An Improvement to COSMO-SAC for Predicting Thermodynamic Properties

Atomistic molecular dynamics simulation and COSMO-SAC approach for enhanced 1,3-propanediol extraction with imidazolium-based ionic liquids

CONTEXT

1,3-Propanediol (1,3-PDO) is a key chemical in various industries, including pharmaceuticals and material sciences, and is projected to see significant market growth. However, the current challenges in its downstream processing, particularly in terms of cost and efficiency, highlight the need for innovative solutions. Our study delves into using ionic liquids (ILs) as a potential alternative, aiming to address these critical separation challenges more sustainably and efficiently. In this study, we utilized molecular dynamics (MD) simulations and the COSMO-SAC to examine 1,3-propanediol (1,3-PDO) extraction using four imidazolium-based ionic liquids with 1-butyl-3-methylimidazolium [Bmim] cation and with different anions bis(pentafluoroethanesulfonyl)imide [NPF2]-, bis(trifluoromethylsulfonyl)imide [NTF2]-, thiocyanate [SCN]-, and trifluoromethanesulfonate [TFO]-. Molecular dynamics simulations, incorporating analysis of radial distribution functions (RDF) and spatial distribution functions (SDF), revealed that [Bmim][SCN] and [Bmim][TFO] exhibit enhanced interactions with 1,3-PDO. Notably, [Bmim][SCN] formed the most hydrogen bonds, averaging 1.639 per molecule, due to its coordinating [SCN]- anion. This was in contrast to the fewer hydrogen bonds formed by non-coordinating anions in [Bmim][NPF2] and [Bmim][NTF2]. In ternary systems, [Bmim][SCN] and [Bmim][TFO] demonstrated superior selectivity for 1,3-PDO extraction compared to the other ionic liquids, with selectivity values around 29. These findings, supported by COSMO-SAC predictive modeling, highlight the potential of [Bmim][SCN] as a promising candidate for 1,3-PDO extraction, emphasizing the importance of anion selection in optimizing ionic liquid properties for this application.

METHODS

In our study, we employed MD simulations, incorporating the OPLS-AA force field, and COSMO-SAC to investigate the extraction of 1,3-PDO using imidazolium-based ionic liquids: [Bmim][NTF2], [Bmim][NPF2], [Bmim][SCN], and [Bmim][TFO]. The MD simulations were conducted using LAMMPS software, focusing on elucidating the RDF, SDF, and hydrogen bonding. Analysis of the distribution coefficient (β) and selectivity (S) for the ternary mixture was also conducted. These aspects of the simulation were analyzed using TRAVIS and VMD software. Additionally, the COSMO-SAC model was employed to determine the activity coefficients of 1,3-PDO in the ionic liquids, with molecular optimization conducted using Gaussian16 and sigma profile calculations performed using COSMO-SAC.

Application of ionic liquid extractant in enhanced separation of 2-propanol-n-hexane azeotrope system

2-Propanol and n-hexane are widely used (as) chemical reagents in electronic, pharmaceutical, and chemical industries. An efficient separation of the azeotropic system of 2-propanol-n-hexane is of profound practical significance. By using the conductor-like screening model for real solve (COSMO-RS) predictive model, ionic liquids as extractants for separating the azeotropic system of 2-propanol-n-hexane were evaluated with selectivity coefficients (S) and capacity (C) as the evaluation indexes. Based on the evaluation results, one high-performance extractants named hydroxylamine Cl (C8A19) was selected from 435 kinds of ionic liquids designed by combining 29 kinds of anions and 15 kinds of cations. Moreover, the reliability of the model in predicting the vapor-liquid phase equilibrium behavior of 2-propanol-n-hexane system was verified. Then, the effect of C8A19 on the vapor-liquid phase equilibrium of the 2-propanol-n-hexane system was investigated theoretically and experimentally. The results show that the azeotrope of the system can be broken when the molar fraction of C8A19 is 0.02, denoting that C8A19 can be used for enhanced separation of 2-propanol-n-hexane system. On the basis of the aforementioned study, the selectivity mechanism of the extractant was analyzed from the perspective of microscopic molecular interactions by using the descriptor (σ-profiles) of COSMO-RS. This study provides both theoretical and data support for further designing high-performance ionic liquid extractants and extraction process.

