Potential Of Mean Force Calculations Research Articles

Affinity-based engineering of carbon nanotube embedded polyamide membranes for simultaneous desalination and boron removal

Reverse osmosis (RO) is the leading technology for obtaining drinking and irrigation water from seawater. Although currently developed RO membranes achieve high salt rejection; several challenges exist, such as permselectivity trade-off, biological/chemical contamination, and insufficient retention of small and neutral molecules like boric acid. Due to its toxicity to living organisms and strictly monitored levels in potable water, removal of boron has gained considerable attention in RO industry. Thin film nanocomposite (TFN) membranes have emerged by incorporating nanomaterials with superior water/salt selectivity into polyamide (PA) layer of composite membranes. For the first time, our group investigated the potential of carboxylated carbon nanotube (CNT) embedding in the selective layer of TFN membranes for boron removal. Within this frame, we hypothesize that embedding fillers with low boron affinity accompanied by high water permeability in the selective layer of TFN membranes improves boron removal without suffering from the permselectivity trade-off. In this study, we investigated the boron removal performance of functionalized CNT (f-CNT) embedded TFN membranes. Initially, CNTs were functionalized with three different functional groups (namely, biotin (BIO), 8-amino caprylic acid (ACA), and zwitterion (ZWT)) to narrow down the tube entrance, provide repulsive electrostatic interactions with boron, and interfere with the hydrogen bonding between water and boric acid molecules. Then, TFN membranes incorporating f-CNTs were fabricated, characterized, and tested. Showing high compatibility with PA, ZWT functionalization has increased water/boron selectivity of TFN membranes by 66% and water permeability by 44%, while maintaining the salt rejection at 98%. Furthermore, we employed molecular dynamics simulations and potential of mean force calculations to elucidate the boron exclusion mechanism in f-CNTs. With its flexible structure and “gate-keeper” ability, ZWT functional group was found to show the highest energy barrier against boron transport. Hence, engineering CNT/PA TFN membranes to promote steric hindrance and decrease solute affinity is promising for efficient removal of detrimental small molecules from seawater.

Free Energy Barriers for Passive Drug Transport through the Mycobacterium tuberculosis Outer Membrane: A Molecular Dynamics Study.

The emergence of multi-drug-resistant tuberculosis strains poses a significant challenge to modern medicine. The development of new antituberculosis drugs is hindered by the low permeability of many active compounds through the extremely strong bacterial cell wall of mycobacteria. In order to estimate the ability of potential antimycobacterial agents to diffuse through the outer mycolate membrane, the free energy profiles, the corresponding activation barriers, and possible permeability modes of passive transport for a series of known antibiotics, modern antituberculosis drugs, and prospective active drug-like molecules were determined using molecular dynamics simulations with the all-atom force field and potential of mean-force calculations. The membranes of different chemical and conformational compositions, density, thickness, and ionization states were examined. The typical activation barriers for the low-mass molecules penetrating through the most realistic membrane model were 6-13 kcal/mol for isoniazid, pyrazinamide, and etambutol, and 19 and 25 kcal/mol for bedaquilin and rifampicin. The barriers for the ionized molecules are usually in the range of 37-63 kcal/mol. The linear regression models were derived from the obtained data, allowing one to estimate the permeability barriers from simple physicochemical parameters of the diffusing molecules, notably lipophilicity and molecular polarizability.

