Condensed Matter

Nanogranular material systems are promising for a variety of applications in research and development. Their physical properties are often determined by grain sizes, shapes, mutual distances and by the chemistry of the embedding matrix With focused electron beam induced deposition arbitrarily shaped nanocomposite materials can be designed, where metallic, nanogranular structures are embedded in a carbonaceous matrix. Using "post-growth" electron beam curing, these materials can be tuned for improved electric transport or mechanical behavior. Such an optimization necessitates a thorough understanding and characterization of the internal changes in chemistry and morphology, which is where conventional projection based imaging techniques fall short. Here, we apply scanning transmission electron tomography to get a comprehensive picture of the distribution and morphology degree of embedded Pt nanograins after initial fabrication, and we demonstrate the impact of electron beam curing, which leads to condensed regions of interconnected metal nanograins.

Intercalation is an effective method to improve and modulate properties of two-dimensional materials. Even so, spatially controlled intercalation at atomic scale, which is important to introduce and modulated properties, has not been successful due to difficulties in controlling the diffusion of intercalants. Here, we show formation of angstrom-wide conductive channels (~4.3 A) in black phosphorus by Cu intercalation. The atomic structure, resultant microstructural effects, intercalation mechanism, and local variations of electronic properties modulated in black phosphorus by Cu intercalation were investigated extensively by transmission electron microscopy including in situ observation, DFT calculation, and conductive atomic force microscopy.

Two broad bands are usually found in the Raman spectrum of many Te-based chalcogenides, which include binary compounds, like ZnTe, CdTe, HgTe, GaTe, GeTe, SnTe, PbTe, GeTe2, As2Te3, Sb2Te3, Bi2Te3, NiTe2, IrTe2, TiTe2, as well as ternary compounds, like GaGeTe, SnSb2Te4, SnBi2Te4, and GeSb2Te5. Many different explanations have been proposed in the literature for the origin of these two anomalous broad bands in tellurides, usually located between 119 and 145 cm-1. They have been attributed to the own sample, to oxidation, to the folding of Brillouin-edge modes onto the zone center, to the existence of a double resonance, like that of graphene, or to the formation of Te precipitates. In this paper, we provide arguments to demonstrate that such bands correspond to clusters or precipitates of trigonal Te in form of nanosize or microsize grains or layers that are segregated either inside or at the surface of the samples. Several mechanisms for Te segregation are discussed and sample heating caused by excessive laser power during Raman scattering measurements is emphasized. Finally, we show that anomalous Raman modes related to Se precipitates also occur in selenides, thus providing a general vision for a better characterization of selenides and tellurides by means of Raman scattering measurements and for a better understanding of chalcogenides in general.

Ferromagnetism was observed in a Pt(100) ultrathin film deposited on a SrTiO3(100) substrate. The ferromagnetism, which appears in films with thicknesses of 2.2-4.4 nm, periodically changes with a period of approximately 1 nm (5-6 ML) depending on the film thickness. This is consistent with the period derived from the quantum-well states formed in the thin film. X-ray magnetic circular dichroism measurements were conducted to understand the intrinsic nature of the ferromagnetism in the Pt(100) ultrathin films, and contrary to our expectations, the orbital magnetic moment of pure Pt is much smaller than that of the Pt/ferromagnetic multilayer system. These results suggest that the origin of the large magnetic anisotropy in Pt components cannot be explained only by the amount of spin-orbit coupling in Pt.

High-spatial-resolution secondary ion mass spectrometry offers a method for mapping lithium at nanoscale lateral resolution. Practical implementation of this technique offers significant potential for revealing the distribution of Li in many materials with exceptional lateral resolution and elemental sensitivity. Here, two state-of-the-art methods are demonstrated on an aluminium-lithium alloy to visualise nanoscale Li-rich phases by mapping the 7Li+ secondary ion. NanoSIMS 50L analysis with a radio frequency O- plasma ion source enabled visualisation of needle-shaped T1 (Al2CuLi) phases as small as 75 nm in width. A compact time-of-flight secondary ion mass spectrometry detector added to a focused ion beam scanning electron microscope facilitated mapping of the T1 phases down to 45 nm in width using a Ga+ ion beam. Correlation with high resolution electron microscopy confirms the identification of T1 precipitates, their sizes and distribution observed during SIMS mapping.

Predicting materials properties from composition or structure is of great interest to the materials science community. Deep learning has recently garnered considerable interest in materials predictive tasks with low model errors when dealing with large materials data. However, deep learning models suffer in the small data regime that is common in materials science. Here we leverage the transfer learning concept and the graph network deep learning framework and develop the AtomSets machine learning framework for consistent high model accuracy at both small and large materials data. The AtomSets models can work with both compositional and structural materials data. By combining with transfer learned features from graph networks, they can achieve state-of-the-art accuracy from using small compositional data (<400) to large structural data (>130,000). The AtomSets models show much lower errors than the state-of-the-art graph network models at small data limits and the classical machine learning models at large data limits. They also transfer better in the simulated materials discovery process where the targeted materials have property values out of the training data limits. The models require minimal domain knowledge inputs and are free from feature engineering. The presented AtomSets model framework opens new routes for machine learning-assisted materials design and discovery.

