Correction: Phase behavior of patchy colloids confined in patchy porous media.

Correction for 'Phase behavior of patchy colloids confined in patchy porous media' by Yurij V. Kalyuzhnyi et al., Nanoscale, 2024, 16, 4668-4677, https://doi.org/10.1039/D3NR02866F.

Phase behavior of patchy colloids confined in patchy porous media.

A simple model for functionalized disordered porous media is proposed and the effects of confinement on self-association, percolation and phase behavior of a fluid of patchy particles are studied. The media are formed by randomly distributed hard-sphere obstacles fixed in space and decorated by a certain number of off-center square-well sites. The properties of the fluid of patchy particles, represented by the fluid of hard spheres each bearing a set of the off-center square-well sites, are studied using an appropriate combination of the scaled particle theory for the porous media, Wertheim's thermodynamic perturbation theory, and Flory-Stockmayer theory. To assess the accuracy of the theory a set of computer simulations have been performed. In general, predictions of the theory appeared to be in good agreement with the computer simulation results. Confinement and competition between the formation of bonds connecting the fluid particles, and connecting fluid particles and obstacles of the matrix, gave rise to a re-entrant phase behavior with three critical points and two separate regions of the liquid-gas phase coexistence.

Development of Heteroatomic Constant Potential Method with Application to MXene-Based Supercapacitors.

We describe a method for modeling constant-potential charges in heteroatomic electrodes, keeping pace with the increasing complexity of electrode composition and nanostructure in electrochemical research. The proposed "heteroatomic constant potential method" (HCPM) uses minimal added parameters to handle differing electronegativities and chemical hardnesses of different elements, which we fit to density functional theory (DFT) partial charge predictions in this paper by using derivative-free optimization. To demonstrate the model, we performed molecular dynamics simulations using both HCPM and conventional constant potential method (CPM) for MXene electrodes with Li-TFSI/AN (lithium bis(trifluoromethane sulfonyl)imide/acetonitrile)-based solvent-in-salt electrolytes. Although the two methods show similar accumulated charge storage on the electrodes, the results indicated that HCPM provides a more reliable depiction of electrode atom charge distribution and charge response compared with CPM, accompanied by increased cationic attraction to the MXene surface. These results highlight the influence of elemental composition on electrode performance, and the flexibility of our HCPM opens up new avenues for studying the performance of diverse heteroatomic electrodes including other types of MXenes, two-dimensional materials, metal-organic frameworks (MOFs), and doped carbonaceous electrodes.

E(n) Equivariant Graph Neural Network for Learning Interactional Properties of Molecules.

We have developed a multi-input E(n) equivariant graph convolution-based model designed for the prediction of chemical properties that result from the interaction of heterogeneous molecular structures. By incorporating spatial features and constraining the functions learned from these features to be equivariant to E(n) symmetries, the interactional-equivariant graph neural network (IEGNN) can efficiently learn from the 3D structure of multiple molecules. To verify the IEGNN's capability to learn interactional properties, we tested the model's performance on three molecular data sets, two of which are curated in this study and made publicly available for future interactional model benchmarking. To enable the loading of these data sets, an open-source data structure based on the PyTorch Geometric library for batch loading multigraph data points is also created. Finally, the IEGNN's performance on a data set consisting of an unknown interactional relationship (the frictional properties resulting between monolayers with variable composition) is examined. The IEGNN model developed was found to have the lowest mean absolute percent error for the predicted tribological properties of four of the six data sets when compared to previous methods.

MoSDeF-GOMC: Python Software for the Creation of Scientific Workflows for the Monte Carlo Simulation Engine GOMC.

MoSDeF-GOMC is a python interface for the Monte Carlo software GOMC to the Molecular Simulation Design Framework (MoSDeF) ecosystem. MoSDeF-GOMC automates the process of generating initial coordinates, assigning force field parameters, and writing coordinate (PDB), connectivity (PSF), force field parameter, and simulation control files. The software lowers entry barriers for novice users while allowing advanced users to create complex workflows that encapsulate simulation setup, execution, and data analysis in a single script. All relevant simulation parameters are encoded within the workflow, ensuring reproducible simulations. MoSDeF-GOMC's capabilities are illustrated through a number of examples, including prediction of the adsorption isotherm for CO2 in IRMOF-1, free energies of hydration for neon and radon over a broad temperature range, and the vapor-liquid coexistence curve of a four-component surrogate for the jet fuel S-8. The MoSDeF-GOMC software is available on GitHub at https://github.com/GOMC-WSU/MoSDeF-GOMC.

