Understanding the adsorption of isolated metal cations from water on to mineral surfaces is critical for toxic waste retention and cleanup in the environment. Heterogeneous nucleation of metal oxyhydroxides and other minerals on material surfaces is key to crystal growth and dissolution. The link connecting these two areas, namely cation dimerization and polymerization, is far less understood. In this work we apply ab initio molecular dynamics calculations to examine the coordination structure of hydroxide-bridged Cu(II) dimers, and the free energy changes associated with Cu(II) dimerization on silica surfaces. The dimer dissociation pathway involves sequential breaking of two Cu2+-OH− bonds, yielding three local minima in the free energy profiles associated with 0-2 OH− bridges between the metal cations, and requires the design of a (to our knowledge) novel reaction coordinate for the simulations. Cu(II) adsorbed on silica surfaces are found to exhibit stronger tendency towards dimerization than when residing in water. Cluster-plus-implicit-solvent methods yield incorrect trends if OH− hydration is not correctly depicted. The predicted free energy landscapes are consistent with fast equilibrium times (seconds) among adsorbed structures, and favor Cu2+ dimer formation on silica surfaces over monomer adsorption.
Tracer gases, whether they are chemical or isotopic in nature, are useful tools in examining the flow and transport of gaseous or volatile species in the underground. One application is using detection of short-lived argon and xenon radionuclides to monitor for underground nuclear explosions. However, even chemically inert species, such as the noble gases, have bene observed to exhibit non-conservative behavior when flowing through porous media containing certain materials, such as zeolites, due to gas adsorption processes. This report details the model developed, implemented, and tested in the open source and massively parallel subsurface flow and transport simulator PFLOTRAN for future use in modeling the transport of adsorbing tracer gases.
The structural and dynamical properties of nanoconfined solutions can differ dramatically from those of the corresponding bulk systems. Understanding the changes induced by confinement is central to controlling the behavior of synthetic nanostructured materials and predicting the characteristics of biological and geochemical systems. A key outstanding issue is how the molecular-level behavior of nanoconfined electrolyte solutions is reflected in different experimental, particularly spectroscopic, measurements. This is addressed here through molecular dynamics simulations of the OH stretching infrared (IR) spectroscopy of NaCl, NaBr, and NaI solutions in isotopically dilute HOD/D 2 O confined in hydroxylated amorphous silica slit pores of width 1–6 nm and pH [Formula: see text]. In addition, the water reorientation dynamics and spectral diffusion, accessible by pump–probe anisotropy and two-dimensional IR measurements, are investigated. The aim is to elucidate the effect of salt identity, confinement, and salt concentration on the vibrational spectra. It is found that the IR spectra of the electrolyte solutions are only modestly blue-shifted upon confinement in amorphous silica slit pores, with both the size of the shift and linewidth increasing with the halide size, but these effects are suppressed as the salt concentration is increased. This indicates the limitations of linear IR spectroscopy as a probe of confined water. However, the OH reorientational and spectral diffusion dynamics are significantly slowed by confinement even at the lowest concentrations. The retardation of the dynamics eases with increasing salt concentration and pore width, but it exhibits a more complex behavior as a function of halide.
Structural properties of the anionic surfactant dioctyl sodium sulfosuccinate (AOT or Aerosol-OT) adsorbed on the mica surface were investigated by molecular dynamics simulation, including the effect of surface loading in the presence of monovalent and divalent cations. The simulations confirmed recent neutron reflectivity experiments that revealed the binding of anionic surfactant to the negatively charged surface via adsorbed cations. At low loading, cylindrical micelles formed on the surface, with sulfate head groups bound to the surface by water molecules or adsorbed cations. Cation bridging was observed in the presence of weakly hydrating monovalent cations, while sulfate groups interacted with strongly hydrating divalent cations through water bridges. The adsorbed micelle structure was confirmed experimentally with cryogenic electronic microscopy, which revealed micelles approximately 2 nm in diameter at the basal surface. At higher AOT loading, the simulations reveal adsorbed bilayers with similar surface binding mechanisms. Adsorbed micelles were slightly thicker (2.2–3.0 nm) than the corresponding bilayers (2.0–2.4 nm). Upon heating the low loading systems from 300 K to 350 K, the adsorbed micelles transformed to a more planar configuration resembling bilayers. The driving force for this transition is an increase in the number of sulfate head groups interacting directly with adsorbed cations.
