Inhibition of Aqueous Chemical Reactions by Strong Liquid Structure Makers: Experimental Demonstration with Amides and Acid-Base Reactions.

The chemical absorption of CO2 and H2S in aqueous tertiary amines is a well-known acid-base reaction. Kinetic and vapor-liquid equilibrium experiments show that the addition of an amide such as HMPA, which is known to be a strong liquid structure maker, significantly inhibits the acid-base reactions. The impact is more pronounced for CO2 than for H2S absorption. Despite the presence of water in the solvent, the absorption becomes almost physical. Due to hydrogen bonding and the hydrophobic effect, each amide molecule is involved in a cluster containing several water molecules, thus rendering the water molecules less available to participate in the reaction and to solvate HS- and HCO3- ions. This effect is absent when ethylene glycol, a weak structure maker, is added, even in large quantities. This study demonstrates the importance of solvent structure in the study of chemical reactions. State-of-the-art molecular dynamics simulations of the water-HMPA system could not reproduce the strongly negative excess volume of the mixture. This illustrates the need for more accurate force fields to simulate the structuring effect and their impact on chemical reactions.

Solving Chemical Absorption Equilibria using Free Energy and Quantum Chemistry Calculations: Methodology, Limitations, and New Open-Source Software.

We developed an open-source chemical reaction equilibrium solver in Python (CASpy, https://github.com/omoultosEthTuDelft/CASpy) to compute the concentration of species in any reactive liquid-phase absorption system. We derived an expression for a mole fraction-based equilibrium constant as a function of excess chemical potential, standard ideal gas chemical potential, temperature, and volume. As a case study, we computed the CO2 absorption isotherm and speciation in a 23 wt % N-methyldiethanolamine (MDEA)/water solution at 313.15 K, and compared the results with available data from the literature. The results show that the computed CO2 isotherms and speciations are in excellent agreement with experimental data, demonstrating the accuracy and the precision of our solver. The binary absorptions of CO2 and H2S in 50 wt % MDEA/water solutions at 323.15 K were computed and compared with available data from the literature. The computed CO2 isotherms showed good agreement with other modeling studies from the literature while the computed H2S isotherms did not agree well with experimental data. The experimental equilibrium constants used as an input were not adjusted for H2S/CO2/MDEA/water systems and need to be adjusted for this system. Using free energy calculations with two different force fields (GAFF and OPLS-AA) and quantum chemistry calculations, we computed the equilibrium constant (K) of the protonated MDEA dissociation reaction. Despite the good agreement of the OPLS-AA force field (ln[K] = -24.91) with the experiments (ln[K] = -23.04), the computed CO2 pressures were significantly underestimated. We systematically investigated the limitations of computing CO2 absorption isotherms using free energy and quantum chemistry calculations and showed that the computed values of µiex are very sensitive to the point charges used in the simulations, which limits the predictive power of this method.

Computational screening methodology identifies effective solvents for CO2 capture.

Carbon capture and storage technologies are projected to increasingly contribute to cleaner energy transitions by significantly reducing CO2 emissions from fossil fuel-driven power and industrial plants. The industry standard technology for CO2 capture is chemical absorption with aqueous alkanolamines, which are often being mixed with an activator, piperazine, to increase the overall CO2 absorption rate. Inefficiency of the process due to the parasitic energy required for thermal regeneration of the solvent drives the search for new tertiary amines with better kinetics. Improving the efficiency of experimental screening using computational tools is challenging due to the complex nature of chemical absorption. We have developed a novel computational approach that combines kinetic experiments, molecular simulations and machine learning for the in silico screening of hundreds of prospective candidates and identify a class of tertiary amines that absorbs CO2 faster than a typical commercial solvent when mixed with piperazine, which was confirmed experimentally.

Chemoinformatics-Driven Design of New Physical Solvents for Selective CO2 Absorption.

The removal of CO2 from gases is an important industrial process in the transition to a low-carbon economy. The use of selective physical (co-)solvents is especially perspective in cases when the amount of CO2 is large as it enables one to lower the energy requirements for solvent regeneration. However, only a few physical solvents have found industrial application and the design of new ones can pave the way to more efficient gas treatment techniques. Experimental screening of gas solubility is a labor-intensive process, and solubility modeling is a viable strategy to reduce the number of solvents subject to experimental measurements. In this paper, a chemoinformatics-based modeling workflow was applied to build a predictive model for the solubility of CO2 and four other industrially important gases (CO, CH4, H2, and N2). A dataset containing solubilities of gases in 280 solvents was collected from literature sources and supplemented with the new data for six solvents measured in the present study. A modeling workflow based on the usage of several state-of-the-art machine learning algorithms was applied to establish quantitative structure-solubility relationships. The best models were used to perform virtual screening of the industrially produced chemicals. It enabled the identification of compounds with high predicted CO2 solubility and selectivity toward other gases. The prediction for one of the compounds, 4-methylmorpholine, was confirmed experimentally.

Vapor pressures and vapor phase compositions of choline chloride urea and choline chloride ethylene glycol deep eutectic solvents from molecular simulation.