The incorporation of impurities during the chemical synthesis of nanomaterials is usually uncontrolled and rarely reported because of the formidable challenge that constitutes measuring trace amounts of often light elements with sub nanometre spatial resolution. Yet these foreign elements influence functional properties, by e.g. doping. Here we demonstrate how the synthesis and partial reduction reaction on hollow TiO2 nanowires leads to the introduction of parts-per-millions of boron, sodium, and nitrogen from the reduction reaction with sodium borohydride at the surface of the TiO2 nanowire. This doping explains the presence of oxygen vacancies at the surface that enhance the activity. Our results obtained on model metal-oxide nanomaterials shed light on the general process leading to the uncontrolled incorporation of trace impurities that can have a dramatic effect on their potential use in energy-harvesting applications.

Transmission electron microscopy and spectroscopy currently enable the acquisition of spatially resolved spectral information from a specimen by focusing electron beams down to a sub-Angstrom spot and then analyzing the energy of the inelastically scattered electrons with few-meV energy resolution. This technique has recently been used to experimentally resolve vibrational modes in 2D materials emerging at mid-infrared frequencies. Here, based on first-principles theory, we demonstrate the possibility of identifying single isotope atom impurities in a nanostructure through the trace that they leave in the spectral and spatial characteristics of the vibrational modes. Specifically, we examine a hexagonal boron nitride molecule as an example of application, in which the presence of a single isotope impurity is revealed through dramatic changes in the electron spectra, as well as in the space-, energy-, and momentum-resolved inelastic electron signal. We compare these results with conventional far-field spectroscopy, showing that electron beams offer superior spatial resolution combined with the ability to probe the complete set of vibrational modes, including those that are optically dark. Our study is relevant for the atomic-scale characterization of vibrational modes in novel materials, including a detailed mapping of isotope distributions.

Cerium oxide (ceria, CeO2) is one of the most promising mixed ionic and electronic conducting materials. Previous atomistic analysis has covered widely the effects of substitution on oxygen vacancy migration. However, an in-depth analysis of the role of cation substitution beyond trivalent cations has rarely been explored. Here, we investigate soluble monovalent, divalent, trivalent and tetravalent cation substituents. By combining classical simulations and quantum mechanical calculations, we provide an insight into defect association energies between substituent cations and oxygen vacancies as well as their effects on the diffusion mechanisms. Our simulations indicate that oxygen ionic diffusivity of subvalent cation-substituted systems follows the order Gd>Ca>Na. With the same charge, a larger size mismatch with Ce cation yields a lower oxygen ionic diffusivity, i.e., Na>K, Ca>Ni, Gd>Al. Based on these trends, we identify species that could tune the oxygen ionic diffusivity: we estimate that the optimum oxygen vacancy concentration for achieving fast oxygen ionic transport is 2.5% for GdxCe1-xO2-x/2, CaxCe1-xO2-x and NaxCe1-xO2-3x/2 at 800 K. Remarkably, such a concentration is not constant and shifts gradually to higher values as the temperature is increased. We find that co-substitutions can enhance the impact of the single substitutions beyond that expected by their simple addition. Furthermore, we identify preferential oxygen ion migration pathways, which illustrate the electro-steric effects of substituent cations in determining the energy barrier of oxygen ion migration. Such fundamental insights into the factors that govern the oxygen diffusion coefficient and migration energy would enable design criteria to be defined for tuning the ionic properties of the material, e.g., by co-doping.

In this paper, the Fe-20Ni-25Cr alloy that is used for fuel cladding or pressure vessels with various grain boundaries (GBs) was investigated by employing molecular dynamics simulations. The bi-crystals comprised of {\Sigma}3(111), {\Sigma}3(112), {\Sigma}9(114), {\Sigma}11(113), {\Sigma}19(116), and {\Sigma}17(223) types GBs were considered to systematically examine the interplay between irradiation defects, irradiation microstructure evolution under stress, and irradiation mechanical properties with irradiation intensity, coincidence site lattice parameter, tilt angle, and GB thickness. It is found that irradiated vacancies and interstitials are annihilated by competitive GB absorption and recombination. Bias absorption of interstitials is observed for most bi-crystals except {\Sigma}3(111) and {\Sigma}11(113) at 15 keV incident energy, and results in abundant residual vacancies clusters in grain interior. In addition, different GBs exhibit quite diverse irradiation defect sink ability, and the number of residual vacancies is inversely related to the GB thickness, where {\Sigma}3(111) and {\Sigma}11(113) GBs with narrow GB thickness are weak in defect absorption and the others are strong. Furthermore, uniaxial tensile simulations perpendicular to the GB reveal that all of the mechanical performance of bi-crystals deteriorates after irradiation, which originates from dislocation propagation facilitated by irradiation defect clusters. In particular, regardless of whether the irradiation is applied, the maximum tensile strain, toughness, and Youngs modulus are monotonically correlated with GB tilt angle, while the ultimate tensile strength is stable for larger GB CSL parameter. Finally, on the basis of the evolution of the irradiation defects, microstructures, and mechanical performances, we proposed guidelines of rational design of irradiation-resistant Fe-Ni-Cr alloy.