The ability to predict transport properties of liquids quickly and accurately will greatly improve our understanding of fluid properties both in bulk and complex mixtures, as well as in confined environments. Such information could then be used in the design of materials and processes for applications ranging from energy production and storage to manufacturing processes. As a first step, we consider the use of machine learning (ML) methods to predict the diffusion properties of pure liquids. Recent results have shown that Artificial Neural Networks (ANNs) can effectively predict the diffusion of pure compounds based on the use of experimental properties as the model inputs. In the current study, a similar ANN approach is applied to modeling diffusion of pure liquids using fluid properties obtained exclusively from molecular simulations. A diverse set of 102 pure liquids is considered, ranging from small polar molecules (e.g., water) to large nonpolar molecules (e.g., octane). Self-diffusion coefficients were obtained from classical molecular dynamics (MD) simulations. Since nearly all the molecules are organic compounds, a general set of force field parameters for organic molecules was used. The MD methods are validated by comparing physical and thermodynamic properties with experiment. Computational input features for the ANN include physical properties obtained from the MD simulations as well as molecular properties from quantum calculations of individual molecules. Fluid properties describing the local liquid structure were obtained from center of mass radial distribution functions (COM-RDFs). Feature sensitivity analysis revealed that isothermal compressibility, heat of vaporization, and the thermal expansion coefficient were the most impactful properties used as input for the ANN model to predict the MD simulated self-diffusion coefficients. The MD-based ANN successfully predicts the MD self-diffusion coefficients with only a subset (2 to 3) of the available computationally determined input features required. A separate ANN model was developed using literature experimental self-diffusion coefficients as model targets. Although this second ML model was not as successful due to a limited number of data points, a good correlation is still observed between experimental and ML predicted self-diffusion coefficients.
Predicting the diffusion coefficient of fluids under nanoconfinement is important for many applications including the extraction of shale gas from kerogen and product turnover in porous catalysts. Due to the large number of important variables, including pore shape and size, fluid temperature and density, and the fluid-wall interaction strength, simulating diffusion coefficients using molecular dynamics (MD) in a systematic study could prove to be prohibitively expensive. Here, we use machine learning models trained on a subset of MD data to predict the self-diffusion coefficients of Lennard-Jones fluids in pores. Our MD data set contains 2280 simulations of ideal slit pore, cylindrical pore, and hexagonal pore geometries. We use the forward feature selection method to determine the most useful features (i.e., descriptors) for developing an artificial neutral network (ANN) model with an emphasis on easily acquired features. Our model shows good predictive ability with a coefficient of determination (i.e., R2) of ∼0.99 and a mean squared error of ∼2.9 × 10-5. Finally, we propose an alteration to our feature set that will allow the ANN model to be applied to nonideal pore geometries.
The objective of this project was to eliminate and/or render bulk agent unusable by a threat entity via neutralization and/or polymerization of the bulk agent using minimal quantities of additives. We proposed the in situ neutralization and polymerization of bulk chemical agents (CAs) by performing reactions in the existing CA storage container via wet chemical approaches using minimal quantities of chemical based materials. This approach does not require sophisticated equipment, fuel to power generators, electricity to power equipment, or large quantities of decontaminating materials. By utilizing the CA storage container as the batch reactor, the amount of logistical resources can be significantly reduced. Fewer personnel are required since no sophisticated equipment needs to be set up, configured, or operated. Employing the CA storage container as the batch reactor enables the capability to add materials to multiple containers in a short period of time as opposed to processing one container at a time for typical batch reactor approaches. In scenarios where a quick response is required, the material can be added to all the CA containers and left to react on its own without intervention. Any attempt to filter the CA plus material solution will increase the rate of reaction due to increased agitation of the solution.
As a general-purpose force field for molecular simulations of layered materials and their fluid interfaces, Clayff continues to see broad usage in atomistic computational modeling for numerous geoscience and materials science applications due to its (1) success in predicting properties of bulk nanoporous materials and their interfaces, (2) transferability to a range of layered and nanoporous materials, and (3) simple functional form which facilitates incorporation into a variety of simulation codes. Here, we review applications of Clayff to model bulk phases and interfaces not included in the original parameter set and recent modifications for modeling surface terminations such as hydroxylated nanoparticle edges. We conclude with a discussion of expectations for future developments.