Hydrocarbon Extraction with Ionic Liquids

Separation and reaction processes are key components employed in the modern chemical industry, and the former accounts for the majority of the energy consumption therein. In particular, hydrocarbon separation and purification processes, such as aromatics extraction, desulfurization, and denitrification, are challenging in petroleum refinement, an industrial cornerstone that provides raw materials for products used in human activities. The major technical shortcomings in solvent extraction are volatile solvent loss, product entrainment leading to secondary pollution, low separation efficiency, and high regeneration energy consumption due to the use of traditional organic solvents with high boiling points as extraction agents. Ionic liquids (ILs), a class of designable functional solvents or materials, have been widely used in chemical separation processes to replace conventional organic solvents after nearly 30 years of rapid development. Herein, we provide a systematic and comprehensive review of the state-of-the-art progress in ILs in the field of extractive hydrocarbon separation (i.e., aromatics extraction, desulfurization, and denitrification) including (i) molecular thermodynamic models of IL systems that enable rapid large-scale screening of IL candidates and phase equilibrium prediction of extraction processes; (ii) structure-property relationships between anionic and cationic structures of ILs and their separation performance (i.e., selectivity and distribution coefficients); (iii) IL-related extractive separation mechanisms (e.g., the magnitude, strength, and sites of intermolecular interactions depending on the separation system and IL structure); and (iv) process simulation and design of IL-related extraction at the industrial scale based on validated thermodynamic models. In short, this Review provides an easy-to-read exhaustive reference on IL-related extractive separation of hydrocarbon mixtures from the multiscale perspective of molecules, thermodynamics, and processes. It also extends to progress in IL analogs, deep eutectic solvents (DESs) in this research area, and discusses the current challenges faced by ILs in related separation fields as well as future directions and opportunities.

Computer-Aided Molecular Design of Ionic Liquids as Advanced Process Media: A Review from Fundamentals to Applications

The unique physicochemical properties, flexible structural tunability, and giant chemical space of ionic liquids (ILs) provide them a great opportunity to match different target properties to work as advanced process media. The crux of the matter is how to efficiently and reliably tailor suitable ILs toward a specific application. In this regard, the computer-aided molecular design (CAMD) approach has been widely adapted to cover this family of high-profile chemicals, that is, to perform computer-aided IL design (CAILD). This review discusses the past developments that have contributed to the state-of-the-art of CAILD and provides a perspective about how future works could pursue the acceleration of the practical application of ILs. In a broad context of CAILD, key aspects related to the forward structure-property modeling and reverse molecular design of ILs are overviewed. For the former forward task, diverse IL molecular representations, modeling algorithms, as well as representative models on physical properties, thermodynamic properties, among others of ILs are introduced. For the latter reverse task, representative works formulating different molecular design scenarios are summarized. Beyond the substantial progress made, some future perspectives to move CAILD a step forward are finally provided.

Screening ionic liquids for efficiently extracting perfluoroalkyl chemicals (PFACs) from wastewater

Liquid-liquid extraction (LLE) using ionic liquids (ILs)-based methods to remove perfluoroalkyl chemicals (PFACs), such as perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS), from wastewater, is an important strategy. However, the lack of physicochemical and LLE data limits the selection of the most suitable ILs for the extraction of PFACs. In this work, 1763 ILs for PFACs extraction from water were systematically screened using COSMOtherm to estimate the infinite dilution activity coefficient (lnγ^∞)of PFOA and PFOS in water and ILs. To evaluate the accuracy of COSMOtherm, 8 ILs with various lnγ^∞ values were selected, and their extraction efficiency (E) and distribution coefficient (D_exp) were measured experimentally. The results showed that the predicted lnγ^∞ decreased as the increase of experimental extraction efficiency of PFOA or PFOS, while the tendency of predicted distribution coefficient (D_pre) was consistent with the experimental (D_exp) results. This work provides an efficient basis for selecting ILs for the extraction of PFACs from wastewater.

