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Experiments and simulations are used jointly to gain a comprehensive insight into the pinching mechanism that generates alginate droplets in an X-microdevice operating in a hydrodynamic flow-focusing configuration. The X-microdevice is fed with an aqueous alginate solution into one inlet channel, while sunflower oil and Span80 are fed into the other two inlet channels. The use of the adaptive mesh refinement and volume of fluid method allows accurate tracking of the interface in numerical simulations. The sensitivities of numerical predictions to the contact angle and the surface tension are estimated through dedicated sets of simulations. Subsequently, numerical simulations and experiments are compared for different flow rates with a satisfactory agreement. We observe that the pinch-off mechanism may lead to the formation of several satellite drops in addition to the main droplet. A pinching performance indicator is suggested based on the amount of alginate that is encapsulated in the main droplet. The effect of operating conditions on the pinching efficiency, frequency, and droplet diameter is discussed to provide valuable information to optimize the droplets production. The pinching efficiency is closely related to the length and diameter of the liquid thread. At low flow rates, a short liquid thread is observed. This leads to the formation of few satellites and, thus, to high pinching efficiency but low droplet production. Increasing the dispersed-phase flow rate slightly reduces the efficiency but significantly increases the production. [ABSTRACT FROM AUTHOR]

Smart at‐ or online process sensors, which employ machine learning (ML) to process data, have been the subject of extensive research in recent years, due to their potential for real‐time process control. In this paper, a passive acoustic emission process sensor has been used to detect gas–liquid regimes within a stirred, aerated vessel using novel ML approaches. Pressure fluctuations (acoustic emissions) in an air‐water system were recorded using a piezoelectric sensor installed on the external wall of three identical cylindrical tanks of diameter, T = 160 mm, filled to a volume of 5 L (height, H = 1.5 T). The tanks were made of either glass, steel, or aluminium, and each tank was equipped with a Rushton turbine of diameter, D = 0.35 T. The investigated flow regimes, flooding, loading, complete dispersion, and un‐gassed, were obtained by changing the air feed flow rates and by varying the impeller speed. The acoustic spectra obtained were processed to select an optimal number of features characterizing each of the regimes, and these were used to train three different ML algorithms. The pre‐processing includes a principal component analysis (PCA) step, which reduces the volume of data fed to the ML algorithms, saving computational time up to a factor of 5. The algorithms (decision tree, k‐nearest neighbour, and support vector machines) were challenged to use these features to identify the correct flow regime. Accurate predictions of the three gas–liquid regimes of interest have been achieved. The accuracy of the prediction ranges from 90% to 99%, and this difference is related to the material used for the vessel. [ABSTRACT FROM AUTHOR]

Numerical simulations based on Computational Fluid Dynamics have been performed for the assisted design of the flexible and transportable flow reactor developed within the Turboflux project. The core of the system consists of a tubular pipe, carrying the main fluids, and multiple injection ducts for the additive components. Mixing is ensured by a series of static mixing elements fitted within the main pipe. More specifically, we focus herein on the production of the sanitizing gel, obtained from three main components, i.e., ethanol, water, and glycerol. Hence, the numerical code is customized by implementing the non-ideal behaviour of the mixture. The degree of mixing and pressure drops are estimated in a wide range of scenarios, covering different flow regimes. The analysis allows one to identify the optimal operating conditions and, also, to put the basis for the setup of a digital twin of the system. [ABSTRACT FROM AUTHOR]

Microfluidic devices may provide significant technological advancement in the production of micro and nanoparticles of interest in the pharmaceutical sector, for instance, particles used as drug carriers (Yeh et al., 2013). Indeed, microfluidics enables their production with precise control of the dimensional distribution, not achievable with conventional beaker methods. The particle size is crucial for the optimal operation, thus representing a key target along with the generation frequency. The device geometry, properties, and flow rates of the fluids are the main parameters that affect the generation process. In this work, we investigate the production of alginate droplets in an X-shaped microdevice (Tomasi Masoni et al., 2022). More specifically, we feed an alginate solution in sunflower oil working in the dripping regime. Experimental visualizations are carried out for different flow rates and concentrations of the surfactant to comprehend their effect on droplet formation. Interestingly, we identify operating conditions that prevent the formation of satellite droplets to preserve a narrow dimensional distribution. [ABSTRACT FROM AUTHOR]

This work is aimed at developing the first version of a digital twin of a plant prototype for the flexible production of different chemical formulates, to be used in various industrial fields, from the medical health to the tanning sector. The analyzed system is a tubular flow reactor characterized by multiple additions of components and by a series of static mixing elements. Firstly, the 1D dynamic modeling of the reactor is addressed, by defining the geometry, parameters, and operating conditions to reasonably describe the process evolution over time. Then, the corresponding feedback control system is designed to obtain the desired final products, by respecting the required specifications, in terms of mean concentration, degree of mixing, and flow rates. Different types of control architectures are derived and compared. The results show that not only SISO control schemes, but also multivariable solutions are possible, which effectively guarantee set-point tracking and disturbance rejection. [ABSTRACT FROM AUTHOR]

