Tracking nitrite's deviation from Stokes-Einstein predictions with pulsed field gradient 15N NMR spectroscopy.

Predicting the behavior of oxyanions in radioactive waste stored at the Department of Energy legacy nuclear sites requires the development of novel analytical methods. This work demonstrates 15N pulsed field gradient nuclear magnetic resonance spectroscopy to quantify the diffusivity of nitrite. Experimental results, supported by molecular dynamics simulations, indicate that the diffusivity of free hydrated nitrite exceeds that of free hydrated sodium despite the greater hydrodynamic radius of nitrite. Investigations are underway to understand how the compositional and dynamical heterogeneities of the ion networks at high concentrations affect rheological and transport properties.

Cation coordination polyhedra lead to multiple lengthscale organization in aqueous electrolytes.

Understanding multiple lengthscale correlations in the pair distribution functions (PDFs) of aq. electrolytes is a persistent challenge. Here, the coordination chemistry of polyoxoanions supports an ion-network of cation-coordination polyhedra in NaNO3(aq) and NaNO2(aq) that induce long-range solution structure. Oxygen correlations associated with Na+-coordination polyhedra have two characteristics lengthscales; 3.5-5.5 Å and 5.5-7.5 Å, the latter solely associated oligomers. The PDF contraction between 5.5-7.5 Å observed in many electrolytes is attributed to the distinct O⋯O correlation found in dimers and dimer subunits within oligomers.

Predicting Outcomes of Nanoparticle Attachment by Connecting Atomistic, Interfacial, Particle, and Aggregate Scales.

Predicting nanoparticle aggregation and attachment phenomena requires a rigorous understanding of the interplay among crystal structure, particle morphology, surface chemistry, solution conditions, and interparticle forces, yet no comprehensive picture exists. We used an integrated suite of experimental, theoretical, and simulation methods to resolve the effect of solution pH on the aggregation of boehmite nanoplatelets, a case study with important implications for the environmental management of legacy nuclear waste. Real-time observations showed that the particles attach preferentially along the (010) planes at pH 8.5 and the (101) planes at pH 11. To rationalize these results, we established the connection between key physicochemical phenomena across the relevant length scales. Starting from molecular-scale simulations of surface hydroxyl reactivity, we developed an interfacial-scale model of the corresponding electrostatic potentials, with subsequent particle-scale calculations of the resulting driving forces allowing successful prediction of the attachment modes. Finally, we scaled these phenomena to understand the collective structure at the aggregate-scale. Our results indicate that facet-specific differences in surface chemistry produce heterogeneous surface charge distributions that are coupled to particle anisotropy and shape-dependent hydrodynamic forces, to play a key role in controlling aggregation behavior.

An Efficient Reactive Force Field without Explicit Coordination Dependence for Studying Caustic Aluminum Chemistry.

Reactive force fields (RFFs) are an expedient approach to sample chemical reaction paths in complex systems, relative to density functional theory. However, there is continued need to improve efficiencies, specifically in systems that have slow transverse degrees of freedom, as in highly viscous and superconcentrated solutions. Here, we present an RFF that is differentiated from current models (e.g., ReaxFF) by omitting explicit dependence on the atom coordination and employing a small parameter set based on Lennard-Jones, Gaussian, and Stillinger-Weber potentials. The model was parametrized from AIMD simulation data and is used to model aluminate reactivity in sodium hydroxide solutions with extensive validation against experimental radial distribution functions, computed free energy profiles for oligomerization, and formation energies. The model enables simulation of early stage Al(OH)3 nucleation which has significant relevance to industrial processing of aluminum and has a computational cost that is reduced by 1 order of magnitude relative to ReaxFF.

Adsorbate Organization Characterized by Sublevelset Persistent Homology.