Hollow and porous TiO2 in PVA matrix nanocomposite green synthesis using ionic liquid micelle for Congo red removal from contaminated water

A new green procedure has been applied to prepare TiO₂ nanocomposite in polyvinyl alcohol (PVA) matrix using an aqueous micelle solution of ionic liquid 1-methyl-3-octylimidazolium bromide by determining critical micelle concentration (CMC). The COSMO-SAC model has been used to calculate the activity coefficient of water and understand the water molecules' behavior in the synthesis mixture. The prepared nanocomposite was porous and layered that has been characterized using FT-IR, XRD, DSC, TGA, SEM, EDX, and elemental mapping. The prepared nanocomposite has been used to remove Congo red dye from contaminated water with the adsorption process. The Langmuir, Freundlich, and Temkin isotherms have been used for modeling equilibrium adsorption of dye removal. Also, the optimized process factors have been evaluated that could achieve 97% dye removal in the following conditions: pH = 12, T = 25 ℃, and t = 45 min using 0.2 g TiO₂@PVA (Mesh 100)/L of 10 ppm Congo red aqueous solution. Also, the efficiency of the nanocomposite was 88% after 5 recovery cycles from the optimized condition.

Exploring the Absorption Mechanisms of Imidazolium-Based Ionic Liquids to Epigallocatechin Gallate

Imidazolium-based ionic liquids are wildly used in natural product adsorption and purification. In this work, one typical polymeric ionic liquid (PIL) was synthesized by using L-proline as the anion, which exhibited excellent adsorption capacity toward tea polyphenol epigallocatechin gallate (EGCG). The adsorption conditions were optimized with the response surface method (RSM). Under the optimum conditions, the adsorption capacity of the PIL for EGCG can reach as high as 552 mg/g. Dynamics and isothermal research shows that the adsorption process of EGCG by the PIL particularly meets the quasi-second-order kinetic equation and monolayer adsorption mechanism. According to thermodynamic parameter analysis, the adsorption process is endothermic and spontaneous. The results of theoretical calculation by molecular docking also demonstrated the interaction mechanisms between EGCG and the ionic liquid. Considering the wide application of imidazolium-based ionic liquids in component adsorption and purification, the present study can not only be extended to other similar experimental mechanism validation, but also be representative for guiding the synthesis of PIL and optimization of adsorption conditions.

Solvation Thermodynamics of Solutes in Water and Ionic Liquids Using the Multiscale Solvation-Layer Interface Condition Continuum Model

Molecular assembly processes are generally driven by thermodynamic properties in solutions. Atomistic modeling can be very helpful in designing and understanding complex systems, except that bulk solvent is very inefficient to treat explicitly as discrete molecules. In this work, we develop and assess two multiscale solvation models for computing solvation thermodynamic properties. The new SLIC/CDC model combines continuum solvent electrostatics based on the solvent layer interface condition (SLIC) with new statistical thermodynamic models for hydrogen bonding and nonpolar modes: cavity formation, dispersion interactions, combinatorial mixing (CDC). Given the structures of 500 solutes, the SLIC/CDC model predicts Gibbs energies of solvation in water with an average accuracy better than 1 kcal/mol, when compared to experimental measurements, and better than 0.8 kcal/mol, when compared to explicit-solvent molecular dynamics simulations. The individual SLIC/CDC energy mode values agree quantitatively with those computed from explicit-solvent molecular dynamics. The previously published SLIC/SASA multiscale model combines the SLIC continuum electrostatic model with the solvent-accessible surface area (SASA) nonpolar energy mode. With our new, improved parametrization method, the SLIC/SASA model now predicts Gibbs energies of solvation with better than 1.4 kcal/mol average accuracy in aqueous systems, compared to experimental and explicit-solvent molecular dynamics, and better than 1.6 kcal/mol average accuracy in ionic liquids, compared to explicit-solvent molecular dynamics. Both models predict solvation entropies, and are the first implicit-solvation models capable of predicting solvation heat capacities.

