Mapping the Flammability Space of Sustainable Refrigerant Mixtures through an Artificial Neural Network Based on Molecular Descriptors

As the EU's mandates to phase out high-GWP refrigerants come into effect, the refrigeration industry is facing a new, unexpected reality: the introduction of more flammable yet environmentally compliant alternatives. This paradigm shift amplifies the need for a rapid, reliable screening methodology to assess the propensity for flammability of emerging fourth generation blends, offering a pragmatic alternative to laborious and time-intensive traditional experimental assessments. In this study, an artificial neural network (ANN) is meticulously constructed, evaluated, and validated to address this emerging challenge by predicting the normalized flammability index (NFI) for an extensive array of pure, binary, and ternary mixtures, reflecting a substantial diversity of compounds like CO2, hydrofluorocarbons (HFCs), hydrofluoroolefins (HFOs), six saturated hydrocarbons (sHCs), hydroolefins (HOs), and others. The optimal configuration ([61 (I) × 14 (HL1) × 24 (HL2) × 1 (O)]) demonstrated a profound fit to the data, with metrics like R 2 of 0.999, root-mean-square error (RMSE) of 0.1735, average absolute relative deviation (AARD)% of 0.8091, and SDav of ±0.0434. Exhaustive assessments were conducted to ensure the most efficient architecture without compromising the accuracy. Additionally, the analysis of the standardized residuals (SDR) and applicability domain (AD) exhibited fine control and consistency over the data points. External validation using quaternary mixtures further attested to the model's adaptability and predictive capability. The exploration into the relative contribution of descriptors led to the identification of 23 significant sigma descriptors derived from conductor-like screening model (COSMO), responsible for 90.98% of the total contribution, revealing potential avenues for model simplification without a substantial loss in predictive power. Moreover, the model successfully predicted the behavior of prospective industry-relevant mixtures, reinforcing its reliability and opening the door to experimentation with untested blends. The results collectively manifest the developed ANN's efficiency, robustness, and adaptability in modeling flammability, catering to the demands of industry standards, environmental concerns, and safety requirements.

Predicting the Surface Tension of Deep Eutectic Solvents Using Artificial Neural Networks

Studies on deep eutectic solvents (DESs), a new class of "green" solvents, are attracting increasing attention from researchers, as evidenced by the rapidly growing number of publications in the literature. One of the main advantages of DESs is that they are tailor-made solvents, and therefore, the number of potential DESs is extremely large. It is essential to have computational methods capable of predicting the physicochemical properties of DESs, which are needed in many industrial applications and research. Surface tension is one of the most important properties required in many applications. In this work, we report a relatively generalized artificial neural network (ANN) for predicting the surface tension of DESs. The database used can be considered comprehensive because it contains 1571 data points from 133 different DES mixtures in 520 compositions prepared from 18 ions and 63 hydrogen bond donors in a temperature range of 277-425 K. The ANN model uses molecular parameter inputs derived from the conductor-like screening model for real solvents (S _σ-profiles). The training and testing results show that the best performing ANN architecture consisted of two hidden layers with 15 neurons each (9-15-15-1). The proposed ANN was excellent in predicting the surface tension of DESs, as R ² values of 0.986 and 0.977 were obtained for training and testing, respectively, with an overall average absolute relative deviation of 2.20%. The proposed models represent an initiative to promote the development of robust models capable of predicting the properties of DESs based only on molecular parameters, leading to savings in investigation time and resources.

Searching for Sustainable Refrigerants by Bridging Molecular Modeling with Machine Learning

We present here a novel integrated approach employing machine learning algorithms for predicting thermophysical properties of fluids. The approach allows obtaining molecular parameters to be used in the polar soft-statistical associating fluid theory (SAFT) equation of state using molecular descriptors obtained from the conductor-like screening model for real solvents (COSMO-RS). The procedure is used for modeling 18 refrigerants including hydrofluorocarbons, hydrofluoroolefins, and hydrochlorofluoroolefins. The training dataset included six inputs obtained from COSMO-RS and five outputs from polar soft-SAFT parameters, with the accurate algorithm training ensured by its high statistical accuracy. The predicted molecular parameters were used in polar soft-SAFT for evaluating the thermophysical properties of the refrigerants such as density, vapor pressure, heat capacity, enthalpy of vaporization, and speed of sound. Predictions provided a good level of accuracy (AADs = 1.3-10.5%) compared to experimental data, and within a similar level of accuracy using parameters obtained from standard fitting procedures. Moreover, the predicted parameters provided a comparable level of predictive accuracy to parameters obtained from standard procedure when extended to modeling selected binary mixtures. The proposed approach enables bridging the gap in the data of thermodynamic properties of low global warming potential refrigerants, which hinders their technical evaluation and hence their final application.

