Structure formation mechanisms in consolidating pigment coatings—Simulation and visualisation

Microstructure development in consolidating pigment coating layers was studied in terms of particle flocculation and clustering mechanisms utilising a 3D particle dynamics model. The model includes hydrodynamic forces, colloidal interactions as well as the Brownian motion. The influence of colloidal interactions and drying strategy on the coating layer thickness development and internal solid concentration gradients, was investigated. A low particle surface potential resulted in the formation of porous particle networks, which impeded the shrinkage of the coating layer. At higher surface potentials particles arranged into denser structures, whereby the solids concentration profile could be controlled by the drying. Low electrostatic double layer thicknesses allowed sharp concentration gradients to form as result of the applied drying strategy. At high double layer thicknesses, the structure formation was similar regardless of drying strategy. This work elucidates the combined effect of drying conditions and colloidal suspension properties on coating microstructure development. Furthermore, the results aid in the understanding of how coating suspension additives may influence the structure development of the coating layer.     

Adsorption of Zn2+ ions onto NaA and NaX zeolites: Kinetic,equilibrium and thermodynamic studies

The adsorption of Zn²⁺ onto NaA and NaX zeolites was investigated. The samples were synthesized according to a hydrothermal crystallization using aluminium isopropoxide (Al[OCH(CH₃)₂]₃) as a new alumina source. The effects of pH, initial concentration, solid/liquid ratio and temperature were studied in batch experiments. The Freundlich and the Langmuir models were applied and the adsorption equilibrium followed Langmuir adsorption isotherm. The uptake distribution coefficient (K_d) indicated that the Zn²⁺ removal was the highest at minimum concentration. Thermodynamic parameters were calculated. The negative values of standard enthalpy of adsorption revealed the exothermic nature of the adsorption process whereas the negative activation entropies reflected that no significant change occurs in the internal structure of the zeolites solid matrix during the sorption of Zn²⁺. The negative values of Gibbs free energy were indicative of the spontaneity of the adsorption process. Analysis of the kinetic and rate data revealed that the pseudo second-order sorption mechanism is predominant and the intra particle diffusion was the determining step for the sorption of zinc ions. The obtained optimal parameters have been applied to wastewater from the industrial zone (Algeria) in order to remove the contained zinc effluents.     

Numerical study on the evaluation of tunnel shotcrete using the Impact-Echo method coupled with Fourier transform and short-time Fourier transform

This study presents a simple but robust evaluation technique of the bonding state of shotcrete applied to tunnels using Impact-Echo (IE) method and thus explores the effect of the ground types, thickness of the shotcrete, undulating surfaces and impact sources on system vibration through numerical simulations based on the finite element method. All the signals obtained from numerical simulation for various conditions are analyzed at the frequency domain using Fourier transform (FT) and at the time–frequency domain using short-time Fourier transform (STFT). As the bonding condition worsens, the resonant frequency (f_n) and the resonance duration (T_R) increase and the geometric damping ratio (D_G) decreases. The results of a comprehensive numerical analysis suggest that the shape of the contour in the time–frequency domain, the level of f_n, and the T_R and D_G values can be used as effective indicators for the evaluation of the shotcrete thickness, ground type, and bonding state. Finally, this paper presents a procedure for evaluating the tunnel shotcrete state, the shotcrete thickness, and the ground type with the IE method coupled with Fourier transform and short-time Fourier transform. Limited field tests were also performed to verify the proposed evaluation chart for tunnel shotcrete states.     

The significance of nanoparticles on bond strength of polymer concrete to steel

Polymer concrete (PC) is a commonly used material in construction due to its improved durability and good bond strength to steel substrate. PC has been suggested as a repair and seal material to restore the bond between the cement annulus and the steel casing in wells that penetrate formations under consideration for CO₂ sequestration. Nanoparticles including Multi-Walled Carbon Nano Tubes (MWCNTs), Aluminum Nanoparticles (ANPs) and Silica Nano particles (SNPs) were added to an epoxy-based PC to examine how the nanoparticles affect the bond strength of PC to a steel substrate. Slant shear tests were used to determine the bond strength of PC incorporating nanomaterials to steel; results reveal that PC incorporating nanomaterials has an improved bond strength to steel substrate compared with neat PC. In particular, ANPs improve the bond strength by 51% over neat PC. Local shear stresses, extracted from Finite Element (FE) analysis of the slant shear test, were found to be as much as twice the apparent/average shear/bond strength. These results suggest that the impact of nanomaterials is higher than that shown by the apparent strength. Fourier Transform Infrared (FTIR) measurements of epoxy with and without nanomaterials showed ANPs to influence curing of epoxy, which might explain the improved bond strength of PC incorporating ANPs.     