Investigating the effects of intermolecular interactions on nonlinear optical properties of binary mixtures with high repetition rate femtosecond laser pulses

Measurements of nonlinear optical (NLO) properties of different binary mixtures having carbon disulfide (CS2) as the common component, namely CS2-acetone, CS2-cyclopentanone, CS2-toluene, and CS2-carbon tetrachloride (CCl4), are carried out by using the z-scan technique. Open-aperture z-scan (OAZS) and close-aperture z-scan (CAZS) experiments are performed to determine the nonlinear absorption coefficient (β) and nonlinear refractive index (n2) of all binary liquid mixtures at various compositions of the components by employing a pulsed, high repetition rate (HRR) femtosecond laser. Also, we were able to use the flowing liquid to measure NLO properties in the CS2-acetone binary mixture to remove the cumulative thermal effects produced due to the pulsed HRR laser light. Nonlinear refractive index (n2) values are found to be influenced by the weak dipole-induced dipole intermolecular interactions between the nonpolar CS2 and polar acetone as well as cyclopentanone of the respective binary mixtures. On the contrary n2 values are not found to be affected by the intermolecular interactions in CS2-toluene and CS2-CCl4 binary mixtures. In comparison, the nonlinear absorption coefficient (β) values are not found to be affected by the same in all different sets of binary mixtures.

Vapor-Liquid Equilibrium Study of the Monochlorobenzene-4,6-Dichloropyrimidine Binary System

The number of newly synthesized and produced organic chemicals has increased extremely quickly. However, the measurements of their physical properties, including their vapor-liquid equilibrium (VLE) data, are time-consuming. It so happens that there is no physical property data about a brand-new chemical. Therefore, the importance of calculating their physicochemical properties has been playing a more and more important role. 4,6-Dichloropyrimidine (DCP) is also a relatively new molecule of high industrial importance with little existing data. Therefore, their measurements and the comparison with the calculated data are of paramount concern. DCP is a widespread heterocyclic moiety that is present in synthetic pharmacophores with biological activities as well as in numerous natural products. Isobaric VLE for the binary system of 4,6-dichloropyrimidine and its main solvent monochlorobenzene (MCB) was measured using a vapor condensate and liquid circulation VLE apparatus for the first time in the literature. Density functional-based VLE was calculated using the COSMO-SAC protocol to verify the laboratory results. The COSMO-SAC calculation was found to be capable of representing the VLE data with high accuracy. Adequate agreement between the experimental and calculated VLE data was acquired with a minimal deviation of 3.0 × 10^-3, which allows for broader use of the results.

Methods for Interpreting the Partitioning and Fate of Petroleum Hydrocarbons in a Sea Ice Environment

Decreases in Arctic Sea ice extent and thickness have led to more open ice conditions, encouraging both shipping traffic and oil exploration within the northern Arctic. As a result, the increased potential for accidental releases of crude oil or fuel into the Arctic environment threatens the pristine marine environment, its ecosystem, and local inhabitants. Thus, there is a need to develop a better understanding of oil behavior in a sea ice environment on a microscopic level. Computational quantum chemistry was used to simulate the effects of evaporation, dissolution, and partitioning within sea ice. Vapor pressures, solubilities, octanol-water partition coefficients, and molecular volumes were calculated using quantum chemistry and thermodynamics for pure liquid solutes (oil constituents) of interest. These calculations incorporated experimentally measured temperatures and salinities taken throughout an oil-in-ice mesocosm experiment conducted at the University of Manitoba in 2017. Their potential for interpreting the relative movements of oil constituents was assessed. Our results suggest that the relative movement of oil constituents is influenced by differences in physical properties. Lighter molecules showed a greater tendency to be controlled by brine advection processes due to their greater solubility. Molecules which are more hydrophobic were found to concentrate in areas of lower salt concentration.

