Σpider diagram: A universal and versatile approach for system comparison and classification

Fabrication of ionic liquid functionalized silica with different anions and the application in mixed-mode and chiral chromatography

To realize the potential of ionic liquid functionalized silica to prepare mixed-mode and chiral stationary phases, two ionic liquid silane reagents with different anions were synthesized via a high-efficiency click reaction. Then they were decorated onto the surface of silica by a one-step bonding reaction. The functionalized silica was characterized by Fourier transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), and elemental analysis (EA). Two stationary phases provided satisfactory performance when compared with a commercial mixed-mode column. Notably, Sil-C10Im-D-BCS with D-3-bromocamphor-8-sulfonate (D-BCS) as anion presented chiral separation capacity towards 1,2,3,4-Tetrahydro-1-naphthol. The separation mechanism was investigated through multiple pathways, and the results revealed that the prepared stationary phases can retain and separate solutes through multiple interactions, like hydrophobic effect, ion exchange, hydrogen-bond interaction, etc. Quantum chemical calculation (QC) was employed to obtain the optimized structures and the binding energy of anions to cations. The results provided some insights into the retention mechanism from a molecular perspective. This work demonstrated the superiority of ionic liquid functionalized silica as mixed-mode stationary phases and the potential of chiral ionic liquid as chiral selectors.

An attempt to apply a subtraction model for characterization of non-polar stationary phase in supercritical fluid chromatography

This study verified the feasibility of using a subtraction model to characterize the non-polar stationary phases (including C4, C8, and phenyl-type) in supercritical fluid chromatography (SFC). The model with 6 terms was expressed as log α = η'H + θ'P + β'A + α'B + κ'C + σ'S, where a term θ'P indicating dipole or induced dipole interaction was intentionally supplemented. Ethylbenzene and SunFire C8 were respectively defined as the reference solute and column. A 7-step modeling procedure was proposed: in the first 6 steps, except σ'S, by the use of a bidirectional fitting method, other parameters were calculated based on the equation: log α = log (k_i/k_ref) ≈ η'H + θ'P + β'A + α'B + κ'C; and in the 7th step, residual analysis was employed to describe the σ'S term according to the equation: σ'S = log α_exp. - log α_pre. Furthermore, six columns that were not involved in modeling process and 12 compounds with unknown retention were used for methodology validation. It showed good predictions of log k, as demonstrated by adjusted determination coefficient (R²_adj) from 0.9927 to 0.9998 (column) and from 0.9940 to 0.9999 (compound), respectively. The subtraction model emphasized the contribution of dipole or induced dipole interaction to the retention in SFC, and it obtained the σ'S term through residual analysis. Moreover, it made reasonable physical-chemical sense as the linear solvation energy relationship (LSER) model did, with the distinct advantages of better fitting and more accurate prediction. This study provided some new insights into the characterization of non-polar stationary phases in SFC.

Selectivity evaluation of extraction systems

Extraction is the most common sample preparation technique prior to chromatographic analysis for samples which are too complex, too dilute, or contain matrix components incompatible with the further use of the separation system or interfere in the detection step. The most important extraction techniques are biphasic systems involving the transfer of target compounds from the sample to a different phase ideally accompanied by no more than a tolerable burden of co-extracted matrix compounds. The solvation parameter model affords a general framework to characterize biphasic extraction systems in terms of their relative capability for solute-phase intermolecular interactions (dispersion, dipole-type, hydrogen bonding) and within phase solvent-solvent interactions for cavity formation (cohesion). The approach is general and allows the comparison of liquid and solid extraction phases using the same terms and is used to explain the features important for the selective enrichment of target compounds by a specific extraction phase using solvent extraction, liquid-liquid extraction, and solid-phase extraction for samples in a gas, liquid, or solid phase. Hierarchical cluster analysis with the system constants of the solvation parameter model as variables facilitates the selection of solvents for extraction, the identification of liquid-liquid distribution systems with non-redundant selectivity, and evaluation of different approaches using liquids and solids for the isolation of target compounds from different matrices.

Chiral chromatography method screening strategies: Past, present and future

Method screening is an integral part of chromatographic method development for the separation of racemates. Due to the highly complex retention mechanism of a chiral stationary-phase, it is often difficult, if not impossible, to device predefined method-development steps that can be successfully applied to a wide group of molecules. The standard approach is to evaluate or screen a series of stationary and mobile-phase combinations to increase the chances of detecting a suitable separation condition. Such a process is often the rate-limiting step for high-throughput analyses and purification workflows. To address the problem, several solutions and strategies have been proposed over the years for reduction of net method-screening time. Some of the strategies have been adopted in practice while others remained confined in the literature. The main objective of this review is to revisit, critically discuss and compile the solutions published over the last two decades. We expect that making the diverse set of solutions available in a single document will help assessing the adequacy of existing screening protocols in laboratories conducting chiral separation.