Despite the widespread acknowledgment that deep eutectic solvents (DESs) have negligible vapor pressures, very few studies in which the vapor pressures of these solvents are measured or computed are available. Similarly, the vapor phase composition is known for only a few DESs. In this study, for the first time, the vapor pressures and vapor phase compositions of choline chloride urea (ChClU) and choline chloride ethylene glycol (ChClEg) DESs are computed using Monte Carlo simulations. The partial pressures of the DES components were obtained from liquid and vapor phase excess Gibbs energies, computed using thermodynamic integration. The enthalpies of vaporization were computed from the obtained vapor pressures, and the results were in reasonable agreement with the few available experimental data in the literature. It was found that the vapor phases of both DESs were dominated by the most volatile component (hydrogen bond donor, HBD, i.e., urea or ethylene glycol), i.e., 100% HBD in ChClEg and 88%-93% HBD in ChClU. Higher vapor pressures were observed for ChClEg compared to ChClU due to the higher volatility of ethylene glycol compared to urea. The influence of the liquid composition of the DESs on the computed properties was studied by considering different mole fractions (i.e., 0.6, 0.67, and 0.75) of the HBD. Except for the partial pressure of ethylene glycol in ChClEg, all the computed partial pressures and enthalpies of vaporization showed insensitivity toward the liquid composition. The activity coefficient of ethylene glycol in ChClEg was computed at different liquid phase mole fractions, showing negative deviations from Raoult's law.

New Features of the Open Source Monte Carlo Software Brick-CFCMC: Thermodynamic Integration and Hybrid Trial Moves.

We present several new major features added to the Monte Carlo (MC) simulation code Brick-CFCMC for phase- and reaction equilibria calculations (https://gitlab.com/ETh_TU_Delft/Brick-CFCMC). The first one is thermodynamic integration for the computation of excess chemical potentials (µex). For this purpose, we implemented the computation of the ensemble average of the derivative of the potential energy with respect to the scaling factor for intermolecular interactions (⟨∂U∂λ⟩). Efficient bookkeeping is implemented so that the quantity ∂U∂λ is updated after every MC trial move with negligible computational cost. We demonstrate the accuracy and reliability of the calculation of µex for sodium chloride in water. Second, we implemented hybrid MC/MD translation and rotation trial moves to increase the efficiency of sampling of the configuration space. In these trial moves, short Molecular Dynamics (MD) trajectories are performed to collectively displace or rotate all molecules in the system. These trajectories are accepted or rejected based on the total energy drift. The efficiency of these trial moves can be tuned by changing the time step and the trajectory length. The new trial moves are demonstrated using MC simulations of a viscous fluid (deep eutectic solvent).

Quantitative Kinetic Model of CO2 Absorption in Aqueous Tertiary Amine Solvents.

Aqueous tertiary amine solutions are increasingly used in industrial CO2 capture operations because they are more energy-efficient than primary or secondary amines and demonstrate higher CO2 absorption capacity. Yet, tertiary amine solutions have a significant drawback in that they tend to have lower CO2 absorption rates. To identify tertiary amines that absorb CO2 faster, it would be efficacious to have a quantitative and predictive model of the rate-controlling processes. Despite numerous attempts to date, this goal has been elusive. The present computational approach achieves this goal by focusing on the reaction of CO2 with OH- forming HCO3-. The performance of the resulting model is demonstrated for a consistent experimental data set of the absorption rates of CO2 for 24 different aqueous tertiary amine solvents. The key to the new model's success is the manner in which the free energy barrier for the reaction of CO2 with OH- is evaluated from the differences among the solvation free energies of CO2, OH-, and HCO3-, while the pKa of the amines controls the concentration of OH-. These solvation energies are obtained from molecular dynamics simulations. The experimental value of the free energy of reaction of CO2 with pure water is combined with information about measured rates of absorption of CO2 in an aqueous amine solvent in order to calibrate the absorption rate model. This model achieves a relative accuracy better than 0.1 kJ mol-1 for the free energies of activation for CO2 absorption in aqueous amine solutions and 0.07 g L-1 min-1 for the absorption rate of CO2. Such high accuracies are necessary to predict the correct experimental ranking of CO2 absorption rates, thus providing a quantitative approach of practical interest.

Understanding the phase behavior of coarse-grained model lipid bilayers through computational calorimetry.

We study the phase behavior of saturated lipids as a function of temperature and tail length for two coarse-grained models: the soft-repulsive model typically employed with dissipative particle dynamics (DPD) and the MARTINI model. We characterize the simulated transitions through changes in structural properties, and we introduce a computational method to monitor changes in enthalpy, as is done experimentally with differential scanning calorimetry. The lipid system experimentally presents four different bilayer phases - subgel, gel, ripple, and fluid - and the DPD model describes all of these phases structurally while MARTINI describes a single order-disorder transition between the gel and the fluid phases. Given both models' varying degrees of success in displaying accurate structural and thermodynamic signatures, there is an overall satisfying extent of agreement for the coarse-grained models. We also study the lipid dynamics displayed by these models for the various phases, discussing this dynamics with relation to fidelity to experiment and computational efficiency.