Screening of metal complexes and organic solvents using the COSMOSAC-LANL model to enhance the energy density in a non-aqueous redox flow cell: an insight into the solubility

In this paper, we have proposed a first-principles methodology to screen transition metal complexes against a particular organic solvent and organic solvents against a particular transition metal complex based on their solubility information without the knowledge of heat of fusion and melting temperature. The energy density of a non-aqueous redox flow cell directly depends on the solubility of the redox active species in the non-aqueous medium. We have used the "COSMOSAC-LANL" activity coefficient model (A. Karmakar, R. Mukundan, P. Yang and E. R. Batista, RSC Adv., 2019, 18506-18526; A. Karmakar and R. Mukundan, Phys. Chem. Chem. Phys., 2019, 19667-19685) which is based on first-principles COSMO calculations where the microscopic information is passed to the macroscopic world via a dielectric continuum solvation model, followed by a post-statistical thermodynamic treatment of the self-consistent properties of the solute particle to calculate the solubility. To model the activity coefficient at infinite dilution for the binary mixtures, a 3-suffix Margules (3sM) function is introduced for the quantitative estimation of the asymmetric interactions and, for the combinatorial term, the Staverman-Guggenheim (SG) form is used. The new activity coefficient model is separately called the "LANL" activity coefficient model. The metal complex and the organic solvent have been treated as a simple binary mixture. The present model has been applied to a set of 14 different organic solvents and 16 different transition metal complexes. Using the new LANL activity coefficient model in combination with the ADF-COSMOSAC-2013 model, we have shown how one can improve the solubility of a transition metal complex in an organic solvent. We applied our model to screen 84 binary mixtures to predict the compatible pair of redox active species and organic solvent to increase the energy density. The solvation mechanism of the transition metal complexes in the organic solvents was obtained using the new model. The results have been compared with the experimental and theoretical results where they are available.

A Benchmark Open-Source Implementation of COSMO-SAC

The COSMO-SAC modeling approach has found wide application in science as well as in a range of industries due to its good predictive capabilities. While other models for liquid phases, as for example UNIFAC, are in general more accurate than COSMO-SAC, these models typically contain many adjustable parameters and can be limited in their applicability. In contrast, the COSMO-SAC model only contains a few universal parameters and subdivides the molecular surface area into charged segments that interact with each other. In recent years, additional improvements to the construction of the sigma profiles and evaluation of activity coefficients have been made. In this work, we present a comprehensive description of how to postprocess the results of a COSMO calculation through to the evaluation of thermodynamic properties. We also assembled a large database of COSMO files, consisting of 2261 compounds, freely available to academic and noncommercial users. We especially focus on the documentation of the implementation and provide the optimized source code in C++, wrappers in Python, and sample sigma profiles calculated from each approach, as well as tests and validation results. The misunderstandings in the literature relating to COSMO-SAC are described and corrected. The computational efficiency of the implementation is demonstrated.

Modeling solubility of CO2 gas in room temperature ionic liquids using the COSMOSAC-LANL model: a first principles study

In this paper we present a thermodynamic model for asymmetric solutions with a special emphasis on solute-solvent interactions. The new "COSMOSAC-LANL" activity coefficient model is rooted in first principles calculations based on the COSMO model where the microscopic information passes to the macroscopic world via a dielectric continuum solvation model followed by a post statistical thermodynamic treatment of self-consistent properties of the solute particle. To model the activity coefficient at infinite dilution for the binary mixtures, a 3-suffix Margules (3sM) function is introduced to model asymmetric interactions and, for the combinatorial term, the Staverman-Guggenheim (SG) form is used. The new "COSMOSAC-LANL" activity coefficient model has been used to calculate the solubility of CO₂ in room temperature ionic liquids and to model the selectivity between CO₂ and CH₄ gases. We have shown improved solubility and selectivity prediction of CO₂ and CH₄ gas in room temperature ionic liquids using the ADF-COSMOSAC-2013 model with the new "LANL" activity coefficient model. The calculated values have been compared with experimental results where they are available.

