Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Two-step sinter-crystallization of K2O–CaO–P2O5–SiO2 (45S5-K) bioactive glass

Bioactive glasses and glass-ceramics (GCs) effectively regenerate bone tissue, however most GCs show improved mechanical properties. In this work, we developed and tested a rarely studied bioactive glass composition (24.4K₂O-26.9CaO-46.1SiO₂-2.6P₂O₅ mol%, identified as 45S5-K) with different particle sizes and heating rates to obtain a sintered GC that combines good fracture strength, low elastic modulus, and bioactivity. We analyzed the influence of the sintering processing conditions in the elastic modulus, Vickers microhardness, density, and crystal phase formation in the GC. The best GC shows improved properties compared with its parent glass. This glass achieves a good densification degree with a two-step viscous flow sintering approach and the resulting GC shows as high bioactivity as that of the standard 45S5 Bioglass®. Furthermore, the GC elastic modulus (56 GPa) is relatively low, minimizing stress shielding. Therefore, we unveiled the glass sintering behavior with concurrent crystallization of this complex bioactive glass composition and developed a potential GC for bone regeneration.     

Effect of beam voltage on the properties of aluminium nitride prepared by ion beam assisted deposition

The effects of nitrogen-beam voltage on the structure, stress, energy band gap and hardness of AIN thin films deposited on Si (111), Si (100) and sapphire (0001) by ion beam assisted deposition (IBAD) are reported. As the nitrogen-beam voltage was increased from 50 to 200 V, the stress and disorder in the AIN films increased as determined by X-ray diffraction, FTIR and Raman spectroscopy. The preferred orientation of the film's c-axis changed from completely normal to the film at 100 V, to a mixture of normal and in the plane of the film at 200 V. For AIN films deposited under the same conditions, the films were more highly oriented on sapphire (0001) than in Si (111). The hardness of the films increased from 18.2 to 23.7 GPa with the nitrogen-beam voltage, and possible reasons for this change in hardness are considered.     

Modeling Solvent Drying of Coated Webs Including the Initial Transient

A complete model for the drying of coated webs. as implemented in the spreadsheet DRYWEB for Lotus and for Excel, is described. The model predicts the temperatures and solvent levels throughout the length of the dryer. The initial transient as the coated web approaches the equilibrium temperature in the consiant rate period is calculated. The coating is divided into slices for a finite difference calculation of solvent diffusion to the surface, using a simple free volume model of diffusion. The semi-empirical constants needed can be found from one or two trial runs. The possible use of infra-red heating in addition to convection heating is included in both the constant and falling rates. The calculation of infra-red energy is discussed. The model assumes that the temperature is uniform from the top of the coating to the bottom of the base, and that assumption is justified.     

Gas-phase selective oxidation of toluene on TiO2–sepiolite supported vanadium oxides: Influence of vanadium loading on conversion and product selectivities

Gas-phase selective oxidation of toluene has been carried out on vanadium oxide systems (5–20 wt.% of V₂O₅, equivalent to 0.4–1.7 theoretical monolayers) supported on TiO₂–sepiolite (with titania loading around the theoretical monolayer, 12 wt.%) and on sepiolite. A study has been made on both the influence of vanadia loading and of the support on the catalytic behaviour of the supported vanadium systems. The reducibility by H₂ TPR was also studied as well as the acid and basic/redox sites from the results of conversion of the 2-propanol test reaction of the solids. Benzaldehyde, benzoic acid and several coupling products were the main ones detected, attaining over 50% selectivity towards the benzaldehyde and benzoic acid products at a total conversion around 10%. The activity and selectivity to the selective products exhibited by vanadium systems supported on mixed support were superior to those exhibited by the systems supported on sepiolite and increased notably in both series with the increase in vanadium loading. The best catalytic behaviour exhibited by the vanadium systems supported on mixed support, which also exhibited the highest density of sites capable of being reduced (as well as their reducibility) and of those responsible for propanone formation, could be attributed not only to the different balance of the vanadia species existing in the two supports (monomeric + oligomeric/polymeric), but also to such other factors as the nature of the support and, concretely, its chemical composition.     

Aflatoxin B1 contamination of shrimp feeds and its effect on growth and hepatopancreas of pre-adult Penaeus monodon

A survey of aflatoxin B₁ (AFLB₁) levels in commonly used commercial shrimp finisher feeds in the Philippines showed a various range of values from not detected to 120 μg kg^?1 using high-performance thin-layer chromatography. Six experimental diets were prepared to contain various levels of AFLB₁ based on survey results to determine the effects of such contamination in pre-adult shrimp Penaeus monodon (17.5 ± 0.6 g). Results showed that shrimps fed diets containing AFLB₁ greater than or equal to 73.8 μg kg^?1 gave comparatively poor growth rate and higher susceptibility to shell diseases. No AFLB₁ residues were detected in sampled whole shrimp tissues after 62 days of exposure to AFLB₁ containing diets indicating a low potential for transmission of the toxin from edible shrimp tissues to consumers. Histopathological alterations in the hepatopancreas of shrimp chronically exposed to AFLB, were observed in all samples. The degree of alterations correlated with the level of AFLB₁. Based on growth performance, pre-adult shrimps can tolerate AFLB₁ levels of up to 52.3 μg kg^?1 in the feeds although histopathological changes were already evident in the tissues of shrimps given diets with 26.5 μg kg^?1 AFLB₁.