Structure-Dynamics Interrelation Governing Charge Transport in Cosolvated Acetonitrile/LiTFSI Solutions.

Concentrated ionic solutions present a potential improvement for liquid electrolytes. However, their conductivity is limited by high viscosities, which can be attenuated via cosolvation. This study employs a series of experiments and molecular dynamics simulations to investigate how different cosolvents influence the local structure and charge transport in concentrated lithium bis(trifluoromethane-sulfonyl)imide (LiTFSI)/acetonitrile solutions. Regardless of whether the cosolvent's dielectric constant is low (for toluene and dichloromethane), moderate (acetone), or high (methanol and water), they preserve the structural and dynamical features of the cosolvent-free precursor. However, the dissimilar effects of each case must be individually interpreted. Toluene and dichloromethane reduce the conductivity by narrowing the distribution of Li+-TFSI- interactions and increasing the activation energies for ionic motions. Methanol and water broaden the distributions of Li+-TFSI- interactions, replace acetonitrile in the Li+ solvation, and favor short-range Li+-Li+ interactions. Still, these cosolvents strongly interact with TFSI-, leading to conductivities lower than that predicted by the Nernst-Einstein relation. Finally, acetone preserves the ion-ion interactions from the cosolvent-free solution but forms large solvation complexes by joining acetonitrile in the Li+ solvation. We demonstrate that cosolvation affects conductivity beyond simply changing viscosity and provide fairly unexplored molecular-scale perspectives regarding structure/transport phenomena relation in concentrated ionic solutions.

Universal Ligands for Dispersion of Two-Dimensional MXene in Organic Solvents.

Ligands can control the surface chemistry, physicochemical properties, processing, and applications of nanomaterials. MXenes are the fastest growing family of two-dimensional (2D) nanomaterials, showing promise for energy, electronic, and environmental applications. However, complex oxidation states, surface terminal groups, and interaction with the environment have hindered the development of organic ligands suitable for MXenes. Here, we demonstrate a simple, fast, scalable, and universally applicable ligand chemistry for MXenes using alkylated 3,4-dihydroxy-l-phenylalanine (ADOPA). Due to the strong hydrogen-bonding and π-electron interactions between the catechol head and surface terminal groups of MXenes and the presence of a hydrophobic fluorinated alkyl tail compatible with organic solvents, the ADOPA ligands functionalize MXene surfaces under mild reaction conditions without sacrificing their properties. Stable colloidal solutions and highly concentrated liquid crystals of various MXenes, including Ti2CTx, Nb2CTx, V2CTx, Mo2CTx, Ti3C2Tx, Ti3CNTx, Mo2TiC2Tx, Mo2Ti2C3Tx, and Ti4N3Tx, have been produced in various organic solvents. Such products offer excellent electrical conductivity, improved oxidation stability, and excellent processability, enabling applications in flexible electrodes and electromagnetic interference shielding.

Controlling the Ion Transport Number in Solvent-in-Salt Solutions.

Solvent-in-salt (SIS) systems present promising materials for the next generation of energy storage applications. The ion dynamics is significantly different in these systems from that of ionic liquids and diluted salt solutions. In this study, we analyze the ion dynamics of two salts, Li-TFSI and Li-FSI, in highly concentrated aqueous and acetonitrile solutions. We performed high-frequency dielectric measurements covering the range of up to 50 GHz and molecular dynamics simulations. The analysis of the conductivity spectra provides the characteristic crossover time between individual charge rearrangements and the normal charge diffusion regime resulting in DC conductivity. Analysis revealed that the onset of normal charge diffusion occurs at the scale of ∼1.5-3.5 Å, comparable to the average distance between the ions. Based on the idea of momentum conservation, distinct ion correlations were estimated experimentally and computationally. The analysis revealed that cation-anion correlations can be suppressed by changing the solvent concentration in SIS systems, leading to an increase of the light ion (Li+ in our case) transport number. This discovery suggests a way for improving the light cation transport number in SIS systems by tuning the solvent concentration.

NMR and Theoretical Study of In-Pore Diffusivity of Ionic Liquid-Solvent Mixtures.

