Novel ionization reagent for the measurement of gas-phase ammonia and amines using a stand-alone atmospheric pressure gas chromatography (APGC) source.

RationaleContaminants present in ambient air or in sampling lines can interfere with the target analysis through overlapping peaks or causing a high background. This study presents a positive outcome from the unexpected presence of N-methyl-2-pyrrolidone, released from a PALL HEPA filter, in the analysis of atmospherically relevant gas-phase amines using chemical ionization mass spectrometry.MethodsGas-phase measurements were performed using a triple quadrupole mass spectrometer equipped with a modified atmospheric pressure gas chromatography (APGC) source which allows sampling of the headspace above pure amine standards. Gas-phase N-methyl-2-pyrrolidone (NMP) emitted from a PALL HEPA filter located in the inlet stream served as the ionizing agent.ResultsThis study demonstrates that some alkylamines efficiently form a [NMP + amine+H]+ cluster with NMP upon chemical ionization at atmospheric pressure. The extent of cluster formation depends largely on the proton affinity of the amine compared with that of NMP. Aromatic amines (aniline, pyridine) and diamines (putrescine) were shown not to form cluster ions with NMP.ConclusionsThe use of NMP as an ionizing agent with stand-alone APGC provided high sensitivity for ammonia and the smaller amines. The main advantages, in addition to sensitivity, are direct sampling into the APGC source and avoiding uptake on sampling lines which can be a significant problem with ammonia and amines

Implementation of stability-based transition model by means of transport equations

A natural laminar-turbulent transition model compatible with Computation Fluid Dynamics is presented. This model accounts for longitudinal transition mechanisms (i.e. Tollmien-Schlichting induced transition) thanks to systematic stability computation on similar boundary profiles from Mach zero to four both on adiabatic and isothermal wall. The model embeds as well the so-called “C1-criterion” for transverse transition mechanisms (i.e. cross-flow waves induced transition). The transition model is written under transport equations formalism and has been implemented in the solver elsA (ONERA-Airbus-Safran property). Validations are performed on three dimensional configurations and comparisons are shown against a database method for natural transition modeling and experiments

Amplitude equations near pattern forming instabilities for strongly driven ferromagnets

A transversally driven isotropic ferromagnet being under the influence of a static external and an uniaxial internal anisotropy field is studied. We consider the dissipative Landau-Lifshitz equation as the fundamental equation of motion and treat it in $1+1$~dimensions. The stability of the spatially homogeneous magnetizations against inhomogeneous perturbations is analyzed. Subsequently the dynamics above threshold is described via amplitude equations and the dependence of their coefficients on the physical parameters of the system is determined explicitly. We find soft- and hard-mode instabilities, transitions between sub- and supercritical behaviour, various bifurcations of higher codimension, and present a series of explicit bifurcation diagrams. The analysis of the codimension-2 point where the soft- and hard-mode instabilities coincide leads to a system of two coupled Ginzburg-Landau equations.Comment: LATeX, 25 pages, submitted to Z.Phys.B figures available via [email protected] in /pub/publications/frank/zpb_95 (postscript, plain or gziped

Deep learning for monthly rainfall–runoff modelling: a large-sample comparison with conceptual models across Australia

A deep learning model designed for time series predictions, the long short-term memory (LSTM) architecture, is regularly producing reliable results in local and regional rainfall–runoff applications around the world. Recent large-sample hydrology studies in North America and Europe have shown the LSTM model to successfully match conceptual model performance at a daily time step over hundreds of catchments. Here we investigate how these models perform in producing monthly runoff predictions in the relatively dry and variable conditions of the Australian continent. The monthly time step matches historic data availability and is also important for future water resources planning; however, it provides significantly smaller training datasets than daily time series. In this study, a continental-scale comparison of monthly deep learning (LSTM) predictions to conceptual rainfall–runoff (WAPABA model) predictions is performed on almost 500 catchments across Australia with performance results aggregated over a variety of catchment sizes, flow conditions, and hydrological record lengths. The study period covers a wet phase followed by a prolonged drought, introducing challenges for making predictions outside of known conditions – challenges that will intensify as climate change progresses. The results show that LSTM models matched or exceeded WAPABA prediction performance for more than two-thirds of the study catchments, the largest performance gains of LSTM versus WAPABA occurred in large catchments, the LSTMs struggled less to generalise than the WAPABA models (e.g. making predictions under new conditions), and catchments with few training observations due to the monthly time step did not demonstrate a clear benefit with either WAPABA or LSTM.</p

