Effect of Hydration and Base Contaminants on Sulfuric Acid Diffusion Measurement: A Computational Study

We used quantum chemical formation free energies of hydrated sulfuric acid-containing molecular clusters and a dynamic model to simulate a flow tube measurement, and determined the effective diffusion coefficient of sulfuric acid as a function of relative humidity. This type of measurement was performed by Hanson and Eisele, who presented and applied a fitting method to obtain equilibrium constants K₁ and K₂ for the formation of sulfuric acid mono- and dihydrates, respectively, from the experimentally determined diffusion coefficients. The fit is derived assuming that only H₂SO₄ molecules hydrated by up to two water molecules are present. To study the sensitivity of the results to this assumption, we implemented the same fit to the modeled diffusion coefficient data, computed including also larger H₂SO₄ hydrates with more than two waters. We show that according to quantum chemical equilibrium constants, the larger hydrates are likely to be present in nonnegligible amounts, which affects the effective diffusion coefficient. This results in the fitted value obtained for K₁ being lower and for K₂ being higher than the actual values. The results are further altered if contaminant base molecules, such as amines, capable of binding to H₂SO₄ molecules, are able to enter the system, for example, with the water vapor. The magnitude and direction of the effect of the contaminants depends not only on the contaminant concentration, but also on the H₂SO₄ concentration and on the hygroscopicity of the H₂SO₄–base clusters.

Copyright 2014 American Association for Aerosol Research     

A comparison of the capsules around smooth and textured silicone prostheses used for breast reconstruction. A light and electron microscopic study

A reversed-phase liquid chromatographic method for the separation of 26 phenylthiocarbamyl derivatives of amino acids in human plasma in ca. 35 min. is described. The method used a C18 column (150 x 4.6 mm I.D., 3 micron) thermostatted at 41 degrees C, and a simple multistep linear gradient of two solvents. Solvent A was 0.05 M sodium acetate (pH 5.1)-acetonitrile (98:2, v/v), and solvent B was water-acetonitrile (40:60, v/v). A simple and successful approach to the optimization of the conditions for the separation of the 26 amino acid derivatives was realized. In the initial phase of development, the composition of the gradient, its timings, the column temperature, the flow-rate and the mobile phase compositions were optimized. At the end the influence of pH was studied, and this approach led to a clear resolution of the 26 amino acids. The method was validated by accuracy, precision, and recovery studies, by analyzing patient samples, and by comparing the quality control sample results with the classical ion-exchange method.     

Molecular-resolution simulations of new particle formation: Evaluation of common assumptions made in describing nucleation in aerosol dynamics models

Aerosol dynamics models that describe the evolution of a particle distribution incorporate nucleation as a particle formation rate at a small size around a few nanometers in diameter. This rate is commonly obtained from molecular models that cover the distribution below the given formation size – although in reality the distribution of nanometer-sized particles cannot be unambiguously divided into separate sections of particle formation and growth. When incorporating nucleation, the distribution below the formation size is omitted, and the formation rate is assumed to be in a steady state. In addition, to reduce the modeled size range, the formation rate is often scaled to a larger size based on estimated growth and scavenging rates and the assumption that also the larger size is in a steady state. This work evaluates these assumptions by simulating sub-10 nm particle distributions in typical atmospheric conditions with an explicit molecular-resolution model. Particle formation is included either (1) dynamically, that is, the whole size range starting from single vapor molecules is modeled explicitly or (2) implicitly by using an input formation rate as is done in aerosol models. The results suggest that while each assumption can affect the outcome of new particle formation modeling, the most significant source of uncertainty affecting the formation rates and resulting nanoparticle concentrations is the steady-state assumption, which may lead to an overprediction of the concentrations by factors of approximately from two to even orders of magnitude. This can have implications for modeling and predicting atmospheric particle formation.

Copyright © 2017 American Association for Aerosol Research