A set of embedded atom model (EAM) interatomic potentials was developed to represent highly idealized face-centered cubic (FCC) mixtures of Fe–Ni–Cr–Co–Al at near-equiatomic compositions. Potential functions for the transition metals and their crossed interactions are taken from our previous work for Fe–Ni–Cr–Co–Cu [D. Farkas and A. Caro: J. Mater. Res. 33 (19), 3218–3225, 2018], while cross-pair interactions involving Al were developed using a mix of the component pair functions fitted to known intermetallic properties. The resulting heats of mixing of all binary equiatomic random FCC mixtures not containing Al is low, but significant short-range ordering appears in those containing Al, driven by a large atomic size difference. The potentials are utilized to predict the relative stability of FCC quinary mixtures, as well as ordered L12 and B2 phases as a function of Al content. These predictions are in qualitative agreement with experiments. This interatomic potential set is developed to resemble but not model precisely the properties of this complex system, aiming at providing a tool to explore the consequences of the addition of a large size-misfit component into a high entropy mixture that develops multiphase microstructures.

Atomically resolved imaging of materials enabled by the advent of aberration-corrected scanning transmission electron microscopy (STEM) has become a mainstay of modern materials science. However, much of the wealth of quantitative information contained in the fine details of atomic structure or spectra remains largely unexplored. In this article, we discuss new opportunities enabled by physics-informed big data and machine learning technologies to extract physical information from static and dynamic STEM images, ranging from statistical thermodynamics of alloys to kinetics of solid-state reactions at a single defect level. The synergy of deep-learning image analytics and real-time feedback further allows harnessing beam-induced atomic and bond dynamics to enable direct atom-by-atom fabrication. Examples of direct atomic motion over mesoscopic distances, engineered doping at selected lattice sites, and assembly of multiatomic structures are reviewed. These advances position the scanning transmission electron microscope to transition from a mere imaging tool toward a complete nanoscale laboratory for exploring electronic, phonon, and quantum phenomena in atomically engineered structures.

A set of embedded atom method model interatomic potentials is presented to represent a high-entropy alloy with five components. The set is developed to resemble but not model precisely face-centered cubic (fcc) near-equiatomic mixtures of Fe–Ni–Cr–Co–Cu. The individual components have atomic sizes deviating up to 3%. With the heats of mixing of all binary equiatomic random fcc mixtures being less than 0.7 kJ/mol and the corresponding value for the quinary being −0.0002 kJ/mol, the potentials predict the random equiatomic fcc quinary mixture to be stable with respect to phase separation or ordering and with respect to bcc and hcp random mixtures. The details of lattice distortion, strain, and stress states in this phase are reported. The standard deviation in the individual nearest neighbor bond lengths was found to be in the range of 2%. Most importantly, individual atoms in the alloy were found to be under atomic strains up to 0.5%, corresponding to individual atomic stresses up to several GPa.

The atomic structure, electronic structure, and physical properties of (TiZrNbCu)1−xNix (x ≤ 0.5) metallic glasses (MGs) were studied in both the high-entropy (0 < x < 0.35) and the higher Ni concentration range (x ≥ 0.35). Atomic structure studies performed with X-ray diffraction and synchrotron powder diffraction provided average atomic volumes, structure factors, radial distribution functions, coordination numbers, and packing densities. Electronic structure studies performed using photoemission spectroscopy and low-temperature specific heat provided information about the electronic density of states within the valence band and at the Fermi level and also about interatomic bonding and atomic vibrations [from the Debye temperature and the boson peak (BP)]. Variations of both atomic structure and electronic structure with x showed a clear change for x ≥ 0.35, which corresponds to a valence electron number ≥7.4. All physical properties, namely, thermal stability parameters, Debye temperatures, BPs, magnetic, elastic, and electronic transport properties, change their concentration-dependence for x ≥ 0.35. The results are compared with those for binary and ternary MGs of the same elements.

This work shows a part of a theoretical study of Polymer-Clay Nanocomposites (PCN) formed by an acetylated amylose segment and fatty acids present in the Pequi oil, a fruit from the Brazilian Cerrado, in aqueous medium, including or not, organophilized montmorillonite (MMT-O). The simulated systems aim to provide qualitative information about the molecular movement among diverse chemical species; their structural and behavioral correlations and essential intermolecular forces. The calculations were carried out by Molecular Mechanics and Dynamics methods with the Polymer Consistent Force Field-interface. Simulation results had shown behavioral differences between systems. Without MMT-O, the acetyl amylose residues quickly became coiled, most of the fatty acids cover its surface, and water molecules are stabilized over the polysaccharide portions free of fatty acids. With MMT-O the fatty acids show a potential plasticizing effect due to the greater compatibility between the components of the studied system, since the organic assemblage is strongly attracted by the electrostatic force of the clay. Besides, water molecules flow to the clay layer, while the non polar portion of fatty acids increase their flexibility, in spite to stay attached to acetyl amylose, progressively coiled, through hydrogen bonds. This behavior is interpreted as an improvement in the miscibility of the oil. The new knowledge acquired about these molecular systems encourages us to increase the models complexity, and undertake further studies in the design of PCNs with biopolymers.

