Structure Modeling with X-ray Absorption and Reverse Monte Carlo: Applications to Water

Water is an important substance. It is part of us, of our environment, and is a fundamental prerequisite for the existence of life as we know it. The structure of water is still, after over 100 years of research on the subject, however under debate. In this thesis x-ray absorption spectroscopy (XAS) and reverse Monte Carlo (RMC) modeling are used to search for structural solutions of water consistent with many different experimental data sets, with emphasis on the combination of different experimental techniques for a reliable structure determination. Neutron and x-ray diffraction are analyzed in combination with the more recent synchrotron radiation based XAS. Geometrical criteria for H-bonding are implemented in RMC to drive the fits and allow to evaluate differently H-bonded structure models against the data. It is shown that the available diffraction data put little constraints on the type of H-bond topology or O-O-O tetrahedrality for the structure of liquid water. It is also demonstrated that classical MD simulations, using some of the most common interaction potentials for water, give rise to O-O and O-H pair-correlation functions with too sharp first peaks at too short distances to be in agreement with diffraction, and furthermore that requiring a large fraction of broken H-bonds is not in itself enough for a structure model to reproduce the experimental XAS. A contribution to the theoretical description of XAS is made by an in-depth investigation of important technical aspects of the TP-DFT spectrum calculations. A novel approach to RMC, applicable also to data that require a significant amount of computer time to evaluate, is developed which makes use of pre-computed properties from a large set of local geometries allowing RMC simulations directly on data from core-level spectroscopies such as XAS.At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4, 5 and 6: Submitte

Temporal Coarse Graining of CO₂ and N₂ Diffusion in Zeolite NaKA: From the Quantum Scale to the Macroscopic

The kinetic CO₂-over-N₂ sieving capabilities in narrow pore zeolites are dependent on the free-energy barriers of diffusion between the zeolite pores, which can be fine-tuned by altering the framework composition. An <i>ab initio</i> level of theory is necessary to accurately compute the energy barriers, whereas it is desirable to predict the macroscopic scale diffusion for industrial applications. Using <i>ab initio</i> molecular dynamics on the picosecond time scale, the free-energy barriers of diffusion can be predicted for different local pore properties in order to identify those that are rate-determining for the pore-to-pore diffusion. Specifically, we investigate the effects of the Na⁺-to-K⁺ exchange at the different cation sites and the CO₂ loading in Zeolite NaKA. These computed energy barriers are then used as input for the Kinetic Monte Carlo method, coarse graining the dynamic simulation steps to the pore-to-pore diffusion. With this approach, we simulate how the identified rate-determining properties as well as the application of skin-layer surface defects affect the diffusion driven uptake in a realistic Zeolite NaKA powder particle model on a macroscopic time scale. Lastly, we suggest a model by combining these effects, which provides an excellent agreement with the experimental CO₂ and N₂ uptake behaviors presented by Liu et al. (<i>Chem. Commun.</i> <b>2010</b>, <i>46</i>, 4502–4504)

Statistical error in simulations of Poisson processes: Example of diffusion in solids

Simulations of diffusion in solids often produce poor statistics of diffusion events. We present an analytical expression for the statistical error in ion conductivity obtained in such simulations. The error expression is not restricted to any computational method in particular, but valid in the context of simulation of Poisson processes in general. This analytical error expression is verified numerically for the case of Gd-doped ceria by running a large number of kinetic Monte Carlo calculations.Funding Agencies|Swedish Energy Agency (STEM) [35515-1]; Carl Tryggers Foundation [CTS 14:433]; Swedish Research Council (VR) [2014-5993, 2011-42-59]; LiLi-NFM; Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linkoping University (Faculty Grant SFO-MatLiU) [2009 00971]</p

Modeling Kinetics of Water Adsorption on the Rutile TiO2 (110) Surface: Influence of Exchange-Correlation Functional

The accuracy of the theoretical description of materials properties in the framework of density functional theory (DFT) inherently depends on the exchange-correlation (XC) functional used in the calculations. Here we investigate the influence of the choice of a XC functional (PBE, RPBE, PW91, and PBE0) on the kinetics of the adsorption, diffusion and dissociation of water on the rutile TiO2(110) surface using a combined Kinetic Monte Carlo (KMC) - DFT approach, where the KMC simulations are based on the barriers for the aforementioned processes calculated with DFT. We also test how the adsorption energy of intact and dissociated water molecules changes when dispersion interactions are included into the calculations. We consider the beginning of the water layer formation varying coverage up to 0.2 monolayer (ML) at temperatures up to 180K. We demonstrate that the dynamics of the simulated water-titania system is extremely sensitive to the choice of the XC functional