Solvation Model Research Articles

A computational DFT study of Imidazolium based Ionic liquids: binding energy calculation with different anions using Solvation Model

Basic knowledge of chemical events in the gaseous or liquid phase, as well as on surfaces, is required to determine the macroscopic process. The structure of ionic liquids were investigated using quantum chemistry. Cation and anion can bond together, according to the findings. Their binding and interaction energies reveal that they are produced by hydrogen bonds. The mechanism of a room temperature ionic liquid, such as [BMIM][Cl] (1-butyl-3-Methylimidazolium chloride) monomer, was studied using Density functional theory (DFT) computations using the modern continum solvation model (IEFPCM-SMD). Ionic liquid [IL] contains both anions and cations, allowing for greater intermolecular interactions. By analyzing the relative minimum energy of [BMIM][Cl] in the presence and absence of water, we were able to establish the minimum energy structures and probable Cl anion binding sites in [BMIM][Cl] ionic liquid. We have found that all 1-butyl-3-methylimidazolium halide ILs investigated had trans conformations due to the butyl group’s dihedral angles. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 9(1), 2022 P 66-70

New Insights in the Computational pKb Determination of Primary Amines and Anilines.

Extensive research has already provided reliable methods for the in silico prediction of pKa, while a trustworthy strategy for pKb determination is still being sought. Indeed, the approaches previously exploited for computing pKa have shown their weakness in predicting pKb. In the light of the exceptional reliability demonstrated in the pKa calculation of a wide panel of organic acids, in this work, we exploited our "easy to use methodology", based on the direct approach, to predict the pKb of primary amines. Herein, CAM-B3LYP was compared to WB97XD and B3PW91, exploring the solvation model based on density (SMD) and the polarizable continuum model (PCM), in the presence of two explicit water molecules. Noteworthy, CAM-B3LYP and WB97XD returned completely different solvent accessible surfaces (SAS) and electron potential maps (EPM) for the bases and the conjugated acids, independently from the nature of the substituents. Once again, CAM-B3LYP/SMD/2H2O method confirmed its remarkable reliability, leading to a minimum average error (MAE) lower than 0.3. This outstanding result strengthens the trustworthiness of our method, already successfully applied to predict the pKa of different substituted phenols and carboxylic acids. Thus, our "easy-to-use" process can predict also the pKb of primary ammines and anilines, always ensuring consistent outputs.

Charge Transfer Mechanism in Guanine-Based Self-Assembled Monolayers on a Gold Surface.

In this work, we have theoretically determined the one-electron oxidation potentials and charge transfer mechanisms in complex systems based on a self-assembled monolayer of guanine molecules adsorbed on a gold surface through different organic linkers. Classical molecular dynamics simulations were carried out to sample the conformational space of both the neutral and the cationic species. Thus, the redox potentials were determined for the ensembles of geometries through multiscale quantum-mechanics/molecular-mechanics/continuum solvation model calculations in the framework of the Marcus theory and in combination with an additive scheme previously developed. In this context, conformational sampling, description of the environment, and effects caused by the linker have been considered. Applying this methodology, we unravel the phenomena of electric current transport by evaluating the different stages in which charge transfer could occur. The results revealed how the positive charge migrates from the organic layer to the gold surface. Specifically, the transport mechanism seems to take place mainly along a single ligand and driven with the help of the electrostatic interactions of the surrounding molecules. Aside, several self-assembled monolayers with different linkers have been analyzed to understand how the nature of that moiety can tune the redox properties and the efficiency of the transport. We have found that the conjugation between the guanine and the linker, at the same time conjugated to the gold surface, gives rise to a more efficient transport. In conclusion, the established computational protocol sheds light on the mechanism behind charge transport in electrochemical DNA-based biosensor nanodevices.

Prediction on Air-Nasal Mucus Partition Coefficients of Odor Compounds.

