Browsing by Author "Foster, Adam S., Prof., Aalto University, Department of Applied Physics, Finland"

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  • Atomistic Simulations of Solid-Liquid Interfaces
    (2013) Reischl, Bernhard
     School of Science | Doctoral dissertation (article-based)
    Solid-liquid interfaces can be encountered in systems and processes ranging from biomineralization to fuel cell technology, and play an important role in growth or dissolution mechanisms of particles or surfaces in solution. The surface-induced changes of material properties not only affect the solid, but also the liquid itself: the structure of the liquid at the interface is very different from bulk. Understanding these processes occurring at solid-liquid interfaces at the atomistic scale is fundamental to a wide range of disciplines. New insight can be gained by combining cutting edge experimental techniques and computer simulations. The atomic force microscope (AFM) can be used to study solid-liquid interfaces in high resolution. We have developed new simulation methods, based on atomistic molecular dynamics and free energy calculations in order to model the complex imaging mechanism. In addition to the direct interactions between AFM tip and surface, our approach takes into account entropic contributions from interactions with water molecules in hydration layers on top of the surface as well as in the solvation shell of the AFM tip. For the Calcite (10-14) surface in water, we find good agreement between our simulations and recent 3D AFM data. We have also developed and tested a simple model to calculate AFM images only from differences in equilibrium local water density in hydration layers, reducing the computational cost by up to three orders of magnitude compared to free energy calculations including an explicit AFM tip. We have further studied the hydration layer structure and dissociation kinetics of the NaCl (100) surface in water from ab initio molecular dynamics, as well as the role of surface premelting of ice in the context of atomic scale friction at the ice-ice interface.
  • Automating high-resolution atomic force microscopy image interpretation
    (2023) Oinonen, Niko
     School of Science | Doctoral dissertation (article-based)
    Atomic force microscopy (AFM) has become an important tool in nanoscale studies of matter, imaging and characterizing its properties, reaching from micrometer scale down to the sub-nanometer scale. In particular, high-resolution AFM performed in ultra-high vacuum with functionalized tips has achieved a resolution capable of identifying individual atoms in single molecules adsorbed on surfaces. However, applications so far have been mostly limited to simple planar molecules due to the difficult interpretability of the obtained images for more complicated sample molecules. At the same time, fast and accurate simulations of high-resolution AFM images have become available in the form of the Probe Particle Model (PPM). The PPM simulations make it easy to go from an atomic structure into an AFM image, but the reverse process is not as easy, often requiring a lot of manual labour with testing different candidate molecule geometries. An automated approach for solving this inverse problem would be a major benefit for the wider applicability AFM into imaging atomic scale systems. To this end, one can note the recent emergence of large-scale machine learning (ML) models, especially deep neural networks, enabling major progress in many fields of science. Utilizing a very large dataset, it is possible to train an ML model to perform a task where no known algorithmic approach works. Given the rapid data-generation capability of the PPM simulations, it should be possible to train an ML model to perform the inverse-imaging task in AFM, going from an AFM image into a molecule geometry or some other property of interest. The work in this thesis utilizes the PPM to generate simulations for a large database of molecules, and uses those simulations to train neural networks for predicting the molecule geometry as well as the electrostatic field from AFM images. The trained models are subsequently tested also on experimental AFM images, where generally good results are found, but in some cases differences in the details between the simulation and the real experiment make the predictions incorrect or ambiguous. At this stage full general automation of the AFM image interpretation process is not yet possible, but the results here present the first steps in this direction. Additionally, an ML method for automatizing the tip functionalization part of the AFM measurement preparation is presented.
  • Nanoscale Friction of Ice
    (2013) Samadashvili, Nino
     School of Science | Doctoral dissertation (monograph)
    Friction between macroscopic surfaces sliding relative to each other has been long investigated, nevertheless it still remains one of the most complex and least understood processes in nature. In connection with the success in both experimental and theoretical fields, through the development of nanotribology offering the possibility of understanding atomic-level origins of friction, the subject continues to be re-examined. In this work we use molecular dynamics simulations to study frictional behavior of an ice-ice system (one of the most interesting systems from friction point of view due to its unusually low friction coefficient and prevalence in life) at the nanoscale, particularly the influence of temperature, applied load and sliding velocity on calculated frictional force. We compare our results to experimental findings and discuss agreement within different ranges of parameters affecting friction. Our work provides useful insight into the field of nanoscale ice friction and can be used as a basis for future development of the field.
