Sposito Simulation Team

Clay Mineral Surface Geochemistry

Current Research Team

	Garrison Sposito Principal Investigator, Earth Sciences Division, Lawrence Berkeley National Laboratory
	Kideok Kwon Postdoctoral Scientist, Earth Sciences Division, Lawrence Berkeley National Laboratory
	Ian C. Bourg Postdoctoral Scientist, Earth Sciences Division, Lawrence Berkeley National Laboratory
	Keith Refson Collaborating Investigator, Rutherford-Appleton Laboratory, UK

Molecular dynamics "snapshot" of water molecules (blue and white), sodium ions (purple), and methane molecules (yellow-brown) intercalated simultaneously between two layers of montmorillonite, a common clay mineral. Original figure created by Dr. Sung-Ho Park (modified from Park, S.-H., and Sposito, G., J. Phys. Chem. B 2003, 107, 2281-2290) and used for the cover of S.A. Auerbach, K.A. Carrado, and P.K. Dutta (eds.) Handbook of Layered Materials Science and Technology. Marcel Dekker, New York, 2004.

Click on this image to view a short movie showing the diffusive motions of water molecules, sodium ions (blue), and a calcium ion (green) intercalated between two layers of montmorillonite. A close-up movie of the calcium ion and its six hydrated wter molecules appears at the top.

Research Goals

Because of their ubiquitous presence in natural materials and their strong surface reactions, colloidal particles figure importantly in a broad range of phenomena, from global climate change to contaminant remediation. Our research is designed to provide molecular-scale information about the structure and surface chemistry of these colloids (in particular, clay minerals, humic acids and manganese oxides), based on state-of-the-art computer simulation using tested codes based on realistic models of colloidal surface interactions with liquid water and a variety of dissolved chemicals.

Methods

We have been developing an approach to the surface geochemistry of 2:1 clay minerals and Mn oxides based on molecular-level simulation. Our research, supported by the DOE-BES program at Lawrence Berkeley National Laboratory, is aimed at understanding the mechanisms by which these minerals interact with water molecules, cations and organic molecules in aqueous subsurface environments. Our principal techniques, Monte Carlo (MC), molecular dynamics (MD), and density functional theory (DFT) simulations, are well-established, essential components of research in theoretical physical chemistry.

The underlying approach in MC and MD simulations is to construct potential functions that model all of the known interactions in a system of ions, atoms, and molecules, then devise a strategy for sampling the phase space of the interacting system in order to compute its properties. In a MC simulation, the configuration space of the system is sampled randomly under the guidance of an algorithm (Metropolis method) based in equilibrium statistical mechanics. In a MD simulation, the phase space of the system is sampled through numerical integration (Beeman algorithm) of the Newton-Euler equations of motion for each molecular species, which is performed consistently with the suite of potential functions assumed.

In recent years the interpretation of both diffraction and spectroscopic data on clay minerals has been facilitated by a class of independent, first-principles (sometimes termed "ab initio") quantum-mechanical simulations, which now have achieved sufficient accuracy to predict crystallographic properties of clay minerals without recourse to empirical parameterization. The ingredients of this scheme are the atomic nuclei and electrons whose interactions are described by the density functional theory (DFT) formulation of quantum mechanics. DFT-based methods are able to describe structure and bonding properties to a high degree of accuracy, including structural trends. Indeed, these methods represent the only practical quantum-mechanical approach for studying complex materials such as clay minerals and metal oxides.

Our MC calculations are performed using the code MONTE, developed by N.T. Skipper and K. Refson, whereas our MD calculations utilize the code MOLDY, developed by K. Refson. Our ab initio calculations are performed using a parallel version of the code CASTEP, developed by the UKCP (United Kingdom Car-Parrinello) consortium. Numerical calculations have been carried out under DOE support on IBM RS/6000 SP supercomputers at the NERSC (National Energy Research Scientific Computing Center).