Many-body potential for simulating the self-assembly of polymer-grafted nanoparticles in a polymer matrix

Many-body interactions between polymer-grafted nanoparticles (NPs) play a key role in promoting their assembly into low-dimensional structures within polymer melts, even when the particles are spherical and isotropically grafted. However, capturing such interactions in simulations of NP assembly is very challenging because explicit modeling of the polymer grafts and melt chains is highly computationally expensive, even using coarse-grained models. Here, we develop a many-body potential for describing the effective interactions between spherical polymer-grafted NPs in a polymer matrix through a machine-learning approach. The approach involves using permutationally invariant polynomials to fit two- and three-body interactions derived from the potential of mean force calculations. The potential developed here reduces the computational cost by several orders of magnitude, thereby, allowing us to explore assembly behavior over large length and time scales. We show that the potential not only reproduces previously known assembled phases such as 1D strings and 2D hexagonal sheets, which generally cannot be achieved using isotropic two-body potentials, but can also help discover interesting phases such as networks, clusters, and gels. We demonstrate how each of these assembly morphologies intrinsically arises from a competition between two- and three-body interactions. Our approach for deriving many-body effective potentials can be readily extended to other colloidal systems, enabling researchers to make accurate predictions of their behavior and dissect the role of individual interaction energy terms of the overall potential in the observed behavior.

Acetylation of Nanocellulose: Miscibility and Reinforcement Mechanisms in Polymer Nanocomposites.

The improvement of properties in nanocomposites obtained by topochemical surface modification, e.g., acetylation, of the nanoparticles is often ascribed to improved compatibility between the nanoparticle and the matrix. It is not always clear however what is intended: specific interactions at the interface leading to increased adhesion or the miscibility between the nanoparticle and the polymer. In this work, it is demonstrated that acetylation of cellulose nanocrystals greatly improves mechanical properties of their nanocomposites with polycaprolactone. In addition, molecular dynamics simulations with a combination of potential of mean force calculations and computational alchemy are employed to analyze the surface energies between the two components. The work of adhesion between the two phases decreases with acetylation. It is discussed how acetylation can still contribute to the miscibility, which leads to a stricter use of the concept of compatibility. The integrated experimental-modeling toolbox used has wide applicability for assessing changes in the miscibility of polymer nanocomposites.

Selective Photonic Gasification of Strained Oxygen Clusters on Graphene for Tuning Pore Size in the Å Regime.

Controlling the size of single-digit pores, such as those in graphene, with an Å resolution has been challenging due to the limited understanding of pore evolution at the atomic scale. The controlled oxidation of graphene has led to Å-scale pores; however, obtaining a fine control over pore evolution from the pore precursor (i.e., the oxygen cluster) is very attractive. Herein, we introduce a novel "control knob" for gasifying clusters to form pores. We show that the cluster evolves into a core/shell structure composed of an epoxy group surrounding an ether core in a bid to reduce the lattice strain at the cluster core. We then selectively gasified the strained core by exposing it to 3.2 eV of light at room temperature. This allowed for pore formation with improved control compared to thermal gasification. This is because, for the latter, cluster-cluster coalescence via thermally promoted epoxy diffusion cannot be ruled out. Using the oxidation temperature as a control knob, we were able to systematically increase the pore density while maintaining a narrow size distribution. This allowed us to increase H2 permeance as well as H2 selectivity. We further show that these pores could differentiate CH4 from N2, which is considered to be a challenging separation. Dedicated molecular dynamics simulations and potential of mean force calculations revealed that the free energy barrier for CH4 translocation through the pores was lower than that for N2. Overall, this study will inspire research on the controlled manipulation of clusters for improved precision in incorporating Å-scale pores in graphene.

Converging PMF Calculations of Antibiotic Permeation across an Outer Membrane Porin with Subkilocalorie per Mole Accuracy.

The emergence of multidrug-resistant pathogens led to a critical need for new antibiotics. A key property of effective antibiotics against Gram-negative bacteria is their ability to permeate through the bacterial outer membrane via transmembrane porin proteins. Molecular dynamics (MD) simulations are, in principle, capable of modeling antibiotic permeation across outer membrane porins (OMPs). However, owing to sampling problems, it has remained challenging to obtain converged potentials of mean force (PMFs) for antibiotic permeation across OMPs. Here, we investigated the convergence of PMFs along a single collective variable aimed at quantifying the permeation of the antibiotic fosmidomycin across the OprO porin. We compared standard umbrella sampling (US) with three advanced flavors of the US technique: (i) Hamiltonian replica exchange with solute tempering in combination with US, (ii) simulated tempering-enhanced US, and (iii) replica-exchange US. To quantify the PMF convergence and to reveal hysteresis problems, we computed several independent sets of US simulations starting from pulling simulations in the outward and inward permeation directions. We find that replica-exchange US in combination with well-chosen restraints is highly successful for obtaining converged PMFs of fosmidomycin permeation through OprO, reaching PMFs converged to subkilocalorie per mole accuracy.