We present a combined molecular dynamics (MD) simulation and X-ray absorption fine structure (XAFS) spectroscopic investigation of aqueous iron adsorption on nanoconfined amorphous silica surfaces. The simulation models examine the effects of pore size, pH (surface charge), iron valency, and counter-ion (chloride or hydroxide). The simulation methods were validated by comparing the coordination environment of adsorbed iron with coordination numbers and bond lengths derived from XAFS. In the MD models, nanoconfinement effects on local iron coordination were investigated by comparing results for unconfined silica surfaces and in confined domains within 2 nm, 4 nm, and 8 nm pores. Experimentally, coordination environments of iron adsorbed onto mesoporous silica with 4 nm and 8 nm pores at pH 7.5 were investigated. The effect of pH in the MD models was included by simulating Fe(ii) adsorption onto negatively charged SiO2surfaces and Fe(iii) adsorption on neutral surfaces. The simulation results show that iron adsorption depends significantly on silica surface charge, as expected based on electrostatic interactions. Adsorption on a negatively charged surface is an order of magnitude greater than on the neutral surface, and simulated surface coverages are consistent with experimental results. Pore size effects from the MD simulations were most notable in the adsorption of Fe(ii) at deprotonated surface sites (SiO−), but adsorption trends varied with concentration and aqueous Fe speciation. The coordination environment of adsorbed iron varied significantly with the type of anion. Considerable ion pairing with hydroxide anions led to the formation of oligomeric surface complexes and aqueous species, resulting in larger iron hydroxide clusters at higher surface loadings.
Water in nano-scale confining environments is a key element in many biological, material, and geological systems. The structure and dynamics of the liquid can be dramatically modified under these conditions. Probing these changes can be challenging, but vibrational spectroscopy has emerged as a powerful tool for investigating their behavior. A critical, evolving component of this approachis a detailed understanding of the connection between spectroscopic features and molecular-level details. In this paper, this issue is addressed by using molecular dynamics simulations to simulate the linear infrared (IR) and Raman spectra for isotopically dilute HOD in D2O confined inhydroxylated amorphous silica slit pores. The effect of slit-pore width and hydroxyl density on thesilica surface on the vibrational spectra is also investigated. The primary effect of confinement is a blueshift in the frequency of OH groups donating a hydrogen bond to the silica surface. Thisappears as a slight shift in the total (measurable) spectra but is clearly seen in the distance-based IR and Raman spectra. Analysis indicates that these changes upon confinement are associated withtheweaker hydrogen-bond accepting properties of silica oxygens compared to water molecules.
González, Rafael I.; Rojas-Nunez, Javier; Valencia, Felipe J.; Munoz, Francisco; Baltazar, Samuel E.; Allende, Sebastián; Rogan, José; Valdivia, Juan A.; Kiwi, Miguel; Ramírez, Ricardo; Greathouse, Jeffery A.
Imogolite is a fascinating inorganic nanotube that is found in nature or synthesized in a laboratory. The synthesis process is carried out in liquid media, and leads to the formation of almost monodisperse diameter nanotubes. Here we investigate, employing classical molecular dynamics simulations, the interaction of water and imogolite for nanotubes of several radii. We established that water penetrates the pores of N = 9 and larger nanotubes, and adopts a coaxial arrangement in it. Also, while water molecules can diffuse along the center of the nanotube, the molecules next to the inner imogolite walls have very low mobility. At the outer nanotube wall, an increase of water density is observed, this effect extends up to 1 nm, beyond which water properties are bulk-like. Both phenomena are affected by the imogolite curvature.
Classical molecular dynamics (MD) simulations were performed to provide a conceptual understanding of the amorphous-crystalline interface for a candidate negative thermal expansion (NTE) material, ZrW2O8. Simulations of pressure-induced amorphization at 300 K indicate that an amorphous phase forms at pressures of 10 GPa and greater, and this phase persists when the pressure is subsequently decreased to 1 bar. However, the crystalline phase is recovered when the slightly distorted 5 GPa phase is relaxed to 1 bar. Simulations were also performed on a two-phase model consisting of the high-pressure amorphous phase in direct contact with the crystalline phase. Upon equilibration at 300 K and 1 bar, the crystalline phase remains unchanged beyond a thin layer of disrupted structure at the crystalline-amorphous interface. Differences in local atomic structure at the interface are quantified from the simulation trajectories.
Here we report molecular level details regarding the adsorption of sarin (GB) gas in a prototypical zirconium-based metal-organic framework (MOF, UiO-66). By combining predictive modeling and experimental spectroscopic techniques, we unambiguously identify several unique bindings sites within the MOF, using the P=O stretch frequency of GB as a probe. Remarkable agreement between predicted and experimental IR spectrum is demonstrated. As previously hypothesized, the undercoordinated Lewis acid metal site is the most favorable binding site. Yet multiple sites participate in the adsorption process; specifically, the Zr-chelated hydroxyl groups form hydrogen bonds with the GB molecule, and GB weakly interacts with fully coordinated metals. Importantly, this work highlights that subtle orientational effects of bound GB are observable via shifts in characteristic vibrational modes; this finding has large implications for degradation rates and opens a new route for future materials design.