Research Projects

Mn-vacancy-induced photoconductivity of layered manganese oxides

Manganese(IV) oxides are known to impact a broad range of biogeochemical processes, mainly through their high capacity for metal sorption and their facile oxidation of organic and inorganic compounds. Mn oxides found in weathering environments and natural waters are produced mainly by bacteria and take on layer structures, i.e., stacks of sheets of edge-sharing MnO₆ octahedra. An important structural characteristic of these oxides is the presence of Mn(IV) cation vacancies whose charge deficit is typically compensated by metal cations or protons. These vacancies have long been identified as strong adsorption sites for metals, but they may also play an important role in Mn redox biogeochemistry, particularly photo-induced redox reactions. Because detailed electronic band structure is the key to understanding photo-induced redox reactions, Mn(IV) oxides both vacancy-free and containing cation vacancies charge-compensated by protons were investigated using ab initio quantum mechanics simulations as realized in the code, CASTEP.

The ab initio study showed that a Mn(IV) vacancy reduces the band gap energy (Figure 1a) and separates photo-excited electrons and holes (Figure 1b). A reduction in band-gap energy generates more pairs of electrons and holes upon illumination, and the distinct separation of charge carriers enhances their transfer before loss by recombination. Therefore, Mn(IV) vacancies enhance effectively the photoconductivity of layer type MnO₂, facilitating photo-redox reactions between the mineral and inorganic or organic compounds.

Recent studies in materials science indicate that synthetic layer type Mn(IV) oxide nanoparticles with cation vacancies like those found in the biogenic MnO₂ minerals are semiconductors that produce photocurrent under visible light stimulation, thus making them very attractive for applications in energy storage, solar cell fabrication, and catalysis. Our prediction of effective band gap energy reduction by cation vacancies indicates that photocurrent production by these layer type MnO₂nanoparticles can be optimized by the control of vacancy concentrations during laboratory synthesis.

Figure 1. Calculated electronic properties of vacancy-free MnO₂ (left) and MnO₂ containing 12.5 or 3.3 % Mn(IV) vacancies charge-compensated by protons (right). (a) Band structures, showing reduction of the band gap energy (denoted by a red double arrow) from 1.3 to 0.3 eV. (Solid lines denote bands for spin-up electrons while dashed lines denote bands for spin-down electrons.) (b) Charge distributions for valence-band maximum hole states (orange) and conduction-band minimum electron states (blue), showing that a cation vacancy compensated by protons (H) effectively separates photo-induced charge carriers against recombination.

Ab initio computational crystallography of clay minerals

Clay minerals are aluminosilicates that predominate in the clay fractions of earth materials at intermediate stages of weathering. These minerals, isostructural with the micas, but with a more random pattern of isomorphic substitution, are sandwiches of tetrahedral and octahedral sheet structures. They are classified into layer types, distinguished by the number of tetrahedral and octahedral sheets combined, and then into groups, differentiated by the kinds of isomorphic cation substitutions that occur. The 2:1 layer type has two tetrahedral sheets that sandwich an octahedral sheet. Figure 2 shows the structure of a 2:1 layer type clay mineral, montmorillonite, as calculated by density functional theory. Isomorphic substitution of Al³⁺ by Mg²⁺ in the octahedral sheet of montmorillonite causes the mineral to carry a net negative structural charge. The structural charge is balanced by cations located between the montmorillonite layers.

Figure 2. Optimized structures determined by DFT simulations of Na-montmorillonite with varying structural charge caused by isomorphic substitutions in the octahedral sheet. In the upper series of "ball-and-stick" structures, which show two layers of the clay mineral, Si are shown in gray and O are shown in red. The substituted octahedral-sheet cation is Mg²⁺ (blue) and the interlayer cation is Na⁺ (purple). Octahedral-sheet Al³⁺ cations are shown in pale brown. The lower series of polyhedral structures show the site of isomorphic substitution in blue.