Oil behavior in sea ice: Changes in chemical composition and resultant effect on sea ice dielectrics

There has been increasing urgency to develop methods for detecting oil in sea ice owing to the effects of climate change in the Arctic. A multidisciplinary study of crude oil behavior in a sea ice environment was conducted at the University of Manitoba during the winter of 2016. In the experiment, medium-light crude oil was injected underneath young sea ice in a mesocosm. The physical and thermodynamic properties of the oil-infiltrated sea ice were monitored over a three-week time span, with concomitant analysis of the oil composition using analytical instrumentation. A resonant perturbation technique was used to measure the oil dielectric properties, and the contaminated sea ice dielectric properties were modeled using a mixture model approach. Results showed that the interactions between the oil and sea ice altered their physical and thermodynamic properties. These changes led to an overall decrease in sea ice dielectrics, potentially detectable by remote sensing systems.

Solubility model of metal complex in ionic liquids from first principle calculations

A predictive model based on first principles calculations has been proposed to study the solid–liquid equilibria comprising of metal complexes and ionic liquids. The model is based on first principle COSMO calculation followed by post statistical thermodynamical treatment of self-consistent properties of solute and solvent molecules. The metal complex and ionic liquid have been treated as a simple binary mixture. The ionic liquid has been treated here as a single intact molecule. The experimentally observed dual-solute relationship between the ionic liquid and redox active species in presence of a third organic solvent has been established using our model in this work. Within the model, the dual-solute relationship appeared as a simple Gibbs–Duhem relationship between these two species at ambient condition. The dual-solute relationship between the metal complex (V(acac)₃, Cr(acac)₃ and Mn(acac)₃) and ionic liquid ([Tea][BF₄]) has been validated by calculating the Gibbs–Duhem relationship, x_solutevs. x_solvent(IL) and 1/γ_solutevs. x_solvent(IL) plots. The present model has been applied to a set of ionic liquids, metal complexes and organic solvent (acetonitrile) for which experimental study has been done. The solvation mechanism of the metal complexes in those ionic liquids was obtained using the model. According to our findings, the ionic liquid containing imidazolium cation and [NTf₂]⁻ anion is appeared as a suitable solvent for the non-aqueous redox flow cell. We have compared our results with the already reported experimental results where they were available for the non-aqueous solvents.

A predictive model based on first principles calculations has been proposed to study the solid–liquid equilibria comprising of metal complexes and ionic liquids.

Estimating system parameters for solvent-water and plant cuticle-water using quantum chemically estimated Abraham solute parameters

Polyparameter Linear Free Energy Relationships (pp-LFERs) using Abraham system parameters have many useful applications. However, developing the Abraham system parameters depends on the availability and quality of the Abraham solute parameters. Using Quantum Chemically estimated Abraham solute Parameters (QCAP) is shown to produce pp-LFERs that have lower root mean square errors (RMSEs) of predictions for solvent-water partition coefficients than parameters that are estimated using other presently available methods. pp-LFERs system parameters are estimated for solvent-water, plant cuticle-water systems, and for novel compounds using QCAP solute parameters and experimental partition coefficients. Refitting the system parameter improves the calculation accuracy and eliminates the bias. Refitted models for solvent-water partition coefficients using QCAP solute parameters give better results (RMSE = 0.278 to 0.506 log units for 24 systems) than those based on ABSOLV (0.326 to 0.618) and QSPR (0.294 to 0.700) solute parameters. For munition constituents and munition-like compounds not included in the calibration of the refitted model, QCAP solute parameters produce pp-LFER models with much lower RMSEs for solvent-water partition coefficients (RMSE = 0.734 and 0.664 for original and refitted model, respectively) than ABSOLV (4.46 and 5.98) and QSPR (2.838 and 2.723). Refitting plant cuticle-water pp-LFER including munition constituents using QCAP solute parameters also results in lower RMSE (RMSE = 0.386) than that using ABSOLV (0.778) and QSPR (0.512) solute parameters. Therefore, for fitting a model in situations for which experimental data exist and system parameters can be re-estimated, or for which system parameters do not exist and need to be developed, QCAP is the quantum chemical method of choice.