Supercritical Antisolvent Fractionation of Antioxidant Compounds from Salvia officinalis

The increasing interest towards greener antioxidants obtained via natural sources and more sustainable processes encourages the development of new theoretical and experimental methods in the field of those compounds. Two advanced separation methods using supercritical CO2 are applied to obtain valuable antioxidants from Salvia officinalis, and a first approximation to a QSAR model relating molecular structure with antioxidant activity is explored in order to be used, in the future, as a guide for the preselection of compounds of interest in these processes. Separation experiments through antisolvent fractionation with supercritical CO2 were designed using a Response Surface Methodology to study the effect of pressure and CO2 flow rate on both mass yields and capability to obtain fractions enriched in three antioxidant compounds: chlorogenic acid, caffeic acid and rosmarinic acid which were tracked using HPLC PDA. Rosmarinic acid was completely retained in the precipitation vessel while chlorogenic and caffeic acids, though distributed between the two separated fractions, had a major presence in the precipitation vessel too. The conditions predicted for an optimal overall yield and enrichment were 148 bar and 10 g/min. Although a training dataset including much more compounds than those now considered can be recommended, descriptors calculated from the σ-profiles provided by COSMO-RS model seem to be adequate for estimating the antioxidant activity of pure compounds through QSAR.

Concerns and breakthroughs of combining ionic liquids with microwave irradiation for the synthesis of Ru nanoparticles via decarbonylation

HYPOTHESIS

Combination of microwave irradiation (MWI) and ionic liquids (IL) is widely used for the synthesis of nanoparticles (NP) via decarbonylation of zero-valent metal carbonyl precursors. However, we carefully raise a question as to whether this combination is always beneficial. Upon MWI, highly-absorbing materials such as ILs would be subject to local intense heating, likely resulting in the occurrence of localized chemical decomposition. The decomposition is expected to influence the growth mechanism of NPs due to changes in the electrostatic and steric effects. If the assumption is valid, it should be possible to decompose IL and destabilize the NPs by modifying the amplitude of the incident microwaves. In other words, it should also be possible to control the particle aggregation by circumventing the decomposition of the IL.

EXPERIMENTS

A series of comparative studies were conducted using a model system (i.e. [BMIm][BF₄] and Ru₃(CO)₁₂). Variables were systematically controlled. After MWI, the decrease in colloidal stability of NPs was identified.

FINDINGS

In the formation of Ru NPs via decarbonylation, the association between incident microwave intensity, chemical decomposition of IL, and initiation of particle aggregation has been demonstrated. Conditions that can accelerate or alleviate the decomposition and the aggregation are also corroborated.

Screening Ionic Liquids Based on Ionic Volume and Electrostatic Potential Analyses

Ionic liquids (ILs) are known to have tunable solvation properties, based on the pairing of different anions and cations, but the compositional landscape is vast and challenging to navigate efficiently. Some computational screening protocols are available, but they can be either time-consuming or difficult to implement. Herein, we perform a detailed investigation of the fundamental role of electrostatic interactions in these systems. We effectively develop a bridge between the previous volume-based approach with a quantum structure-property relationship approach to create fast, simple screening guidelines. We propose a new parameter that is applicable to both monovalent and multivalent ions, the ionic polarity index (IPI), which is defined as the ratio of the average electrostatic surface potential (V̅) of the ion to the net charge of the ion (q). The IPI correlation has been tested on a diverse data set of 121 ions, and reliable predictions can be obtained within a homologous series of IL compounds.

Representation of the Structure-A Key Point of Building QSAR/QSPR Models for Ionic Liquids

The process of encoding the structure of chemicals by molecular descriptors is a crucial step in quantitative structure-activity/property relationships (QSAR/QSPR) modeling. Since ionic liquids (ILs) are disconnected structures, various ways of representing their structure are used in the QSAR studies: the models can be based on descriptors either derived for particular ions or for the whole ionic pair. We have examined the influence of the type of IL representation (separate ions vs. ionic pairs) on the model's quality, the process of the automated descriptors selection and reliability of the applicability domain (AD) assessment. The result of the benchmark study showed that a less precise description of ionic liquid, based on the 2D descriptors calculated for ionic pairs, is sufficient to develop a reliable QSAR/QSPR model with the highest accuracy in terms of calibration as well as validation. Moreover, the process of a descriptors' selection is more effective when the possible number of variables can be decreased at the beginning of model development. Additionally, 2D descriptors usually demand less effort in mechanistic interpretation and are more convenient for virtual screening studies.