Capillary suction under unsaturated condition drives strong specific affinity of ions at the surface of clay mineral

Mineral-solution interface is of great importance in many soil and geochemical processes as well as industrial applications. Most relevant studies were based on saturated condition and given the corresponding theory, model, and mechanism. However, soils are usually in the non-saturation with different capillary suction. Our study presents substantially different scenery for ions interacting with mineral surface under unsaturated condition using molecular dynamics method. Under partially hydrated state, both cations (Ca2+) and anions (Cl−) can be adsorbed as outer-sphere complexes at the montmorillonite surface, and the number significantly increased with the increase of unsaturated degree. Ions preferred to interact with clay mineral instead of water molecules under unsaturated state, and the mobility of both cations and anions substantially decreased with the increase of capillary suction as reflected by the diffusion coefficient analysis. Potential of mean force calculations further clearly revealed that the adsorption strength of both Ca2+ and Cl− increased with capillary suction. Such an increase was more obvious for Cl− compared to Ca2+, despite the adsorption strength of Cl− was much weaker than Ca2+ at a certain capillary suction. Therefore, it is the capillary suction under unsaturated condition that drives the strong specific affinity of ions at the surface of clay mineral, which was tightly related to the steric effect of confined water film, the destruction of EDL structure, and the cation-anion pair interaction. This suggests that our common understanding of mineral-solution interaction should be largely improved.

Ligand Effects in Assembly of Cubic and Spherical Nanocrystals: Applications to Packing of Perovskite Nanocubes.

We establish the formula representing cubic nanocrystals (NCs) as hard cubes taking into account the role of the ligands and describe how these results generalize to any other NC shapes. We derive the conditions under which the hard cube representation breaks down and provide explicit expressions for the effective size. We verify the results from the detailed potential of mean force calculations for two nanocubes in different orientations as well as with spherical nanocrystals. Our results explicitly demonstrate the relevance of certain ligand conformations, i.e., "vortices", and show that edges and corners provide natural sites for their emergence. We also provide both simulations and experimental results with single component cubic perovskite nanocrystals assembled into simple cubic superlattices, which further corroborate theoretical predictions. In this way, we extend the Orbifold Topological Model (OTM) accounting for the role of ligands beyond spherical nanocrystals and discuss its extension to arbitrary nanocrystal shapes. Our results provide detailed predictions for recent superlattices of perovskite nanocubes and spherical nanocrystals. Problems with existing united atom force fields are discussed.

Whether carbon nanotubes are suitable for delivering small drugs with aromatic rings through non-covalent adsorption?

Carbon Nanotubes (CNTs) have shown great prospect in the field of biomedicine. CNTs often act as vehicles to carry drugs through covalent attachment or noncovalent adsorption, due to their large surface area. Their hollow channels can also accommodate small drugs. However, the drugs may be trapped because of the great potential well of drugs in CNT, which is unfavorable to drug release. Whether CNTs are suitable for delivering small drugs especially those with aromatic rings is still unclear. In this work, we performed molecular dynamics simulations to study the transmembrane transport of drug carried by CNTs. Primidone (abbreviated as PRI) was selected as a model small drug, which has two aromatic rings that can interact with CNTs through π-π stacking. Two patterns of drug loading were taken into consideration. One is that drugs are trapped in the CNTs and another is that drugs are adsorbed on outer CNT surface. The two formed CNT-PRI complexes are thermodynamically stable in the water. Potential of mean force calculations show that CNTs have a great potential well to trap PRI molecules, which is not beneficial for PRI release from CNTs into the membrane. When PRI adsorbed on CNT surface, the complex can readily permeate into the membrane. Only after entering the lipid bilayer, can PRI leave the CNT and then diffuse in the membrane. Our results demonstrate that CNT’s inner space is not suitable to carry small drugs with aromatic rings, as π-π stacking enhances the trap of drugs in CNT and drugs are hard to leave. However, using CNT outer space to carry and deliver small drugs with aromatic rings is theoretically feasible. These findings may provide new insights for the drug delivery using CNTs as vehicles.

