Density Functional Theory Dynamics Research Articles

Designing the next generation of polymers with machine learning and physics-based models

Abstract The development of next-generation polymers necessitates optimizing several key properties simultaneously, a task that is expensive and infeasible using traditional trial-and-error experimental approaches. A promising alternative is employing a combination of machine learning and physics-based tools to rapidly screen the polymer design space and provide suggestions of new polymers that meet the critical properties required for industrial applications. In this study, we introduce a comprehensive workflow that utilizes machine learning and molecular modeling approaches to design new polymers with the focus on improving five polymer properties: (1) glass transition temperature, (2) dielectric constant, (3) refractive index, (4) stress optic coefficient, and (5) linear coefficient of thermal expansion. Using a small dataset ( < 200 unique polymers), we developed quantitative structure-property relationships (QSPRs) models to accurately predict the experimental polymer properties for both homo- and co-polymer systems. We tested several ML algorithms and identified the best models for predicting these polymer properties, achieving test set R 2 greater than 0.77 across all properties. We then explored new polymers by creating a library of over ∼10 000 homopolymers using R-group enumeration tools and applied the trained QSPR models to rapidly predict the five polymer properties. The predictions of QSPR models were used to create a multi-parameter optimization score, which helped downselect the large polymer space to ∼10 promising candidates. The properties of these selected polymer candidates were subsequently validated with classical molecular dynamics simulations and density functional theory, revealing a strong correlation with the QSPR model predictions. Finally, one of the top candidates was validated by experiments, which showed good agreement against QSPR and physics-based models. Our workflow underscores the power of combining data-driven and theoretical methods in the polymer design process given a small dataset size, offering a valuable resource for experimentalists looking to leverage computer-aided strategies in materials innovation.

Ultraflat Cu(111) foils by surface acoustic wave-assisted annealing

Ultraflat metal foils are essential for semiconductor nanoelectronics applications and nanomaterial epitaxial growth. Numerous efforts have been devoted to metal surface engineering studies in the past decades. However, various challenges persist, including size limitations, polishing non-uniformities, and undesired contaminants. Thus, further exploration of advanced metal surface treatment techniques is essential. Here, we report a physical strategy that utilizes surface acoustic wave assisted annealing to flatten metal foils by eliminating the surface steps, eventually transforming commercial rough metal foils into ultraflat substrates. Large-area, high-quality, smooth 2D materials, including graphene and hexagonal boron nitride (hBN), were successfully grown on the resulting flat metal substrates. Further investigation into the oxidation of 2D-material-coated metal foils, both rough and flat, revealed that the hBN-coated flat metal foil exhibits enhanced anti-corrosion properties. Molecular dynamics simulations and density functional theory validate our experimental observations.

High-Energy LiNiO2 Li Metal Batteries Enabled by Hybrid Electrolyte Consisting of Ionic Liquid and Weakly Solvating Fluorinated Ether.

In pursuit of the highest possible energy density, researchers shift their focus to the ultimate anode material, lithium metal (Li0), and high-capacity cathode materials with high nickel content (Ni > 80%). The combination of these aggressive electrodes presents unprecedented challenges to the electrolyte. Here, wereport a hybrid electrolyte consisting of a highly fluorinated ionic liquid and a weakly solvating fluorinated ether, whose hybridization structure enables the reversible operation of a battery chemistry based on Li0 and LiNiO2 (Ni = 100%), delivering nearly theoretical capacity of the latter (up to 249mAhg-1) for >300cycles with retention of 78.6% and in absence of unwanted morphological changes in both electrodes. Extensive characterization assisted by molecular dynamic simulation and density functional theory calculations reveals the function of the fluorinated ether to be far more profound than simple dilution and viscosity reduction. Instead, it induces drastic changes in Li+-solvation environment, the consequence of which engenders simultaneous stabilization of electrode/electrolyte and interfacing via formation of respective interfacial chemistries. This study further unlocks fundamental knowledge underneath the prevailing "diluent strategy" that is extensively applied by the electrolyte researchers and opens more design space for the next-generation electrolytes and interphases for these coveted battery chemistries.