Chemometrics for Selection, Prediction, and Classification of Sustainable Solutions for Green Chemistry—A Review

In this review, we present the applications of chemometric techniques for green and sustainable chemistry. The techniques, such as cluster analysis, principal component analysis, artificial neural networks, and multivariate ranking techniques, are applied for dealing with missing data, grouping or classification purposes, selection of green material, or processes. The areas of application are mainly finding sustainable solutions in terms of solvents, reagents, processes, or conditions of processes. Another important area is filling the data gaps in datasets to more fully characterize sustainable options. It is significant as many experiments are avoided, and the results are obtained with good approximation. Multivariate statistics are tools that support the application of quantitative structure–property relationships, a widely applied technique in green chemistry.

Selective extraction of bioactive compounds from plants using recent extraction techniques: A review

Plant extraction has existed for a long time and is still of interest. Due to technological improvements, it is now possible to obtain extracts with higher yields. While global yield is a major parameter because it assesses the extraction performance, it can be of interest to focus on the extraction of particular compounds (specific metabolites) to enrich the sample and to avoid the extraction of unwanted ones, for instance the primary metabolites (carbohydrates, triacylglycerols). The objective then is to improve extraction selectivity is then considered. In solid-liquid extraction, which is often called maceration, the solvent has a major impact on selectivity. Its polarity has a direct influence on the solutes extracted, related to the chemical structure of the compounds, and modelling compound/solvent interactions by using various polarity or interaction scales is a great challenge to favor the choice of the appropriate extracting liquid. Technical advances have allowed the development of recent, and sometimes green, extraction techniques, such as Microwave-Assisted Extraction (MAE), Ultrasound-Assisted Extraction (UAE), Pressurized Liquid Extraction (PLE) and Supercritical Fluid Extraction (SFE). This review focuses on the specificity of these recent techniques and the influence of their physical parameters (i.e. pressure, intensity, etc.). In addition to the solvent selection, which is of prime interest, the physical parameters applied by the different techniques influence the extraction results in different ways. Besides, SFE is a versatile and green technique suitable to achieve selectivity for some compounds. Due to its properties, SC-CO₂ allows tailoring conditions to improve the selectivity.

Supercritical Fluid Chromatography development of a predictive analytical tool to selectively extract bioactive compounds by supercritical fluid extraction and pressurised liquid extraction

Selective extraction is a great concern in the field of natural products. The interest is to apply specific conditions favouring the solubility of targeted secondary metabolites and avoiding the simultaneous extraction of unwanted ones. Different ways exist to reach selective extractions with suited conditions. These conditions can be determined from experimental studies through experimental design, but a full experimental design takes time, energy, and uses plant samples. Prediction from varied solubility models can also be applied allowing a better understanding of the final selected conditions and eventually less experiments. The aim of this work was to develop and use a chromatographic model to determine optimal extraction conditions without the need for numerous extraction experiments. This model would be applied on the selective extraction of the desired antioxidant compounds in rosemary leaves (rosmarinic and carnosic acids) vs chlorophyll pigments to limit the green colour in extracts. This model was achieved with Supercritical Fluid Chromatography (SFC) and then applied to Supercritical Fluid Extraction (SFE) and Pressurised Liquid Extraction (PLE) assays. SFC models predicted low solubility of chlorophylls for low (5%) and high (100%) percentage of solvent in carbon dioxide. Also, low solubility was predicted with acetonitrile solvent compared to methanol or ethanol. This was confirmed with different extractions performed using SFE with different percentages of solvent (5, 30, and 70%) and with the three solvents used in the SFC models (acetonitrile, methanol and ethanol). Also extractions using PLE were carried out using the same neat solvents in order to confirm the SFC models obtained for 100% of solvent. Globally, extractions validated the SFC models. Only some differences were observed between ethanol and methanol showing the complexity of plant extraction due to matrix effect. For all these extracts, the content of carnosic acid and rosmarinic acid was also monitored and selective extraction conditions of bioactive compounds could be determined.