Simulated Tempering-Enhanced Umbrella Sampling Improves Convergence of Free Energy Calculations of Drug Membrane Permeation.

Molecular dynamics simulations have been widely used to study solute permeation across biological membranes. The potential of mean force (PMF) for solute permeation is typically computed using enhanced sampling techniques such as umbrella sampling (US). For bulky drug-like permeants, however, obtaining converged PMFs remains challenging and often requires long simulation times, resulting in an unacceptable computational cost. Here, we augmented US with simulated tempering (ST), an extended-ensemble technique that consists in varying the temperature of the system along a pre-defined temperature ladder. Simulated tempering-enhanced US (STeUS) was employed to improve the convergence of PMF calculations for the permeation of methanol and three common drug molecules. To obtain sufficient sampling of the umbrella histograms, which were computed only from the ground temperature, we modified the simulation time fraction spent at the ground temperature between 1/K and 50%, where K is the number of ST temperature states. We found that STeUS accelerates convergence, when compared to standard US, and that the benefit of STeUS is system-dependent. For bulky molecules, for which standard US poorly converged, the application of ST was highly successful, leading to a more than fivefold accelerated convergence of the PMFs. For the small methanol solute, for which conventional US converges moderately, the application of ST is only beneficial if 50% of the STeUS simulation time is spent at the ground temperature. This study establishes STeUS as an efficient and simple method for PMF calculations, thereby strongly reducing the computational cost of routine high-throughput studies of drug permeability.

Overcoming hysteresis in ligand binding potential of mean force calculations.

Accurate estimation of ligand binding free energy and elucidation of the corresponded binding pathway are key challenges in computational drug design. Umbrella sampling (US) molecular dynamic simulations are widely used to tackle these challenges; however, they frequently suffer from massive hysteresis between the ligand binding and unbinding pathways, limiting the applicability of US for ligand-protein interaction studies. The convergence of US is affected by the complexity of the system, the selection of reaction coordinate(s), simulation time, and by the selection of additional restraints.

Comparative Study of Receptor-, Receptor State-, and Membrane-Dependent Cholesterol Binding Sites in A2A and A1 Adenosine Receptors Using Coarse-Grained Molecular Dynamics Simulations.

We used coarse-grained molecular dynamics (CG MD) simulations to study protein-cholesterol interactions for different activation states of the A2A adenosine receptor (A2AR) and the A1 adenosine receptor (A1R) and predict new cholesterol binding sites indicating amino acid residues with a high residence time in three biologically relevant membranes. Compared to 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC)-cholesterol and POPC-phosphatidylinositol-bisphosphate (PIP2)-cholesterol, the plasma mimetic membrane best described the cholesterol binding sites previously detected for the inactive state of A2AR and revealed the binding sites with long-lasting amino acid residues. We observed that using the plasma mimetic membrane and plotting residues with cholesterol residence time ≥2 μs, our CG MD simulations captured most obviously the cholesterol-protein interactions. For the inactive A2AR, we identified one more binding site in which cholesterol is bound to residues with a long residence time compared to the previously detected, for the active A1R, three binding sites, and for the inactive A1R, two binding sites. We calculated that for the active states, cholesterol binds to residues with a much longer residence time compared to the inactive state for both A2AR and A1R. The stability of the identified binding sites to A1R or A2AR with CG MD simulations was additionally investigated with potential of mean force calculations using umbrella sampling. We observed that the binding sites with residues to which cholesterol has a long residence time in A2AR have shallow binding free energy minima compared to the related binding sites in A1R, suggesting a stronger binding for cholesterol to A1R. The differences in binding sites in which cholesterol is stabilized and interacts with residues with a long residence time between active and inactive states of A1R and A2AR can be important for differences in functional activity and orthosteric agonist or antagonist affinity and can be used for the design of allosteric modulators, which can bind through lipid pathways. We observed a stronger binding for cholesterol to A1R (i.e., generally higher association rates) compared to A2AR, which remains to be demonstrated. For the active states, cholesterol binds to residues with much longer residence times compared to the inactive state for both A2AR and A1R. Taken together, binding sites of active A1R may be considered as promising allosteric targets.