Interfacial adsorbate organization influences a variety physicochemical properties and reactivity. Surfaces that are rough, defect laden, or have large fluctuations (as in soft matter interfaces) can lead to complex adsorbate structures. This is amplified if adsorbate-adsorbate interactions lead to self-assembly. Although image analysis algorithms are somewhat common for the study of solid interfaces (from microscopy for example), images are often not readily available for adsorbates at soft matter surfaces, and the complexity of adsorbate organization necessitates the development of new characterization approaches. Here we propose the use of adsorbate "density" images from molecular dynamics simulations of liquid/vapor and liquid/liquid interfaces. Topological data analysis is employed to characterize surface active amphiphile self-assembly under nonreactive and reactive conditions. We develop a chemical interpretation of sublevelset persistent homology barcode representations of the density images, in addition to descriptors that clearly differentiate between different reactive and nonreactive organizational regimes. The complexity of amphiphile self-assembly at highly dynamic liquid/liquid interfaces represents a worst-case scenario for adsorbate characterization, and as such the methodology developed is completely generalizable to a wide variety of surface image data, whether from experiment or computer simulation.

Additive energy functions have predictable landscape topologies.

Recent work [Mirth et al., J. Chem. Phys. 154, 114114 (2021)] has demonstrated that sublevelset persistent homology provides a compact representation of the complex features of an energy landscape in 3 N-dimensions. This includes information about all transition paths between local minima (connected by critical points of index ≥1) and allows for differentiation of energy landscapes that may appear similar when considering only the lowest energy pathways (as tracked by other representations, such as disconnectivity graphs, using index 1 critical points). Using the additive nature of the conformational potential energy landscape of n-alkanes, it became apparent that some topological features-such as the number of sublevelset persistence bars-could be proven. This work expands the notion of predictable energy landscape topology to any additive intramolecular energy function on a product space, including the number of sublevelset persistent bars as well as the birth and death times of these topological features. This amounts to a rigorous methodology to predict the relative energies of all topological features of the conformational energy landscape in 3N dimensions (without the need for dimensionality reduction). This approach is demonstrated for branched alkanes of varying complexity and connectivity patterns. More generally, this result explains how the sublevelset persistent homology of an additive energy landscape can be computed from the individual terms comprising that landscape.

Disordered interfaces of alkaline aluminate salt hydrates provide glimpses of Al3+ coordination changes.

HYPOTHESIS: The precipitation and dissolution of aluminum-bearing mineral phases in aqueous systems often proceed via changes in both aluminum coordination number and connectivity, complicating molecular-scale interpretation of the transformation mechanism. Here, the thermally induced transformation of crystalline sodium aluminum salt hydrate, a phase comprised of monomeric octahedrally coordinated aluminate which is of relevance to industrial aluminum processing, has been studied. Because intermediate aluminum coordination states during melting have not previously been detected, it is hypothesized that the transition to lower coordinated aluminum ions occurs within ahighly disordered quasi-two-dimensional phase at the solid-solution interface. EXPERIMENTS AND SIMULATIONS: In situ X-ray diffraction (XRD), Raman and27Al nuclear magnetic resonance (NMR) spectroscopy were used to monitor the melting transition of nonasodium aluminate hydrate (NSA, Na9[Al(OH)6]2·3(OH)·6H2O). A mechanistic interpretation was developed based on complementary classical molecular dynamics (CMD) simulations including enhanced sampling. A reactive forcefield was developed to bridge speciation in the solution and in the solid phase. FINDINGS: In contrast to classical dissolution, aluminum coordination change proceeds through a dynamically stabilized ensemble of intermediate states in a disordered layer at the solid-solution interface. In both melting and dissolution of NSA, octahedral, monomeric aluminum transition through an intermediate of pentahedral coordination. The intermediate dehydroxylates to form tetrahedral aluminate (Al(OH)4-) in the liquid phase. This coordination change is concomitant with a breaking of the ionic aluminate-sodium ionlinkages. The solution phase Al(OH)4- ions subsequently polymerize into polynuclear aluminate ions. However, there are some differences between bulk melting and interfacial dissolution, with the onset of the surface-controlled process occurring at a lower temperature (∼30 °C) and the coordination change taking place more gradually as a function of temperature. This work to determine the local structure and dynamics of aluminum in the disordered layer provides a new basis to understand mechanisms controlling aluminum phase transformations in highly alkaline solutions.

