Long-range Electrostatic Interactions Research Articles

Enhanced ethanol dehydration performance of cationic COFs filled anionic alginate hybrid membranes

Adding charged fillers to incorporate long-range electrostatic interactions is an effective way to reduce structure defects and improve separation performance of polyelectrolyte membranes. In this study, three cationic covalent organic frameworks (COFs), TpEB, TpTGCl, and TpPy, were incorporated into anionic alginate to prepare hybrid membranes for pervaporation dehydration of ethanol. With the increase of electrostatic interaction, the decrease in the mobility of polymer chains leads to an increase in the crystallinity and selectivity. Meanwhile, the inherent hydrophilic channels of iCOFs provided additional mass transfer channels, increasing the membrane permeability. When separating a 90 wt% ethanol/water mixture at 76 °C, the hybrid membrane containing 15 wt% TpEB exhibited the highest separation performance with a permeation flux of 2460 g m-2 h-1 and a separation factor of 2110, and it also demonstrated ideal long-term stability. This work provides a new perspective for the selection of fillers in the design process of hybrid membranes in the future.

Peptides and metal ions: A successful marriage for developing artificial metalloproteins.

The mutual relationship between peptides and metal ions enables metalloproteins to have crucial roles in biological systems, including structural, sensing, electron transport, and catalytic functions. The effort to reproduce or/and enhance these roles, or even to create unprecedented functions, is the focus of protein design, the first step toward the comprehension of the complex machinery of nature. Nowadays, protein design allows the building of sophisticated scaffolds, with novel functions and exceptional stability. Recent progress in metalloprotein design has led to the building of peptides/proteins capable of orchestrating the desired functions of different metal cofactors. The structural diversity of peptides allows proper selection of first- and second-shell ligands, as well as long-range electrostatic and hydrophobic interactions, which represent precious tools for tuning metal properties. The scope of this review is to discuss the construction of metal sites in de novo designed and miniaturized scaffolds. Selected examples of mono-, di-, and multi-nuclear binding sites, from the last 20 years will be described in an effort to highlight key artificial models of catalytic or electron-transfer metalloproteins. The authors' goal is to make readers feel like guests at the marriage between peptides and metal ions while offering sources of inspiration for future architects of innovative, artificial metalloproteins.

Modelling iodine diffusion in 2D-Perovskites as a function of the length of the organic spacer molecules

Two-dimensional (2D) hybrid perovskites have emerged as promising materials for solar cell applications, offering increased stability and reduced ionic movements compared to the more commonly used 3D-perovskites. The atomistic mechanisms behind the lower ionic diffusion in these perovskites have remained rather underexplored. In this study, we have used density functional theory (DFT) to investigate the potential tunability of ionic movements in 2D-perovskites by varying the spacer molecules in the structure. We demonstrate that by changing the length of the spacer molecule, and thus the distance between the two-dimensional inorganic slabs of corner sharing lead halide octahedra, it is possible to significantly modulate the periodic potential distribution and long-range electrostatic interactions within these materials. This modulation has a distinct impact on the energy barriers for ionic movement. Notably, we find that longer spacer molecules decrease the energy barrier for in-plane iodine diffusion, while increasing the energy barrier for inter-layer diffusion. Furthermore, we observe a logarithmic relationship between the energy barrier for inter-layer diffusion and the inter-layer distance. These results clarify the mechanisms underlying the lower ionic movement in 2D-perovskites and open avenues for engineering ionic migration in novel 2D-perovskite structures, thus enhancing their applicability in optoelectronic technologies.

Towards atomistic modelling of solid Pb-O formation and dissolution in liquid lead coolant: Interatomic potential development

Microscopic description of solid Pb-O formation and dissolution in liquid lead coolant is important for the modelling of fast neutron reactors. For this purpose, in this work we develop interatomic potential models for lead melt with dissolved oxygen. Potentials fitting is based on ab initio density functional theory (DFT) calculations and quantum molecular dynamics. Two different potential models are trained on the DFT data using the force-matching method: a computationally cheap embedded atom method (EAM) potential and a computationally expensive machine-learned moment tensor potential (MTP) that allows reproducing DFT data very accurately. The potentials are further validated to reproduce the properties of lead melt and the coordination of oxygen atoms in molten lead. The diffusion coefficient for oxygen in molten lead is calculated and compared with the available experimental data. We analyse how these interatomic potential models describe the crystal structure of the solid lead oxide to consider PbO nucleation and dissolution in molten lead. We extensively discuss the arising problems with the description of long-range electrostatic interactions. The possibility of matching the experimental data on the oxygen solubility limit by tuning the EAM potential is shown.