The air-nasal mucus partition coefficient is a crucial property among all of the interaction mechanisms between odor molecules and olfactory receptors, since this property contributes to our sense of smell. Due to the complexity of the mucus composition, in vivo determination of the air-mucus partition coefficient is a technical challenge. A predictable model of the air-mucus partition coefficient can provide valuable insights into the chemical properties that govern olfactory perception and can help design desired odorants. In this study, we propose a novel model based on the deep-layer neural network (DNN) algorithm to predict the air-mucus partition coefficients for a range of odor compounds. The molecular surface charge density (σ-profile) calculated from the COnductor like Screening MOdel for Real Solvents (COSMO-RS) thermodynamic package was adapted as descriptors of structural features of odor molecules. The results revealed that the air-mucus partition coefficients are highly correlated to the σ-profile of the studied compounds. The information obtained from the study provided interpretable results, which not only help in identifying the molecular features that contribute to the air-mucus partition coefficient of odorants but also aid in the design of compounds with the desired odor properties.

Revisiting the electrochemical reduction of CO2 on Au25(SR)18− nanocluster

Experiments show that Au25(SR)18− is a potential electrocatalyst for the electrochemical reduction of CO2, but elucidation of the reaction mechanisms remain challenging experimentally. We evaluate key steps in the active site formation, CO2 reduction, and H2 evolution on the nanocluster employing density functional theory coupled with an explicit solvent model of the electrochemical interface to calculate activation barriers. The predicted preferred pathway for activating the nanocluster involves dethiolation, resulting in an exposed Au site that is both active and selective for CO2 reduction. The alternative S site is found to be kinetically prohibitive and does not facilitate CO2 reduction.

First and Second Reductions in an Aprotic Solvent: Comparing Computational and Experimental One-Electron Reduction Potentials for 345 Quinones.

Using reference reduction potentials of quinones recently measured relative to the saturated calomel electrode (SCE) in N,N-dimethylformamide (DMF), we benchmark absolute one-electron reduction potentials computed for 345 Q/Q•- and 265 Q•-/Q2- half-reactions using adiabatic electron affinities computed with density functional theory and solvation energies computed with four continuum solvation models: IEF-PCM, C-PCM, COSMO, and SM12. Regression analyses indicate a strong linear correlation between experimental and absolute computed Q/Q•- reduction potentials with Pearson's correlation coefficient (r) between 0.95 and 0.96 and the mean absolute error (MAE) relative to the linear fit between 83.29 and 89.51 mV for different solvation methods when the slope of the regression is constrained to 1. The same analysis for Q•-/Q2- gave a linear regression with r between 0.74 and 0.90 and MAE between 95.87 and 144.53 mV, respectively. The y-intercept values obtained from the linear regressions are in good agreement with the range of absolute reduction potentials reported in the literature for the SCE but reveal several sources of systematic error. The y-intercepts from Q•-/Q2- calculations are lower than those from Q/Q•- by around 320-410 mV for IEF-PCM, C-PCM, and SM12 compared to 210 mV for COSMO. Systematic errors also arise between molecules having different ring sizes (benzoquinones, naphthoquinones, and anthraquinones) and different substituents (titratable vs nontitratable). SCF convergence issues were found to be a source of random error that was slightly reduced by directly optimizing the solute structure in the continuum solvent reaction field. While SM12 MAEs were lower than those of the other solvation models for Q/Q•-, SM12 had larger MAEs for Q•-/Q2- pointing to a larger error when describing multiply charged anions in DMF. Altogether, the results highlight the advantages of, and further need for, testing computational methods using a large experimental data set that is not skewed (e.g., having more titratable than nontitratable substituents on different parent groups or vice versa) to help further distinguish between sources of random and systematic errors in the calculations.

Force Field X: A computational microscope to study genetic variation and organic crystals using theory and experiment.

Force Field X (FFX) is an open-source software package for atomic resolution modeling of genetic variants and organic crystals that leverages advanced potential energy functions and experimental data. FFX currently consists of nine modular packages with novel algorithms that include global optimization via a many-body expansion, acid-base chemistry using polarizable constant-pH molecular dynamics, estimation of free energy differences, generalized Kirkwood implicit solvent models, and many more. Applications of FFX focus on the use and development of a crystal structure prediction pipeline, biomolecular structure refinement against experimental datasets, and estimation of the thermodynamic effects of genetic variants on both proteins and nucleic acids. The use of Parallel Java and OpenMM combines to offer shared memory, message passing, and graphics processing unit parallelization for high performance simulations. Overall, the FFX platform serves as a computational microscope to study systems ranging from organic crystals to solvated biomolecular systems.