Despite having a lower energy density than common batteries, electric double-layer capacitors (EDLCs) offer several advantages for high-power applications, including high power density, quick charge and discharge time, and long cycle life. Room-temperature ionic liquids (RTILs) have been intensely studied as promising electrolytes for applications in ELDCs because of their wide potential window, low volatility, as well as thermal and chemical stability. The main deficiency of neat RTILs in such applications is the sluggish diffusivity, which restricts the EDLCs' power density. To alleviate the slow diffusivity, RTILs can be used in a mixture with organic solvents. In this study, we applied two-dimensional exchange nuclear magnetic resonance spectroscopy (2D EXSY NMR) and molecular dynamics (MD) simulations to investigate the diffusivity of anions of an RTIL, namely, 1-butyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl)imide (BMIM+-TFSI-), dissolved in five different organic solvents, in the micropores of activated carbon. We determined that the relative concentrations of ions in solutions in the micropores were higher than those in the bulk solutions and were also solvent-dependent. The ion diffusivities in the pores were found to be almost 2 orders of magnitude slower than in the bulk solutions, with methanol showing the largest relative disparity. These results suggested that the interactions of solvents with the activated carbon are critical not only to the power density of EDLCs but also to the energy density. The comparisons of ion diffusivities between the experiments and the MD simulations suggest the need to consider also the surface functionalities of activated carbon for the simulation of ion diffusion in the micropores of activated carbon.

High-throughput screening of tribological properties of monolayer films using molecular dynamics and machine learning.

Monolayer films have shown promise as a lubricating layer to reduce friction and wear of mechanical devices with separations on the nanoscale. These films have a vast design space with many tunable properties that can affect their tribological effectiveness. For example, terminal group chemistry, film composition, and backbone chemistry can all lead to films with significantly different tribological properties. This design space, however, is very difficult to explore without a combinatorial approach and an automatable, reproducible, and extensible workflow to screen for promising candidate films. Using the Molecular Simulation Design Framework (MoSDeF), a combinatorial screening study was performed to explore 9747 unique monolayer films (116 964 total simulations) and a machine learning (ML) model using a random forest regressor, an ensemble learning technique, to explore the role of terminal group chemistry and its effect on tribological effectiveness. The most promising films were found to contain small terminal groups such as cyano and ethylene. The ML model was subsequently applied to screen terminal group candidates identified from the ChEMBL small molecule library. Approximately 193 131 unique film candidates were screened with approximately a five order of magnitude speed-up in analysis compared to simulation alone. The ML model was thus able to be used as a predictive tool to greatly speed up the initial screening of promising candidate films for future simulation studies, suggesting that computational screening in combination with ML can greatly increase the throughput in combinatorial approaches to generate in silico data and then train ML models in a controlled, self-consistent fashion.

Direct Correlation of the Salt-Reduced Diffusivities of Organic Solvents with the Solvent's Mole Fraction.

Lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in organic solvents (especially propylene carbonate) has demonstrated extraordinary pseudocapacitive performance as an electrolyte in the supercapacitor configuration ( Nat. Energy 2019, 4, 241-248). However, the influence of the solvated ions on the diffusivity of the solvent molecules is yet to be understood. We examine the impact of LiTFSI on the diffusivity in five organic solvents: acetonitrile (ACN), tetrahydrofuran (THF), methanol (MeOH), dimethyl sulfoxide (DMSO), and propylene carbonate (PC) using a combination of neutron scattering, conductivity measurements, and molecular dynamics simulations. The extent of the diffusivity reduction in the concentration regime of ≤1 M directly correlates with the solvent mole fraction at which the solvation shells around Li+ ions are of similar size in all the solvents, resulting in a universal ∼50% reduction in the solvent diffusivity. These results provide guidance for formulation of the new electrolytes to enhance the performance of energy storage devices.

Investigation of Multilayered Structures of Ionic Liquids on Graphite and Platinum Using Atomic Force Microscopy and Molecular Simulations.

The molecular-level orientation and structure of ionic liquids (ILs) at liquid-solid interfaces are significantly different than in the bulk. The interfacial ordering influences both IL properties, such as dielectric constants and viscosity, and their efficacy in devices, such as fuel cells and electrical capacitors. Here, we report the layered structures of four ILs on unbiased, highly ordered pyrolytic graphite (HOPG) and Pt(111) surfaces, as determined by atomic force microscopy. The ILs investigated are 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([emim][Tf2N]), 1-ethyl-3-methylimidazolium perfluorobutylsulfonate ([emim][C4F9SO3]), 7-methyl-1,5,7-triazabicyclo[4.4.0]dec-5-ene bis(trifluoromethylsulfonyl)imide ([MTBD][Tf2N]), and 7-methyl-1,5,7-triazabicyclo[4.4.0]dec-5-ene perfluorobutylsulfonate ([MTBD][C4F9SO3]). Molecular dynamics simulations provide complementary information on the position and orientation of the ions. These ILs form a cation layer at the IL-solid interface, followed by a layer of anions. [Emim]+ and [MTBD]+ have similar orientations at the surface, but [MTBD]+ forms a thinner layer compared to [emim]+ on both HOPG and Pt(111). In addition, [Tf2N]- shows stronger interactions with Pt(111) surfaces than [C4F9SO3]-.

