Interaction of Graphene and Templated Cluster Arrays with CO, H2, and O2

Interaction of graphene and templated cluster arrays with CO, H2 and O2 was studied by means of scanning tunneling microscopy (STM) and X-ray photoemission spectroscopy (XPS). The experimental data was complemented by ab initio density functional theory (DFT) calculations. As a prerequisite for studies of gas interaction, the binding mechanism of the clusters to graphene, as well as the growth and structure of Pt clusters, was investigated in detail. The formation of cluster lattices on graphene on Ir(111) has been explained by graphene rehybridization. This DFT picture was tested by comparing calculated core level spectra to XPS measurements. For pristine graphene, DFT and XPS agree on a 140 meV modulation of the C 1s core level shifts (CLS), which correlates with the height modulation of the graphene layer above the Ir surface. With Pt clusters adsorbed, measured Pt 4f CLS of the adsorbed clusters also support the calculations. The modulation of the C 1s spectrum is strengthened with clusters adsorbed, and C atoms both under and in the vicinity of the Pt clusters are experimentally distinguished as a broad shoulder of positive C 1s CLS. The calculations suggest that the sp2 to sp3 rehybridization of graphene displaces the involved C atoms closer to the Ir(111) surface, implying chemical bond formation. The signature of these bonds in the Ir 4f spectrum was identified. The growth of Pt clusters, their structure, and their interaction with the graphene layer was studied as a function of Pt coverage. STM measurements revealed that once Pt clusters are two-layered, their further growth is restricted to two dimensions. The threshold for sintering was found to be at 0.75ML Pt, so that the upper size limit for Pt clusters arranged in a lattice is 65 atoms. The cluster-graphene interaction, as well as the graphene-Ir surface interaction was investigated with spectra of the C 1s and the Ir 4f regions, respectively. It was found that the related components, namely the C 1s shoulder and the Ir interface component, agree regarding their relative intensities. Combining these results, schematic representations of the clusters and their binding geometry with the graphene layer was derived. Pt cluster arrays were tested for their stability with respect to CO gas exposure. Cluster stability and adsorption-induced processes were analyzed as a function of cluster size. Small clusters containing fewer than 10 atoms are unstable upon CO adsorption. They sinter through Smoluchowski ripening – cluster diffusion and coalescence – rather than the frequently reported Ostwald ripening mediated by metal-adsorbate complexes. Larger clusters remain immobile upon CO adsorption, but become more three-dimensional. An implication of the CO-induced cluster mobility is the sensitivity of Pt cluster array growth to the CO background pressure. In order to generalize the results, the study was extended to the adsorption of other gases (H2, O2) on Pt clusters, as well as to the adsorption of CO on other metal clusters (Ir, Au). The temperature, time and flake-size-dependent intercalation phases of oxygen underneath graphene on Ir(111) formed upon exposure to molecular oxygen were studied. Through the applied pressure of molecular oxygen, the atomic oxygen created on the bare Ir terraces is driven underneath the graphene flakes. The importance of substrate steps and of the unbinding of graphene flake edges from the substrate for the intercalation is identified. Using CO titration to selectively remove oxygen from the bare Ir terraces, the energetics of intercalation were uncovered. Cluster decoration techniques were used as an efficient tool to visualize intercalation processes in real space. To give an outlook, the study was extended to the intercalation of hydrogen. Intercalation of graphene often leads doping of graphene. Comparing XPS and angular resolved photoemission spectroscopy (ARPES) data for various systems, it was found that the Dirac point and the C 1s core level shift in the same direction. These shifts can be described in terms of a rigid band model and the C 1s core level shift may be used to estimate the level of doping. It was found that graphene/Ir(111)is p-doped by H and O intercalation, whereas it is n-doped after Eu intercalation. The graphene layer is also doped by Pt and Ir clusters on top of it. The smallest clusters n-dope the graphene by charge spill-out. The largest Pt coverage results in a slight p-doping of the graphene layer. When Pt clusters coalesce upon CO exposure, the level of doping is reduced

A versatile fabrication method for cluster superlattices

On the graphene moire on Ir(111) a variety of highly perfect cluster superlattices can be grown as shown is for Ir, Pt, W, and Re. Even materials that do not form cluster superlattices upon room temperature deposition may be grown into such by low temperature deposition or the application of cluster seeding through Ir as shown for Au, AuIr, FeIr. Criteria for the suitability of a material to form a superlattice are given and largely confirmed. It is proven that at least Pt and Ir even form epitaxial cluster superlattices. The temperature stability of the cluster superlattices is investigated and understood on the basis of positional fluctuations of the clusters around their sites of minimum potential energy. The binding sites of Ir, Pt, W and Re cluster superlattices are determined and the ability to cover samples macroscopically with a variety of superlattices is demonstrated

Microstructural investigation of hybrid CAD/CAM restorative dental materials by micro-CT and SEM

Objectives: An increasing number of CAD/CAM (computer-aided design/computer-aided manufacturing) hybrid materials have been introduced to the dental market in recent years. In addition, CAD/CAM hybrid materials for additive manufacturing (AM) are becoming more attractive in digital dentistry. Studies on material microstructures using micro-computed tomography ($\mu$-CT) combined with scanning electron microscopy (SEM) have only been available to a limited extent so far. Methods: One CAD/CAM three-dimensional- (3D-) printable hybrid material (VarseoSmile Crown plus) and two CAD/CAM millable hybrid materials (Vita Enamic; Voco Grandio), as well as one direct composite material (Ceram.x duo), were included in the present study. Cylindrical samples with a diameter of 2 mm were produced from each material and investigated by means of synchrotron radiation $\mu$-CT at a voxel size of 0.65 $\mu$m. Different samples from the same materials, obtained by cutting and polishing, were investigated by SEM. Results: The 3D-printed hybrid material showed some agglomerations and a more irregular distribution of fillers, as well as a visible layered macrostructure and a few spherical pores due to the printing process. The CAD/CAM millable hybrid materials revealed a more homogenous distribution of ceramic particles. The direct composite material showed multiple air bubbles and microstructural irregularities based on manual processing. Significance: The $\mu$-CT and SEM analysis of the materials revealed different microstructures even though they belong to the same class of materials. It could be shown that $\mu$-CT and SEM imaging are valuable tools to understand microstructure and related mechanical properties of materials.Comment: 22 pages, 3 tables, 11 figures including supplementary materia

