Collective action of water molecules in zeolite dealumination

When exposed to steam, zeolite catalysts are irreversibly deactivated by loss of acidity and framework degradation caused by dealumination. Steaming typically occurs at elevated temperatures, making it challenging to investigate the mechanism with most approaches. Herein, we follow the dynamics of zeolite dealumination in situ, in the presence of a realistic loading of water molecules by means of enhanced sampling molecular dynamics simulations. H-SSZ-13 zeolite is chosen as a target system. Monte Carlo simulations predict a loading of more than 3 water molecules per unit cell at representative steaming conditions (450 °C, 1 bar steam). Our results show that a higher water loading lowers the free energy barrier of dealumination, as water molecules cooperate to facilitate hydrolysis of Al–O bonds. We find free energies of activation for dealumination that agree well with the available experimental measurements. Clearly, the use of enhanced sampling molecular dynamics yields a major step forward in the molecular level understanding of the dealumination; insight which is very hard to derive experimentally

Efficient workflows in molecular dynamics simulations and applications

I denne avhandlingen har Anders Hafreager utviklet forskningsverktøyet Atomify som syr sammen de forskjellige stegene i et numeriment: planlegging, kjøring og analyse. Ved å kunne se numerimentet i sanntid i et og samme program er det både lettere å bruke, og tiden fra en kreativ idè til svar kan reduseres betraktlig. Dette er nyttig både for erfarne forskere, men også i undervisning for uerfarne studenter med et brukervennlig grensesnitt. Atomify har blitt brukt av over tusen mennesker til forskning og undervisning, og er internasjonalt anerkjent. Atomify er her brukt til å studere hvordan den geometriske formen til en nanopartikkel utvikler seg over tid. Jo høyere temperatur på partikkelen, desto mer energi har atomene til å bevege seg rundt på overflaten og reorganisere seg mot statistisk likevekt. Dette kalles diffusjon og er prosessen som lager de rette flatene på blant annet diamanter og saltkrystaller. Arbeidet i denne avhandlingen er det første av sitt slag som studerer transformasjonen av en nanopartikkel fra en vilkårlig form til dens likevektsform ved å følge atomenes dynamiske reise. Hafreager har også videreført en statistisk metode kjent fra spill- og filmindustri til å generere nanoporøse materialer; faste stoffer med små hulrom og kanaler som væske kan strømme gjennom. Denne metoden kan brukes for å lage statistisk like materialer gitt en prøve som kan komme fra for eksempel et dyrt eksperiment. Disse systemene kan så studeres i sanntid ved bruk av VR-visualiseringer (virtual reality) i sanntid ved hjelp av spillmoteren Unreal Engine. Dette kan brukes for å få en dypere innsikt i hvilke fysiske prosesser som foregår ved at man har et 3-dimensjonalt synsfelt og kan bruke hender, hode og resten av kroppen til å navigere seg naturlig rundt inni systemet

Flow of dilute gases in complex nanoporous media

Most of the worlds currently accessible hydrocarbon resources are found in tight rocks - rocks with permeabilities in the millidarcy range and with pore sizes in the nanometer range. Tight rocks pose new scientific problems because of the small length-scales involved. Traditional oil plays are found in, for example, sand stone reservoirs with millimeter to micrometer sized pores. For such systems, standard hydrodynamics is a sufficient tool to understand, describe and predict fluid transport. In tight rocks, however, typical pore sizes are in the range of tens to hundreds of nanometers. At this scale, the mean free path - the average distance a particle moves between collisions - may become comparable to the characteristic sizes of the porous medium, and the standard assumption that the fluid can be described as a continuum no longer holds. The mean free path of dilute gases are often tens of nanometers, or higher. The gas from tight rocks, like shales, is stored inside closed pore networks or adsorbed onto organic matter. In order to extract adequate levels of gas from such rocks, we generate fractures to increase the permeability of the rock. The gas flows from small pore networks with diameters down to a few nanometers. The rate at which the gas flows through such networks is proportional to the permeability of the material - a result known as Darcy's law. Dilute gases in nanoporous media have a non-zero slip velocity which can cause an increase of permeability of a factor 50 compared to what continuum theory predicts. This is an effect known as the Klinkenberg effect. In order to be able to increase gas production rates in a safe way, we need to understand the physics at this scale. This requires models that are valid at these length scales. In this thesis, we implement two numerical particle models. The first is called Molecular Dynamics. It describes the motion of atoms by using parameterized potentials to compute forces between them. The second model, Direct Simulation Monte Carlo, uses the principles of statistical mechanics allowing larger systems to be studied. Both implementations support arbitrary geometries, and show promising scaling efficiency on massive parallel machines. We use these models to study the Klinkenberg effect and confirm that the Knudsen permeability correction correctly predicts the permeability for systems with pore sizes down to a few nanometers. We also analyze more complicated geometries, and argue that a stochastic version of the Knudsen correction is needed for geometries without a well defined Knudsen number. Highly efficient custom 3D visualization tools are developed using modern OpenGL techniques such as instanced geometry shaders, billboards and the marching cubes algorithm. Systems with tens of millions of particles can be rendered realtime with decent frame rate, allowing us to study larger systems than what can be done with already existing free software. All software developed during this thesis can serve as tools for further study in the field

Direct Atomic Simulations of Facet Formation and Equilibrium Shapes of SiC Nanoparticles