Unveiling the mechanism of hydrotropy: evidence for water-mediated aggregation of hydrotropes around the solute

The mechanism of hydrotropy is experimentally proven in this work. Apolarity is shown to be the driving force of hydrotropy.

Theoretical study on degradation mechanism of ornidazole on anatase TiO2(101) and (001) surfaces

The degradation mechanism of one new emerging pollutant ornidazole (ONZ) on TiO₂surface is explored using DFT calculations.

A comprehensive study on the impact of chemical structures of ionic liquids on the solubility of ethane

The solubility of ethane is not only governed by the electrostatic–misfit of the solute toward ionic liquids, but also the existence of a preferential site for ethane to interact with the ionic liquid's non-polar moiety.

Chemoinformatic Approaches To Predict the Viscosities of Ionic Liquids and Ionic Liquid-Containing Systems

Modelling, predicting, and understanding the factors influencing the viscosities of ionic liquids and related mixtures are sequentially checked in this work. The molecular maps of atom-level properties (MOLMAP codification system) is adapted for a straightforward inclusion of ionic liquids and mixtures containing ionic liquids. Random Forest models have been tested in this context and an optimal model was selected. The interpretability of the selected Random Forest model is highlighted with selected structural features that might contribute to identify low viscosities. The constructed model is able to recognize the influence of different structural variables, temperature, and pressure for a correct classification of the different systems. The codification and interpretation systems are highlighted in this work.

A Method of Calculating the Kamlet-Abboud-Taft Solvatochromic Parameters Using COSMO-RS

There is demand for safer and bio-based solvents, brought on by legislation and sustainability objectives. The prediction of physical properties is highly desirable to help design new molecules. Here we present an in silico approach to obtain calculated Kamlet-Abboud-Taft solvatochromic parameters using virtual experiments. The tautomerisation equilibrium of methyl acetoacetate and dimedone was calculated in different solvents with COSMO-RS theory and converted into estimates of solvent dipolarity and hydrogen bond accepting ability, respectively. Hydrogen bond donating ability was calculated as a function of the electron deficient surface area on protic solvents. These polarity descriptors correlate with rate constants and equilibria, and so ability of calculated Kamlet-Abboud-Taft solvatochromic parameters to recreate experimental free energy relationships was tested with sixteen case studies taken from the literature. The accuracy of the calculated parameters was also satisfactory for solvent selection, as demonstrated with a 1,4-addition reaction and a multicomponent heterocycle synthesis.

Hydrogen bond basicity of ionic liquids and molar entropy of hydration of salts as major descriptors in the formation of aqueous biphasic systems

Aqueous biphasic systems (ABS) composed of ionic liquids (ILs) and conventional salts have been largely investigated and successfully used in separation processes, for which the determination of the corresponding ternary phase diagrams is a prerequisite. However, due the large number of ILs that can be prepared and their high structural versatility, it is impossible to experimentally cover and characterize all possible combinations of ILs and salts that may form ABS. The development of tools for the prediction and design of IL-based ABS is thus a crucial requirement. Based on a large compilation of experimental data, a correlation describing the formation of IL-based ABS is shown here, based on the hydrogen-bonding interaction energies of ILs (EHB) obtained by the COnductor-like Screening MOdel for Real Solvents (COSMO-RS) and the molar entropy of hydration of the salt ions. The ability of the proposed model to predict the formation of novel IL-based ABS is further ascertained.

