The extent to which cations and anions in ionic liquids (ILs) and ionic liquid solutions are dissociated is of both fundamental scientific interest and practical importance because ion dissociation ...has been shown to impact viscosity, density, surface tension, volatility, solubility, chemical reactivity, and many other important chemical and physical properties. When mixed with solvents, ionic liquids provide the unique opportunity to investigate ion dissociation from infinite dilution in the solvent to a completely solvent-free state, even at ambient conditions. The most common way to estimate ion dissociation in ILs and IL solutions is by comparing the molar conductivity determined from ionic conductivity measurements such as electrochemical impedance spectroscopy (EIS) (which measure the movement of only the charged, i.e., dissociated, ions) with the molar conductivity calculated from ion diffusivities measured by pulse field gradient nuclear magnetic resonance spectroscopy (PFG-NMR, which gives movement of all of the ions). Because the NMR measurements are time-consuming, the number of ILs and IL solutions investigated by this method is relatively limited. We have shown that use of the Stokes–Einstein equation with estimates of the effective ion Stokes radii allows ion dissociation to be calculated from easily measured density, viscosity, and ionic conductivity data (ρ, η, λ), which is readily available in the literature for a much larger number of pure ILs and IL solutions. Therefore, in this review, we present values of ion dissociation for ILs and IL solutions (aqueous and nonaqueous) determined by both the traditional molar conductivity/PFG-NMR method and the ρ, η, λ method. We explore the effect of cation and anion alkyl chain length, structure, and interaction motifs of the cation and anion, temperature, and the strength of the solvent in IL solutions.
Abstract
pyspeckit
is a toolkit and library for spectroscopic analysis in Python. We describe the
pyspeckit
package and highlight some of its capabilities, such as interactively fitting a model to ...data, akin to the historically widely-used
splot
function in
IRAF
.
pyspeckit
employs the Levenberg–Marquardt optimization method via the
mpfit
and
lmfit
implementations, and important assumptions regarding error estimation are described here. Wrappers to use
pymc
and
emcee
as optimizers are provided. A parallelized wrapper to fit lines in spectral cubes is included. As part of the
astropy
affiliated package ecosystem,
pyspeckit
is open source and open development, and welcomes input and collaboration from the community.
Feature selection can greatly enhance the performance of a learning algorithm when dealing with a high dimensional data set. The filter method and the wrapper method are the two most commonly ...approaches. However, these approaches have limitations. The filter method uses independent evaluation to evaluate and select features, which is computationally efficient but less accurate than the wrapper method. The wrapper method uses a predetermined classifier to compute the evaluation, which can afford high accuracy for particular classifiers, but is computationally expensive. In this study, we introduce a new feature selection method that we refer to as the large margin hybrid algorithm for feature selection (LMFS). In this method, we first utilize a new distance-based evaluation function, in which ideally samples from the same class are close together, whereas samples from other classes are far apart, and a weighted bootstrapping search strategy to find a set of candidate feature subsets. Then, we use a specific classifier and cross-validation to select the final feature subset from the candidate feature subsets. Six vibrational spectroscopic data sets and three different classifiers, namely k-nearest neighbors, partial least squares discriminant analysis and least squares support vector machine were used to validate the performance of the LMFS method. The results revealed that LMFS can effectively overcome the over-fitting between the optimal feature subset and a given classifier. Compared with the filter and wrapper methods, the features selected by the LMFS method have better classification performance and model interpretation. Furthermore, LMFS can effectively overcomes the impact of classifier complexity on computational time, and distance-based classifiers were found to be more suitable for selecting the final subset in LMFS.
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•A new margin-based objective function for measuring the quality of features.•A new large margin hybrid algorithm for feature selection (LMFS).•LMFS effectively overcomes the influence of classifier complexity on computational time in wrapper methods based on WBS.
We investigate the properties of a spinless Fermi gas close to a p-wave interaction resonance. We show that the effects of interaction near a p-wave resonance are captured by two contacts, which are ...related to the variation of energy with the p-wave scattering volume v and with the effective range R in two adiabatic theorems. Exact pressure and virial relations are derived. We show how the two contacts determine the leading and subleading asymptotic behavior of the momentum distribution (∼1/k^{2} and ∼1/k^{4}) and how they can be measured experimentally by radio-frequency and photoassociation spectroscopies. Finally, we evaluate the two contacts at high temperature with a virial expansion.