Dynamic Community Detection Decouples Multiple Time Scale Behavior of Complex Chemical Systems.

Although community or cluster identification is becoming a standard tool within the simulation community, traditional algorithms are challenging to adapt to time-dependent data. Here, we introduce temporal community identification using the Δ-screening algorithm, which has the flexibility to account for varying community compositions, merging and splitting behaviors within dynamically evolving chemical networks. When applied to a complex chemical system whose varying chemical environments cause multiple time scale behavior, Δ-screening is able to resolve the multiple time scales of temporal communities. This computationally efficient algorithm is easily adapted to a wide range of dynamic chemical systems; flexibility in implementation allows the user to increase or decrease the resolution of temporal features by controlling parameters associated with community composition and fluctuations therein.

Modulating Aggregation in Microemulsions: The Dispersion by Competitive Intermolecular Interaction Model.

A phenomenological model has been developed for the mechanism of action of phase modifiers as additives that control aggregation phenomena within water-in-oil emulsions. The "Dispersion by Competitive Intermolecular Interaction" model (DCI) explicitly considers the strength and prevalence of different intermolecular interactions that influence the molecular association of amphiphiles, the resulting distribution of aggregate size, and interaggregate interactions that influence phase phenomena. The existing "cosolvent" and "cosurfactant" association models, which describe the distribution of these amphiphiles within the solution, are re-examined in the context of intermolecular interactions. The different contributions of intermolecular interactions to the potential energy landscape of molecular association create distinct regimes within the DCI model that explain prior observations of cosolvent and cosurfactant behavior. The specific system under consideration, the N,N,N',N'-tetraoctyl diglycolamide amphiphile extractant with tributyl phosphate or dihexyl octanamide phase modifier additives, represents a new regime-labeled the polar disruption regime-where strong hydrogen bonding of the phase modifier with the polar-solutes disrupts the internal hydrogen bonding network of the polar micellar core, thereby decreasing aggregate size and narrowing the polydispersity in solution.

Concentration dependent interfacial chemistry of the NaOH(aq): gibbsite interface.

Caustic conditions are often employed for dissolution of a wide variety of minerals, where ion sorption, surface diffusion, and interfacial organization impact surface reactivity. In the case of gibbsite, γ-Al(OH)3, the chemistry at the NaOH(aq) interface is deeply intertwined with industrial processing of aluminum, including metal production and the disposition of Al-containing wastes. To date, little is known about the structure, speciation, and dynamic behavior of gibbsite interfaces (and that of many other minerals) with NaOH(aq)-particularly as a function of ionic strength. Yet concentration-dependent interfacial organization and dynamics are a critical starting point to develop a fundamental understanding of the factors that influence dissolution. This work reports equilibrium molecular dynamics simulations of the γ-Al(OH)3:NaOH(aq) interface, revealing the sorption behavior and speciation of ions from 0.5-10 M [NaOH]. As inner-sphere complexes, Na+ primarily coordinates to the side of the gibbsite hexagonal cavities, while OH- accepts hydrogen-bonding from the surface-OH groups. The mobility of inner-sphere Na+ and OH- ions is significantly reduced due to a strong surface affinity in comparison to previous reports of NaCl, CaCl2, or BaCl2 electrolytes. At high [NaOH], contact ion pairing that is observed in the bulk solution is partially disrupted upon sorption to the gibbsite surface by the individual ion-surface interactions. The molecular-scale changes to surface speciation and competition between ion-surface vs. ion-ion interactions influence surface characterization of gibbsite and potential dissolution processes, providing a valuable baseline for starting conditions needed within future reactive molecular simulations.

pH dependent reactivity of boehmite surfaces from first principles molecular dynamics.