This report describes the potential of a novel class of materials--a-ZrW 2 0 8 , Zr 2 WP 2 0 12 , and related compounds that contract upon amorphization as possible radionuclide waste-forms. The proposed ceramic waste-forms would consist of zoned grains, or sintered ceramics with center- loaded radionuclides and barren shells. Radiation-induced amorphization would result in core shrinkage but would not fracture the shells or overgrowths, maintaining isolation of the radionuclide. In this report, we have described synthesis techniques to produce phase-pure forms of the materials, and how to fully densify those materials. Structural models for the materials were developed and validated using DFPT approaches, and radionuclide substitution was evaluated; U(IV), Pu(IV), Tc(IV) and Tc(VII) all readily substitute into the material structures. MD modeling indicated that strain associated with radiation-induced amorphization would not affect the integrity of surrounding crystalline materials, and these results were validated via ion beam experimental studies. Finally, we have evaluated the leach rates of the barren materials, as determined by batch and flow-through reactor experiments. ZrW 2 0 8 leaches rapidly, releasing tungstate while Zr is retained as a solid oxide or hydroxide. Tungsten release rates remain elevated over time and are highly sensitive to contact times, suggesting that this material will not be an effective waste-form. Conversely, tungsten releases rates from Zr2WP2012 rapidly drop, show little dependence on short-term changes in fluid contact time, and in over time, become tied to P release rates. The results presented here suggest that this material may be a viable waste-form for some hard-to-handle radionuclides such as Pu and Tc. ACKNOWLEDGEMENTS The authors acknowledge the contributions to this report from Sandia National Laboratories researchers Steven Meserole, Mark Rodriguez, Clay Payne, Tim Boyle, Nate Padilla, Khalid Hattar, Anthony Monterrosa, Trevor Clark, and Daniel Perry.
A molecular-scale understanding of the transition between hydration states in clay minerals remains a challenging problem because of the very fast stepwise swelling process observed from X-ray diffraction (XRD) experiments. XRD profile modeling assumes the coexistence of multiple hydration states in a clay sample to fit the experimental XRD pattern obtained under humid conditions. While XRD profile modeling provides a macroscopic understanding of the heterogeneous hydration structure of clay minerals, a microscopic model of the transition between hydration states is still missing. Here, for the first time, we use molecular dynamics simulation to investigate the transition states between a dry interlayer, one-layer hydrate, and two-layer hydrate. We find that the hydrogen bonds that form across the interlayer at the clay particle edge make an important contribution to the energy barrier to interlayer hydration, especially for initial hydration.
The phonon, infrared, and Raman spectroscopic properties of zirconium tungsten phosphate, Zr2(WO4)(PO4)2 (space group Pbcn, IT No. 60; Z = 4), have been extensively investigated using density functional perturbation theory (DFPT) calculations with the Perdew, Burke, and Ernzerhof exchange-correlation functional revised for solids (PBEsol) and validated by experimental characterization of Zr2(WO4)(PO4)2 prepared by hydrothermal synthesis. Using DFPT-simulated infrared, Raman, and phonon density-of-state spectra combined with Fourier transform infrared and Raman measurements, new comprehensive and extensive assignments have been made for the spectra of Zr2(WO4)(PO4)2, resulting in the characterization of its 29 and 34 most intense IR- and Raman-active modes, respectively. DFPT results also reveal that ν1(PO4) symmetric stretching and ν3(PO4) antisymmetric stretching bands have been interchanged in previous Raman experimental assignments. Negative thermal expansion in Zr2(WO4)(PO4)2 appears to have very limited impact on the spectral properties of this compound. This work shows the high accuracy of the PBEsol exchange-correlation functional for studying the spectroscopic properties of crystalline materials using first-principles methods.
Toward the development of classical force fields for the accurate modeling of clay mineral-water systems, we have extended the use of metal-O-H (M-O-H) angle bending terms to describe surface Si-O-H bending for hydrated kaolinite edge structures. Kaolinite, comprising linked octahedral Al and tetrahedral Si sheets, provides a rigorous test by combining aluminol and silanol groups with water molecules in hydrated edge structures. Periodic density functional theory and classical force fields were used with molecular dynamics to evaluate the structure, dynamics, hydrogen bonding, and power spectra for deriving optimum bending force constants and optimal equilibrium angles. Cleavage energies derived from density functional theory molecular dynamics calculations indicate the relative stabilities of both AC 1 and AC 2 edge terminations of kaolinite where Si-OH and Al-(OH 2 ) or Si-OH, Al-OH, and Al-(OH 2 ) groups exist, respectively. Although not examined in this study, the new Si-O-H angle bending parameter should allow for improved modeling of hydroxylated surfaces of silica minerals such as quartz and cristobalite, as well as amorphous silica-based surfaces and potentially those of other silicate and aluminosilicate phases.