From proton transfer to ionic liquids: How isolated domains of ion pairs grow to form extended network in diphenyl phosphate-bis(2-ethylhexyl) amine mixtures

HypothesisDiphenyl phosphate (DPP)/bis(2-ethylhexyl) amine (BEEA) liquid mixtures are expected to show peculiar self-assembly behavior due to their, respectively, acidic and basic nature which can trigger acid-base reaction. ExperimentThe properties of DPP/BEEA mixtures of different compositions are explored by a combined theoretical (Ab initio calculations) and experimental (rheology, X-ray and light scattering) approach. Findings(i) a proton transfer from DPP to BEEA takes place with formation of cationic and anionic species in liquid phase (ion pair formation); (ii) due to the strong and long-range electrostatic interactions, each of the two charged species is preferentially surrounded by the other one, in a picture resembling the structure of ionic materials; (iii) this gives rise to a striking viscosity increase takes place as DPP concentration increases; (iv) the composition dependencies of all measured parameters show clear deviations around DPP molar fraction of 0.2, indicating unequivocally the formation of isolated domains, formed by DPP-BEEA pairs which coalescence/percolate into a unique, extended, network at higher DPP concentrations.

Incorporating long-range electrostatics in neural network potentials via variational charge equilibration from shortsighted ingredients

We present a new approach to construct machine-learned interatomic potentials including long-range electrostatic interactions based on a charge equilibration scheme. This new approach can accurately describe the potential energy surface of systems with ionic and covalent interactions as well as systems with multiple charge states. Moreover, it can either be regressed against known atomic charge decompositions or trained without charge targets, without compromising the accuracy of energy and forces. We benchmark our approach against other state-of-the-art models and prove it to have equivalent performances on a set of simple reference systems while being less computationally expensive. Finally, we demonstrate the accuracy of our approach on complex systems: solid and liquid state sodium chloride. We attain accuracy in energy and forces better than the model based on local descriptors and show that our electrostatic approach can capture the density functional theory tail of the potential energy surface of the isolated Na-Cl dimer, which the local descriptor-based model fails to describe.

Implementing the spherical grids and treecode algorithm for efficient parallelization of long-range electrostatic interactions

Implementing the spherical grids and treecode algorithm for efficient parallelization of long-range electrostatic interactions

Effect of histidine protonation state on ligand binding at the ATP-binding site of human protein kinase CK2

Histidine residues contribute to numerous molecular interactions, owing to their structure with the ionizable aromatic side chain with pKa close to the physiological pH. Herein, we studied how the two histidine residues, His115 and His160 of the catalytic subunit of human protein kinase CK2, affect the binding of the halogenated heterocyclic ligands at the ATP-binding site. Thermodynamic studies on the interaction between five variants of hCK2α (WT protein and four histidine mutants) and three ionizable bromo-benzotriazoles and their conditionally non-ionizable benzimidazole counterparts were performed with nanoDSF, MST, and ITC. The results allowed us to identify the contribution of interactions involving the particular histidine residues to ligand binding. We showed that despite the well-documented hydrogen bonding/salt bridge formation dragging the anionic ligands towards Lys68, the protonated His160 also contributes to the binding of such ligands by long-range electrostatic interactions. Simultaneously, His 115 indirectly affects ligand binding, placing the hinge region in open/closed conformations.

Ligand coupling mechanism of the human serotonin transporter differentiates substrates from inhibitors

The presynaptic serotonin transporter (SERT) clears extracellular serotonin following vesicular release to ensure temporal and spatial regulation of serotonergic signalling and neurotransmitter homeostasis. Prescription drugs used to treat neurobehavioral disorders, including depression, anxiety, and obsessive-compulsive disorder, trap SERT by blocking the transport cycle. In contrast, illicit drugs of abuse like amphetamines reverse SERT directionality, causing serotonin efflux. Both processes result in increased extracellular serotonin levels. By combining molecular dynamics simulations with biochemical experiments and using a homologous series of serotonin analogues, we uncovered the coupling mechanism between the substrate and the transporter, which triggers the uptake of serotonin. Free energy analysis showed that only scaffold-bound substrates could initiate SERT occlusion through attractive long-range electrostatic interactions acting on the bundle domain. The associated spatial requirements define substrate and inhibitor properties, enabling additional possibilities for rational drug design approaches.