Computational Multiscale Study of the Interaction Between the PDMS Polymer and Sunscreen-Related Pollutant Molecules

Sunscreen molecules play a critical role in protecting skin from ultraviolet radiation, yet their efficient detection and separation pose challenges in environmental and analytical contexts. In this work, we employ a multilevel modeling approach to investigate the molecular interactions between representative sunscreen molecules and the polydimethylsiloxane (PDMS) polymer, a material widely recognized for its sorbent properties. Our goal is to explore how these interactions can be fine-tuned to facilitate the effective separation of sunscreen molecules in portable membrane inlet mass spectrometry (MIMS) systems, potentially leading to the development of new membrane materials. Using a combination of advanced computational techniques—force field molecular dynamics simulations, semiempirical GFN2-xTB, and density functional theory calculations—we assess the interaction strength and noncovalent interactions of sunscreen molecules, namely oxybenzone, naphthalene, benzo[a]anthracene, avobenzone, and 1,3,5-trichlorobenzene, with PDMS. Additionally, the effect of temperature on the interaction dynamics is evaluated, with the aim of extending the sorbent capacities of PDMS beyond light polar molecules to larger, polar sunscreen compounds. This study provides critical insights into the molecular-level interactions that may guide the design of novel membrane materials for efficient molecular separation.

MultiShape: a spectral element method, with applications to Dynamic Density Functional Theory and PDE-constrained optimization

Abstract A new numerical framework is developed to solve general nonlinear and nonlocal PDEs on complicated two-dimensional domains. This enables the solution of a wide range of both steady and time-dependent problems on nonstandard geometries, as well as providing the ability to impose nonlinear and nonlocal boundary conditions (typical of those arising in the modelling of physical phenomena) in a flexible and automated way. This spectral element methodology, which we called MultiShape, is compatible with other state-of-the-art numerical methods, such as differential–algebraic equation solvers and optimization algorithms. MultiShape is an open-source Matlab library, in which the numerical implementation is designed to be user-friendly: the problem set-up and computations are done automatically through intuitive operator definitions and notation. Validation tests are presented, before we showcase the power and versatility of MultiShape with three motivating examples in Dynamic Density Functional Theory and PDE-constrained optimization.

On-demand imidazolidinyl urea-based tissue-like, self-healable, and antibacterial hydrogels for infectious wound care

Bacterial wound infections are a growing challenge in healthcare, posing severe risks like systemic infection, organ failure, and sepsis, with projections predicting over 10 million deaths annually by 2050. Antibacterial hydrogels, with adaptable extracellular matrix-like features, are emerging as promising solutions for treating infectious wounds. However, the antibacterial properties of most of these hydrogels are largely attributed to extrinsic agents, and their mechanisms of action remain poorly understood. Herein we introduce for the first time, modified imidazolidinyl urea (IU) as the polymeric backbone for developing tissue-like antibacterial hydrogels. As-designed hydrogels behave tissue-like mechanical features, outstanding antifreeze behavior, and rapid self-healing capabilities. Molecular dynamics (MD) simulation and density functional theory (DFT) calculation were employed to well-understand the extent of H-bonding and metal-ligand coordination to finetune hydrogels’ properties. In vitro studies suggest good biocompatibility of hydrogels against mouse fibroblasts & human skin, lung, and red blood cells, with potential wound healing capacity. Additionally, the hydrogels exhibit good 3D printability and remarkable antibacterial activity, attributed to concentration dependent ROS generation, oxidative stress induction, and subsequent disruption of bacterial membrane. On top of that, in vitro biofilm studies confirmed that developed hydrogels are effective in preventing biofilm formation. Therefore, these tissue-mimetic hydrogels present a promising and effective platform for accelerating wound healing while simultaneously controlling bacterial infections, offering hope for the future of wound care.