Graphene on Ir(111): Physisorption with chemical modulation

The nonlocal van der Waals density functional (vdW-DF) approach is applied to calculate the binding of graphene to Ir(111). The precise agreement of the calculated mean height h = 3.41 Å ; of the C atoms with their mean height h = (3.38 ± 0.04) Å ; as measured by the X-ray standing wave (XSW) technique provides a benchmark for the applicability of the non-local functional. We find bonding of graphene to Ir(111) to be due to the van der Waals interaction with an antibonding average contribution from chemical interaction. Despite its globally repulsive character, in certain areas of the large graphene moiré unit cell charge accumulation between Ir substrate and graphene C atoms is observed, signaling a weak covalent bond formation

Does Exchange Splitting persist above TCT_C? A spin-resolved photoemission study of EuO

The electronic structure of the ferromagnetic semiconductor EuO is investigated by means of spin- and angle-resolved photoemission spectroscopy and density functional theory (GGA+$U$). Our spin-resolved data reveals that, while the macroscopic magnetization of the sample vanishes at the Curie temperature, the exchange splitting of the O 2$p$ band persists up to $T_{C}$. Thus, we provide evidence for short-range magnetic order being present at the Curie temperature

Ambulatory assessment for physical activity research. State of the science, best practices and future directions

Technological and digital progress benefits physical activity (PA) research. Here we compiled expert knowledge on how Ambulatory Assessment (AA) is utilized to advance PA research, i.e., we present results of the 2nd International CAPA Workshop 2019 "Physical Activity Assessment - State of the Science, Best Practices, Future Directions" where invited researchers with experience in PA assessment, evaluation, technology and application participated. First, we provide readers with the state of the AA science, then we give best practice recommendations on how to measure PA via AA and shed light on methodological frontiers, and we furthermore discuss future directions. AA encompasses a class of methods that allows the study of PA and its behavioral, biological and physiological correlates as they unfold in everyday life. AA includes monitoring of movement (e.g., via accelerometry), physiological function (e.g., via mobile electrocardiogram), contextual information (e.g., via geolocation-tracking), and ecological momentary assessment (EMA; e.g., electronic diaries) to capture self-reported information. The strengths of AA are data assessment that near real-time, which minimizes retrospective biases in real-world settings, consequentially enabling ecological valid findings. Importantly, AA enables multiple assessments across time within subjects resulting in intensive longitudinal data (ILD), which allows unraveling within-person determinants of PA in everyday life. In this paper, we show how AA methods such as triggered e-diaries and geolocation-tracking can be used to measure PA and its correlates, and furthermore how these findings may translate into real-life interventions. In sum, AA provides numerous possibilities for PA research, especially the opportunity to tackle within-subject antecedents, concomitants, and consequences of PA as they unfold in everyday life. In-depth insights on determinants of PA could help us design and deliver impactful interventions in real-world contexts, thus enabling us to solve critical health issues in the 21st century such as insufficient PA and high levels of sedentary behavior. (DIPF/Orig.

Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics

Timm W, Scherbart A, Boecker S, Kohlbacher O, Nattkemper TW. Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics. BMC Bioinformatics. 2008;9(1):443.Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides and proteins, however, is the fact that absolute quantification is severely hampered by the unclear relationship between the observed peak intensity and the peptide concentration in the sample. While there are numerous approaches to circumvent this problem experimentally (e. g. labeling techniques), reliable prediction of the peak intensities from peptide sequences could provide a peptide-specific correction factor. Thus, it would be a valuable tool towards label-free absolute quantification. Results: In this work we present machine learning techniques for peak intensity prediction for MALDI mass spectra. Features encoding the peptides' physico-chemical properties as well as string-based features were extracted. A feature subset was obtained from multiple forward feature selections on the extracted features. Based on these features, two advanced machine learning methods (support vector regression and local linear maps) are shown to yield good results for this problem (Pearson correlation of 0.68 in a ten-fold cross validation). Conclusion: The techniques presented here are a useful first step going beyond the binary prediction of proteotypic peptides towards a more quantitative prediction of peak intensities. These predictions in turn will turn out to be beneficial for mass spectrometry-based quantitative proteomics

Thermodynamic stability and control of oxygen reactivity at functional oxide interfaces: EuO on ITO

As a prototypical all-oxide heterostructure, the ferromagnetic insulator europium monoxide (EuO) issynthesized on transparent and conductive indium tin oxide (ITO) virtual substrates. Non-destructivehard X-ray photoelectron spectroscopy is employed to depth profile the chemical composition of themagnetic layer and the buried oxide–oxide interface. We find that thermally activated oxygen diffusionfrom ITO affects the EuO growth process. We present how to control the oxygen reactivity at the interfaceand discuss its origin in a thermodynamic analysis. Our complementary methodical strategy allowsfor a significant improvement of the EuO chemical quality with sizeable magnetic properties. Generally,our approach derives guidelines for the proper choice of oxide substrates and buffer layer materials forfunctional all-oxide heterostructures