Abstract: During the last decade, 3D-Electron Diffraction (3D-ED) has emerged as a powerful technique for studying the structure of sub-micron particles. It is used in a variety of applications, from unit cell and space group determination to the complete solution of the structure similar to X-ray diffraction techniques. So far, this technique has been only implemented in Transmission Electron Microscopes (TEMs). Performing such an experiment in a Scanning Electron Microscope (SEM) can be challenging, mainly due to the lower acceleration voltage. This lower beam energy raises concerns about severe multiple scattering and limited transmissivity of the sample for the weakly accelerated electrons.
In this work, we show the possibilities of operating similar studies in a modified SEM. For this aim, we equipped our SEM with a custom stage and holder, a direct electron detector and a custom high-angle annular dark-field detector (HAADF). A range of samples was studied in the form of lamellas and sub-micron particles, and the quality of the diffraction data was evaluated for different purposes, such as unit cell determination and space group determination. Moreover, the ability to integrate the diffraction data for structure solution and refinement has been assessed and compared to similar data acquired in a TEM.
Finally, we also demonstrate the potential for combining diffraction tomography and 4-dimensional scanning transmission electron microscopy (4D-STEM) in our setup. This method opens an avenue to obtain multiple 3DED datasets out of 5D-STEM data. These 3DED datasets can be created using object tracking methods from several regions of a multi-domain particle or from multiple single crystals within the scanning region. This provides an attractive route to high-throughput and statistically relevant characterization of polycrystalline materials or powders of nanoparticles.

Abstract: The synthesis of a new class of fluorescent carbon nanomaterials, carbon-dot-decorated nanodiamonds (CDD-ND), is reported. These CDD-NDs are produced by specific acid treatment of detonation soot, forming tiny rounded sp2 carbon species (carbon dots), 12 atomic layers thick and 12 nm in size, covalently attached to the surface of the detonation diamond nanoparticles. A combination of nanodiamonds bonded with a graphitic phase as a starting material and the application of graphite intercalated acids for oxidation of the graphitic carbon is necessary for the successful production of CDD-ND. The CDD-ND photoluminescence (PL) is stable, 20 times more intense than the intrinsic PL of well-purified NDs and can be tailored by changing the oxidation process parameters. Carbon-dot-decorated DNDs are shown to be excellent probes for bioimaging applications and inexpensive additives for PL nanocomposites.

Abstract: The self-assembly of nanoparticles into clusters and the effect of the different parameters of the competing interaction potential on it are investigated. For a small number of particles, the structural organization of the clusters is almost unaffected by the attractive part of the potential, and for an intermediate number of particles the configuration strongly depends on the strength of it. The cluster size is controlled by the range of the interaction potential, and the structural arrangement is guided by the strength of the potential: i.e., the self-assembled cluster transforms from a faceted configuration at low strength to a spherical shell-like structure at high strength. Nonmonotonic behavior of the cluster size is found by increasing the interaction range. An approximate analytical expression is obtained that predicts the smallest cluster for a specific set of potential parameters. A Mendeleev-like table is constructed for different values of the strength and range of the attractive part of the potential in order to understand the structural ordering of the ground-state configuration of the self-assembled clusters.

Abstract: The ground-state energy of three-particle systems consisting of electrons and holes as found in semiconducting quantum wells is studied. The degree of confinement is determined by the quantum-well width and we can vary the dimensionality of the system from two to three dimensions. The energy levels of the system can further be altered by the application of an external magnetic field which is directed perpendicular to the well.

Abstract: Superconductivity is a macroscopic coherent state exhibiting various quantum phenomena such as magnetic flux quantization. When a superconducting ring is placed in a magnetic field, a current flows to expel the field from the ring and to ensure that the enclosed flux is an integer multiple of h/(2|e|). Although the quantization of magnetic flux in ring structures is extensively studied in literature, the applied magnetic field is typically assumed to be homogeneous, implicitly implying an interplay between field expulsion and flux quantization. Here, we propose to decouple these two effects by employing an Aharonov-Bohm-like structure where the superconducting ring is threaded by a magnetic core (to which the applied field is confined). Although the magnetic field vanishes inside the ring, the formation of vortices takes place, corresponding to a change in the flux state of the ring. The time evolution of the density of superconducting electrons is studied using the time-dependent Ginzburg-Landau equations.