Infrared spectroscopy is a powerful tool widely used in research and industry for a label-free and unambiguous identification of molecular species. Inconveniently, its application to spectroscopic ...analysis of minute amounts of materials, for example, in sensing applications, is hampered by the low infrared absorption cross-sections. Surface-enhanced infrared spectroscopy using resonant metal nanoantennas, or short “resonant SEIRA”, overcomes this limitation. Resonantly excited, such metal nanostructures feature collective oscillations of electrons (plasmons), providing huge electromagnetic fields on the nanometer scale. Infrared vibrations of molecules located in these fields are enhanced by orders of magnitude enabling a spectroscopic characterization with unprecedented sensitivity. In this Review, we introduce the concept of resonant SEIRA and discuss the underlying physics, particularly, the resonant coupling between molecular and antenna excitations as well as the spatial extent of the enhancement and its scaling with frequency. On the basis of these fundamentals, different routes to maximize the SEIRA enhancement are reviewed including the choice of nanostructures geometries, arrangements, and materials. Furthermore, first applications such as the detection of proteins, the monitoring of dynamic processes, and hyperspectral infrared chemical imaging are discussed, demonstrating the sensitivity and broad applicability of resonant SEIRA.
The paper presents the results of spectroscopic measurements for selected dust analogues, based on which change in cometary brightness was determined. In the first part of the article, we present the ...results of laboratory measurements of hemispherical albedo for selected dust analogues using a Cary 5000 spectrometer with an integrating sphere. In the case of this system and the tested samples, the obtained hemispherical albedo values ranged from 0.35 ± 0.07% to 41.58 ± 0.07%. The obtained measurement results were used to determine the bolometric albedo and geometric albedo. For the analogue consisting of charcoal, the Bond albedo was equal to A B (charcoal) = 2.15%, whereas the geometric albedo was equal to p v (charcoal) = 6.76%. The second part of the paper presents an analytical method allowing us to calculate the amplitude of the change of cometary brightness during the outburst. The calculations show that the upper value of the amplitude is 6.5 magnitudes, which is within the medium range amplitude of the outburst. Calculations have shown that as the bolometric albedo increases for a given agglomerate porosity, the temperature decreases, which determines a smaller sublimation flux, which translates into a larger change in the cometary brightness.
•‘Point’ visible - NIR spectroscopy of fruit is a mature technology.•Applications include estimation of both present and future attributes.•Current commercial use in estimation of harvest time and ...internal quality attributes.•Future work should characterise instrumentation and demonstrate application robustness.
The application of visible (Vis; 400–750 nm) and near infrared red (NIR; 750–2500 nm) region spectroscopy to assess fruit and vegetables is reviewed in context of ‘point’ spectroscopy, as opposed to multi- or hyperspectral imaging. Vis spectroscopy targets colour assessment and pigment analysis, while NIR spectroscopy has been applied to assessment of macro constituents (principally water) in fresh produce in commercial practice, and a wide range of attributes in the scientific literature. This review focusses to key issues relevant to the widespread implementation of Vis-NIR technology in the fruit sector. A background to the concepts and technology involved in the use of Vis-NIR spectroscopy is provided and instrumentation for in-field and in-line applications, which has been available for two and three decades, respectively, is described. A review of scientific effort is made for the period 2015 - February 2020, in terms of the application areas, instrumentation, chemometric methods and validation procedures, and this work is critiqued through comparison to techniques in commercial use, with focus to wavelength region, optical geometry, experimental design, and validation procedures. Recommendations for future research activity in this area are made, e.g., application development with consideration of the distribution of the attribute of interest in the product and the matching of optically sampled and reference method sampled volume; instrumentation comparisons with consideration of repeatability, optimum optical geometry and wavelength range). Recommendations are also made for reporting requirements, viz. description of the application, the reference method, the composition of calibration and test populations, chemometric reporting and benchmarking to a known instrument/method, with the aim of maximising useful conclusions from the extensive work being done around the world.
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