  • Simulating atomic force microscopy at the solid-liquid interface
    (2017) Tracey, John
     School of Science | Doctoral dissertation (article-based)
    NC-AFM is an experimental technique that is capable of imaging, in principle, any surface at atomic resolution in any environment. Despite the clear advantages of NC-AFM, the biggest drawback is with regards to the interpretation of the results. Typically theoretical simulations are conducted to assist with this. A key component in linking theoretical simulations and the experimental results is the use of virtual machines. These aim to reproduce the experiment, allowing for a more complete simulation. The PyVAFM presented within, is such a virtual machine allowing users to reproduce any experimental setup or operational mode. It is fully open source, allowing future users to update the software with new cutting edge experimental components. Solid-liquid interfaces play a key role in many natural processes such as weathering or biomineralisation. In order to understand these processes, it is important to gain insight into the atomic structure behind them. Exploration of solid-liquid interfaces by NC-AFM is common, although due to the additional complexity of the environment as well as the experiment, the measured signal is difficult to relate to physical processes. As part of this work, we examine experimental results of Frequency Modulated-Atomic Force Microscopy (FM-AFM) on calcite in water and reproduce them using the PyVAFM, in an attempt to understand them in terms of average tip-sample distance. Building upon this we also considered steps on a calcite surface, studied using a new high speed AFM set-up. It was found that a shadow appeared at the step edge that was previously unseen. Using a combination of molecular dynamics and simulated AFM images we developed a model of the shadow region giving insight into the dissolution process. A chemically similar material to calcite, dolomite contains a similar crystal structure, but every second Ca is replaced with a Mg. Up until now identification of chemically alike species with the same surface charge has not been demonstrated in liquids and represents a new benchmark in sensitivity. By comparing the subtle differences in FM-AFM frequency shift curves as well as the simulated water densities above the various cations, it was possible for us to identify the Mg and Ca sites on dolomite. The main theme linking all these topics is in the analysis of NC-AFM images. From this it is clear that it still remains challenging and is typically done by eye. This is a very subjective approach and unscientific. In this final section we endeavour to produce an algorithm that uses Fourier analysis of images to produce a score of how similar the two images are. We produced an algorithm that is insensitive to phase, rotation, scale and resolution and designed specifically for comparison of NC-AFM images, allowing increased objectivity when making such comparisons.
  • Structural and dynamic properties of the solid-liquid interfaces studied by Molecular Dynamics simulations
    (2018) Zivanovic, Lidija
     School of Science | Doctoral dissertation (article-based)
    The solid-liquid interface represents systems of great and diverse technological importance. The interfacial phenomena at solid-liquid interfaces play an important role in a wide range of biological, chemical and industrial processes, such as heterogeneous catalysis, environmental remediation, waste disposal, biomineralization, and others. In order to understand these processes, it is important to study solid-liquid interfaces at the atomic level.    Nowadays, these interfaces are mainly explored at the atomic scale with AFM, providing detailed insights into the liquid structure. Since it was discovered, AFM experienced numerous technical improvements that led to the development of 2D and 3D force mapping technique. Although these new techniques allow us to visualize hydration layers at solid-liquid interfaces with molecular resolution, the biggest flaw is with regards to the interpretation of the results due to the very complex nature of the experiments themselves. Hence, the connection between the measured signal and physical processes usually requires additional analysis tools.    In order to provide a better understanding of the processes being investigated by AFM, in this work classical molecular dynamics techniques (MD) are employed. As part of this work, we used MD simulations to support and explain AFM images obtained at highly reactive surface steps. Up until now, AFM imaging of the heterogeneous step edges was accompanied by many difficulties and as such, has not been obtained. In this thesis, we represented the first obtained 3D AFM topographic images of the hydration structures at heterogeneous edges and provided additional understanding of the atomic structure of the hydration layers and the processes at such edges by performing MD simulations. The distribution of charge in the solid-liquid interfaces plays an essential role in a wide range of processes in biology, geology, and technology. It was also noticed that AFM measurements in electrolytic solutions resulted in improved atomic-scale image stability and resolution in respect to the AFM experiments performed in pure water. Hence, in this thesis we demonstrated the mechanism of ion influences on the interface structures by performing MD simulations at hydrophilic solid-liquid interfaces such as muscovite mica and calcite in high molar solutions (~5 M), also expanding the understanding of AFM measurements in high molar solutions.    The last topic included in this thesis refers to the theoretical investigation of the origin of the hydration layers. We showed that ordering at the interface is mainly the result the attractive interactions only, although there are some indications that confinement alone (in the absence of the attractive interactions) can also be a source of layering.