Protein A chromatography increases monoclonal antibody aggregation rate during subsequent low pH virus inactivation hold

Protein A chromatography is a near-ubiquitous method of mAb capture in bioprocesses. The use of low pH buffer for elution from protein A is known to contribute to product aggregation. Yet, a more limited set of evidence suggests that low pH may not be the sole cause of aggregation in protein A chromatography, rather, other facets of the process may contribute significantly. This paper presents a well-defined method for investigating this problem. An IgG4 was incubated in elution buffer after protein A chromatography (typical of the viral inactivation hold) and the quantity of monomer in neutralised samples was determined by size exclusion chromatography; elution buffers of different pH values predetermined to induce aggregation of the IgG4 were used. Rate constants for monomer decay over time were determined by fitting exponential decay functions to the data. Similar experiments were implemented in the absence of a chromatography step, i.e. IgG4 aggregation at low pH. Rate constants for aggregation after protein A chromatography were considerably higher than those from low pH exposure alone; a distinct shift in aggregation rates was apparent across the pH range tested

Turing Instability in a Boundary-fed System

The formation of localized structures in the chlorine dioxide-idodine-malonic acid (CDIMA) reaction-diffusion system is investigated numerically using a realistic model of this system. We analyze the one-dimensional patterns formed along the gradients imposed by boundary feeds, and study their linear stability to symmetry-breaking perturbations (Turing instability) in the plane transverse to these gradients. We establish that an often-invoked simple local linear analysis which neglects longitudinal diffusion is inappropriate for predicting the linear stability of these patterns. Using a fully nonuniform analysis, we investigate the structure of the patterns formed along the gradients and their stability to transverse Turing pattern formation as a function of the values of two control parameters: the malonic acid feed concentration and the size of the reactor in the dimension along the gradients. The results from this investigation are compared with existing experiments.Comment: 41 pages, 18 figures, to be published in Physical Review

Transition in incompressible boundary layers with two-dimensional excrescences

An experimental investigation of the transition process in boundary layers subjected to forward- or aft-facing two-dimensional step excrescences is described. The objective of the work was to characterize the variation of transition Reynolds numbers with measurable roughness and boundary layer parameters, with the specific goal of specifying new tolerance criteria for laminar flow airfoils, alongside a fundamental investigation of linear boundary layer stability mechanisms. Results from an ongoing program of increasing complexity on effects of pressure gradient on excrescence-induced transition are presented. Preliminary N-factor calculations are used to determine the effects of boundary layer stability and attempt to isolate the effect of the disturbance due to the excrescence

Transitions/relaxations in polyester adhesive/PET system

The correlations between the transitions and the dielectric relaxation processes of the oriented poly(ethylene terephthalate) (PET) pre-impregnated of the polyester thermoplastic adhesive have been investigated by differential scanning calorimetry (DSC) and dynamic dielectric spectroscopy (DDS). The thermoplastic polyester adhesive and the oriented PET films have been studied as reference samples. This study evidences that the adhesive chain segments is responsible for the physical structure evolution in the PET-oriented film. The transitions and dielectric relaxation modes’ evolutions in the glass transition region appear characteristic of the interphase between adhesive and PET film, which is discussed in terms of molecular mobility. The storage at room temperature of the adhesive tape involves the heterogeneity of the physical structure, characterized by glass transition dissociation. Thus, the correlation between the transitions and the dielectric relaxation processes evidences a segregation of the amorphous phases. Therefore, the physical structure and the properties of the material have been linked to the chemical characteristics