Spontaneous sieving of water from ethanol using angstrom-sized nanopores.

Ethanol is widely used as a precursor in products ranging from drugs to cosmetics. However, distillation of ethanol from aqueous solution is energy intensive and expensive. Here, we show that angstrom-sized nanopores with precisely controlled pore sizes can spontaneously remove water from ethanol-water mixtures through molecular sieving at room temperature and pressure. For small-diameter nanotubes, water-filling is observed, but ethanol is completely excluded, as evidenced by time-dependent density functional theory (TD-DFT) calculations and spectroscopy measurements. Potential of mean force calculations were performed to determine how the free energy barriers for water and ethanol-filling of the nanotubes change with increasing pore size. Water/ethanol selectivity ratio reaching as high as 6700 is observed with a (6,4) nanotube, which has a pore size of 0.204 nm. This selectivity vanishes as the pore size increases beyond 0.306 nm. These findings provide insights that may help realize energy efficient molecular sieving of ethanol and water.

Computational Evaluation of Peptide-Protein Binding Affinities: Application of Potential of Mean Force Calculations to SH2 Domains.

Many biological functions are mediated by protein-protein interactions (PPIs), often involving specific structural modules, such as SH2 domains. Inhibition of PPIs is a pharmaceutical strategy of growing importance. However, a major challenge in the design of PPI inhibitors is the large interface involved in these interactions, which, in many cases, makes inhibition by small organic molecules ineffective. Peptides, which cover a wide range of dimensions and can be opportunely designed to mimic protein sequences at PPI interfaces, represent a valuable alternative to small molecules. Computational techniques able to predict the binding affinity of peptides for the target domain or protein represent a crucial stage in the workflow for the design of peptide-based drugs. This chapter describes a protocol to obtain the potential of mean force (PMF) for peptide-SH2 domain binding, starting from umbrella sampling (US) molecular dynamics (MD) simulations. The PMF profiles can be effectively used to predict the relative standard binding free energies of different peptide sequences.

Limitations of non-polarizable force fields in describing anion binding poses in non-polar synthetic hosts.

Transmembrane anion transport by synthetic ionophores has received increasing interest not only because of its relevance for understanding endogenous anion transport, but also because of potential implications for therapeutic routes in disease states where chloride transport is impaired. Computational studies can shed light on the binding recognition process and can deepen our mechanistic understanding of them. However, the ability of molecular mechanics methods to properly capture solvation and binding properties of anions is known to be challenging. Consequently, polarizable models have been suggested to improve the accuracy of such calculations. In this study, we calculate binding free energies for different anions to the synthetic ionophore, biotin[6]uril hexamethyl ester in acetonitrile and to biotin[6]uril hexaacid in water by employing non-polarizable and polarizable force fields. Anion binding shows strong solvent dependency consistent with experimental studies. In water, the binding strengths are iodide > bromide > chloride, and reversed in acetonitrile. These trends are well captured by both classes of force fields. However, the free energy profiles obtained from potential of mean force calculations and preferred binding positions of anions depend on the treatment of electrostatics. Results from simulations using the AMOEBA force-field, which recapitulate the observed binding positions, suggest strong effects from multipoles dominate with a smaller contribution from polarization. The oxidation status of the macrocycle was also found to influence anion recognition in water. Overall, these results have implications for the understanding of anion host interactions not just in synthetic ionophores, but also in narrow cavities of biological ion channels.