Unveiling Solvent Effects on β-Scissions through Metadynamics and Mean Force Integration.

This study introduces a methodology that combines accelerated molecular dynamics and mean force integration to investigate solvent effects on chemical reaction kinetics. The newly developed methodology is applied to the β-scission of butyl acrylate (BA) dimer in polar (water) and nonpolar (xylene and BA monomer) solvents. The results show that solvation in both polar and nonpolar environments reduces the free energy barrier of activation by ∼4 kcal/mol and decreases the pre-exponential factor 2-fold. Employing a hybrid quantum mechanics/molecular mechanics approach with explicit solvent modeling, we compute kinetic rate constants that better match experimental measurements compared to previous gas-phase calculations. This methodology presents promising potential for accurately predicting kinetic rate constants in liquid-phase polymerization and depolymerization processes.

Prediction of Redox Potentials for U, Np, Pu, and Am in Aqueous Solution.

The redox properties of the actinides in aqueous solution are important for fuel production/reprocessing and understanding the environmental impact of nuclear waste. The redox potentials for U, Np, Pu, and Am in oxidation states from 0 up to VII (as appropriate) in aqueous solutions have been predicted at the density functional theory level with the B3LYP functional, Stuttgart small core pseudopotential basis sets for the actinides, and explicit (30H2O molecules)/implicit treatment of the aqueous solvent using the self-consistent reaction field COSMO and SMD approaches for the implicit solvation. The predictions of the structural parameters of clusters incorporating first and second solvation shells are consistent with the available experimental data. Our results are typically within 0.2 V of the available experimental data using two explicit solvation shells with an implicit solvent model. The use of the PW91 functional substantially improved the prediction of the Pu(VI/V) redox couple. The redox couples for An(VI/IV) and An(V/IV) which involve the addition of protons and removal of the actinyl oxygens led to slightly larger differences from an experiment. The An(IV/0) and An(III/0) couples were reliably predicted with our approach. Predictions of the unknown An(II/I) redox potentials were negative, consistent with expectations, and predictions for unknown An(VII/VI), An(III/II), and An(II/0) redox couples improve prior estimates.

DdX: Polarizable continuum solvation from small molecules to proteins

AbstractPolarizable continuum solvation models are popular in both, quantum chemistry and in biophysics, though typically with different requirements for the numerical methods. However, the recent trend of multiscale modeling can be expected to blur field‐specific differences. In this regard, numerical methods based on domain decomposition (dd) have been demonstrated to be sufficiently flexible to be applied all across these levels of theory while remaining systematically accurate and efficient. In this contribution, we present ddX, an open‐source implementation of dd‐methods for various solvation models, which features a uniform interface with classical as well as quantum descriptions of the solute, or any hybrid versions thereof. We explain the key concepts of the library design and its application program interface, and demonstrate the use of ddX for integrating into standard chemistry packages. Numerical tests illustrate the performance of ddX and its interfaces.This article is categorized under: Software > Quantum Chemistry Software > Simulation Methods

Role of heads and tails on tetrahydrofuran- and dimethyl sulfoxide-water separation by glycerol and sucrose esters

Tetrahydrofuran (THF) and dimethylsulfoxide (DMSO) are miscible in water due to hydrogen (H) bonding. Amphiphilic glycerol and sucrose esters with a different number of tails and heads separate them, depending on the organic solvent concentration. Separation is worse in solutions where amphiphiles are most soluble. Separation occurs due to interactions between the amphiphiles and either organic solvents or water, as shown by attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR). Separation is best with glycerol esters with more heads and tails. Multiple tails hamper interactions between glycerol ester heads, thereby facilitating interactions with organic solvents or water to promote solvent–water separation. THF interacts with the glycerol ester tails, while water H bonds with the glycerol ester heads, as indicated by activity coefficients estimated with conductor-like screening model for real solvents. In THF, amphiphiles self-assemble into micelles, as shown by small angle x ray scattering (SAXS). Without water, THF is likely both inside and outside the micelles. SAXS shows that micelles shrink with 4% water in THF because water molecules partition inside them and are smaller than THF. With additional water, micelles swell into emulsions. Dissimilar to THF, DMSO preferentially interacts with the glycerol ester heads rather than their tails. ATR-FTIR shows that the proportion of free vs bonded S=O groups of DMSO decreases upon mixing with glycerol esters. DMSO and glycerol esters primarily accept H bonds, as indicated by their sigma profile. This leads to competition for interactions with water, displacing DMSO.