An accurate crystal structure for montmorillonite is not yet known because it is not possible to prepare a single crystal of this mineral. Quantum mechanical structural calculations based on density function theory can assist powder X-ray diffraction methods in determining the structure. Total-energy optimizations with ultrasoft pseudopotentials and plane-wave basis functions were performed using 64 processors to calculate Na-montmorillonite structure with varying charge (shown above, left to right), thus obtaining complete crystallographic information without adjustable parameters. Our DFT results were consistent with experimental X-ray diffraction data on montmorillonites with 0.0 e, -0.5 e, and -1.0 e structural charge (shown below, left to right), although predicted interatomic distances were 2-3 % too large on average, a known shortcoming of DFT simulations of minerals.

Unit Cell	DFT 0.0 e	Observed 0.0 e	DFT -0.5 e	Observed -0.5 e	DFT -1.0 e	Observed -1.0 e
a (Å)	5.22	5.16	5.27	5.18	5.28	5.18
b (Å)	9.08	9.00	9.13	8.97	9.14	8.97
c (Å)	10.00	9.35	10.41	10.05	10.55	10.05

Structure and dynamics of water and solutes near the surfaces of clay minerals

The plane of oxygen atoms on the cleavage surface of a 2:1 clay mineral is called a siloxane surface. This plane is characterized by hexagonal symmetry among its constituent oxygen ions. Associated with the siloxane surface is a roughly hexagonal cavity, formed by the bases (triads of oxygen ions) of six corner-sharing silica tetrahedra. This cavity has a diameter of about 0.26 nm. If there is no structural charge localized near a cavity, it can bind water molecules (Figure 3) attracted to the proton in the structural OH group nestled inside it (Figure 2), or it can bind hydrophobic molecules, such as methane (Figure 4), that are attracted to its oxygen atoms in preference to those in more polar water molecules. If there is structural charge localized near a cavity, then interlayer cations and water molecules both are attracted to this charge and may compete (Figure 5).

	Figure 3. Monte Carlo simulation snapshot of adsorbed water molecules attracted to uncharged hexagonal cavities.
	Figure 4. Monte Carlo simulation snapshot of the structure of a methane hydrate in the interlayer of Na-montmorillonite. Methane is coordinated to oxygens in both water (umbrella-like cage at the top) and the siloxane surface (bottom surface).
	Figure 5. Molecular dynamics simulation snapshot of cesium ions (red) and water molecules (blue) in a Cs-hectorite interlayer (Hectorite is a 2:1 clay mineral with structural charge created by substitution of Li⁺ for Mg²⁺ in its octahedral sheet. Grayish purple spheres symbolize the surface oxygen atoms of the lower clay layer surrounding this interlayer region. Click on the image to view a short movie showing the cesium ions competing with water molecules for adsorption sites (produced in collaboration with Wes Bethel of the NERSC Scientific Visualization Group).

Diffusion of solutes in water

The transport of solutes through porous media and their reactivity at nanoparticle surfaces can be kinetically controlled by molecular diffusion in bulk water or near hydrated mineral surfaces. Molecular diffusion in water can also result in significant isotopic fractionation, allowing the inference of geochemical fluxes from observed isotopic distributions. This emerging area of experimental research is being developped by our collaborator, Frank Richter (University of Chicago). Essential to the interpretation of these distributions is molecular-scale information about the magnitude and mechanisms of solute diffusion and diffusive fractionation, which can be obtained from molecular dynamics simulations.

Figure 6. Snapshot of a molecular dynamics simulation cell containing one lithium ion (green) and 215 water molecules (O atoms in red, H atoms in gray). The image was created with VMD.

Figure 7. Molecular dynamics simulation snapshot of a lithium ion (green) and four water molecules in its first solvation shell (Li-O distance of 0.3 nm or less). Click on the image to view a short movie of the co-diffusion of a lithium ion and water molecules located in its first solvation shell. The movie shows that the solvation structure of the lithium ion, predominantly tetrahedral, experiences temporary perturbations during which short-lived Li(H₂O)₅ or Li(H₂O)₆ structures exist. The movie was created with Videomach from images produced with VMD.