In situ investigation of water on MXene interfaces.

A continuum of water populations can exist in nanoscale layered materials, which impacts transport phenomena relevant for separation, adsorption, and charge storage processes. Quantification and direct interrogation of water structure and organization are important in order to design materials with molecular-level control for emerging energy and water applications. Through combining molecular simulations with ambient-pressure X-ray photoelectron spectroscopy, X-ray diffraction, and diffuse reflectance infrared Fourier transform spectroscopy, we directly probe hydration mechanisms at confined and nonconfined regions in nanolayered transition-metal carbide materials. Hydrophobic (K+) cations decrease water mobility within the confined interlayer and accelerate water removal at nonconfined surfaces. Hydrophilic cations (Li+) increase water mobility within the confined interlayer and decrease water-removal rates at nonconfined surfaces. Solutes, rather than the surface terminating groups, are shown to be more impactful on the kinetics of water adsorption and desorption. Calculations from grand canonical molecular dynamics demonstrate that hydrophilic cations (Li+) actively aid in water adsorption at MXene interfaces. In contrast, hydrophobic cations (K+) weakly interact with water, leading to higher degrees of water ordering (orientation) and faster removal at elevated temperatures.

Investigating the Accuracy of Water Models through the Van Hove Correlation Function.

We present molecular-simulation-based calculations of the Van Hove correlation function (VHF) of water using multiple modeling approaches: classical molecular dynamics with simple three-site nonpolarizable models, with a polarizable model, and with a reactive force field; density functional tight-binding molecular dynamics; and ab initio molecular dynamics. Due to the many orders of magnitude difference in the computational cost of these approaches, we investigate how small and short the simulations can be while still yielding sufficiently accurate and interpretable results for the VHF. We investigate the accuracy of the different models by comparing them to recently published inelastic X-ray scattering measurements of the VHF. We find that all of the models exhibit qualitative agreement with the experiments, and in some models and for some properties, the agreement is quantitative. This work lays the foundation for future simulation approaches to calculating the VHF for aqueous solutions in bulk and under nanoconfinement.

A mathematical model for Escherichia coli chemotaxis to competing stimuli.

Chemotactic bacteria sense and respond to temporal and spatial gradients of chemical cues in their surroundings. This phenomenon plays a critical role in many microbial processes such as groundwater bioremediation, microbially enhanced oil recovery, nitrogen fixation in legumes, and pathogenesis of the disease. Chemical heterogeneity in these natural systems may produce numerous competing signals from various directions. Predicting the migration behavior of bacterial populations under such conditions is necessary for designing effective treatment schemes. In this study, experimental studies and mathematical models are reported for the chemotactic response of Escherichia coli to a combination of attractant (α-methylaspartate) and repellent (NiCl2 ), which bind to the same transmembrane receptor complex. The model describes the binding of chemoeffectors and phosphorylation of the kinase in the signal transduction mechanism. Chemotactic parameters of E. coli (signaling efficiency σ , stimuli sensitivity coefficient γ , and repellent sensitivity coefficient κ ) were determined by fitting the model with experimental results for individual stimuli. Interestingly, our model naturally identifies NiCl2 as a repellent for κ>1 . The model is capable of describing quantitatively the response to the individual attractant and repellent, and correctly predicts the change in direction of bacterial population migration for competing stimuli with a twofold increase in repellent concentration.

MoSDeF Cassandra: A complete Python interface for the Cassandra Monte Carlo software.

We introduce a new Python interface for the Cassandra Monte Carlo software, molecular simulation design framework (MoSDeF) Cassandra. MoSDeF Cassandra provides a simplified user interface, offers broader interoperability with other molecular simulation codes, enables the construction of programmatic and reproducible molecular simulation workflows, and builds the infrastructure necessary for high-throughput Monte Carlo studies. Many of the capabilities of MoSDeF Cassandra are enabled via tight integration with MoSDeF. We discuss the motivation and design of MoSDeF Cassandra and proceed to demonstrate both simple use-cases and more complex workflows, including adsorption in porous media and a combined molecular dynamics - Monte Carlo workflow for computing lateral diffusivity in graphene slit pores. The examples presented herein demonstrate how even relatively complex simulation workflows can be reduced to, at most, a few files of Python code that can be version-controlled and shared with other researchers. We believe this paradigm will enable more rapid research advances and represents the future of molecular simulations.