Elucidation of the Decomplexation and Reverse Migration Mechanism of Uranyl Ions from the Oil Phase to the Aqueous Phase Using Microsecond (0.2 μs) Molecular Dynamics Simulations.

Interphase ion transfer is ubiquitous in chemistry, physics, biology, and various engineering sciences. Ion transfer from the aqueous phase to the oil phase or vice versa is a complex chemical phenomenon, and its fundamental understanding is crucial for efficient and economical mass transfer. This ion transfer is much more complex for radionuclide metal ions. Therefore, an attempt has been made to elucidate the decomplexation and mechanism of reverse migration of uranyl ions from the loaded oil phase to the aqueous phase using large time-scale molecular dynamics simulations (microseconds) and density functional theory (DFT). The strength of the metal-ligand complex is the key factor for stripping among other mass transfer parameters. Stronger the metal-ligand complex, the lower the tendency for reverse migration into the aqueous phase, which was demonstrated by three different ligands for reverse migration using water as the stripping agent. The interaction energy of the metal-ligand complex has been calculated using DFT. The reverse migration is validated by the distance between the centers of mass. Higher interface thickness and lower interfacial tension belong to N,N,N',N'-tetra-octyldiglycolamide (TODGA), which are favorable for mass transfer across the liquid-liquid interface. The computed distribution coefficient (KD) is favorable for tributyl phosphate (TBP) and tri-iso-amyl phosphate (TiAP), whereas TODGA shows a higher KD, indicating a less favorable value for reverse migration. The distance between the uranyl ion and the TODGA molecule confirms that the entrapment of uranyl ions in the TODGA phase might be attributed to aggregation. Further, the aggregation tendency of TODGA molecules reduces the back extraction and the recovery of uranyl ions into the aqueous phase. The present MD results might be important for predicting an efficient back-extracting agent for the recovery of the metal ions from the oil phase.

Atomistic simulations of polysaccharide materials for insights into their crystal structure, nanostructure, and dissolution mechanism

AbstractCrystalline polysaccharides are abundant in nature and can be transformed into highly functional materials. However, the molecular basis for the formation of higher-order structures remains unclear. Computer simulation is an advanced tool for modeling macromolecular structures, and the atomistic simulations provide valuable information on the crystalline polysaccharides. Fiber deformation, crystalline transition, and novel nanostructures of cellulose were characterized through molecular dynamics simulations and density functional theory calculations of models of molecular chain sheets extracted from the crystal structure of the cellulose polymorphs. Extended ensemble molecular dynamics simulations were applied to analyze the artificial crystal structure of non-natural amylose analog polysaccharides, revealing the hexagonal packing of double helices through the self-assembly of molecular chains dispersed in aqueous solution. Dissolution simulations of the cellulose and chitin crystalline fibers revealed that the anions of ionic liquids, with their solvation power, played a key role in the cleavage of intermolecular hydrogen bonds in the crystal structure, whereas the cations contributed to irreversible molecular chain dispersion. The good correlation between the actual solubility of polysaccharides and the predicted number of intermolecular hydrogen bonds prompted the development of a platform that combined simulations and machine learning for high-throughput screening of solvents for cellulose and chitin.

Pyrolysis mechanism of 1,1,1,2-tetrafluoroethane and 1,1,1,2-tetrafluoroethane/carbon dioxide as working fluids for transcritical power cycles: Insights from reactive force field molecular dynamics and density functional theory studies