The structural descriptions of even the most basic amorphous materials are under considerable debate. In this work, an intuitive computational technique has been developed to construct 3D statistical density maps to directly visualize and identify local atomic structures from simple monatomic amorphous germanium (a-Ge) to complex multi-atom systems such as copper zirconium metallic glass. We show motifs in copper zirconium that are unresolvable through traditional tools such as Voronoi indexing. This self-sorted local atomic motif (SLAM) method builds upon the Kabsch algorithm incorporating techniques in computer vision to produce least-squares optimized 3D density maps. Simultaneously, the SLAM method incorporates self-contained categorization to define local motifs based upon atomic structures. We present the methodology of the SLAM method and also present resulting motifs comparing models a-Ge and demonstrate its broad capability on metallic glass.

We provide an overview of the field of rigidity theory applied at the atomic scale. This theoretical approach, initially designed for macroscopic structures such as bridges or buildings, has gained renewed interest in the past few years thanks to new methodological developments and to attractive applications in a variety of materials, such as scratch-resistant glassy sheets for mobile phones, phase-change memory, tough cement, dielectrics, and photonic devices. In parallel, basic phenomena associated with the onset of rigidity have been discovered, which have challenged our current understanding of the structural modification induced by changes in composition. This has led to the identification of “smart” glasses with multiple functionalities and superior mechanical performances. Topological prediction and engineering of physical properties are also enabling intelligent design of new disordered materials.

Kohn–Sham density functional theory is the most widely used method of electronic-structure calculation in materials physics and chemistry because it reduces the many-electron ground-state problem to a computationally tractable self-consistent one-electron problem. Exact in principle for the ground-state energy and electron density, it requires in practice an approximation to the density functional for the exchange-correlation energy. Common approximations fall on the rungs of a ladder, with higher rungs being more complicated to construct and use but potentially more accurate. Each rung of the ladder introduces an additional ingredient to the energy density. From bottom to top, the rungs are (1) the local spin density approximation, (2) the generalized gradient approximation (GGA), (3) the meta-GGA, (4) the hybrid functional, and (5) the generalized random phase approximation. The semi-local rungs (1–3) are important, because they are computationally efficient, they can be constructed non-empirically, they can serve as input to fourth-rung functionals, and the meta-GGA by itself can be accurate for equilibrium properties. Recent and continuing improvements to the meta-GGA are emphasized here.

Using a new methodology of elaboration of PDF data (G(r) function), which is based on the analysis of individual inter-atomic distances (ri), a function describing differences between average inter-atomic distances in CdSe nanograins derived experimentally and those in the parent bulk crystal was determined. Based on that methodology a unique atomic architecture of CdSe QDs is proposed. The results show that a good knowledge about the grain surface of nanocrystals alone may be insufficient for understanding the nanomaterials properties, and that the real atomic structure of the interior of nanograins is of importance as well.

This article discusses some of the many-body potentials used for simulations of processes and energies in materials at the atomic scale, emphasizing their motivation and underlying physical concepts, particularly where these are not entirely empirical. The perspective is somewhat historical and describes the importance of developments of the theory of electrons in solids for the derivation of many-body (or many-atom) potential models. The models include density-dependent pairwise potentials, effective medium and embedded-atom models, and polarizable ion models. As a recent radical departure from approaches derived from the physics of electrons, the development of models based on information theory is also described.

In this work we present preliminary results from multi-million fully atomistic classical molecular dynamics simulations carried out to test different existing mechanisms that have been proposed in the literature to explain the drawing of yarns from carbon nanotube forests. Despite the fact that it has been almost ten years since yarns were first drawn, there are still controversies on the mechanisms and necessary conditions that can produce yarns and sheets drawn from carbon nanotube forests. Moreover, few works have tried to understand at atomistic level the details of yarn drawing mechanisms, and no fully atomistic simulations have been carried out so far on this particular subject. Our preliminary results suggest that only direct van der Waals interactions among large bundles seem not to be enough to explain the yarn drawing process. Bundle interconnectors (such as small bundles connecting large bundles) were observed to play a critical role in our simulations. Depending on the topology of these interconnectors it was possible to observe from the simulations fibers/yarn formation from proposed structural models. These models were built based on structural information inferred from scanning electron microscopy data.

In the scanning transmission electron microscope, multiple signals can be simultaneously collected, including the transmitted and scattered electron signals (bright field and annular dark field or Z-contrast images), along with spectroscopic signals such as inelastically scattered electrons and emitted photons. In the last few years, the successful development of aberration correctors for the electron microscope has transformed the field of electron microscopy, opening up new possibilities for correlating structure to functionality. Aberration correction not only allows for enhanced structural resolution with incident probes into the sub-Ångstrom range, but can also provide greater probe currents to facilitate mapping of intrinsically weak spectroscopic signals at the nanoscale or even the atomic level. In this issue of MRS Bulletin, we illustrate the power of the new generation of electron microscopes with a combination of imaging and spectroscopy. We show the mapping of elemental distributions at atomic resolution and also the mapping of electronic and optical properties at unprecedented spatial resolution, with applications ranging from graphene to plasmonic nanostructures, and oxide interfaces to biology.