Integral equation theory for mixtures of spherical and patchy colloids. 2. Numerical results.

Thermodynamic properties and structure of binary mixtures of patchy and spherical colloids are studied using a recently developed theory [Y. V. Kalyuzhnyi, et al., Soft Matter, 2020, 16, 3456]. The theory is based on a solution of the multidensity Ornstein-Zernike equation and provides completely analytical expressions for the structure factors of these systems and for all their major thermodynamical quantities. The considered mixtures are made up of particles of different size and with a different number of patches. A set of molecular simulation data has been generated to enable a systematic comparison and to access thus accuracy of the theoretical predictions. In general, the predictions of the theory appear to be in good agreement with computer simulation data. For the models with a lower number of patches (np = 1, 2) the theoretical results show very good accuracy. Less accurate are the predictions for the four-patch versions of the model. While theoretical results for the radial distribution functions are, generally, relatively accurate for all the models, results for thermodynamics deteriorate with increasing concentration of the spherical colloids. Possible ways to improve the theory are briefly outlined.

Towards Molecular Simulations that are Transparent, Reproducible, Usable By Others, and Extensible (TRUE).

Systems composed of soft matter (e.g., liquids, polymers, foams, gels, colloids, and most biological materials) are ubiquitous in science and engineering, but molecular simulations of such systems pose particular computational challenges, requiring time and/or ensemble-averaged data to be collected over long simulation trajectories for property evaluation. Performing a molecular simulation of a soft matter system involves multiple steps, which have traditionally been performed by researchers in a "bespoke" fashion, resulting in many published soft matter simulations not being reproducible based on the information provided in the publications. To address the issue of reproducibility and to provide tools for computational screening, we have been developing the open-source Molecular Simulation and Design Framework (MoSDeF) software suite. In this paper, we propose a set of principles to create Transparent, Reproducible, Usable by others, and Extensible (TRUE) molecular simulations. MoSDeF facilitates the publication and dissemination of TRUE simulations by automating many of the critical steps in molecular simulation, thus enhancing their reproducibility. We provide several examples of TRUE molecular simulations: All of the steps involved in creating, running and extracting properties from the simulations are distributed on open-source platforms (within MoSDeF and on GitHub), thus meeting the definition of TRUE simulations.

Diffusivity and Structure of Room Temperature Ionic Liquid in Various Organic Solvents.

Room-temperature ionic liquids (RTILs) hold promise for applications in electric double layer capacitors (EDLCs), owing to a much wider potential window, lower vapor pressure, and better thermal and chemical stabilities compared to conventional aqueous and organic electrolytes. However, because the low diffusivity of ions in neat RTILs negates the EDLCs' advantage of high power density, the ionic liquids are often used in mixture with organic solvents. In this study, we measured the diffusivity of cations and anions in RTIL, 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl) ([BMIM+][TFSI-]), mixed with 10 organic solvents, by using the pulsed-field gradient NMR method. The ion diffusivity was found to follow that of neat solvents and in most studied solvents showed an excellent agreement with the predicted values reported in the recent molecular dynamics (MD) study [Thompson, M. W.; J. Phys. Chem. B 2019, 123, 1340-1347]. In two solvents consisting of long-chain molecules, however, the MD simulations predictions slightly underestimated the ionic diffusivities. The degree of ion dissociation was also estimated for each solvent by comparing the ionic conductivity with the molar conductivity derived from the diffusion measurements. The degree of ion dissociation and the hydrodynamic radius of ions suggest that the ions are coordinated by ∼1 solvent molecule. The scarcity of solvent-ion interactions explains the fact that the diffusivity of ions in the mixture significantly depends on the viscosity of the solvent.

Integral equation theory for a mixture of spherical and patchy colloids: analytical description.

An analytic theory for the structure and thermodynamics of two-component mixtures of patchy and spherical colloids is developed. The theory is based on an analytical solution of the multidensity Ornstein-Zernike equation supplemented by the associative Percus-Yevick closure relations. We derive closed-form analytic expressions for the partial structure factors and thermodynamic properties using the energy route for the model with arbitrary number of patches and any hard-sphere size ratio of the particles. To assess the accuracy of the theoretical predictions we compare them against existing and newly generated set of computer simulation data. In our numerical calculations we consider the model with equal hard-sphere sizes and one patch. Very good agreement between results of the theory and simulation for the pair correlation functions, excess internal energy and pressure is observed for almost all values of the system density, temperature and composition studied. Only in the region of low concentrations of spherical colloids the theoretical results become less accurate.