First-principles study of small aluminum clusters: Oxygen adsorptions, oxidation and phase stability

It is important to understand the properties of individual nanometals before we can exploit full potential of their applications, for example, as energetic materials, enhancing additives, or catalysts. Here, we present a density functional theory study of the structure and properties of clean Al₁₃ clusters, oxygen adsorptions on the cluster surface, and the completely oxidized clusters. The relative stability of various phases at various oxygen pressures and temperatures is investigated based on the so-called “atomistic thermodynamics”, which was previously employed for studying metals. The effect of temperature and oxygen pressure on the phase stability is taken into account via the oxygen chemical potential and reflected in the (P, T) phase diagram. Our results show that only intact and completely oxidized clusters are thermodynamically stable, and that the O adsorption phases are never thermodynamically stable. Also, our results show that the Al₁₃ clusters are extremely easy to get oxidized. The present study provides valuable insight into the basic behaviors of small Al clusters in the presence of oxygen and a theoretical basis for exploring practical applications of these clusters.     

Crystal structure of potassium tris[3-(2-pyridyl)pyrazolyl]hydroborate

The crystal structure of the potassium tris[3-(2-pyridyl)pyrazolyl]hydroborate has been determined. Potassium tris[3-(2-pyridyl)pyrazolyl]hydroborate crystallizes in the orthorhombic space group Pca2₁ with the parameters a=30.7323(5) ?, b=8.3083(1) ? and c=9.2173(2) ?, V=2353.48(7) ?³ with Z=4. The crystal structure reveals the formation of continuous chains where two bidentate arms of the hydroborate ligand are coordinated to one potassium and the third to another cation. The structures of numerous transition metal and actinide salts have been reported during the last decades but no alkali metal complexes were available.     

Characterization of silane layers on modified stainless steel surfaces and related stainless steel-plastic hybrids

The aim of this work was to characterize silane layers on the modified stainless steel surfaces and relate it to the adhesion in the injection-molded thermoplastic urethane-stainless steel hybrids. The silane layers were characterized with scanning electron microscope and transmission electron microscope, allowing the direct quantization of silane layer thickness and its variation. The surface topographies were characterized with atomic force microscope and chemical analyses were performed with X-ray photoelectron spectroscopy. The mechanical strength of the respective stainless steel-thermoplastic urethane hybrids was determined by peel test. Polishing and oxidation treatment of the steel surface improved the silane layer uniformity compared to the industrially pickled surface and increased the adhesion strength of the hybrids, resulting mainly cohesive failure in TPU. XPS analysis indicated that the improved silane bonding to the modified steel surface was due to clean Fe₂O₃-type surface oxide and stronger interaction with TPU was due to more amino species on the silane layer surface compared to the cleaned, industrially pickled surface. Silane layer thickness affected failure type of the hybrids, with a thick silane layer the hybrids failed mainly in the silane layer and with a thinner layer cohesively in plastic.     

Dynamic systems view of learning a three‐tiered theory in physics: robust learning outcomes as attractors

The process of learning scientific knowledge from the dynamic systems viewpoint is studied in terms probabilistic learning model (PLM), where learning accrues from foraging in the epistemic landscape. The PLM leads to the formation of attractor‐type regions of preferred models in an epistemic landscape. The attractor‐type states correspond to robust learning outcomes which are more probable than others. These can be assigned either to the high confidence in model selection or to the dynamic evolution of a learner's proficiency, which depends on the learning history. The results suggest that robust learning states are essentially context dependent, and that learning is a continuous development between these context dependent states. © 2016 Wiley Periodicals, Inc. Complexity 21: 259–267, 2016     

Ab initio studies of crystalline nitromethane under high pressure

We have studied the mechanical compressibility and band structure of solid nitromethane both in equilibrium and compressed states using Hartree-Fock and density functional theory (DFT) with atom-centered all-electron linear combination of atomic orbitals basis sets. Hartree-Fock calculations with a 6-21G basis set, uncorrected for basis set superposition error, gave the best agreement with experimental compression studies. These results may be due to the cancellation of basis set superposition error with dispersion force errors. The equilibrium DFT band gap is comparable to the lowest-energy feature in electron-impact spectroscopy of nitromethane but underpredicts the optical absorption gap; we interpret these features in terms of the presence of tightly bound excitons. Only minor changes in the gap are observed under hydrostatic compression.