PMC-IZ: A Simple Algorithm for the Electrostatics Calculation in Slab Geometric Molecular Dynamics Simulations.

Slab geometric systems are widely utilized in molecular simulations. However, an efficient, straightforward, and accurate method for calculating electrostatic interactions in these systems for molecular dynamics (MD) simulations is still needed. This review introduces a PME-like approach called PMC-IZ, specifically designed for slab geometric systems. Traditional approaches for long-range electrostatic interaction calculations in slab geometry typically involve Ewald summation, where the Gaussian charge density is summed within 3D unit cells and then integrated in the 2D periodic space. In the proposed approach here, the Poisson equation was solved for a single Gaussian charge density within 2Dl periodic space, followed by convolution within 3D unit cells using an effective potential as the convolution kernel for summation. The effective potential ensures that the solution within the region of interest adheres strictly to 2D periodic boundary conditions while inherently possessing 3D periodic boundary condition properties. The PMC-IZ method provides for such systems accurate treatment of electrostatic interactions, overcomes limitations associated with finite vacuum layers, and offers improved computational efficiency. We thus postulate that this method provides a valuable tool for studying electrostatic interactions in slab geometric system MD simulations. It has promising applications in various areas such as surface science, catalysis, and materials research, where accurate modeling of slab geometric electrostatic interactions is essential.

Guidelines for Free-Energy Calculations Involving Charge Changes.

The Coulomb interactions in molecular simulations are inherently approximated due to the finite size of the molecular box sizes amenable to current-day compute power. Several methods exist for treating long-range electrostatic interactions, yet these approaches are subject to various finite-size-related artifacts. Lattice-sum methods are frequently used to approximate long-range interactions; however, these approaches also suffer from artifacts which become particularly pronounced for free-energy calculations that involve charge changes. The artifacts, however, also affect the sampling when plain simulations are performed, leading to a biased ensemble. Here, we investigate two previously described model systems to determine if artifacts continue to play a role when overall neutral boxes are considered, in the context of both free-energy calculations and sampling. We find that ensuring that no net-charge changes take place, while maintaining a neutral simulation box, may be sufficient provided that the simulation boxes are large enough. Addition of salt to the solution (when appropriate) can further alleviate the remaining artifacts in the sampling or the calculated free-energy differences. We provide practical guidelines to avoid finite-size artifacts.

Influence of ion and hydration atmospheres on RNA structure and dynamics: insights from advanced theoretical and computational methods.

RNA, a highly charged biopolymer composed of negatively charged phosphate groups, defies electrostatic repulsion to adopt well-defined, compact structures. Hence, the presence of positively charged metal ions is crucial not only for RNA's charge neutralization, but they also coherently decorate the ion atmosphere of RNA to stabilize its compact fold. This feature article elucidates various modes of close RNA-ion interactions, with a special emphasis on Mg2+ as an outer-sphere and inner-sphere ion. Through examples, we highlight how inner-sphere chelated Mg2+ stabilizes RNA pseudoknots, while outer-sphere ions can also exert long-range electrostatic interactions, inducing groove narrowing, coaxial helical stacking, and RNA ring formation. In addition to investigating the RNA's ion environment, we note that the RNA's hydration environment is relatively underexplored. Our study delves into its profound interplay with the structural dynamics of RNA, employing state-of-the-art atomistic simulation techniques. Through examples, we illustrate how specific ions and water molecules are associated with RNA functions, leveraging atomistic simulations to identify preferential ion binding and hydration sites. However, understanding their impact(s) on the RNA structure remains challenging due to the involvement of large length and long time scales associated with RNA's dynamic nature. Nevertheless, our contributions and recent advances in coarse-grained simulation techniques offer insights into large-scale structural changes dynamically linked to the RNA ion atmosphere. In this connection, we also review how different cutting-edge computational simulation methods provide a microscopic lens into the influence of ions and hydration on RNA structure and dynamics, elucidating distinct ion atmospheric components and specific hydration layers and their individual and collective impacts.

Multiscale Frozen Density Embedding/Molecular Mechanics Approach for Simulating Magnetic Response Properties of Solvated Systems.

We present a three-layer hybrid quantum mechanical/quantum embedding/molecular mechanics approach for calculating nuclear magnetic resonance (NMR) shieldings and J-couplings of molecular systems in solution. The model is based on the frozen density embedding (FDE) and polarizable fluctuating charges (FQ) and fluctuating dipoles (FQFμ) force fields and permits the accurate ab initio description of short-range nonelectrostatic interactions by means of the FDE shell and cost-effective treatment of long-range electrostatic interactions through the polarizable force field FQ(Fμ). Our approach's accuracy and potential are demonstrated by studying NMR spectra of Brooker's merocyanine in aqueous and nonaqueous solutions.