Quantum Chemically Estimated Abraham Solute Parameters Using Multiple Solvent-Water Partition Coefficients and Molecular Polarizability

Polyparameter Linear Free Energy Relationships (pp-LFERs), also called Linear Solvation Energy Relationships (LSERs), are used to predict many environmentally significant properties of chemicals. A method is presented for computing the necessary chemical parameters, the Abraham parameters (AP), used by many pp-LFERs. It employs quantum chemical calculations and uses only the chemical's molecular structure. The method computes the Abraham E parameter using density functional theory computed molecular polarizability and the Clausius-Mossotti equation relating the index refraction to the molecular polarizability, estimates the Abraham V as the COSMO calculated molecular volume, and computes the remaining AP S, A, and B jointly with a multiple linear regression using sixty-five solvent-water partition coefficients computed using the quantum mechanical COSMO-SAC solvation model. These solute parameters, referred to as Quantum Chemically estimated Abraham Parameters (QCAP), are further adjusted by fitting to experimentally based APs using QCAP parameters as the independent variables so that they are compatible with existing Abraham pp-LFERs. QCAP and adjusted QCAP for 1827 neutral chemicals are included. For 24 solvent-water systems including octanol-water, predicted log solvent-water partition coefficients using adjusted QCAP have the smallest root-mean-square errors (RMSEs, 0.314-0.602) compared to predictions made using APs estimated using the molecular fragment based method ABSOLV (0.45-0.716). For munition and munition-like compounds, adjusted QCAP has much lower RMSE (0.860) than does ABSOLV (4.45) which essentially fails for these compounds.

In silico environmental chemical science: properties and processes from statistical and computational modelling

Quantitative structure-activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with "in silico" results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs using descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for "in silico environmental chemical science" are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.

A Review of Biorefinery Separations for Bioproduct Production via Thermocatalytic Processing

With technological advancement of thermocatalytic processes for valorizing renewable biomass carbon, development of effective separation technologies for selective recovery of bioproducts from complex reaction media and their purification becomes essential. The high thermal sensitivity of biomass intermediates and their low volatility and high reactivity, along with the use of dilute solutions, make the bioproducts separations energy intensive and expensive. Novel separation techniques, including solvent extraction in biphasic systems and reactive adsorption using zeolite and carbon sorbents, membranes, and chromatography, have been developed. In parallel with experimental efforts, multiscale simulations have been reported for predicting solvent selection and adsorption separation. We discuss various separations that are potentially valuable to future biorefineries and the factors controlling separation performance. Particular emphasis is given to current gaps and opportunities for future development.

Predicting solvent-water partitioning of charged organic species using quantum-chemically estimated Abraham pp-LFER solute parameters

Methods for obtaining accurate predictions of solvent-water partitioning for neutral organic chemicals (e.g., K_ow) are well-established. However, methods that provide comparable accuracy are not available for predicting the solvent-water partitioning of ionic species. Previous methods for addressing charge contributions to solvent-water partitioning rely on charged solute descriptors which are obtained from regressions to neutral species descriptors as well as charged descriptors which are specific to unique charge-functionalities and structural moieties. This paper presents a method for obtaining Abraham poly-parameter linear free energy relationship (pp-LFER) descriptors using quantum chemical calculations and molecular structure, only. The method utilizes a large number of solvent-water systems to overcome large errors in individual quantum chemical computations of ionic solvent-water partition coefficients. The result is a single set of quantum-chemically estimated Abraham solute parameters (QCAP) which are solvent-independent, and can be used to predict the solvent-water partitioning of ionic species. Predictions of solvent-water partition coefficients for ionic species using quantum-chemically estimated Abraham parameters (QCAPs) are shown to provide improved accuracy compared over both existing Absolv-estimated Abraham solute parameters (AAP) as well as direct a priori quantum chemical (QC) calculations for partitioning of anionic solutes in 4 organic solvent-water systems (RMS = 0.740, 2.48 and 0.426 for the Absolv, QC and QCAP methods, respectively). For quaternary amine cations in the octanol-water system the RMS errors of the solvent-water partition coefficients were larger and similar between the two Abraham models (RMSE = 0.997 and 1.16, for the AAP and QCAP methods, respectively). Both methods showed significant improvement over direct QC calculations (RMSE = 2.82).