Carbon dioxide-based mixtures in transcritical power cycle systems can enhance thermodynamic performance but may pose risks of thermal decomposition, potentially compromising system performance and safety. This study investigates the pyrolysis mechanism of 1,1,1,2-tetrafluoroethane (R134a)/carbon dioxide (CO₂), a typical CO₂-based mixture, using reactive force field molecular dynamics (ReaxFF-MD) simulations and density functional theory (DFT). ReaxFF-MD simulations are conducted at pressures ranging from 4 to 12 MPa and temperatures between 1800 K and 3200 K for various fluid compositions, including pure R134a and R134a/CO₂ mixtures at mole ratios of 0.7/0.3, 0.5/0.5, and 0.3/0.7. The effects of temperature, pressure, and composition on the thermal decomposition of both pure R134a and R134a/CO₂ mixtures are examined, with particular focus on behavior at 8 MPa. In the thermal decomposition of R134a/CO₂ mixtures, CO₂ inhibits the formation of F radicals and reduces their concentration through chemical reactions, thereby suppressing R134a decomposition. Pure R134a decomposes into primary products such as hydrogen fluoride (HF), fluorine (F), tetrafluoroethylene (C2HF4), trifluoromethyl radicals (CF3), and diatomic carbon (C2). The addition of CO2 results in the formation of additional products, including carbonyl fluoride (COF), oxygen (O), hydroxyl (HO), and formyl radicals (CHO). The decomposition pathways involve two reaction types: self-decomposition reactions dominate initially, while extraction reactions become more prominent later. Using the DFT approach, reaction energy barriers are analyzed to corroborate the ReaxFF-MD simulation findings. Moreover, the apparent activation energies for these reactions are quantified using first-order kinetics based on the Arrhenius equation, indicating that the thermal decomposition of R134a/CO2 mixtures is more challenging than that of pure R134a.

Periodate activation with polyaniline-derived carbon for bisphenol A degradation: Insight into the roles of nitrogen dopants and non-radical species formation

Periodate-based advanced oxidation processes (PI-AOPs) activated by carbon catalysts have shown promising application prospects in the removal of emerging contaminants. Herein, a series of N-doped carbon catalysts (NC) were prepared by in-situ pyrolysis of N-containing polymers (polyaniline) to unveil the potential mechanism of N dopants on PI activation. The optimized sample NC700 showed a satisfying degradation performance, achieving 100 % removal of bisphenol A (BPA) at a concentration of 10 mg/L within 90 min in the presence of 0.1 mM PI. The impacts of various N types on PI activation were systematically investigated by dynamic fitting and density functional theory computations. These analyses highlighted the crucial role of graphitic N configuration on carbon surface, which exhibited the highest adsorption energy and a positive correlation with the normalized degradation efficiency. The chemical quenching experiments and electrochemical experiments confirmed that the BPA oxidation mechanism was primarily mediated electron transfer by [NC-PI]* complex, with singlet oxygen (1O2) /superoxide radicals (O2•–) playing a supplementary role. In situ ATR-SERAS measurement strengthened the understanding of PI activation by carbon catalyst based on electron transfer pathway. Owing to the non-radical oxidation mechanism, the NC/PI system had a broad pH adaptability and great anti-interference ability against typical wastewater components. This study provides mechanistic insights into the carbon-driven PI activation process for wastewater treatment, advancing the practical application of PI-AOPs.

The Sword of Damocles: Microplastics and the molecular dynamics of sulfamonomethoxine revealed

In recent years, the environmental impact of microplastics (MPs) and antibiotics (ATs) as pollutants cannot be ignored. In order to evaluate the carrier effect of MPs in the aqueous environment, three MPs, polyamide (PA), polyethylene (PE) and polyethylene terephthalate (PET), were selected in this study, and their structures were analyzed by means of characterization. A preliminary description of their interactions with sulfamonomethoxine was carried out by adsorption kinetics and isotherm fitting. The dominance of non-bonding capacity (van der Waals and electrostatic interaction forces) in the adsorption process was demonstrated using molecular dynamics (MD) simulations and density functional theory (DFT), with the interaction strengths ranked as PA > PE > PET, respectively. PA is less adsorbent stable at the molecular level but exhibits the largest adsorption capacity influenced by the characterized structure and multiple interaction forces. PET possesses a stronger stability and is not easily replaced by other substances. This will help to further understand the complex effect mechanism between MPs and organic pollutants, and provide an important reference for the prevention and control of environmental pollution.