Isotopes of noble gases dissolved in groundwater are widely used as geochemical indicators of hydrologic transport processes and climatic change. Despite the reliance of these applications on a knowlege of the diffusion coefficients of noble gas isotopes in liquid water, very few measurements of these critical parameters have been reported, primarily because of significant analytical difficulties. Molecular dynamics simulations, which are not limited in this way, can then be very useful tools for examining the isotopic mass dependence of noble gas diffusion coefficients.

Figure 8. Molecular dynamics snapshot of a ⁴⁰Ar atom (in green) and water molecules located in its first solvation shell (i.e., at Ar-O distances < 0.52 nm). First-shell water molecules preferentially adopt a 'straddling' configuration by orienting either a lone pair of electrons (highlighted water molecule) or a hydrogen atom directly away from the solute. Click on the image to view a short movie of the motions of the Ar atom and the water molecules in its first solvation shell. The movie shows that the straddling configuration of the solvating water molecules is maintained on a time scale of several picoseconds.

Publications

Kwon, K.D., Refson, K., Sposito, G., 2008. Density functional theory predicts defect-induced photoconductivity in layered manganese oxides. Phys. Rev. Lett. 100, 146601.

Bourg, I.C., Sposito, G., 2008. Isotopic fractionation of noble gases by diffusion in liquid water: Molecular dynamics simulations and hydrologic applications. Geochim. Cosmochim. Acta 72, 2237-2247.

Bourg, I.C., Sposito, G., Bourg, A.C.M., 2007. Modeling cation diffusion in compacted water-saturated sodium bentonite at low ionic strength. Environ. Sci. Technol. 41, 8118-8122.

Bourg, I.C., Sposito, G., Bourg, A.C.M., 2007. Modeling the acid-base surface chemistry of montmorillonite. J. Colloid Interface Sci. 312, 297-310.

Bourg, I.C., Sposito, G., 2007. Molecular dynamics simulations of kinetic isotope fractionation during the diffusion of ionic species in liquid water. Geochim. Cosmochim. Acta 71, 5583-5589.

Sutton, R., Sposito, G., 2006. Molecular simulation of humic substance-Ca-montmorillonite complexes. Geochim. Cosmochim. Acta 70, 3566-3581.

Bourg, I.C., Sposito, G., Bourg, A.C.M., 2006. Tracer diffusion in compacted water-saturated bentonite. Clays Clay Miner. 54, 363-374.

Sutton, R., Sposito, G., 2005. Molecular structure in soil humic substances: The new view. Environ. Sci. Technol. 39, 9009-9015.

Sutton, R., Sposito, G., Diallo, M.S., Schulten, H.R., 2005. Molecular simulation of a model of dissolved organic matter. Environ. Toxicol. Chem. 24, 1902-1911.

Sposito, G., Park, S.-H., Refson, K., 2005. NERSC supercomputers are being used to predict the atomic structures of environmental nanoparticles that play important roles in global geochemical cycles. DOE Greenbook: Needs and Directions in High Performance Computing for the Office of Science, U.S. Department of Energy, Office of Science, June 2005 (PPPL-4090), pp. 30-31.

Park, S.-H., Sposito, G., 2004. Molecular modeling of clay structure and surface chemistry. In S.A. Auerbach, K.A. Carrado, and P.K. Dutta (eds.), Handbook of Layered Materials Science & Technology, Chap. 2. Marcel Dekker, New York.

Refson, K., Park, S.-H., Sposito, G., 2003. Ab initio computational crystallography of 2:1 clay minerals: 1. Pyrophyllite-1Tc. J. Phys. Chem. B 107, 13376-13383.

Park, S.H., Sposito, G., 2003. Do montmorillonite surfaces promote methane hydrate formation?: Monte Carlo and molecular dynamics simulations. J. Phys. Chem. B 107, 2281-2290.

Sutton, R., Sposito, G., 2002. Animated molecular dynamics simulations of hydrated caesium-smectite interlayers. Geochem. Trans. 3(9), 73-80.

Park, S.-H., Sposito, G., 2002. Structure of water adsorbed on a mica surface. Phys. Rev. Lett. 89, 85501.