pH dependent interfacial chemistry depends upon the distribution and respective pKa values of different surface active sites. This is highly relevant to the chemistry of nanoparticle morphologies that expose faces with varying surface termination. Recent synthetic advances for nanoparticles of various minerals, including AlO(OH) (boehmite), present an excellent opportunity to compare and contrast predicted surface pKa on low Miller index planes so as to reinterpret reported interfacial properties (i.e., point of zero charge - PZC) and reactivity. This work employs ab initio molecular dynamics and empirical models to predict site-specific pKa values of accurate (benchmarked) surface models of boehmite. Using the different surface site populations, the PZC is determined and the influence this has upon reported interfacial chemistry is described.

Behavior of Linear and Nonlinear Dimensionality Reduction for Collective Variable Identification of Small Molecule Solution-Phase Reactions.

Identifying collective variables (CVs) for chemical reactions is essential to reduce the 3N-dimensional energy landscape into lower dimensional basins and barriers of interest. However, in condensed phase processes, the nonmeaningful motions of bulk solvent often overpower the ability of dimensionality reduction methods to identify correlated motions that underpin collective variables. Yet solvent can play important indirect or direct roles in reactivity, and much can be lost through treatments that remove or dampen solvent motion. This has been amply demonstrated within principal component analysis (PCA), although less is known about the behavior of nonlinear dimensionality reduction methods, e.g., uniform manifold approximation and projection (UMAP), that have become recently utilized. The latter presents an interesting alternative to linear methods though often at the expense of interpretability. This work presents distance-attenuated projection methods of atomic coordinates that facilitate the application of both PCA and UMAP to identify collective variables in the presence of explicit solvent and further the specific identity of solvent molecules that participate in chemical reactions. The performance of both methods is examined in detail for two reactions where the explicit solvent plays very different roles within the collective variables. When applied to raw molecular dynamics data in solution, both PCA and UMAP representations are dominated by bulk solvent motions. On the other hand, when applied to data preprocessed by our attenuated projection methods, both PCA and UMAP identify the appropriate collective variables (though varying sensitivity is observed due to the presence of explicit solvent that results from the projection method). Importantly, this approach allows identification of specific solvent molecules that are relevant to the CVs and their importance.

Unexpected inverse correlations and cooperativity in ion-pair phase transfer.

Liquid/liquid extraction is one of the most widely used separation and purification methods, where a forefront of research is the study of transport mechanisms for solute partitioning and the relationships that these have to solution structure at the phase boundary. To date, organized surface features that include protrusions, water-fingers, and molecular hinges have been reported. Many of these equilibrium studies have focused upon small-molecule transport - yet the extent to which the complexity of the solute, and the competition between different solutes, influence transport mechanisms have not been explored. Here we report molecular dynamics simulations that demonstrate that a metal salt (LiNO3) can be transported via a protrusion mechanism that is remarkably similar to that reported for H2O by tri-butyl phosphate (TBP), a process that involves dimeric assemblies. Yet the LiNO3 out-competes H2O for a bridging position between the extracting TBP dimer, which in-turn changes the preferred transport pathway of H2O. Examining the electrolyte concentration dependence on ion-pair transport unexpectedly reveals an inverse correlation with the extracting surfactant concentration. As [LiNO3] increases, surface adsorbed TBP becomes a limiting reactant in correlation with an increased negative surface charge induced by excess interfacial NO3 -, however the rate of transport is enhanced. Within the highly dynamic interfacial environment, we hypothesize that this unique cooperative effect may be due to perturbed surface organization that either decreases the energy of formation of transporting protrusion motifs or makes it easier for these self-assembled species to disengage from the surface.

Theory-Guided Inelastic Neutron Scattering of Crystalline Alkaline Aluminate Salts Bearing Principal Motifs of Solution-State Species.