Unraveling the Stability and Magnetic Properties of Bis-Hydrated Mn(II) Complexes via Tailored Ligand Design.

Exploring the electronic structure and dynamic behavior of Mn(II) complexes reveals fascinating magnetic properties and prospective biomedical applications. In this study, we investigate the solvent phase dynamics of heptacoordinated Mn(II) complexes through ab initio molecular dynamics simulations and density functional theory (DFT) calculations with effectively varying temperatures. We observed that the complex with high stability ([Mn(pmpa)(H2O)2]) remains relatively rigid as the temperature increases to 90 °C, with only a minor change in its radial distribution functions (RDFs), compared to the RDF peaks at 25 °C. To elucidate the impact of halogens on the magnetic anisotropy of seven-coordinated Mn(II) complexes, we performed both DFT and multireference calculations. This shows that the zero-field splitting (ZFS) parameter D follows the order D(I)> D(Br)> D(Cl). We observed a significant increase in the D-value following the substitution of soft Se-donors in the equatorial position and heavier halogens in the axial position. The D-value of halogen derivatives of Se-analogues varies in the order of D(Cl) < D(I) < D(Br), deviating from the regular spectrochemical series with the discrepancy between the covalency of the Mn(II)-Se bond and the ligand field strength. We anticipate that this study will enhance our understanding of the solvent phase dynamics and structural aspects of ZFS in various Mn(II) complexes with different electronic environments.

Dynamic density functional theory of polymers with salt in electric fields.

We present a dynamic density functional theory for modeling the effects of applied electric fields on the local structure of polymers with added salt (polymer electrolytes). Time-dependent equations for the local electrostatic potential and volume fractions of polymer, cation, and anion of added salt are developed using the principles of linear irreversible thermodynamics. For such a development, a field theoretic description of the free energy of polymer melts doped with salts is used, which captures the effects of local variations in the dielectric function. Connections of the dynamic density functional theory with experiments are established by relating the three phenomenological Onsager's transport coefficients of the theory to the mutual diffusion of electrolyte, ionic conductivity, and transference number of one of the ions. The theory is connected with a statistical mechanical model developed by Bearman and Kirkwood [J. Chem. Phys. 28, 136 (1958)] after relating the three transport coefficients to friction coefficients. The steady-state limit of the dynamic density functional theory is used to understand the effects of dielectric inhomogeneity on the phase separation in polymer electrolytes. The theory developed here provides not only a way to connect with experiments but also to develop multi-scale models for studying connections between local structure and ion transport in polymer electrolytes.

Adsorption of Guanine on Oxygen-Deficient TiO2 Surface: A Combined MD-DFTB/DFT Strategy.

Metal oxides (MOs) are key materials in many fields, including technological, industrial, and biomedical applications. In most of these implementations, surface reactivity and reducibility properties are critical considerations. In their nanosized form, MOs exhibit enhanced reactivity that is connected to toxicity. Besides the fact that the biological molecule and the surface of the corresponding material interact chemically, little is known about the toxicological mechanisms involved on the atomic scale. The goal of this study is to investigate the role of TiO2 surfaces in interaction with one genetic base, namely guanine. Using a combination of the quasi-electronic density functional-tight binding molecular dynamics simulations and density functional theory calculations, we explored the adsorption modes of guanine with a stoichiometric and oxygen-deficient anatase TiO2 (101) surface. With such an approach, we have characterized new adsorption modes not previously found, and we have highlighted the relevance of defective surfaces in the adsorption of genetic basis, as a model for explaining possible toxicology mechanisms induced by the adsorption process.