Quantum Chemical Methods for the Prediction of Energetic, Physical, and Spectroscopic Properties of Ionic Liquids

The accurate prediction of physicochemical properties of condensed systems is a longstanding goal of theoretical (quantum) chemistry. Ionic liquids comprising entirely of ions provide a unique challenge in this respect due to the diverse chemical nature of available ions and the complex interplay of intermolecular interactions among them, thus resulting in the wide variability of physicochemical properties, such as thermodynamic, transport, and spectroscopic properties. It is well understood that intermolecular forces are directly linked to physicochemical properties of condensed systems, and therefore, an understanding of this relationship would greatly aid in the design and synthesis of functionalized materials with tailored properties for an application at hand. This review aims to give an overview of how electronic structure properties obtained from quantum chemical methods such as interaction/binding energy and its fundamental components, dipole moment, polarizability, and orbital energies, can help shed light on the energetic, physical, and spectroscopic properties of semi-Coulomb systems such as ionic liquids. Particular emphasis is given to the prediction of their thermodynamic, transport, spectroscopic, and solubilizing properties.

Understanding positive and negative deviations in polarity of ionic liquid mixtures by pseudo-solvent approach

Physico-chemical properties of liquid mixtures in general display large deviations from linear behaviour, arising out of complex specific and non-specific intermolecular interactions. The polarity of liquid mixtures displaying large positive and negative deviations can be minimized and linear mixing can be achieved in liquids using a pseudo-solvent methodology. The work described herein is designed to investigate the influence of different physical parameters on the linear pseudo-solvent composition in ionic liquid mixtures. For this purpose, we have determined the deviations from linearity, ΔE values (defined as given by ) for binary mixtures of a variety of ionic liquids, including two molecular solvents, DMSO and formamide. Firstly, the investigations were carried out in three 1-butyl-3-methylimidazolium cation based aprotic ionic liquids and the roles of anionic structure and hydrogen bond acceptor basicities (β values) of the ionic liquids were determined. The influence of the cationic structure, i.e., the hydrogen bond donor acidity (α values) and non-associative nature of the ionic liquids, was determined using C2-methylated analogs, 1-butyl-2,3-dimethylimidazolium cation based ionic liquids. The role of the protic nature of ionic liquids was studied in two protic ionic liquids, viz., 1-methylimidazolium formate and 1-methylimidazolium acetate. The effects of the temperature, pseudo-solvent structure and solvatochromic probe structure on the ΔE values were also explored.

Physicochemical and electrochemical properties of a new series of protic ionic liquids with N-chloroalkyl functionalized cations

Six new protic ionic liquids (PILs) based on N-chloroalkyl functionalized morpholinium, piperidinium, pyrrolidinium and alkylammonium cations, with bis[(trifluoromethyl)sulfonyl]imide as counter-ion, were synthesized by a metathesis reaction.

Deviation of polarity from linearity in liquid mixtures containing an ionic liquid

The physico-chemical properties of liquid mixtures, in general, exhibit deviations from linear behaviour with respect to their composition, arising out of different types of cross-intermolecular interactions (both specific and non-specific). These specific and non-specific interactions can however be monitored to obtain the linear mixing in liquid mixtures using the pseudo-solvent methodology in such a manner that the interactions causing deviations from linearity are cancelled out and mixtures display linear behaviour.

Contact angles and wettability of ionic liquids on polar and non-polar surfaces

Many applications involving ionic liquids (ILs) require the knowledge of their interfacial behaviour, such as wettability and adhesion. In this context, herein, two approaches were combined aiming at understanding the impact of the IL chemical structures on their wettability on both polar and non-polar surfaces, namely: (i) the experimental determination of the contact angles of a broad range of ILs (covering a wide number of anions of variable polarity, cations, and cation alkyl side chain lengths) on polar and non-polar solid substrates (glass, Al-plate, and poly-(tetrafluoroethylene) (PTFE)); and (ii) the correlation of the experimental contact angles with the cation-anion pair interaction energies generated by the Conductor-like Screening Model for Real Solvents (COSMO-RS). The combined results reveal that the hydrogen-bond basicity of ILs, and thus the IL anion, plays a major role through their wettability on both polar and non-polar surfaces. The increase of the IL hydrogen-bond accepting ability leads to an improved wettability of more polar surfaces (lower contact angles) while the opposite trend is observed on non-polar surfaces. The cation nature and alkyl side chain lengths have however a smaller impact on the wetting ability of ILs. Linear correlations were found between the experimental contact angles and the cation-anion hydrogen-bonding and cation ring energies, estimated using COSMO-RS, suggesting that these features primarily control the wetting ability of ILs. Furthermore, two-descriptor correlations are proposed here to predict the contact angles of a wide variety of ILs on glass, Al-plate, and PTFE surfaces. A new extended list is provided for the contact angles of ILs on three surfaces, which can be used as a priori information to choose appropriate ILs before a given application.