Abstract: In van der Waals heterostructures consisting of graphene and a substrate, lattice mismatch often leads to a moire pattern with a huge supercell, preventing its treatment within first- principles calculations. Previous theoretical works considered mostly simple stacking models such as AB, AA with straining the lattice of graphene to match that of the substrate. Here, we propose a moire superlattice build from graphene and porous graphene or graphyne like monolayers, having a lower interlayer binding energy, needing little strain in order to match the lattices. In contrast to the results from the simple stacking models, the present ab initio calculations for the moire superlattices show different properties in lattice structure, energy, and band structures. For example, the Dirac cone at the K point is preserved and a linear energy dispersion near the Fermi level is obtained.

Abstract: The electronic and vibrational properties of germanane and fluorinated germanene are studied within density functional theory (DFT) and density functional perturbation theory frameworks. Different structural configurations of germanane and fluorinated germanene are investigated. The energy difference between the different configurations are consistently smaller than the energy of thermal fluctuations for all the analyzed DFT functionals LDA, GGA, and hybrid functionals, which implies that, in principle, it is possible to find these different configurations in different regions of the sample as minority phases or local defects. We calculate the Raman and infrared spectra for these configurations by using ab initio calculations and compare it with available experimental spectra for germanane. Our results show the presence of minority phases compatible with the configurations analyzed in this work. As these low energy configurations are metastable the present work shows that the synthesis of these energy competing phases is feasible by selectively changing the synthesis conditions, which is an opportunity to expand in this way the availability of new two-dimensional compounds.

Abstract: The metallic interface between two oxide insulators, such as LaAlO3/SrTiO3 (LAO/STO), provides new opportunities for electronics and spintronics. However, due to the presence of multiple orbital populations, tailoring the interfacial properties such as the ground state and metal-insulator transitions remains challenging. Here, an unforeseen tunability of the phase diagram of LAO/STO is reported by alloying LAO with a ferromagnetic LaMnO3 insulator without forming lattice disorder and at the same time without changing the polarity of the system. By increasing the Mn-doping level, x, of LaAl1-xMnxO3/STO (0 <= x <= 1), the interface undergoes a Lifshitz transition at x = 0.225 across a critical carrier density of n(c) = 2.8 x 10(13) cm(-2), where a peak T-SC approximate to 255 mK of superconducting transition temperature is observed. Moreover, the LaAl1-xMnxO3 turns ferromagnetic at x >= 0.25. Remarkably, at x = 0.3, where the metallic interface is populated by only d(xy) electrons and just before it becomes insulating, a same device with both signatures of superconductivity and clear anomalous Hall effect (7.6 x 10(12) cm(-2) < n(s) <= 1.1 x 10(13) cm(-2)) is achieved reproducibly. This provides a unique and effective way to tailor oxide interfaces for designing on-demand electronic and spintronic devices.

Abstract: 2D ternary systems provide another degree of freedom of tuning physical properties through stoichiometry variation. However, the controllable growth of 2D ternary materials remains a huge challenge that hinders their practical applications. Here, for the first time, by using a gallium/indium liquid alloy as the precursor, the synthesis of high-quality 2D ternary Ga2In4S9 flakes of only a few atomic layers thick (approximate to 2.4 nm for the thinnest samples) through chemical vapor deposition is realized. Their UV-light-sensing applications are explored systematically. Photodetectors based on the Ga2In4S9 flakes display outstanding UV detection ability (R-lambda = 111.9 A W-1, external quantum efficiency = 3.85 x 10(4)%, and D* = 2.25 x 10(11) Jones@360 nm) with a fast response speed (tau(ring) approximate to 40 ms and tau(decay) approximate to 50 ms). In addition, Ga2In4S9-based phototransistors exhibit a responsivity of approximate to 10(4) A W-1@360 nm above the critical back-gate bias of approximate to 0 V. The use of the liquid alloy for synthesizing ultrathin 2D Ga2In4S9 nanostructures may offer great opportunities for designing novel 2D optoelectronic materials to achieve optimal device performance.

Abstract: Solar energy plays an important role in solving serious environmental
problems and meeting the high energy demand. However, the lack of suitable
materials hinders further progress of this technology. Here, we present the largest
inorganic solar cell material search till date using density functional theory (DFT) and
machine-learning approaches. We calculated the spectroscopic limited maximum
efficiency (SLME) using the Tran−Blaha-modified Becke−Johnson potential for 5097
nonmetallic materials and identified 1997 candidates with an SLME higher than 10%,
including 934 candidates with a suitable convex-hull stability and an effective carrier
mass. Screening for two-dimensional-layered cases, we found 58 potential materials
and performed G0W0 calculations on a subset to estimate the prediction uncertainty. As the above DFT methods are still computationally expensive, we developed a high accuracy machine-learning model to prescreen efficient materials and applied it to over a million materials. Our results provide a general framework and universal strategy for the design of high-efficiency solar
cell materials. The data and tools are publicly distributed at: https://www.ctcms.nist.gov/~knc6/JVASP.html, https://www.
ctcms.nist.gov/jarvisml/, https://jarvis.nist.gov/, and https://github.com/usnistgov/jarvis.