Potassium chloride (KCl) is widely used in many fields of the processing industry. The application in the food industry, as well the one in the pharmaceutic sector, requires very pure KCl crystals (not less than 99.0%), therefore the elimination of impurities in the production process is a mandatory task. The case study analyzed in this work is a real pilot plant for producing high-purity KCl developed by an Italian chemical company. The major issue of this process is given by the occasional presence of potassium sulfate (K2SO4) in the final product which invalidates the stringent purity specifications required. The actual socio-economic situation linked to the energy and raw materials markets makes it very difficult for the industries to spend efforts for experimental investigations that are normally often long and expensive. Therefore, a rigorous simulation model of the plant has been built using UniSim Design® with the thermodynamic package OLI® that enables the possibility to consider different liquid-solid equilibria. The developed model has been used to verify the formation of the impurities in three different ways: checking the process normal operation, verifying the fluid dynamics design of the crystallization unit, and investigating the start-up conditions. The analysis shows a potential source of formation of K2SO4 nucleus under the actual brine concentration recirculated in the crystallizer during the startup phase, albeit further investigations have to be performed on the pilot plant to confirm such a hypothesis. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries (LIBs) have become a widespread technology for electrochemical energy storage in the current era of digitalization and transport electrification, being used as electric stationary storage as well as for powering electric vehicles, e-bikes and portable electronic devices such as smartphones and laptops. However, LIBs contain valuable materials, such as cobalt, nickel, lithium and graphite, whose supply has become critical to meet the increasing demand of batteries. Therefore, proper recycling processes are required in order to recover these materials from spent batteries and re-use them to produce new batteries in a sustainable cycle. This contribution provides an extensive survey of the main recycling routes available today, focusing specifically on pyrometallurgical and hydrometallurgical processes based in Europe, North America and Asia. Attention is also devoted to the recycling behaviour of individuals and companies and to the possible ways to increase their recycling rate. The comparison of different processes allows for the ranking of best practices as well as the drawbacks of different process units, with identification of which materials can be recovered, their recovery rate, and an assessment of the overall recycling efficiency of the process for different battery sizes (small and large, for portable electronics and electric vehicles, respectively). The analysis reveals that pyrometallurgical processes can flexibly treat different LIB chemistries but, since the electrolyte and graphite are burnt in the process, the global recycling efficiency cannot compete with hydrometallurgical processes, especially for small format batteries. Nevertheless, hydrometallurgical processes typically require preliminary mechanical separation treatments to separate the black mass, which contains valuable electrodic materials, as well as complex precipitation steps, which eventually reduce the material recovery rate and the applicability to diverse LIB chemistries. Finally, the study reports an analysis of the electrochemical performance of a battery made with recycled materials, showing that even if recycled cathodic materials had a lower gravimetric capacity and solid-state diffusivity, the performance of a recycled battery could be compensated by simple minor changes to the cell design which would ultimately decrease the specific energy density by a few percent compared to a LIB made with virgin materials. [ABSTRACT FROM AUTHOR]

Microfluidics is gaining increasing interest in the field of chemical engineering, as miniaturization may lead to a significant intensification of chemical processes. Since the flow is laminar, achieving a good mixing of reactants is one of the main challenges. The simplest geometry is constituted by a T-shaped mixer in which the two inlets join perpendicularly the mixing channel. The inlet cross section is usually square while the mixing channel cross-section is a rectangle as straight walls facilitate experimental and modelling analysis. The present work, on the contrary, is aimed at investigating through Computational Fluid Dynamics the effect of a cross-section with lateral inclined walls, to emulate a microfabrication technology based on laser machining. The presence of inclined walls is found to hamper mixing at high Reynolds numbers as the flow is unable to break the mirror symmetry and thus to undergo the engulfment regime. However, at low Reynold numbers the mixing is improved because the vortex regime presents a lower degree of symmetry with respect to that of T-mixers with straight walls. [ABSTRACT FROM AUTHOR]

Computational fluid dynamics (CFD) is very appealing to investigate mixing and reaction in microdevices, as it allows easily investigating different operating conditions as well as mixer geometries. This latter aspect is very important as the flow in microdevices is laminar so the mixing between reactants should be promoted by a clever mixer design, aimed at breaking the flow symmetries. Recently time periodic motions that improve mixing have been observed to take place in a T‐junction at low Reynolds numbers. In this case the numerical modelling should be based on direct numerical simulations (DNS), thus involving high computational resources. In this work, two different CFD approaches, i.e., finite volume and spectral element methods, are applied and compared for the analysis of the mixing process in the well known T‐shaped micromixer. Spectral elements methods are particularly suited for DNS; however, they have been scarcely applied to study micromixers, while plenty of works can be found with finite volume methods. The analysis is carried out using both ideal and non‐ideal liquid binary mixtures, the latter presenting a negative fluidity of mixing (i.e., the viscosity of the mixture is higher than that of the pure components). Moreover the numerical results are validated with simple flow visualization experiments. [ABSTRACT FROM AUTHOR]