Large scale atomistic and quantum mechanical study of Na+ ion transport in liquid electrolytes for batteries

Lithium–ion batteries (LIBs) have long dominated energy storage markets due to their high energy density and reliability. However, concerns over lithium scarcity and geographic distribution necessitate alternatives. Sodium-ion batteries (SIBs) offer a promising solution due to sodium's abundance, cost-effectiveness, and favorable electrochemical properties. This study investigates Na+ ion transport, aggregation, and performance in various organic electrolytes using molecular dynamics (MD) simulations and density functional theory (DFT) calculations. The electrolytes studied include ethylene carbonate (EC), propylene carbonate (PC), dimethoxyethane (DME), and dimethyl carbonate (DMC) at 320 K. We focused on conductivity, diffusivity, and survival probability of Na+ ions at different salt concentrations. Furthermore, the solvation structure and the binding energy of ions in the electrolytes are thoroughly analyzed. Key findings reveal that at 2 M salt concentration, Na+ ion diffusivity and ionic conductivity follow the order EC>PC>DME>DMC. Increasing salt concentration decreases self–diffusion coefficients of Na+ and PF6− ions across all electrolytes, affecting conductivity. EC shows the highest ionic conductivity at both 1 M and 2 M salt concentrations. These insights suggest that a 2 M NaPF6 concentration in EC optimizes ionic conductivity, making it ideal for high–performance SIBs. This study provides crucial understanding for optimizing electrolytes in SIBs, advancing their development for scalable energy storage solutions.

Nonequilibrium relaxation of soft responsive colloids.

Stimuli-responsive macromolecules display large conformational changes during their dynamics, sometimes switching between states. Such a multi-stability is useful for the development of soft functional materials. Here, we introduce a mean-field dynamical density functional theory for a model of responsive colloids to study the nonequilibrium dynamics of a colloidal dispersion in time-dependent external fields, with a focus on the coupling of translational and conformational dynamics during their relaxation. Specifically, we consider soft Gaussian particles with a bimodal size distribution between two confining walls with time-dependent (switching-on and off) external gravitational and osmotic fields. We find a rich relaxation behavior of the systems in excellent agreement with particle-based Brownian dynamics computer simulations. In particular, we find time-asymmetric relaxations of integrated observables (wall pressures, mean size, and liquid center-of-mass) for activation/deactivation of external potentials, respectively, which are tunable by the ratio of translational and conformational diffusion time scales. Our work thus paves the way for studying the nonequilibrium relaxation dynamics of complex soft matter with multiple degrees of freedom and hierarchical relaxations.

Mussel-Bioinspired Lignin Adhesive for Wearable Bioelectrodes.

As a natural "binder," lignin fixes cellulose in plants to foster growth and longevity. However, isolated lignin has a poor binding ability, which limits its biomedical applications. In this study, inspired by mussel adhesive proteins, acidic/basic amino acids (AAs) are introduced in alkali lignin (AL) to form ionic-π/spatial correlation interactions, followed by demethylation to create catechol residues for enhanced adhesion activity. Atomic force microscopy reveals that catechol residues are the primary adhesion structures, with basic AAs exhibiting superior synergistic effects compared to acidic AAs. Demethylated lysine-grafted AL exhibits the strongest adhesion force toward skin tissue. Molecular dynamic simulation and density functional theory calculations indicate that adhesion against skin tissue mainly results from hydrogen bonds and cation-π interactions, with the adhesion mechanism being based on the Gibbs free energy of the Schiff base reaction. In summary, a biomimetic electrode based on lignin inspired by mussel adhesive proteins is prepared; the presented method offers a straightforward strategy for the development of biomimetic adhesives. Furthermore, this mussel-inspired adhesive can be used as a wearable bioelectrode in biomedical applications.