Hydrogen-bond acidity of ionic liquids: an extended scale

One of the main drawbacks comprising an appropriate selection of ionic liquids (ILs) for a target application is related to the lack of an extended and well-established polarity scale for these neoteric fluids. Albeit considerable progress has been made on identifying chemical structures and factors that influence the polarity of ILs, there still exists a high inconsistency in the experimental values reported by different authors. Furthermore, due to the extremely large number of possible ILs that can be synthesized, the experimental characterization of their polarity is a major limitation when envisaging the choice of an IL with a desired polarity. Therefore, it is of crucial relevance to develop correlation schemes and a priori predictive methods able to forecast the polarity of new (or not yet synthesized) fluids. In this context, and aiming at broadening the experimental polarity scale available for ILs, the solvatochromic Kamlet-Taft parameters of a broad range of bis(trifluoromethylsulfonyl)imide-([NTf2](-))-based fluids were determined. The impact of the IL cation structure on the hydrogen-bond donating ability of the fluid was comprehensively addressed. Based on the large amount of novel experimental values obtained, we then evaluated COSMO-RS, COnductor-like Screening MOdel for Real Solvents, as an alternative tool to estimate the hydrogen-bond acidity of ILs. A three-parameter model based on the cation-anion interaction energies was found to adequately describe the experimental hydrogen-bond acidity or hydrogen-bond donating ability of ILs. The proposed three-parameter model is also shown to present a predictive capacity and to provide novel molecular-level insights into the chemical structure characteristics that influence the acidity of a given IL. It is shown that although the equimolar cation-anion hydrogen-bonding energies (EHB) play the major role, the electrostatic-misfit interactions (EMF) and van der Waals forces (EvdW) also contribute, admittedly in a lower extent, towards the hydrogen-bond acidity of ILs. The new extended scale provided for the hydrogen-bond acidity of ILs is of high value for the design of new ILs for task-specific applications.

Applications and mechanisms of ionic liquids in whole-cell biotransformation

Ionic liquids (ILs), entirely composed of cations and anions, are liquid solvents at room temperature. They are interesting due to their low vapor pressure, high polarity and thermostability, and also for the possibility to fine-tune their physicochemical properties through modification of the chemical structures of their cations or anions. In recent years, ILs have been widely used in biotechnological fields involving whole-cell biotransformations of biodiesel or biomass, and organic compound synthesis with cells. Research studies in these fields have increased from the past decades and compared to the typical solvents, ILs are the most promising alternative solvents for cell biotransformations. However, there are increasing limitations and new challenges in whole-cell biotransformations with ILs. There is little understanding of the mechanisms of ILs' interactions with cells, and much remains to be clarified. Further investigations are required to overcome the drawbacks of their applications and to broaden their application spectrum. This work mainly reviews the applications of ILs in whole-cell biotransformations, and the possible mechanisms of ILs in microbial cell biotransformation are proposed and discussed.

A step towards the a priori design of ionic liquids

A range of methods for the computational prediction of experimentally derived α and β Kamlet-Taft parameters, indicators of hydrogen bond (H-bond) acidity and basicity for ionic liquids (ILs) have been explored. Most usefully, a good correlation has been established between several simple and easily computed quantities which allow for a "quick bench-top" evaluation. More accurate, but also more sophisticated methods employing TD-DFT calculations involving the Kamlet-Taft dyes have been examined and evaluated. Importantly, these techniques open up the opportunity for pre-screening and a priori prediction of properties for ILs not yet synthesised. A key fundamental insight into IL H-bonds has been the determination of an estimate for the energy associated with replacing both neutral molecules in a H-bond with ionic molecules, thus forming the "doubly ionic" H-bond found in ILs.

Ionic liquids: a pathway to environmental acceptability

Ionic liquids were initially proposed as replacements for conventional organic solvents; however, their chemistry has developed remarkably and offers unexpected opportunities in numerous fields, ranging from electrochemistry to biology. As a consequence of ionic liquids advancing towards potential and actual applications, a comprehensive determination of their environmental, health and safety impact is now required. This critical review aims to present an overview of the current understanding of the toxicity and environmental impact of the principal ionic liquid groups, and highlights some emerging concerns. Each cation type is considered separately, examining the significance of the biological data, and identifying the most critical questions, some yet unresolved. The need for more, and more detailed, studies is highlighted (176 references).