Unveiling Enhanced Electrostatic Repulsion in Silica Nanosphere Assembly: Formation Dynamics of Body-Centered-Cubic Colloidal Crystals.

We demonstrate the effective establishment of long-range electrostatic interactions among colloidal silica nanospheres through acid treatment, enabling their assembly into colloidal crystals at remarkably low concentrations. This novel method overcomes the conventional limitation in colloidal silica assembly by removing entrapped NH4+ ions and enhancing the electrical double layer (EDL) thickness, offering a time-efficient alternative to increase electrostatic interactions compared with methods like dialysis. The increased EDL thickness facilitates the assembly of SiO2 nanospheres into a body-centered-cubic lattice structure at low particle concentrations, allowing for broad spectrum tunability and high tolerance to particle size polydispersity. Further, we uncover a disorder-order transition during colloidal crystallization at low particle concentrations, with the optimal concentration for crystal formation governed by both thermodynamic and kinetic factors. This work not only provides insights into assembly mechanisms but also paves the way for the design and functionalization of colloidal silica-based photonic crystals in diverse applications.

Probing the self-ionization of liquid water with ab initio deep potential molecular dynamics.

The chemical equilibrium between self-ionized and molecular water dictates the acid-base chemistry in aqueous solutions, yet understanding the microscopic mechanisms of water self-ionization remains experimentally and computationally challenging. Herein, Density Functional Theory (DFT)-based deep neural network (DNN) potentials are combined with enhanced sampling techniques and a global acid-base collective variable to perform extensive atomistic simulations of water self-ionization for model systems of increasing size. The explicit inclusion of long-range electrostatic interactions in the DNN potential is found to be crucial to accurately reproduce the DFT free energy profile of solvated water ion pairs in small (64 and 128 H2O) cells. The reversible work to separate the hydroxide and hydronium to a distance [Formula: see text] is found to converge for simulation cells containing more than 500 H2O, and a distance of [Formula: see text] 8 Å is the threshold beyond which the work to further separate the two ions becomes approximately zero. The slow convergence of the potential of mean force with system size is related to a restructuring of water and an increase of the local order around the water ions. Calculation of the dissociation equilibrium constant illustrates the key role of long-range electrostatics and entropic effects in the water autoionization process.

Manipulation of Hierarchical Chiral Self-assembly and Anion Recognition by Supramolecular Systems of β-Glucopyranoside, Pillar[5]arenes, and Polyoxometalates.

Hierarchical chiral structures have broad applications in optical devices, asymmetric catalysis, and biological systems. The delicate balance of various interactions are key to the self-assembly of chiral structures. Herein, a ternary co-assembly consisting of cationic pillar[5]arenes (P5As), anionic β-glucopyranoside (βGlcD/βGlcL), and Anderson-type polyoxometalates (POMs) were constructed. Through adjusting the stoichiometry of βGlcD, the assemblies were effectively controlled to form hierarchical nano-leaf assemblies with twisted nanoribbons in a homochiral direction. The co-assemblies exhibit strong Cotton effects, and successfully induced the chirality of Anderson-type POMs. More interestingly, by changing the central metal in Anderson-type POMs (XMo6 O24 3- (X=Cr, Al, and Ga)), even though the three clusters have the same numbers of charge and size, the hierarchical chirality of the related assemblies varied in the morphology of the assemblies and the Cotton effect in the CD spectra. Results in theoretical calculations and ITC titration indicates that the tiny difference in long-range electrostatic interaction would result in the anion recognition of POMs, modulated by βGlcD through host-guest inclusion and hydrogen bonding in the assembly process.

Visualizing interfacial collective reaction behaviour of Li-S batteries.