Abstract: Orpiment and realgar, both arsenic sulfide pigments respectively used for their vivid yellow and red-orange hues, are two of many artists' pigments that appear not to be stable upon light exposure, quickly degrading to arsenic trioxide and arsenate. This often results in whitening or transparency in the painted surfaces. While conventional techniques such as microscopic Raman (mu-RS) and microscopic Fourier transform infrared (mu-FTIR) spectroscopies can allow a quick and relatively easy identification of the orpiment, realgar, artificial arsenic sulfide glass and, to some extent, arsenic oxide, the identification and visualization of distributions of the degradation products – and especially arsenate compounds – in the paint micro-samples is generally more challenging. This challenge is due to the rather unfavorable limit of detection and low spectral resolution of such conventional spectroscopic techniques. This restricts the conclusions that can be drawn regarding the conservation state of valuable works of art. In this paper, we present how synchrotron radiation (SR) based techniques can overcome this challenge while working on painting cross-sections taken from a 17th-century painting by the Flemish artist Daniel Seghers (oil on canvas, Statens Museum for Kunst, Denmark) and an 18th-century French Chinoiserie (private collection, France). SR micro-X-ray fluorescence (m-XRF) mapping analysis performed on a visually degraded orpiment-containing paint stratigraphy reveals that arsenic is distributed throughout the entire cross-section, while X-ray absorption near edge structure (mu-XANES) demonstrated that the arsenic is present in both arsenite (As-III) and arsenate (As-V) forms. The latter compound(s), despite being barely identifiable by means of FTIR, were not only located at the surface of large and partially altered grains of arsenic sulfide but also spread throughout the entire paint stratigraphy. Their presence and distribution are attributed either to the complete degradation of smaller arsenic sulfide grains or to migration of the arsenates within the paint layer away from their original location of formation. The combination of mu-XRF and mu-XANES was very useful for the characterization of the advanced degradation state of the arsenic-containing pigments in paint systems; this type of information could not be obtained by means of conventional spectroscopic methods of microanalysis.

Abstract: Ginkgo biloba L. is a precious relic tree species with important economic value. Seeds, as a vital reproductive organ of plants, can be used to distinguish cultivars of the species. We chose 400 seeds from two cultivars of ginkgo (Fozhi and Maling; 200 seeds for each cultivar) as the study material and used the Gielis equation to fit the projected shape of these seeds. The coefficients of variation (CV) in root mean squared errors (RMSE) obtained from the fitted data were used to compare the level of inter-cultivar variations in seed shape. We also used the covariance analysis to compare the allometric relationships between seed weights and projected areas of these two cultivars. The Gielis equation fitted well the seed shapes of two ginkgo cultivars. The lower CV in RMSE of cultivar Fozhi than Maling indicated a less symmetrical seed shape in the latter than the former. The bootstrap percentile method showed that the seed shape differences between the two cultivars were significant. However, there was no significant difference in the exponents between the seed weights and the projected areas of these two cultivars. Overall, the significant differences in shapes between the seeds of two ginkgo cultivars were well explained by the Gielis equation; this model can be further extended to compare morphological differences in other ginkgo cultivars, and even for plant seeds or animal eggs that have similar oval shapes.

Abstract: Following an extensive investigation of various monolayer transition metal dichalcogenides (MX2), research interest has expanded to include multilayer systems. In bilayer MX2, the stacking order strongly impacts the local band structure as it dictates the local confinement and symmetry. Determination of stacking order in multilayer MX(2)domains usually relies on prior knowledge of in-plane orientations of constituent layers. This is only feasible in case of growth resulting in well-defined triangular domains and not useful in-case of closed layers with hexagonal or irregularly shaped islands. Stacking order can be discerned in the reciprocal space by measuring changes in diffraction peak intensities. Advances in detector technology allow fast acquisition of high-quality four-dimensional datasets which can later be processed to extract useful information such as thickness, orientation, twist and strain. Here, we use 4D scanning transmission electron microscopy combined with multislice diffraction simulations to unravel stacking order in epitaxially grown bilayer MoS2. Machine learning based data segmentation is employed to obtain useful statistics on grain orientation of monolayer and stacking in bilayer MoS2.