Multifunctional “Solvent‐in‐Diluent” High Voltage Electrolyte for Lithium Metal Batteries

AbstractSulfone liquids can be used as solvents for high‐voltage electrolytes and have been extensively studied for their strong oxidation resistance. However, the problem of high viscosity and susceptibility to side reactions with metallic lithium has been the subject of criticism. To solve the issue of incompatibility with lithium, researchers adopted a high‐concentration electrolyte, namely solvent‐in‐salt, which allows the anions in the lithium salt to preferentially contact the surface of the lithium metal and react to form an SEI film to block the reaction between sulfone solvents and lithium. However, the issue of high viscosity is particularly severe. This work proposes a new solvent model called “solvent‐in‐diluent” electrolyte to address both of these issues simultaneously, different from previous models of salt‐in‐solvent, the model not only effectively prevents sulfone contact with lithium metal surfaces, but also maintains a capacity retention rate of 82% after 500 cycles in the voltage range of 2.8–4.6 V, additionally, the temperature range in which the battery can operate using this electrolyte model has been extended (−20–60°C). This work proposes a new solvent model and challenges the minimum concentration of high‐voltage electrolytes (0.04 m), providing a new approach and possibility for studying high‐voltage electrolytes.

Screening of ionic liquids for the solubility enhancement of quinine using COSMO-RS

Quinine has traditionally been used in medicine to treat parasitic disease malaria due to its antimalarial activities. It is sparingly soluble in water and highly soluble in organic solvents. However, these solvents are not environmentally friendly, so greener solvents need to be explored and designed. Ionic liquids (ILs) were successfully observed to be greener and capable of dissolving biologically active compounds. However, finding a potential IL from millions of possible IL combinations is challenging. This work utilizes the conductor-like screening model for real solvents (COSMO-RS) to address this issue. This study aims to determine the dissolution behavior of quinine in ILs employing the COSMO-RS. A total of 540 IL combinations of 9 cations and 60 anions were investigated. The efficacy of each IL was evaluated by predicting the activity coefficients at infinite dilution, solvation-free energy, selectivity, capacity, and performance index (P.I.). This study reveals that ILs with shorter alkyl chains, polar and non-aromatic characteristics, and smaller anions are advantageous for the solubility enhancement ofquinine.The most effective ILs, choline acetate, choline glycinate, and choline threoninate, displayed the highest selectivity, capacity, P.I., and lowest activity coefficient and solvation-free energies. The findings of the current study unlock key insights into the solubility behaviour of quinine in an aqueous solution employing ILs.

Solvation model effects on the static first hyperpolarizability of a push–pull π‐conjugated molecule

AbstractIn this work, we presented the results of density functional theory calculations for the static first hyperpolarizability for one representative push–pull π‐conjugated molecule, 2‐dimethylamino‐7‐nitrofluorene, in six organic solvents (p‐dioxane, chloroform, tetrahydrofuran, acetone, acetonitrile, and dimethylsulfoxide) spanning a large range of dielectric constant. The finite‐field formalism was used to calculate the longitudinal component of the static first hyperpolarizability. The solvent effect was calculated using two distinct polarizable continuum solvation models: the linear response and the state‐specific polarizable continuum models. The calculations demonstrated the existence of solvation model effects on the property of interest, which warranted further analysis. The two‐level model was then employed to illustrate the impact of solvation model. Our findings suggested that the state‐specific polarizable continuum model gave a decrease of the dipole moment of the excited state in high polarity solvent for a bathochromic molecule whose excited state should have a larger polarization than its ground state.

Computational explorations about the solvent-polarity-associated excited state proton transfer behaviors for the novel F-BSD compound.