Benefiting from high energy density (2,600 Wh kg-1) and low cost, lithium-sulfur (Li-S) batteries are considered promising candidates for advanced energy-storage systems1-4. Despite tremendous efforts in suppressing the long-standing shuttle effect of lithium polysulfides5-7, understanding of the interfacial reactions of lithium polysulfides at the nanoscale remains elusive. This is mainly because of the limitations of in situ characterization tools in tracing theliquid-solid conversion of unstable lithium polysulfides at high temporal-spatial resolution8-10. There is an urgent need to understand the coupled phenomena inside Li-S batteries, specifically, the dynamic distribution, aggregation, deposition and dissolution of lithium polysulfides. Here, by using in situ liquid-cell electrochemical transmission electron microscopy, we directly visualized the transformation of lithium polysulfides over electrode surfaces at the atomic scale. Notably, an unexpected gathering-induced collective charge transfer of lithium polysulfides was captured onthe nanocluster active-centre-immobilized surface. It further induced an instantaneous deposition of nonequilibrium Li2S nanocrystals from the dense liquid phase of lithium polysulfides. Without mediation of active centres, the reactions followed a classical single-molecule pathway, lithium polysulfides transforming into Li2S2 and Li2S step by step. Molecular dynamics simulations indicated that the long-range electrostatic interaction between active centres and lithium polysulfides promoted the formation of adense phase consisting of Li+ and Sn2- (2 < n ≤ 6), and the collective charge transfer in thedense phase was further verified by ab initio molecular dynamics simulations. The collective interfacial reaction pathway unveils a new transformation mechanism and deepens the fundamental understanding of Li-S batteries.

Charge-driven liquid-crystalline behavior of ligand-functionalized nanorods in apolar solvent.

Concentrated colloidal suspensions of nanorods often exhibit liquid-crystalline (LC) behavior. The transition to a nematic LC phase, with long-range orientational order of the particles, is usually well-captured by Onsager's theory for hard rods, at least qualitatively. The theory shows how the volume fraction at the transition decreases with increasing aspect ratio of the rods. It also explains that the long-range electrostatic repulsive interaction occurring between rods stabilized by their surface charge can significantly increase their effective diameter, resulting in a decrease in the volume fraction at the transition, as compared to sterically stabilized rods. Here, we report on a system of ligand-stabilized LaPO4 nanorods, of aspect ratio ≈11, dispersed in apolar medium exhibiting the counter-intuitive observation that the onset of nematic self-assembly occurs at an extremely low volume fraction of ≈0.25%, which is lower than observed (≈3%) with the same particles when charged-stabilized in polar solvent. Furthermore, the nanorod volume fraction at the transition increases with increasing concentration of ligands, in a similar way as in polar media where increasing the ionic strength leads to surface charge screening. This peculiar system was investigated by dynamic light scattering, Fourier-transform infrared spectroscopy, zetametry, electron microscopy, polarized light microscopy, photoluminescence measurements, and X-ray scattering. Based on these experimental data, we formulate several tentative scenarios that might explain this unexpected phase behavior. However, at this stage, its full understanding remains a pending theoretical challenge. Nevertheless, this study shows that dispersing anisotropic nanoparticles in an apolar solvent may sometimes lead to spontaneous ordering events that defy our intuitive ideas about colloidal systems.

PANNA 2.0: Efficient neural network interatomic potentials and new architectures.

We present the latest release of PANNA 2.0 (Properties from Artificial Neural Network Architectures), a code for the generation of neural network interatomic potentials based on local atomic descriptors and multilayer perceptrons. Built on a new back end, this new release of PANNA features improved tools for customizing and monitoring network training, better graphics processing unit support including a fast descriptor calculator, new plugins for external codes, and a new architecture for the inclusion of long-range electrostatic interactions through a variational charge equilibration scheme. We present an overview of the main features of the new code, and several benchmarks comparing the accuracy of PANNA models to the state of the art, on commonly used benchmarks as well as richer datasets.

Nucleoside Analog Reverse-Transcriptase Inhibitors in Membrane Environment: Molecular Dynamics Simulations.

The behavior of four drugs from the family of nucleoside analog reverse-transcriptase inhibitors (zalcitabine, stavudine, didanosine, and apricitabine) in a membrane environment was traced using molecular dynamics simulations. The simulation models included bilayers and monolayers composed of POPC and POPG phospholipids. It was demonstrated that the drugs have a higher affinity towards POPG membranes than POPC membranes due to attractive long-range electrostatic interactions. The results obtained for monolayers were consistent with those obtained for bilayers. The drugs accumulated in the phospholipid polar headgroup region. Two adsorption modes were distinguished. They differed in the degree of penetration of the hydrophilic headgroup region. Hydrogen bonds between drug molecules and phospholipid heads were responsible for adsorption. It was shown that apricitabine penetrated the hydrophilic part of the POPC and POPG membranes more effectively than the other drugs. Van der Waals interactions between S atoms and lipids were responsible for this.