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Combining in situ studies of the catalyst activity during single-walled carbon nanotube (SWCNT) growth by mass spectrometry with differential scanning calorimetry and Raman spectroscopy results, the authors expose the favorable features of small catalyst for SWCNT growth and their relationship with synthesis parameters. The sequential introduction of C12 and C13 labeled hydrocarbon reveals the influence of catalyst composition on its lifetime and the growth termination path. Ab initio and molecular dynamics simulations corroborate “V”-shape liquidus line of metal-carbon nanoparticle binary phase diagram, which explains observed carbon-induced solid-liquid-solid phase transitions during nanotube growth.

Thermodynamic properties of Ne, Ar, Kr, and Xe adsorbed on an Al-Ni-Co quasicrystalline surface (QC) are studied with Grand Canonical Monte Carlo by employing Lennard-Jones interactions with parameter values derived from experiments and traditional combining rules. In all the gas/QC systems, a layer-by-layer film growth is observed at low temperature. The monolayers have regular epitaxial fivefold arrangements which evolve toward sixfold close-packed structures as the pressure is increased. The final states can contain either considerable or negligible amounts of defects. In the latter case, there occurs a structural transition from five to sixfold symmetry which can be described by introducing an order parameter, whose evolution characterizes the transition to be continuous or discontinuous as in the case of Xe/QC (first-order transition with associated latent heat). By simulating fictitious noble gases, we find that the existence of the transition is correlated with the size mismatch between adsorbate and substrate's characteristic lengths. A simple rule is proposed to predict the phenomenon., Comment: 19 pages. 8 figures. (color figures can be seen at http://alpha.mems.duke.edu/wahyu/ or http://www.iop.org/EJ/abstract/0953-8984/19/1/016007/)

Molecular dynamics simulations have been used to study the structural and dynamic changes during melting of free and supported iron clusters ranging from 150 to 10000atoms. The results reveal a method for determining effective diameters of supported metal clusters, so that the melting point dependence on cluster size can be predicted in a physically meaningful way by the same analytic model used for free clusters.

In this manuscript we present the thermodynamics of iron-carbon nano particles at low temperature. By combining classical molecular dynamics simulations, ab initio calculations, finite temperature thermodynamics modeling, and the “size/pressure approximation”, we address carbon-induced fluidization, size-induced eutectic point shift, and reduced solubility at the nanoscale. The results are used to describe, as functions of particle size, three scenarios in the catalytic chemical vapor deposition growth of single single-walled carbon nanotubes, corresponding to steady state-, limitedand no-growth.

$\textit{A priori}$ prediction of phase stability of materials is a challenging practice, requiring knowledge of all energetically-competing structures at formation conditions. Large materials repositories $\unicode{x2014}$ housing properties of both experimental and hypothetical compounds $\unicode{x2014}$ offer a path to prediction through the construction of informatics-based, $\textit{ab-initio}$ phase diagrams. However, limited access to relevant data and software infrastructure has rendered thermodynamic characterizations largely peripheral, despite their continued success in dictating synthesizability. Herein, a new module is presented for autonomous thermodynamic stability analysis implemented within the open-source, $\textit{ab-initio}$ framework AFLOW. Powered by the AFLUX Search-API, AFLOW-CHULL leverages data of more than 1.8 million compounds currently characterized in the AFLOW.org repository and can be employed locally from any UNIX-like computer. The module integrates a range of functionality: the identification of stable phases and equivalent structures, phase coexistence, measures for robust stability, and determination of decomposition reactions. As a proof-of-concept, thorough thermodynamic characterizations have been performed for more than 1,300 binary and ternary systems, enabling the identification of several candidate phases for synthesis based on their relative stability criterion $\unicode{x2014}$ including 18 promising $C15_{b}$-type structures and two half-Heuslers. In addition to a full report included herein, an interactive, online web application has been developed showcasing the results of the analysis, and is located at aflow.org/aflow-chull., 22 pages, 7 figures

The continued advancement of science depends on shared and reproducible data. In the field of computational materials science and rational materials design this entails the construction of large open databases of materials properties. To this end, an Application Program Interface (API) following REST principles is introduced for the AFLOWLIB.org materials data repositories consortium. AUIDs (Aflowlib Unique IDentifier) and AURLs (Aflowlib Uniform Resource locator) are assigned to the database resources according to a well-defined protocol described herein, which enables the client to access, through appropriate queries, the desired data for post-processing. This introduces a new level of openness into the AFLOWLIB repository, allowing the community to construct high-level work-flows and tools exploiting its rich data set of calculated structural, thermodynamic, and electronic properties. Furthermore, federating these tools would open the door to collaborative investigation of the data by an unprecedented extended community of users to accelerate the advancement of computational materials design and development., 22 pages, 7 figures

Computing vibrational free energies (Fvib) and entropies (Svib) has posed a long-standing challenge to the high-throughput ab initio investigation of finite temperature properties of solids. Here, we use machine-learning techniques to efficiently predict Fvib and Svib of crystalline compounds in the Inorganic Crystal Structure Database. Using descriptors based simply on the chemical formula and using a training set of only 300 compounds, mean absolute errors of less than 0.04 meV/K/atom (15 meV/atom) are achieved for Svib (Fvib), whose values are distributed within a range of 0.9 meV/K/atom (300 meV/atom.) In addition, for training sets containing fewer than 2000 compounds, the chemical formula alone is shown to perform as well as, if not better than, four other more complex descriptors previously used in the literature. The accuracy and simplicity of the approach means that it can be advantageously used for fast screening of chemical reactions at finite temperatures.

Reducing parameter spaces via exploiting symmetries has greatly accelerated and increased the quality of electronic-structure calculations. Unfortunately, many of the traditional methods fail when the global crystal symmetry is broken, even when the distortion is only a slight perturbation (e.g., Jahn-Teller like distortions). Here we introduce a flexible and generalizable parametric relaxation scheme and implement it in the all-electron code FHI-aims. This approach utilizes parametric constraints to maintain symmetry at any level. After demonstrating the method’s ability to relax metastable structures, we highlight its adaptability and performance over a test set of 359 materials, across 13 lattice prototypes. Finally we show how these constraints can reduce the number of steps needed to relax local lattice distortions by an order of magnitude. The flexibility of these constraints enables a significant acceleration of high-throughput searches for novel materials for numerous applications.