The dependences of unit cell parameter, x-ray diffraction line width B, and microhardness H on the composition of PbTe-Bi2Te3 (0–10 mol% Bi2Te3) semiconductor alloys, subjected to different types of heat treatment, were obtained. In the concentration ranges ∼0.5–1.5 and 3–4 mol% Bi2Te3 within the homogeneity region of PbTe (0–6 mol% Bi2Te3), anomalous constancy or decrease in B and H was observed. A long room temperature aging leads to a more distinct manifestation of these effects. It is suggested that the observed peculiarities in the concentration dependences of the properties are connected with percolation effects and self-organization processes in the solid solution.

In various binary and ternary transition-metal-based systems, two or even three different polytypes of Laves phases coexist as equilibrium phases. A comparison of different phase diagrams reveals that the coexistence is characterized by some common features. In binary systems with cubic and hexagonal Laves phases existing at the same temperature but different compositions, the cubic C15 polytype always crystallizes at and around the stoichiometric composition whereas the hexagonal C14 and C36 polytypes are observed on the A-rich (C14) and B-rich (C36) side of the stoichiometry, respectively. On replacing the B atoms of an AB2 Laves phase by ternary additions, the highest solubility is always found in the C14 Laves phase. Ternary Laves phases A(B,C)2 in systems where none of the binary boundary systems contains a Laves phase are always of the C14 type. It is discussed how these observations are related to crystallographic differences between the three polytypic structures C14, C15, and C36.

Combined nano- and mesoscale simulation of chemical ordering kinetics in nano-layered L10 AB binary system was performed. In the nano- (atomistic) scale Monte Carlo (MC) technique with vacancy mechanism of atomic migration was implemented with diverse system models. The mesoscale microstructure evolution was, in turn, modeled by means of MC procedure simulating antiphase boundary (APB) motion as controlled by APB energies evaluated within the nano-scale simulations. The study addressed FePt thin layers considered as a material for ultra-high density magnetic storage media and revealed metastability of the L10 c-variant superstructure with monoatomic planes parallel to the (001) free surface and off-plane easy magnetization. The layers, initially perfectly ordered in the L10 c-variant, showed homogenous disordering running in parallel with a spontaneous re-orientation of the monoatomic planes into a mosaic-microstructure composed of L10 a- and b-variant domains with (100)- and (010)-type monoatomic planes, respectively. The domains nucleated heterogeneously on the Fe free surface of the layer, grew discontinuously inwards its volume and finally relaxed generating an equilibrium microstructure of the system. Two �atomistic-scale� processes: (i) homogenous disordering and (ii) nucleation of the L10 a- and b-variant domains showed characteristic time scales. The same was observed for the meso-scale processes: (i) heterogeneous L10 variant domain growth and (ii) domain microstructure relaxation. The above phenomena modelled within the present study by means of multiscale MC simulations have recently been observed experimentally in epitaxially deposited thin films of FePt.

One of the foremost challenges in today's materials science is the design and development of materials with physical properties customized for technical application. Due to their excellent corrosion resistance and their advantageous mechanical and in many cases also magnetic properties, intermetallic alloys are among the most important materials of the 21st century. Most of their outstanding qualities are linked to long-range order, the fact that unlike atoms are preferred as neighbours, which then segregate to different sublattices. In most intermetallics atomic order persists up to rather high temperatures, if not up to melting. However, connected with the entropy gain, the degree of order depends on temperature and thereby the stability of the designed beneficial materials properties is affected. By monitoring changes in the degree of atomic order an access to atom migration is gained, which is complementary to the usual diffusion experiments, where the degree of order is not changed on average. It is shown in this review on some selected examples how an adequate thermal treatment of the samples in combination with the experimental approach gives detailed information on atom jump mechanisms and structural changes, especially if experiment is combined with up-to-date kinetic Monte Carlo simulations.

Pd segregation at (001) B2-NiSi/Si epitaxial interface was studied by using density functional theory (DFT). An epitaxial interface between 2×2×4 (001) B2-NiSi supercell and 1×1×2 (001) Si supercell was first constructed by adjusting the lattice parameters of B2-NiSi structure to be matched with those of Si structure. We chose Ni atoms as terminating layer of the B2-NiSi, and an equilibrium gap between the B2-NiSi and Si was calculated to be 1.1 Å. The Ni atoms in the structure moved away from the original positions along z-direction in a systematic way during the energy minimization. Two different Ni sites were identified at the interface and the bulk, respectively. The Ni sites at the interface farther away from the interface were more favorable for Pd substitution.

Nanoscience: an area that promises new understanding of nature with the aid of rapid progress of nanotechnology. Nanotechnology: the use of nanoscience to build new technologies that will change the world. Nanoscience and Nanotechnology have captured the attention of the public, government, and corporations. How they will influence our lives depend on how we prepare ourselves, and our successors. Here we present a brief outline of the efforts being taken at Osaka University since 2004, in order to prepare our future scientists, engineers, and leaders in the rapidly flourishing trans-/multi-disciplinary field of Nanoscience and Nanotechnology.