Characterization of a high throughput approach for large scale retention measurement in liquid chromatography

Many contemporary challenges in liquid chromatography—such as the need for “smarter” method development tools, and deeper understanding of chromatographic phenomena—could be addressed more efficiently and effectively with larger volumes of experimental retention data than are available. The paucity of publicly accessible, high-quality measurements needed for the development of retention models and simulation tools has largely been due to the high cost in time and resources associated with traditional retention measurement approaches. Recently we described an approach to improve the throughput of such measurements by using very short columns (typically 5 mm), while maintaining measurement accuracy. In this paper we present a perspective on the characteristics of a dataset containing about 13,000 retention measurements obtained using this approach, and describe a different sample introduction method that is better suited to this application than the approach we used in prior work. The dataset comprises results for 35 different small molecules, nine different stationary phases, and several mobile phase compositions for each analyte/phase combination. During the acquisition of these data, we have interspersed repeated measurements of a small number of compounds for quality control purposes. The data from these measurements not only enable detection of outliers but also assessment of the repeatability and reproducibility of retention measurements over time. For retention factors greater than 1, the mean relative standard deviation (RSD) of replicate (typically n=5) measurements is 0.4%, and the standard deviation of RSDs is 0.4%. Most differences between selectivity values measured six months apart for 15 non-ionogenic compounds were in the range of +/- 1%, indicating good reproducibility. A critically important observation from these analyses is that selectivity defined as retention of a given analyte relative to the retention of a reference compound (kx/kref) is a much more consistent measure of retention over a time span of months compared to the retention factor alone. While this work and dataset also highlight the importance of stationary phase stability over time for achieving reliable retention measurements, we are nevertheless optimistic that this approach will enable the compilation of large databases (>> 10,000 measurements) of retention values over long time periods (years), which can in turn be leveraged to address some of the most important contemporary challenges in liquid chromatography. All the data discussed in the manuscript are provided as Supplemental Information

Grape berry size is a key factor in determining New Zealand Pinot noir wine composition

Making high quality but affordable Pinot noir (PN) wine is challenging in most terroirs and New Zealand (NZ)’s situation is no exception. To increase the probability of making highly typical PN wines, producers choose to grow grapes in cool climates on lower fertility soils while adopting labour intensive practices. Stringent yield targets and higher input costs necessarily mean that PN wine cost is high, and profitability lower, in affordable varietal wine ranges. To understand if higher-yielding vines produce wines of lower quality we have undertaken an extensive study of PN in NZ. Since 2018, we established a network of twelve trial sites in three NZ regions to find individual vines that produced acceptable commercial yields (above 2.0 kg per metre of row) and wines of composition comparable to “Icon” labels. Approximately 20 % of 660 grape lots (N = 135) were selected within a narrow juice Total Soluble Solids (TSS) range of 22.0 ± 1.0 °Brix and made into single-vine wines under controlled conditions. Multiple Factor Analysis of the vine, berry, juice and wine parameters from three vintages found grape Berry Weight to be the most effective clustering variable. As the Berry Weight category decreased, there was a systematic increase in the probability of higher berry red colour and total phenolics with a parallel increase in wine phenolics and decreased juice amino acids. The influence of berry weight on wine composition would appear stronger than the individual effects of Vintage, Region, Vineyard or vine Yield. Our observations support the hypothesis that it is possible to produce PN wines that fall within an “Icon” benchmark composition range at yields above 2.5 kg per vine, provided that the Leaf Area:Fruit Weight ratio is above 11 cm² per g, mean berry weight is below 1.2 g and juice TSS is above 22 °Brix

An asymptotic treatment of the Elenbaas–Heller equation for a radiating wall‐stabilized high‐pressure gas‐discharge arc

An asymptotic analysis of the Elenbaas–Heller equation for a radiating wall-stabilized high-pressure gas-discharge arc is given. This analysis applies when the operating temperatures within the arc are lower than the ionization temperature by an order of magnitude. It is shown that for arcs that are radiating highly efficiently a further asymptotic treatment can be given. It is shown under what conditions, governed by a dimensionless parameter M, this limiting case prevails. Comparison with earlier results put forward by Zollweg [J. Appl. Phys. 49, 1077 (1978)] shows satisfactory agreement

Computation of Solar Radiative Fluxes by 1D and 3D Methods Using Cloudy Atmospheres Inferred from A-train Satellite Data

The main point of this study was to use realistic representations of cloudy atmospheres to assess errors in solar flux estimates associated with 1D radiative transfer models. A scene construction algorithm, developed for the EarthCARE satellite mission, was applied to CloudSat, CALIPSO, and MODIS satellite data thus producing 3D cloudy atmospheres measuring 60 km wide by 13,000 km long at 1 km grid-spacing. Broadband solar fluxes and radiances for each (1 km)2 column where then produced by a Monte Carlo photon transfer model run in both full 3D and independent column approximation mode (i.e., a 1D model)