Effect of salinity on water/oil interface with model asphaltene and non-ionic surfactant: Insights from molecular simulations

Water or brine always co-exist with oil during petroleum production, often in the form of emulsions which can be stabilized by surface-active components such as asphaltenes. Polymeric demulsifiers were frequently applied to destabilize the water/oil interface. To understand the demulsification mechanisms of water/oil emulsion, it is important to understand the effect of salinity on the stability of water/oil interface with adsorbed asphaltenes and polymeric demulsifiers. In this work, molecular dynamics simulations were performed on water/heptol interfaces under the influence of a model asphaltene (VO-79), a polymer demulsifier (PEO5-PPO10-PEO5) and varying concentrations of NaCl. Potential of mean force calculation indicated that when NaCl was added the magnitude of the adsorption free energy for VO-79 had insignificant changes and that for the polymer increased. In the absence of VO-79, the interfacial tension (IFT) at the water/heptol interface first increased upon increasing the NaCl concentration to 6 wt% and then decreased. The initial increase was attributed to the negative surface excess of salt while the subsequent decrease was due to the evident aggregation of salt ions in the water phase. With both polymer and VO-79 at the interface, the effect of salinity on IFT followed the same non-monotonic trend, except that the transition occurred at a lower concentration, which was caused by the mutual influence of H-bonds between adsorbates and water, and the surface excess of salt. The results provide useful insights into the effect of salinity on the stabilization and destabilization of water/oil interface.

PEGylated PAMAM dendrimers as eptifibatide nanocarriers: An atomistic view from molecular dynamics simulations

Acetylation and PEGylation can decrease cytotoxicity, improve biocompatibility, and reduce the rate of PAMAM dendrimers elimination from systemic circulation. However, there is scarce information on the microstructure and drug loading capacity of PEGylated dendrimers at atomic level. We have performed molecular dynamics simulations in order to explore the association of eptifibatide (EPT) with native acetyl-terminated G4-PAMAM dendrimer and its partially (25, 50, and 75 %) PEGylated analogues. The impact of PEG length was investigated using chains with molecular weight of 500 and 1000 Da. Maximum loading capacity was achieved by G4-16PEG1000 system (1:7) through the encapsulation of 4 EPT in internal cavities and conjugation of 3 EPT on surface. Potential of mean force calculations revealed that G4-48PEG500 tightly holds EPT molecules. In view of loading capacity, preferential binding sites of drug molecules, and release patterns, G4-16PEG1000 can be considered as the most promising carrier for EPT.

Liquid-phase exfoliation of graphitic carbon nitrides studied by molecular dynamics simulation

HypothesisThe superiority of graphitic carbon nitride (g-C3N4) nanosheet results from its large specific surface area, which can be achieved by exfoliation of the bulk layered structure. Liquid-phase exfoliation (LPE) is the best-known method for the synthesis of two-dimensional (2D) g-C3N4 nanosheets. However, experimental investigations do not allow for a molecular-level understanding of the process. Molecular dynamics (MD) simulations are expected to provide microscopic insights and quantitative evaluation of the energy consumption during LPE, thus facilitating the search of effective solvents for the LPE of 2D materials. SimulationsMD simulations are carried out to simulate the LPE process by performing potential of mean force calculations for the separation of two stacked g-C3N4 nanosheets. Free energy of exfoliation is evaluated and compared among nine common solvents with distinct molecular structures. FindingsThe most probable path for the exfoliation process is identified. The free energy of exfoliation is found to correlate directly with the solvent free energy of a single g-C3N4 nanosheet. The solvation is enthalpy-driven and affected by the mobility of the solvent molecules around the nanosheet. Based on the MD results, several strategies are proposed to guide the selection of solvents for effective LPE.