Park, S.-H., Sposito, G., Sutton, R., Greathouse J., 2001. Density functional theory calculations on the structures of 2:1 clay materials. Earth Sciences Division 2000-2001 Annual Report, Lawrence Berkeley National Laboratory, p. 22.

Sutton, R., Sposito, G., 2001. Molecular simulation of interlayer structure and dynamics in 12.4 Å Cs-smectite hydrates. J. Colloid Interface Sci. 237, 174-184.

Greathouse, J.A., Refson, K., Sposito, G., 2000. Molecular dynamics simulation of water mobility in magnesium-smectite hydrates. J. Am. Chem. Soc. 122, 11459-11464.

Park, S.-H., Sposito, G., 2000. Monte Carlo simulation of total radial distribution functions for interlayer water in Li-, Na-, and K-montmorillonite hydrates. J. Phys. Chem. B 104, 4642-4648.

Park, S.-H., Sposito, G., Sutton, R., Greathouse, J.A., 2000. Formation and stability of methane hydrates in clay interlayers. Earth Sciences Division 1999-2000 Annual Report, Lawrence Berkeley National Laboratory.

Sposito, G., Skipper, N.T., Sutton, R., Park, S.-H., Soper, A.K., Greathouse, J., 1999. Surface geochemistry of the clay minerals. Proc. Natl. Acad. Sci. USA 96, 3358-3364.

Sposito, G., Park, S.-H., Sutton, R., 1999. Monte Carlo simulation of the total radial distribution function for interlayer water in sodium and potassium montmorillonites. Clays Clay Miner. 47, 192-200.

Chang, F.-R., Skipper, N.T., Refson, K., Greathouse, J.A., Sposito, G., 1999. Interlayer molecular structure and dynamics in Li-, Na-, and K-montmorillonite-water systems. ACS Symposium Series No. 715. American Chemical Society, Washington, D.C., pp. 88-106.

Sutton, R., Sposito, G., Park, S-H. Greathouse, J.A., 1999. Molecular modeling of clay mineral surface geochemistry: Hydrated cesium-smectites. Earth Sciences Division 1998-1999 Annual Report, Lawrence Berkeley National Laboratory, pp. 31-32.

Sposito, G., Park, S.-H., Sutton, R., 1999. Molecular simulations of clay mineral surface geochemistry. Science Highlights in 1998 Annual Report, National Energy Research Computing Center (NERSC), Lawrence Berkeley National Laboratory, p. 61.

Sposito, G., Greathouse, J.A., Park, S.-H., Sutton, R., 1998. Molecular scale simulation of clay mineral surface geochemistry. Earth Science Division 1997 Annual Report, Lawrence Berkeley National Laboratory, pp. 19-20.

Greathouse, J., Sposito, G., 1998. Monte Carlo and molecular dynamics studies of interlayer structure in Li(H₂O)₃ smectites. J. Phys. Chem. B 102, 2406-2414.

Chang, F.-R., Skipper, N.T., Sposito, G., 1998. Monte Carlo and molecular dynamics simulations of electrical double layer structure in potassium-montmorillonite hydrates. Langmuir 14, 1201-1207.

Chang, F.-R., Skipper, N.T., Sposito, G., 1997. Monte Carlo and molecular dynamics simulations of interfacial structure in lithium-montmorillonite hydrates. Langmuir 13, 2074-2082.

Chang, F.-R., Skipper, N.T., Sposito, G., 1995. Computer simulation of interlayer molecular structure in sodium montmorillonite hydrates. Langmuir 11, 2734-2741.

Skipper, N.T., Sposito, G., Chang, F.-R., 1995. Monte Carlo simulations of interlayer molecular structure in swelling clay minerals. 1. Methodology. Clays Clay Miner. 43, 285-293.

Skipper, N.T., Chang, F.-R., Sposito, G., 1995. Monte Carlo simulations of interlayer molecular structure in swelling clay minerals. 2. Monolayer hydrates. Clays Clay Miner. 43, 285-293.