Understanding the shapes of nanoparticles is an important interdisciplinary problem because particle shapes can affect their properties, functionality, and applications. Advances in nanoscale imaging probes have revealed exquisite details of nanofaceting phenomena. However, quantitative theoretical predictions have not kept up the pace with experimental advances, and the atomic pathways of facet formation are largely unknown due to a lack of direct observations and simulations. Here we examine facet formation in spherical and cubic SiC nanoparticles and in SiC nanowires using molecular dynamics simulations reaching microseconds. We characterize layer-by-layer formation, diffusional motion along edges and corners, and determine energy barriers. We find that the equilibrium shapes are identical regardless of the initial shape of SiC nanoparticles or nanowires. For spherical and cubic nanoparticles, (110) facets form within 10 ns by lateral liquid-like diffusion of atoms. In contrast, faceting in SiC nanowires also involves normal diffusional motion with a higher energy barrier and hence much longer faceting times. These results have important implications for molecular-level understanding of the synthesis and stability of ceramic nanocrystals and nanowires

Molecular dynamics study of confined water in the periclase-brucite system under conditions of reaction-induced fracturing

The volume-increase associated with hydration reactions in rocks may lead to reaction-induced fracturing, but requires a stable water film to be present at reactive grain boundaries even when subject to compressive stress. Hydration of periclase to brucite is associated with a solid volume increase of ca. 110%. Recent experiments on the periclase-brucite system observed that when the effective mean stress exceeds 30 MPa, the reaction rate slows down dramatically. We hypothesize that for the brucite forming reaction to progress, the fluid film between grains must remain stable. If the applied pressure becomes larger than the hydration force, the fluid film will collapse and be squeezed out of the grain contacts. To quantify this effect, we study the behavior of a water film confined between periclase or brucite surfaces subject to compressive stress, by performing molecular dynamics simulations. The simulations are carried out using the ClayFF force field and the single point charge (SPC) water model in the molecular dynamics simulations program LAMMPS. The setup consists of two interfaces of either periclase or brucite surrounded by water. Our simulations show that when the pressure reaches a few tens of MPa, the water film collapses and reduces the water film to one or two water layers, while the self-diffusion coefficient of water molecules by a factor of eight. A water film thickness below two water layers is thinner than the size of the hydration shell around Mg2+-ions, which will limit ion-transport. The observed collapse of the water film to a single layer at a normal pressure of 25–30 MPa might explain the observed slow-down of reaction-induced fracturing in the periclase-brucite system

Altering thermal transport by strained-layer epitaxy

Since strain changes the interatomic spacing of matter and alters electron and phonon dispersion, an applied strain can modify the thermal conductivity k of a material. We show how the strain induced by heteroepitaxy is a passive mechanism to change k in a thin film. Molecular dynamics simulations of the deposition and epitaxial growth of ZnTe thin films provide insights into the role of interfacial strain in the conductivity of a deposited film. ZnTe films grow strain-free on latticematched ZnTe substrates, but similar thin films grown on a lattice-mismatched CdTe substrate exhibit 6% biaxial in-plane tensile strain and 7% uniaxial out-of-plane compressive strain. In the T ¼ 700 K–1100 K temperature range, the conductivities of strained ZnTe layers decrease to 60% of their unstrained values. The resulting understanding of dk/dT shows that strain engineering can be used to alter the performance of a thermal rectifier and also provides a framework for enhancing thermoelectric devices

Neuronify: An educational simulator for neural circuits

Educational software (apps) can improve science education by providing an interactive way of learning about complicated topics that are hard to explain with text and static illustrations. However, few educational apps are available for simulation of neural networks. Here, we describe an educational app, Neuronify, allowing the user to easily create and explore neural networks in a plug-and-play simulation environment. The user can pick network elements with adjustable parameters from a menu, i.e., synaptically connected neurons modelled as integrate-and-fire neurons and various stimulators (current sources, spike generators, visual, and touch) and recording devices (voltmeter, spike detector, and loudspeaker). We aim to provide a low entry point to simulation-based neuroscience by allowing students with no programming experience to create and simulate neural networks. To facilitate the use of Neuronify in teaching, a set of premade common network motifs is provided, performing functions such as input summation, gain control by inhibition, and detection of direction of stimulus movement. Neuronify is developed in C++ and QML using the cross-platform application framework Qt and runs on smart phones (Android, iOS) and tablet computers as well personal computers (Windows, Mac, Linux)

Game-Engine-Assisted Research platform for Scientific computing (GEARS) in Virtual Reality

The Game-Engine-Assisted Research platform for Scientific computing (GEARS) is a visualization framework developed at the Materials Genome Innovation for Computational Software (MAGICS) center to perform simulations and on-the-fly data exploration in virtual reality (VR) environments. This hardware-agnostic framework accommodates multiple programming languages and game engines in addition to supporting integration with a widely-used materials simulation engine called LAMMPS. GEARS also features a novel data exploration tool called virtual confocal microscopy, which endows scientific visualization with enhanced functionality. Keywords: Virtual reality, Real-time simulation visualization, Molecular dynamics, LAMMP

Energy dependence of the prompt gamma-ray emission from the (d,p)-induced fission of U-234 and Pu-240

Prompt-fission γ rays are responsible for approximately 5% of the total energy released in fission, and therefore important to understand when modeling nuclear reactors. In this work we present prompt γ -ray emission characteristics in fission as a function of the nuclear excitation energy of the fissioning system. Emitted γ -ray spectra were measured, and γ -ray multiplicities and average and total γ energies per fission were determined for the 233 U ( d , p f ) reaction for excitation energies between 4.8 and 10 MeV, and for the 239 Pu ( d , p f ) reaction between 4.5 and 9 MeV. The spectral characteristics show no significant change as a function of excitation energy above the fission barrier, despite the fact that an extra ∼ 5 MeV of energy is potentially available in the excited fragments for γ decay. The measured results are compared with model calculations made for prompt γ -ray emission with the fission model code gef. Further comparison with previously obtained results from thermal neutron induced fission is made to characterize possible differences arising from using the surrogate ( d , p ) reaction