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Abstract: We present a comprehensive, quantitative multimethod characterization of the geometric and electronic interfacial structure of zinc-porphine (Zn-P) on coinage metal supports, namely, Ag(111) and Cu(111). Complementary techniques including X-ray standing waves, X-ray photoelectron spectroscopy, scanning tunneling microscopy, bond-resolved atomic force microscopy, and density functional theory calculations reveal the molecular conformations, signal a temperature-dependence of element-specific adsorption heights, rule out a decisive role of the d10 nature of the Zn center for the adsorption configuration, and uncover a considerably increased Zn-P adsorption height on Ag(111) compared to Cu(111). Furthermore, a pronounced out-of-plane displacement of the Zn center upon water ligation is demonstrated, a manifestation of the surface trans-effect. This study thus sheds light on effects of temperature, chemical nature of the metal center, its ligation, and the coinage metal support on interfacial structure and molecular deformation of an archetypical surface-anchored metal-tetrapyrrole.

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Abstract: Using the normal incidence x-ray standing-wave technique as well as low-energy electron microscopy we have investigated the structure of quasifreestanding monolayer graphene (QFMLG) obtained by intercalation of antimony under the ( 6 √ 3 × 6 √ 3 ) R 30 ∘ reconstructed graphitized 6 H -SiC(0001) surface, also known as zeroth-layer graphene. We found that Sb intercalation decouples the QFMLG well from the substrate. The distance from the QFMLG to the Sb layer almost equals the expected van der Waals bonding distance of C and Sb. The Sb intercalation layer itself is monoatomic, flat, and located much closer to the substrate, at almost the distance of a covalent Sb-Si bond length. All data is consistent with Sb located on top of the uppermost Si atoms of the SiC bulk.

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Abstract: Although scanning probe microscopy (SPM) techniques have allowed researchers to interact with the nanoscale for decades now, little improvement has been made to the incredibly manual, time consuming process of setting up, running, and analysing the results of these experiments, often arising due to the constantly varying shape of the probe apex. Unlike traditional computing methods, machine learning methods (with neural networks in particular) are considerably more capable of automating subjective tasks such as these, and we are only just beginning to explore the potential applications of this technology in SPM. In this thesis we explore a number of areas where machine learning could potentially massively change the way we go about SPM experimentation. We begin by discussing the history, theory, and experimental concepts of scanning tunnelling microscopy (STM), atomic force microscopy (AFM), and normal-incidence-x-ray standing wave (NIXSW). We then explore the makeup of a neural network and demonstrate how they can be applied to a variety of use-cases in SPM, including classification and policy prediction. Moving to the experimental chapters, we first discuss how we can successfully distinguish between STM tip states of the H:Si(100), Au(111) and Cu(111) surfaces. We also show that by adapting this network to work in real time, we improve performance while requiring on the order of 100x less data. We next discuss our attempts to combine these networks with expert examples to intelligently maintain tip apex sharpness during experimentation, envisioning an end-to-end automatic experiment. Because one of the main difficulties in applying machine learning is the frequent need to manually label data, we then show how we can use Monte Carlo simulations of self-organised AFM nanostructures to automatically label training data for a network, and then combine it with classical statistics and preprocessing to find specific structures in a mixed, messy dataset of real, experimental AFM images. As part of this, we also build a network to denoise experimental images. Finally, we present NIXSW results from an investigation into the temperature dependence of H20@C60, discussing the potential to use unsupervised clustering techniques to distinguish between noisy human-indistinguishable spectra to overcome limitations in data collection.

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Abstract: In the field of van der Waals heterostructures, the twist angle between stacked two-dimensional layers has been identified to be of utmost importance for the properties of the heterostructures. In this context, we previously reported the growth of a single layer of unconventionally oriented epitaxial graphene that forms in a surfactant atmosphere [F. C. Bocquet et al., Phys. Rev. Lett. 125, 106102 (2020)]. The resulting G- R 0 ∘ layer is aligned with the SiC lattice, and hence represents an important milestone towards high-quality twisted bilayer graphene, a frequently investigated model system in this field. Here, we focus on the surface structures obtained in the same surfactant atmosphere, but at lower preparation temperatures at which a boron nitride template layer forms on SiC(0001). In a comprehensive study based on complementary experimental and theoretical techniques, we find—in contrast to the literature—that this template layer is a hexagonal B x N y layer, but not high-quality hBN. It is aligned with the SiC lattice and gradually replaced by low-quality graphene in the 0 ∘ orientation of the B x N y template layer upon annealing.

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Abstract: X-ray standing-wave (XSW) excited photoelectron emission was used to measure the site-specific valence band (VB) for ½ monolayer (ML) Pt grown on a SrTiO 3 (001) surface. The XSW induced modulations in the core level (CL), and VB photoemission from the surface and substrate atoms were monitored for three h k l substrate Bragg reflections. The XSW CL analysis shows the Pt to have a face-centered-cubic-like cube-on-cube epitaxy with the substrate. The XSW VB information compares well to a density functional theory calculated projected density of states from the surface and substrate atoms. Overall, this Letter represents a novel method for determining the contribution to the density of states by valence electrons from specific atomic surface sites.