Fuzzy Divisive Hierarchical Clustering of Solvents According to Their Experimentally and Theoretically Predicted Descriptors

The present study describes a simple procedure to separate into patterns of similarity a large group of solvents, 259 in total, presented by 15 specific descriptors (experimentally found and theoretically predicted physicochemical parameters). Solvent data is usually characterized by its high variability, different molecular symmetry, and spatial orientation. Methods of chemometrics can usefully be used to extract and explore accurately the information contained in such data. In this order, advanced fuzzy divisive hierarchical-clustering methods were efficiently applied in the present study of a large group of solvents using specific descriptors. The fuzzy divisive hierarchical associative-clustering algorithm provides not only a fuzzy partition of the solvents investigated, but also a fuzzy partition of descriptors considered. In this way, it is possible to identify the most specific descriptors (in terms of higher, smallest, or intermediate values) to each fuzzy partition (group) of solvents. Additionally, the partitioning performed could be interpreted with respect to the molecular symmetry. The chemometric approach used for this goal is fuzzy c-means method being a semi-supervised clustering procedure. The advantage of such a clustering process is the opportunity to achieve separation of the solvents into similarity patterns with a certain degree of membership of each solvent to a certain pattern, as well as to consider possible membership of the same object (solvent) in another cluster. Partitioning based on a hybrid approach of the theoretical molecular descriptors and experimentally obtained ones permits a more straightforward separation into groups of similarity and acceptable interpretation. It was shown that an important link between objects’ groups of similarity and similarity groups of variables is achieved. Ten classes of solvents are interpreted depending on their specific descriptors, as one of the classes includes a single object and could be interpreted as an outlier. Setting the results of this research into broader perspective, it has been shown that the fuzzy clustering approach provides a useful tool for partitioning by the variables related to the main physicochemical properties of the solvents. It gets possible to offer a simple guide for solvents recognition based on theoretically calculated or experimentally found descriptors related to the physicochemical properties of the solvents.

Advances and Opportunities of Oil-in-Oil Emulsions

Emulsions are mixtures of two immiscible liquids in which droplets of one are dispersed in a continuous phase of the other. The most common emulsions are oil-water systems, which have found widespread use across a number of industries, for example, in the cosmetic and food industries, and are also of advanced scientific interest. In addition, the past decade has seen a significant increase in both the design and application of nonaqueous emulsions. This has been primarily driven by developments in understanding the mechanism of effective stabilization of oil-in-oil (o/o) systems, either using block copolymers (BCPs) or solid (Pickering) particles with appropriate surface functionality. These systems, as highlighted in this review, have enabled emergent applications in areas such as pharmaceutical delivery, energy storage, and materials design (e.g., polymerization, monolith, and porous polymer synthesis). These o/o emulsions complement traditional emulsions that utilize an aqueous phase and allow the use of materials incompatible with water. We assess recent advances in the preparation and stabilization of o/o emulsions, focusing on the identity of the stabilizer (BCP or particle), the interplay between stabilizer and oils, and highlighting applications and opportunities associated with o/o emulsions.

Mixed Organic Ligand Shells: Controlling the Nanoparticle Surface Morphology toward Tuning the Optoelectronic Properties

Precise control over the ratio of perylene bisimide (PBI) monomers and aggregates, immobilized on alumina nanoparticle (NP) surfaces, is demonstrated. Towards this goal, phosphonic acid functionalized PBI derivatives (PA-PBI) are shown to self-assemble into stoichiometrically mixed monolayers featuring aliphatic, glycolic, or fluorinated phosphonic acid ligands, serving as imbedding matrix (PA-M) to afford core-shell NPs. Different but, nevertheless, defined PBI monomer/aggregate composition is achieved by either the variation in the PA-PBI to PA-M ratios, or the utilization of different PA-Ms. Various steady-state as well as time-resolved spectroscopy techniques are applied to probe the core-shell NPs with respect to changes in their optical properties upon variations in the shell composition. To this end, the ratio between monomer and excimer-like emission assists in deriving information on the self-assembled monolayer composition, local ordering, and corresponding aggregate content. With the help of X-ray reflectivity measurements, accompanied by molecular dynamics simulations, the built-up of the particle shells, in general, and the PBI aggregation behavior, in particular, are explored in depth.

Classification of biphasic solvent systems according to Abraham descriptors for countercurrent chromatography

The method development of liquid-liquid chromatography, either countercurrent chromatography or centrifugal partition chromatography, is slowed down by the selection of the biphasic solvent system that constitutes its column. This paper introduces a classification of 19 solvent systems, including the most popular systems based on heptane/ethyl acetate/methanol/water, some non-aqueous systems and some greener systems. This classification is based on Abraham descriptors determined through the partition coefficients of 43 probes. Among 21 determined models, nine of them allow an accurate prediction of partition coefficients from solute descriptors and another ten provide a description of the chromatographic interactions at the 5% significance level. A graphical tool (spider diagram) is built for the comparison of the chromatographic columns previously characterized with the solvation parameter model. The position of a solvent system in this spider diagram relates to the interactions at stake, thus the selection of columns offering similar or orthogonal interactions is facilitated, with no previous knowledge of the solute required. This semi-empirical strategy cannot fully predict the retention behavior but can judiciously orientate the user towards a limited number of solvent systems to be experimentally tested.