Molecular dynamics simulation of model asphaltenes between surfaces of varying polarity

The molecular interaction behaviors of a model asphaltene, N-(1-Hexylheptyl)-N'-(5-carboxylicpentyl) perylene-3,4,9,10-tetracarboxylic bisimide (C5Pe), between two solid surfaces of varying polarity, were studied by molecular dynamics simulations. The C5Pe molecules were solvated in water, toluene, or heptane, and the two substrate surfaces are hydrophilic alumina and relatively more hydrophobic siloxane surfaces (as model surfaces of two basal planes of kaolinite). Distinct adsorption behaviors were revealed by the simulations, which were driven and caused by the interaction of C5Pe molecules and surfaces of varying polarity in solvents of different nature. In water, both C5Pe monomer and aggregates adsorbed on the alumina surface, instead of the siloxane surface or staying in the liquid medium. Interestingly, in the control systems where a C5Pe molecule was placed between two identical surfaces in water, it displayed weaker adsorption when placed between two alumina surfaces than between two siloxane surfaces. Potential of mean force (PMF) calculations demonstrated the interplay between enthalpy-driven adsorption on the alumina surface and entropy-driven adsorption on the siloxane surface in water. In the adsorbed C5Pe aggregates on the alumina surface, the hydrophobic parts of the molecules stacked in a parallel manner and aligned perpendicularly to the alumina surface, while the hydrophilic parts formed hydrogen bonds with the surface. In toluene, C5Pe adsorbed on the alumina surface, driven by van der Waals and Coulomb interactions, as well as hydrogen bonding. A multi-layered C5Pe aggregate on the alumina surface in toluene was observed, which resulted from coordination bonds established through Ca2+ between C5Pe molecules. In heptane, adsorption was found on both alumina and siloxane surfaces, and PMF calculations showed similar strength of binding to the two surfaces. The adsorbed aggregates were compact, with intermolecular π-π stackings that were parallel to the surfaces. This work provides a mechanistic understanding of the interaction behaviors of asphaltenes in solution media when different clay surfaces are simultaneously present, how such behaviors may be influenced by the nature of the solvent, and the molecular forces driving such behaviors.

Modeling approaches for atmospheric ion–dipole collisions: all-atom trajectory simulations and central field methods

Abstract. Ion–dipole collisions can facilitate the formation of atmospheric aerosol particles and play an important role in their detection in chemical ionization mass spectrometers. Conventionally, analytical models, or simple parametrizations, have been used to calculate the rate coefficients of ion–dipole collisions in the gas phase. Such models, however, neglect the atomistic structure and charge distribution of the collision partners. To determine the accuracy and applicability of these approaches under atmospheric conditions, we calculated collision cross sections and rate coefficients from all-atom molecular dynamics collision trajectories, sampling the relevant range of impact parameters and relative velocities, and from a central field model using an effective attractive interaction fitted to the long-range potential of mean force between the collision partners. We considered collisions between various atmospherically relevant molecular ions and dipoles and charged and neutral dipolar clusters. Based on the good agreement between collision cross sections and rate coefficients obtained from molecular dynamics trajectories and a generalized central field model, we conclude that the effective interactions between the collision partners are isotropic to a high degree, and the model is able to capture the relevant physicochemical properties of the systems. In addition, when the potential of mean force is recalculated at the respective temperatures, the central field model exhibits the correct temperature dependence of the collision process. The classical parametrization by Su and Chesnavich (1982), which combines a central field model with simplified trajectory simulations, is able to predict the collision rate coefficients and their temperature dependence quite well for molecular systems, but the agreement worsens for systems containing clusters. Based on our results, we propose the combination of potential of mean force calculation and a central field model as a viable and elegant alternative to the brute force sampling of individual collision trajectories over a large range of impact parameters and relative velocities.