric pressure plasma assisted reaction chemical ionization (PARCI) source with liquid sample introduction, enabling high sensitivity detection of chlorine in LC-separated compounds. In this novel approach, analytes are introduced into an argon inductively coupled plasma for high-temperature reactions including atomization. The plasma reaction products are then guided into an atmospheric pressure reaction tube where formation of negative ions is enhanced at lower temperatures. Cl− ions emerging from the reaction tube are then detected by an atmospheric sampling single quadrupole mass spectrometer without any modifications. We demonstrate that Cl− ions are generated in PARCI with similar efficiencies between inorganic and organic chlorine-containing compounds, confirming the elemental nature of the ionization for quantitative measurements. We further demonstrate that the ionization reactions within the reaction tube can be controlled by addition of ionization reagents to the plasma. Specifically, we find that addition of low ionization potential elements such as sodium in conjunction with methanol leads to significant enhancements in sensitivity. Chlorine sensitivity and detection limits using LC-PARCI-MS compare favorably with those obtained using state-of-the-art LC-ICP-MS/MS. Operation of PARCI in negative mode alleviates the isobaric interferences for chlorine detection and obviates the need for complex mass analyzers. Notably, the simplicity of PARCI and compatibility with atmospheric sampling mass spectrometers make this approach readily adoptable for integration of elemental quantification with molecular characterization using other ion sources. [ABSTRACT FROM AUTHOR]

Rietveld refinement of X-ray and neutron diffraction patterns is routinely used to solve crystal and magnetic structures of organic and inorganic materials over many length scales. Despite its success over the past few decades, conventional Rietveld analysis suffers from tedious iterative methodologies, and the unfortunate consequence of many least-squares algorithms discovering local minima that are not the most accurate solutions. Bayesian methods which allow the explicit encoding of a priori knowledge pose an attractive alternative to this approach by enhancing the ability to determine the correlations between parameters and to provide a more robust method for model selection. Global approaches also avoid the divergences and local minima often encountered by practitioners of the traditional Rietveld technique. The goal of this work is to demonstrate the effectiveness of an automated Bayesian algorithm for Rietveld refinement of neutron diffraction patterns in the solution of crystallographic and magnetic structures. A new software package, BLAND (Bayesian library for analyzing neutron diffraction data), based on the Markov-Chain Monte Carlo minimization routine, is presented. The benefits of such an approach are demonstrated through several examples and compared with traditional refinement techniques. [ABSTRACT FROM AUTHOR]