Bubble-Point Measurements of <i>n</i>‑Butane + <i>n</i>‑Octane and <i>n</i>‑Butane + <i>n-</i>Nonane Binary Mixtures

Mixtures of small gaseous hydrocarbons with longer chain hydrocarbons are of interest to the natural gas industry as well as other industries in which separations are critical. In particular, binary mixtures of <i>n-</i>nonane are of interest, because <i>n-</i>nonane was recently incorporated into the GERG-2008 equation of state, but there is little experimental vapor–liquid equilibrium (VLE) data available to support the equation. The bubble-point pressures of four compositions of each of the binary mixtures <i>n</i>-butane + <i>n</i>-octane and <i>n</i>-butane + <i>n-</i>nonane were measured over the temperature range of 270 to 370 K. The data and the expanded uncertainty (at a 95 % confidence level, <i>k</i> = 2) of each point are reported. Additionally, the data are compared to existing literature data for the <i>n-</i>butane + <i>n</i>-octane and the GERG-2008 equation for both systems. This is the first report of vapor–liquid equilibrium measurements on <i>n</i>-butane + <i>n-</i>nonane binary mixtures

Bubble-Point Measurements of <i>n</i>‑Propane + <i>n</i>‑Decane Binary Mixtures with Comparisons of Binary Mixture Interaction Parameters for Linear Alkanes

To develop comprehensive models for multicomponent natural gas mixtures, it is necessary to have binary interaction parameters for each of the pairs of constituent fluids that form the mixture. The determination of accurate mixture interaction parameters depends on reliably collected experimental data. In this work, we have carried out an experimental campaign to measure the bubble-point pressures of mixtures of <i>n</i>-propane and <i>n</i>-decane, a mixture that has been thus far poorly studied with only four existing data sets. The experimental measurements of bubble-point states span a composition range (in <i>n</i>-propane mole fraction) from 0.148 to 0.731, and the bubble-point pressures are measured in the temperature range from 270 to 370 K. These data, in conjunction with data from a previous publication on mixtures of <i>n</i>-butane + <i>n</i>-octane and <i>n</i>-butane + <i>n</i>-nonane, are used to determine binary interaction parameters. The newly obtained binary interaction parameters for the mixture of <i>n</i>-propane and <i>n</i>-decane represent the experimental bubble-point pressures given here to within 8% (coverage factor, <i>k</i> = 2), as opposed to previous deviations up to 19%

Quantification of Carbon Nanotubes in Environmental Matrices: Current Capabilities, Case Studies, and Future Prospects

Carbon nanotubes (CNTs) have numerous exciting potential applications and some that have reached commercialization. As such, quantitative measurements of CNTs in key environmental matrices (water, soil, sediment, and biological tissues) are needed to address concerns about their potential environmental and human health risks and to inform application development. However, standard methods for CNT quantification are not yet available. We systematically and critically review each component of the current methods for CNT quantification including CNT extraction approaches, potential biases, limits of detection, and potential for standardization. This review reveals that many of the techniques with the lowest detection limits require uncommon equipment or expertise, and thus, they are not frequently accessible. Additionally, changes to the CNTs (e.g., agglomeration) after environmental release and matrix effects can cause biases for many of the techniques, and biasing factors vary among the techniques. Five case studies are provided to illustrate how to use this information to inform responses to real-world scenarios such as monitoring potential CNT discharge into a river or ecotoxicity testing by a testing laboratory. Overall, substantial progress has been made in improving CNT quantification during the past ten years, but additional work is needed for standardization, development of extraction techniques from complex matrices, and multimethod comparisons of standard samples to reveal the comparability of techniques