Molecular simulation of the effect of cholesterol on lipid-mediated protein-protein interactions.

Experiments and molecular simulations have shown that the hydrophobic mismatch between proteins and membranes contributes significantly to lipid-mediated protein-protein interactions. In this article, we discuss the effect of cholesterol on lipid-mediated protein-protein interactions as function of hydrophobic mismatch, protein diameter and protein cluster size, lipid tail length, and temperature. To do so, we study a mesoscopic model of a hydrated bilayer containing lipids and cholesterol in which proteins are embedded, with a hybrid dissipative particle dynamics-Monte Carlo method. We propose a mechanism by which cholesterol affects protein interactions: protein-induced, cholesterol-enriched, or cholesterol-depleted lipid shells surrounding the proteins affect the lipid-mediated protein-protein interactions. Our calculations of the potential of mean force between proteins and protein clusters show that the addition of cholesterol dramatically reduces repulsive lipid-mediated interactions between proteins (protein clusters) with positive mismatch, but does not affect attractive interactions between proteins with negative mismatch. Cholesterol has only a modest effect on the repulsive interactions between proteins with different mismatch.

Molecular simulation of the DMPC-cholesterol phase diagram.

In this paper, we present a coarse-grained model of a hydrated saturated phospholipid bilayer (dimyristoylphosphatidylcholine, DMPC) containing cholesterol that we study using a hybrid dissipative particle dynamics-Monte Carlo method. This approach allows us to reach the time and length scales necessary to study structural and mechanical properties of the bilayer at various temperatures and cholesterol concentrations. The properties studied are the area per lipid, condensation, bilayer thickness, tail order parameters, bending modulus, and area compressibility. Our model quantitatively reproduces most of the experimental effects of cholesterol on these properties and reproduces the main features of the experimental phase and structure diagrams. We also present all-atom simulation results of the system and use these results to further validate the structure of our coarse-grained bilayer. On the basis of the changes in structural properties, we propose a temperature-composition structure diagram, which we compare with the experimental phase and structure diagrams. Attention is paid to the reliability and interpretation of the model and simulation method and of the different experimental techniques. The lateral organization of cholesterol in the bilayer is discussed.

Towards an understanding of membrane-mediated protein-protein interactions.

We propose a computational framework to study the lipid-mediated clustering of integral membrane proteins. Our method employs a hierarchical approach. The potential of mean force (PMF) of two interacting proteins is computed under a coarse-grained 3-D model that successfully describes the structural properties of reconstituted lipid bilayers of dymiristoylphophatidylcholine (DMPC) molecules. Subsequently, a 2-D model is adopted, where proteins represented as self-avoiding disks interact through the previously computed PMF, which is modified to take into account three body corrections. The aggregation of the proteins is extensively studied under the condition of negative hydrophobic mismatch: the formation of clusters with increasing size agrees with previous computational and experimental findings.

Effect of cholesterol on the structure of a phospholipid bilayer.

Cholesterol plays an important role in regulating the properties of phospholipid membranes. To obtain a detailed understanding of the lipid-cholesterol interactions, we have developed a mesoscopic water-lipid-cholesterol model. In this model, we take into account the hydrophobic-hydrophilic interactions and the structure of the molecules. We compute the phase diagram of dimyristoylphosphatidylcholine-cholesterol by using dissipative particle dynamics and show that our model predicts many of the different phases that have been observed experimentally. In quantitative agreement with experimental data our model also shows the condensation effect; upon the addition of cholesterol, the area per lipid decreases more than one would expect from ideal mixing. Our calculations show that this effect is maximal close to the main-phase transition temperature, the lowest temperature for which the membrane is in the liquid phase, and is directly related to the increase of this main-phase transition temperature upon addition of cholesterol. We demonstrate that no condensation is observed if we slightly change the structure of the cholesterol molecule by adding an extra hydrophilic head group or if we decrease the size of the hydrophobic part of cholesterol.

Molecular simulations of lipid-mediated protein-protein interactions.

Recent experimental results revealed that lipid-mediated interactions due to hydrophobic forces may be important in determining the protein topology after insertion in the membrane, in regulating the protein activity, in protein aggregation and in signal transduction. To gain insight into the lipid-mediated interactions between two intrinsic membrane proteins, we developed a mesoscopic model of a lipid bilayer with embedded proteins, which we studied with dissipative particle dynamics. Our calculations of the potential of mean force between transmembrane proteins show that hydrophobic forces drive long-range protein-protein interactions and that the nature of these interactions depends on the length of the protein hydrophobic segment, on the three-dimensional structure of the protein and on the properties of the lipid bilayer. To understand the nature of the computed potentials of mean force, the concept of hydrophilic shielding is introduced. The observed protein interactions are interpreted as resulting from the dynamic reorganization of the system to maintain an optimal hydrophilic shielding of the protein and lipid hydrophobic parts, within the constraint of the flexibility of the components. Our results could lead to a better understanding of several membrane processes in which protein interactions are involved.