Journal of Non-Crystalline Solids: X最新文献

Amorphous metal coatings have great potential for corrosion protection but finding alloy compositions which form a stable amorphous structure can be an overwhelming task. We use combinatorial magnetron sputtering and X-ray analysis to map out the phase space of TaSiM (M = Al, Cr, Fe, Ti) alloys in order to identify amorphous compositions. Atomic percentages of above 10–15 at.% of each constituent yield amorphous coatings in all four systems. TaSiAl coatings are stable when annealed in air up to and including 550 °C whereas TaSiFe, TaSiCr and TaSiTi remain amorphous up to and including 750 °C. In particular, Ta₃₅Si₁₅Cr₅₀ is almost unchanged at that temperature, and has a stable surface oxide shell less than 20 nm in thickness at 650 °C. The stability of these materials at high temperatures means that they could be suitable as anti-corrosion coatings in high temperature applications.

Understanding the atomic structure of amorphous solids or glasses is a perennial, and ultimately insoluble, challenge, since the randomness involved means that structural information can only ever be obtained, from either experiment or structural modelling, in a statistical form, unlike the case for crystalline materials. The particular atomic structure, in a glass or crystal, is dictated by the underlying chemical bonding between the atoms. The question arises therefore, conversely, to what extent can one infer anything about the nature of the bonding in amorphous/glassy solids from some knowledge of the atomic structure? In this focused perspective article, I discuss the case of telluride glassy materials, and show that they represent a special case of bonding in chalcogenide materials. The near-linear axial structural configurations characteristic of certain telluride crystals, also prevalent in the corresponding glasses, and giving rise to a particular degree of linear medium-range structural order, are shown to arise from hyperbonding (e.g. three-centre/four-electron) interactions, rather than being associated with conventional (two-centre/two-electron) covalent bonds, as in other chalcogenide materials. These structural configurations are responsible for the unique ‘phase-change memory’ behaviour exhibited by some telluride materials. An experimental technique is proposed which should be capable of detecting such linear-character, medium-range structural order in telluride glasses.

Particles of borophosphate glasses with the nominal molar compositions 16Na₂O-(24-y)CaO-ySrO-xB₂O₃-(60-x)P₂O₅ (mol%), where 0 ≤ x ≤ 60 and y = 0, 12, and 24, were reacted in deionized water and in simulated body fluid (SBF) at 37 °C. For the dissolution experiments in water, the pH of the solution at the conclusion of the experiments increased systematically, from 2.1 to 9.5, for y = 0 glasses when ‘x’ increased from 0 to 60. The reaction rates over the first 8–24 h of dissolution in both SBF and deionized water followed linear kinetics, with reaction rates dependent on glass composition. For glass particles in SBF, replacing P₂O₅ with up to 20 mol% B₂O₃ decreased the dissolution rate (fraction dissolved) by two orders of magnitude, from 7.0 × 10⁻³ h⁻¹ for x = 0 to 2.0 × 10⁻⁵ h⁻¹ for x = 20. Further replacement of P₂O₅ by B₂O₃ increased dissolution rates by three orders of magnitude, to 2.3 × 10⁻² h⁻¹ at x = 60. The compositional dependence of the dissolution rates is explained by changes in the glass structure, with the most durable glasses possessing the greatest fraction of tetrahedral borophosphate sites in the glass network. Crystalline brushite was detected on Ca-glasses with 35 and 40 mol% B₂O₃, but the dominant precipitation phase on both the Ca- and Sr-glasses is an x-ray amorphous material constituted from orthophosphate and pyrophosphate anions.

After assessing compositional dependence of thermal and optical properties of Ge-Ga-Se glasses, we introduce Te, via replacing Se, into Ge₂₅Ga₅Se₇₀ and Ge₃₅Ga₅Se₆₀ (mol%) glasses in an attempt to enhance their refractive index. In the case of Se-deficient Ge₃₅Ga₅Se₆₀ composition, vitrification is achieved for Te content up to 20 mol%. In the case of Se-sufficient Ge₂₅Ga₅Se₇₀ composition, however, formation of bulk glass is realized only when Te content ranges from 25 to 45 mol%. Being proportional to Te content, refractive index of Ge₂₅Ga₅Se₃₀Te₄₀ glass is measured to approach 2.855 at 10 μm, which is far superior to that of any commercialized selenide glasses for infrared-imaging applications. This compositionally tailored Ge₂₅Ga₅Se₃₀Te₄₀ glass is further verified to be compatible with the conventional precision glass molding process, and infrared-imaging performance of the resulting molded lens is as excellent as the existing selenide-glass-based lenses.

Quantitative structure-property relationship (QSPR) is a powerful analytical method to find correlations between the structure of a molecule and its physicochemical properties. The glass transition temperature (T_g) is one of the most reported properties, and its characterisation is critical for tuning the physical properties of materials. In this work, we explore the use of machine learning in the field of QSPR by developing a recurrent neural network (RNN) that relates the chemical structure and the glass transition temperature of molecular glass formers. In addition, we performed a chemical embedding from the last hidden layer of the RNN architecture into an m-dimensional T_g-oriented space. Then, we test the model to predict the glass transition temperature of essential amino acids and peptides. The results are very promising and they can open the door for exploring and designing new materials.