Inspired by the excellent potential application prospects from the precisely controlled attributes displayed by fluorine-substituted-bis(salicylidene)-1,5-diaminonaphthalene (F-BSD) and its derivatives in the domains of photochemistry and photophysics, our present undertaking predominantly focuses on exploring the complexities of photo-induced excited state reactions for F-BSD fluorophores dissolved in solvents with diverse levels of polarity. Our simulations reveal that the excited state intramolecular double proton transfer (ESIDPT) reaction for F-BSD chemosensor can be significantly regulated by solvent polarity-dependent hydrogen bonding interactions and charge recombination induced by photoexcitation, which result from variations in geometries and vertical excitation charge reorganizations. By constructing potential energy surfaces (PESs), we also demonstrate that the stepwise ESIDPT reaction of F-BSD occurs with alternative dual intramolecular hydrogen bonds (O1-H2···N3 or O4-H5···N6). Interestingly, we affirm polar solvents should be conducive to the first-step of ESIDPT process, while nonpolar solvents are in favor of the second step. We sincerely hope solvent polarity-dependent ESIDPT behavior will pave the way for future design of novel luminescent materials. The molecular geometries were optimized by DFT//TDDFT D3-B3LYP/TZVP theoretical level with IEFPCM solvent model in S0 and S1 states, respectively. This work also explores the energy level of target molecules with the computational vertical absorption spectra by TDDFT. All the simulations were carried out based on Gaussian 16 software. The core-valence bifurcation (CVB) indexes were obtained by using Multiwfn 3.8. Potential energy surfaces were constructed by the DFT//TDDFT D3-B3LYP/TZVP level based on restricted optimization, also the transition state (TS) forms were searched using the same level.

Machine learning approach to predict Hansen solubility parameters of cocrystal coformers via integrating group contribution and COSMO-RS

Hansen Solubility Parameters (HSPs) have been a hot topic on predicting the tendency of pharmaceutical cocrystals formation and cocrystal coformers (CCFs) screening. However, the limitation of such application is the lack of models to accurately predict the values of HSPs for drug CCFs with more structural complexity. Accordingly, three ML (machine learning) models, i.e. ANN (Artificial Neural Network), XGBoostRegressor (Extreme Gradient Boosting Regressor) and LGBMRegressor (Light Gradient Boosting Machine Regressor), were developed for predicting the HSPs on CCFs screening for drugs. The HSPs database for 181 CCFs (containing alcohols, alkenes, aromatics, haloalkanes, amines, ketones, ethers, amides, esters, pharmaceuticals, alkanes, acids, nitroalkanes) were established and classified into the training set (140 compounds) and the test set (41 compounds with various functional polarity and groups, covering solid reagents and solvents). The prediction molecular descriptors were combined from the GC (Group Contribution) methods, the COSMO-RS (the Conductor-like Screening Model for Real Solvents) sigma-moments and energy descriptors. The results showed that ANN and XGBoostRegressor beat out LGBMRegressor in predicting HSPs for CCFs. Finally, SHapley Additive exPlanations (SHAP) was employed to visualize and explain the most important characteristics and effects on predicting HSPs via XGBoostRegressor, indicating that CH3, M2 and MHbdon3 had a significant influence and high contribution to the prediction of δd, δp and δh, respectively. The coupled GC and COSMO-RS strategy had been proven as a promising tool to predict HSPs through XGBoostRegressor for screening, designing, and selecting CCFs for drugs.

Efficient screening and catalytic mechanism of TM@β-Te for nitrogen reduction reaction