Could non-Saccharomyces yeasts contribute on innovative brewing fermentations?

With the advances in the production of beer worldwide, more challenges arise each year in the search for new approaches to the development of distinctive beverages. Attempts to obtain products with more complex sensory characteristics have led experts and brewers to prospect for non-conventional yeasts, i.e., non-Saccharomyces yeasts that may provide a new range of perspectives in terms of techniques and approaches. Besides the widespread use of Dekkera/Brettanomyces for the production of sour beers, other species are emerging for presenting unusual metabolic features that include the production of fruity esters, and a distinctive enzymatic apparatus. Wickerhamomyces anomalus and Torulaspora delbrueckii stand out as the most promising yeasts in brewing processes. Such new tendencies in the use of non-Saccharomyces yeasts comprise the production of low-alcohol beers, functional beers, and bioflavoring approaches. This is a little explored field in brewing practice, still requiring extensive research with practical application. In this sense, this review aims to present the main points for the application of non-conventional yeasts in beer production, and thus contribute to future advances in the topic.     

Modelling to generate alternatives with an energy system optimization model

Energy system optimization models (ESOMs) should be used in an interactive way to uncover knife-edge solutions, explore alternative system configurations, and suggest different ways to achieve policy objectives under conditions of deep uncertainty. In this paper, we do so by employing an existing optimization technique called modeling to generate alternatives (MGA), which involves a change in the model structure in order to systematically explore the near-optimal decision space. The MGA capability is incorporated into Tools for Energy Model Optimization and Analysis (Temoa), an open source framework that also includes a technology rich, bottom up ESOM. In this analysis, Temoa is used to explore alternative energy futures in a simplified single region energy system that represents the U.S. electric sector and a portion of the light duty transport sector. Given the dataset limitations, we place greater emphasis on the methodological approach rather than specific results.     

Transition metal nanoparticles doped carbon paper as a cost-effective anode in a microbial fuel cell powered by pure and mixed biocatalyst cultures

The poor wettability and high cost of the carbonaceous electrodes materials prohibited the practical applications of microbial fuel cells (MFCs) on large scale. Here, a novel nanoparticles of metal sheathed with metal oxide is electrodeposited on carbon paper (CP) to introduce as high-performance anodes of microbial fuel cell (MFC). This thin layer of metal/metal oxide significantly enhance the microbial adhesion, the wettability of the anode surface and decrease the electron transfer resistance. The investigation of the modified CP anodes in an air-cathode MFCs fed by various biocatalyst cultures shows a significant improving in the MFC performance. Where, the generated power and current density was 140% and 210% higher as compared to the pristine CP. Mixed culture of exoelectrogenic microorganism in wastewater exhibited good performance and generated higher power and current density compared to yeast as pure culture. The excellent capacitance with a distinctive nanostructure morphology of the modified-CP open an avenues for practical applications of MFCs.     

Performance prediction of hard rock Tunnel Boring Machines (TBMs) in difficult ground

Performance prediction of TBMs is an essential part of project scheduling and cost estimation. This process involves a good understanding of the complexities in the site geology, machine specification, and site management. Various approaches have been used over the years to estimate TBM performance in a given ground condition, many of them were successful and within an acceptable range, while some missing the actual machine performance by a notable margin. Experience shows that the best approach for TBM performance prediction is to use various models to examine the range of estimated machine penetration and advance rates and choose a rate that best represents the working conditions that is closest to the setting of the model used for the estimation. This allows the engineers to avoid surprises and to identify the parameters that could dominate machine performance in each case. This paper reviews the existing models for performance prediction of TBMs and some of the ongoing research on developing better models for improved accuracy of performance estimate and increasing TBM utilization.