Aluminate salts precipitated from caustic alkaline solutions exhibit a correlation between the anionic speciation and the identity of the alkali cation in the precipitate, with the aluminate ions occurring either in monomeric (Al(OH)4-) or dimeric (Al2O(OH)62-) forms. The origin of this correlation is poorly understood as are the roles that oligomeric aluminate species play in determining the solution structure, prenucleation clusters, and precipitation pathways. Characterization of aluminate solution speciation with vibrational spectroscopy results in spectra that are difficult to interpret because the ions access a diverse and dynamic configurational space. To investigate the Al(OH)4- and Al2O(OH)62- anions within a well-defined crystal lattice, inelastic neutron scattering (INS) and Raman spectroscopic data were collected and simulated by density functional theory for K2[Al2O(OH)6], Rb2[Al2O(OH)6], and Cs[Al(OH) 4]·2H2O. These structures capture archetypal solution aluminate species: the first two salts contain dimeric Al2O(OH)62- anions, while the third contains the monomeric Al(OH)4- anion. Comparisons were made to the INS and Raman spectra of sodium aluminate solutions frozen in a glassy state. In contrast to solution systems, the crystal lattice of the salts results in well-defined vibrations and associated resolved bands in the INS spectra. The use of a theory-guided analysis of the INS of this solid alkaline aluminate series revealed that differences were related to the nature of the hydrogen-bonding network and showed that INS is a sensitive probe of the degree of completeness and strength of the bond network in hydrogen-bonded materials. Results suggest that the ionic size may explain cation-specific differences in crystallization pathways in alkaline aluminate salts.

The Middle Science: Traversing Scale In Complex Many-Body Systems.

A roadmap is developed that integrates simulation methodology and data science methods to target new theories that traverse the multiple length- and time-scale features of many-body phenomena.

Shear stress dependence of force networks in 3D dense suspensions.

The geometric organization and force networks of 3D dense suspensions that exhibit both shear thinning and thickening have been examined as a function of varying strength of interparticle attractive interactions using lubrication flow discrete element simulations. Significant rearrangement of the geometric topology does not occur at either the local or global scale as these systems transition across the shear thinning and shear thickening regimes. In contrast, massive rearrangements in the balance of attractive, lubrication, and contact forces are observed with interesting behavior of network growth and competition. In agreement with prior work, in shear thinning regions the attractive force is dominant, however as the shear thickening region is approached there is growth of lubrication forces. Lubrication forces oppose the attraction forces, but as viscosity continues to increase under increasing shear stress, the lubrication forces are dominated by contact forces that also resist attraction. Contact forces are the dominant interactions during shear thickening and are an order of magnitude higher than their values in the shear-thinning regime. At high attractive interaction strength, contact networks can form even under shear thinning conditions, however high shear stress is still required before contact networks become the driving mechanism of shear thickening. Analysis of the contact force network during shear thickening generally indicates a uniformly spreading network that rapidly forms across empty domains; however the growth patterns exhibit structure that is significantly dependent upon the strength of interparticle interactions, indicating subtle variations in the mechanism of shear thickening.

Ensemble effects on allylic oxidation within explicit solvation environments.

Umbrella-sampling density functional theory molecular dynamics (DFT-MD) has been employed to study the full catalytic cycle of the allylic oxidation of cyclohexene using a Cu(ii) 7-amino-6-((2-hydroxybenzylidene)amino)quinoxalin-2-ol complex in acetonitrile to create cyclohexenone and H2O as products. After the initial H-atom abstraction step, two different reaction pathways have been identified that are distinguished by the participation of alkyl hydroperoxide (referred to as the "open" cycle) versus the methanol side-product (referred to as the "closed" cycle) within the catalyst recovery process. Importantly, both pathways involve dehydrogenation and re-hydrogenation of the -NH2 group bound to the Cu-site - a feature that is revealed from the ensemble sampling of configurations of the reactive species that are stabilized within the explicit solvent environment of the simulation. Estimation of the energy span from the experimental turnover frequency yields an approximate value of 22.7 kcal mol-1 at 350 K. Whereas the closed cycle value is predicted to be 26.2 kcal mol-1, the open cycle value at 16.5 kcal mol-1. Both pathways are further consistent with the equilibrium between Cu(ii) and Cu(iii) that has previously been observed. In comparison to prior static DFT calculations, the ensemble of both solute and solvent configurations has helped to reveal a breadth of processes that underpin the full catalytic cycle yielding a more comprehensive understanding of the importance of radical reactions and catalysis recovery.