At present, nitrogen reduction reaction (NRR) has become one critical method for NH3 production through the single-atom catalyst (SAC). A variety of TM@β-Te SACs, constructed by 28 transition metal (TM) atoms anchoring on monovacant β-Te substrate, are systematically investigated by using DFT calculations. An efficient “six-step” screening scheme is proposed to screen out potential NRR catalysts, during which the implicit and explicit solvent models are involved to evaluate competitive reactions of H2O and H+. The final selected (Ta, W)@β-Te catalysts have limiting potentials (UL) of −0.32 V and −0.37 V, respectively. Three intrinsic descriptors of φ (the ratio of number of valence electrons and electronegativity of TM atom), ΔG∗N(adsorption energy of a single N atom on the substrate) and ICOHP (Crystal orbital Hamiltonian integrals for TM-N bonds) are proposed and their correlations with UL are investigated to expound the catalytic activity and mechanism. The relationships of dN≡N ∼ φ, ΔG∗N2∼ φ, ΔG∗N∼ φ and ICOHP ∼ φ resemble “volcanoes”, where (Ta, W)@β-Te are located near the vertex as potential catalysts, which can be verified by scaling relationship of ICOHP and ΔG∗N. Moreover, the UL ∼ φ, UL ∼ ΔG∗Nand UL ∼ ICOHP can be used to determine the potential catalysts from rough catalyst screening to accurate determination of potential determining step (PDS) in catalytic reaction. The constant potential model is adopted to investigate the influences of electrode potentials on adsorption strength of NRR intermediates. This work is informative for the research of NRR process and catalyst design of monoalkenes, which offers an efficient and dependable approach for screening excellent NRR catalysts and revealing the origin of catalytic activity.

Evaluating asphaltene dispersion with choline chloride or menthol based deep eutectic solvents: A COSMO-RS analysis

Deep Eutectic Solvents (DESs) have emerged as a distinct class of solvents with unique properties and advantages over conventional Ionic Liquids (ILs) and organic solvents. This study specifically focuses on evaluating the potential of DESs as aggregation inhibitors for asphaltenes. Utilizing the Conductor-like Screening Model for Real Solvent (COSMO-RS) method, we investigated a series of DESs based on choline chloride and menthol. The COSMO-RS approach enabled the accurate prediction of key thermodynamic properties, including density, σ profiles (charge distribution), and σ potentials (electrostatic potential) of the DESs. Our findings identified eight DESs as particularly effective in dispersing asphaltenes, providing a promising foundation for further experimental validation and potential application in the petroleum industry.

Optical Rotation Predictions for Rigid Chiral Solute-Achiral Solvent 1:1 Complexes with the PCM Model

We computed specific optical rotations (ORs) in solution for forty-two solute–solvent combinations, involving seventeen chiral solutes and eight achiral solvents, using cam-B3LYP/aug-cc-PVTZ. Explicit solvent effects were considered by calculating Boltzmann-averaged ORs from multiple conformers of a 1:1 solute–solvent complex, with additional implicit solvation. The PCM solvation model correctly predicted OR signs for all combinations, while the “1:1 complex plus PCM“ schemes misjudged it in two cases. Norbornenone in cyclohexane displayed the largest absolute deviation, indicating an inadequate description of the cam-B3LYP functional’s delocalized electronic structure. Incorrect OR signs for fenchone in methanol with the ”1:1 complex plus PCM“ schemes underscored the limitations of our simplistic scheme, which incorporates explicit effects by averaging one-to-one interactions between solute and solvent. Considering computational costs, the ”1:1 complex plus PCM“ scheme may not be the optimal choice for our test set, as the PCM model alone suffices for accurate specific OR calculations in solution.

Inclusion of Water Multipoles into the Implicit Solvation Framework Leads to Accuracy Gains.

The current practical "workhorses" of the atomistic implicit solvation─the Poisson-Boltzmann (PB) and generalized Born (GB) models─face fundamental accuracy limitations. Here, we propose a computationally efficient implicit solvation framework, the Implicit Water Multipole GB (IWM-GB) model, that systematically incorporates the effects of multipole moments of water molecules in the first hydration shell of a solute, beyond the dipole water polarization already present at the PB/GB level. The framework explicitly accounts for coupling between polar and nonpolar contributions to the total solvation energy, which is missing from many implicit solvation models. An implementation of the framework, utilizing the GAFF force field and AM1-BCC atomic partial charges model, is parametrized and tested against the experimental hydration free energies of small molecules from the FreeSolv database. The resulting accuracy on the test set (RMSE ∼ 0.9 kcal/mol) is 12% better than that of the explicit solvation (TIP3P) treatment, which is orders of magnitude slower. We also find that the coupling between polar and nonpolar parts of the solvation free energy is essential to ensuring that several features of the IWM-GB model are physically meaningful, including the sign of the nonpolar contributions.