Assessing the production of jet mix columns using alkali activated waste based on mechanical and financial performance and CO2 (eq) emissions

Recent research has proved the potential of alkaline activated fly-ash for soil stabilisation. However, such studies have not focused on the link between financial, mechanical and environmental aspects of this solution, but only on their absolute mechanical properties. The present paper characterises the mechanical behaviour of a large spectrum of activator-ash-soil combinations used to build jet mixing columns, analysing also the cost and CO2 (eq) emissions. The concern with these two vectors forced a decrease in the quantity of stabilising agent added to the soil, relatively to previous research, and the effects of such low quantities have not yet been published. However, the results clearly showed a significant improve in strength, still well above the average values expected when improving the stressstrain behaviour of a weak soil. Uniaxial compressive strength tests were used to assess the effects of the fly-ash percentage, the alkalieash ratio and the water content. The carbon calculator recently developed by the European Federation of Foundation Contractors and the Deep Foundations Institute was used to quantify the CO2 (eq) emissions associated with this technique. The financial cost was estimated based on the experience of a major Portuguese contractor. For comparison purposes, soil cement mixtures were also analysed, using similar conditions and tools used for the soil-ash analysis. Results showed that the cement and ash solutions are very similar in terms of overall performance, with some advantage of the former regarding financial cost, and a significant advantage of the latter regarding the CO2 (eq) emissions. This new grout, although it is in an embryonic stage, it has the potential for broader developments in the field.

Surface plasmon resonance-coupled photoluminescence and resistive switching behavior of pulsed laser-deposited Ag:SiC nanocermet thin films

In this study, Ag:SiC nanocermets were prepared via rapid thermal annealing (RTA) of pulsed laser-deposited SiC/Ag/SiC trilayers grown on Si substrate. Atomic force microscope images show that silver nanoparticles (Ag NPs) are formed after RTA, and the size of NPs increases with increasing Ag deposition time (t Ag). Sharp dip observed in the reflectance spectra confirmed the existence of Ag surface plasmons (SPs). The infrared transmission spectra showed an intense and broad absorption band around 780–800 cm−1 that can be assigned to Si-C stretching vibration mode. Influence of t Ag on the spectral characteristics of SP-enhanced photoluminescence (PL) and electrical properties of silicon carbide (SiC) films has been investigated. The maximum PL enhancement by 5.5 times for Ag:SiC nanocermets is achieved when t Ag ≈ 50 s. This enhancement is due to the strong resonant coupling between SiC and the SP oscillations of the Ag NPs. Presence of Ag NPs in SiC also induces a forming-free resistive switching with switching ratio of 2 × 10−2. The analysis of I–V curves demonstrates that the trap-controlled space-charge-limited conduction with filamentary model is the governing mechanism for the resistive switching in nanocerment thin films.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Silicon nanowire arrays coupled with cobalt phosphide spheres as low-cost photocathodes for efficient solar hydrogen evolution

We demonstrate the first example of silicon nanowire array photocathodes coupled with hollow spheres of the emerging earth-abundant cobalt phosphide catalysts. Compared to bare silicon nanowire arrays, the hybrid electrodes exhibit significantly improved photoelectrochemical performance toward the solar-driven H2 evolution reaction.

Nonsymmetrical separations in thermal diffusion columns

The influence of the feed composition upon the actual degrees of separation attained at the top and bottom sections of a thermogravitational column is discussed using the classical phenomenological theory of Furry, Jones, and Onsager. It is shown that, except for a feed composition of C 0 = 0.5 (mass fraction), the separation profile is nonsymmetric, i.e., the separations in the top and bottom sections of the column are nonsymmetric with respect to the feed composition, the asymmetry increasing as the feed composition moves away from C 0 = 0.5. An equation for the determination of the optimum feed location as a function of the feed composition is derived.

Some observations on asymmetrical separation in thermal diffusion columns

Data have been obtained in steady-state batch operated thermogravitational separation columns using different binary mixtures to test the theory recently published by Morgado et al. The experimental results confirm that separations by thermal diffusion are asymmetrical except when the initial concentration is 0.5 and that the asymmetry is larger as the initial concentration deviates from 0.5 and as the separation potential increases.