Cluster Identification Using Modularity Optimization to Uncover Chemical Heterogeneity in Complex Solutions.

Structural heterogeneity is commonly manifested in solutions and liquids that feature competition of different interparticle forces. Identifying and characterizing heterogeneity across different length scales requires multimodal experimental measurement and/or the application of new techniques for the interrogation of atomistic simulation data. Within the latter, the parsing of networks of interparticle interactions (chemical networks) has been demonstrated to be a valuable tool for identifying subensembles of chemical environments. However, chemical networks can adopt a wide variety of topologies that challenge generalizable methods for identifying heterogeneous behavior, and few network analysis algorithms have been proposed for multiscale resolution. In this study, we apply a method of partitioning using the graph theoretic concept of clusters and communities. Using a modularity optimization algorithm, the cluster partition creates subgraphs based on their relative internal and external connectivities. The methodology is tested on two soft matter systems that have significantly different network topologies so as to probe its ability to identify multiple scale features and its generalizability. A binary Lennard-Jones fluid is first examined, where one component causes subgraphs that have high internal network connectivity yet are still connected to the rest of the interparticle network of interactions. The impact of connectivity and edge weighting on the cluster partition is investigated. In the second system, hierarchically organized molecular structures comprised of hydrogen bonded water molecules are identified at a liquid/liquid interface. These structures have a much more sparse network with significantly varied internal connectivity that is a challenge to differentiate from the background hydrogen bonding network of water molecules at the instantaneous interface. The organized macrostructures are effectively isolated from the background network using the cluster partition, and a time-dependent implementation allows us to reveal their reactivity. These studies indicate that cluster partitioning based upon intermolecular network connectivity patterns is broadly generalizable, depending only on user-defined intermolecular connectivity, is operable across different length scales, and is extensible to the study of dynamic phenomena.

Origins of Clustering of Metalate-Extractant Complexes in Liquid-Liquid Extraction.

Effective and energy-efficient separation of precious and rare metals is very important for a variety of advanced technologies. Liquid-liquid extraction (LLE) is a relatively less energy intensive separation technique, widely used in separation of lanthanides, actinides, and platinum group metals (PGMs). In LLE, the distribution of an ion between an aqueous phase and an organic phase is determined by enthalpic (coordination interactions) and entropic (fluid reorganization) contributions. The molecular scale details of these contributions are not well understood. Preferential extraction of an ion from the aqueous phase is usually correlated with the resulting fluid organization in the organic phase, as the longer-range organization increases with metal loading. However, it is difficult to determine the extent to which organic phase fluid organization causes, or is caused by, metal loading. In this study, we demonstrate that two systems with the same metal loading may impart very different organic phase organizations and investigate the underlying molecular scale mechanism. Small-angle X-ray scattering shows that the structure of a quaternary ammonium extractant solution in toluene is affected differently by the extraction of two metalates (octahedral PtCl62- and square-planar PdCl42-), although both are completely transferred into the organic phase. The aggregates formed by the metalate-extractant complexes (approximated as reverse micelles) exhibit a more long-range order (clustering) with PtCl62- compared to that with PdCl42-. Vibrational sum frequency generation spectroscopy and complementary atomistic molecular dynamics simulations on model Langmuir monolayers indicate that the two metalates affect the interfacial hydration structures differently. Furthermore, the interfacial hydration is correlated with water extraction into the organic phase. These results support a strong relationship between the organic phase organizational structure and the different local hydration present within the aggregates of metalate-extractant complexes, which is independent of metalate concentration.