Neural force functional for non-equilibrium many-body colloidal systems

Abstract We combine power functional theory and machine learning to study non-equilibrium overdamped many-body systems of colloidal particles at the level of one-body fields. We first sample in steady state the one-body fields relevant for the dynamics from computer simulations of Brownian particles under the influence of randomly generated external fields. A neural network is then trained with this data to represent locally in space the formally exact functional mapping from the one-body density and velocity profiles to the one-body internal force field. The trained network is used to analyse the non-equilibrium superadiabatic force field and the transport coefficients such as shear and bulk viscosities. Due to the local learning approach, the network can be applied to systems much larger than the original simulation box in which the one-body fields are sampled. Complemented with the exact non-equilibrium one-body force balance equation and a continuity equation, the network yields viable predictions of the dynamics in time-dependent situations. Even though training is based on steady states only, the predicted dynamics is in good agreement with simulation results. A neural dynamical density functional theory can be straightforwardly implemented as a limiting case in which the internal force field is that of an equilibrium system. The framework is general and directly applicable to other many-body systems of interacting particles following Brownian dynamics.

Adsorption mechanism of cefradine on three microplastics: A combined molecular dynamics simulation and density functional theory calculation study

Microplastics and antibiotics are receiving increasing attention as two emerging pollutants in the aquatic ecosystem. The absorption of antibiotics by microplastics can potentially intensify their impact on marine organisms and human health. However, the detailed mechanisms underlying this interaction remain to be elucidated. Through molecular dynamics (MD) simulations and density functional theory (DFT) calculations, this study investigated the adsorption of cefradine (CED) onto three typical microplastics (MPs)-polyethylene (PE), polypropylene (PP), and polyamide (PA). The results of the molecular dynamics simulations showed that the interaction energy between CED and microplastics followed the order of PA-CED > PP-CED > PE-CED, indicating that PA microplastics had the highest adsorption capacity for CED antibiotics. The total energy contribution of the microplastics-cefradine (MPs-CED) systems suggested that the van der Waals and electrostatic interactions were the two primary mechanisms for the adsorption of CED by these three microplastics. In DFT calculations, the adsorption of CED on PA was found to be significantly influenced by both electrostatic and van der Waals effects, while the main driving force in the adsorption of PE and PP is van der Waals effect. In addition, IGMH analysis and AIM topological analysis confirmed that the adsorption of CED on PA relied heavily on the synergistic effect of hydrogen bonding and the van der Waals effect. The findings of this study validate the results obtained from molecular dynamics simulations, laying a foundation for a comprehensive exploration of the interaction mechanisms between microplastics and organic pollutants by integrating MD simulations and DFT calculations.

Unraveling the Roles of Ionic Size and Hydrogen Bonding in Electric Field-Driven Ion Emission from Hydroxylamine Nitrate-Based Ionic Liquids.

Ionic size and hydrogen bonding (HB) may play significant roles in controlling ion emission from HAN (hydroxylamine nitrate)-based ionic liquids (ILs) but have received little attention. In this paper, the ion emission behavior and mechanism in an external electric field are meticulously investigated using the molecular dynamics (MD) method and density functional theory. We find that the higher the proportion of ionic HAN in the blend of ILs, the longer the delay time of the ion start-up emission. In the positive mode, cations can evaporate directly from the surface of the studied ILs and manifest exclusively as the [EMIM]+ monomers within the simulation time scale, whereas in the negative mode, a variety of complicated anion clusters are emitted. As a result, the average charge-to-mass ratio of the positively charged species remarkably exceeds that of the negatively charged species. This large difference is attributed to the relatively larger size of the [EMIM]+ ion and the absence of substantial HB interactions between the [EMIM]+ ion and any other monomer, leading to diminished binding energies. Conversely, the strong HB interactions, primarily constituted by N-H--O and O-H--O hydrogen bonds, are clearly found in the [EtSO4]--based and HAN-based clusters. In addition, the [NO3]- and [EtSO4]- ions tend to combine with the small-sized [HA]+ ions to form large anion clusters rather than with the [EMIM]+ ions. The energy decomposition results further elucidate that the orbital interaction plays a pivotal role in the [NO3]- and [EtSO4]--based clusters. The findings clearly elucidate the experimental phenomena observed in previous studies and have implications for the formulation of multimode IL propellants.