The design of a multi-stream plate-fin heat exchanger is a highly integrated task with multiple opposing objectives and many degrees of freedom. This work shows how it can be fully or partially automated by the combination of a detailed three-dimensional simulation model and an optimization routine. The desired task is formulated as the target of a multi-objective optimization and solved using a genetic algorithm. The workflow is presented using a cryogenic plate-fin heat exchanger with four process streams. The design is optimized towards high efficiency, low pressure drop, and low unit weight by adjusting the outer geometry, the inlet and outlet distributor configuration, and the detailed stream geometry. A detailed analysis of the Pareto-set gives a good overview of possible solutions, and the optimization routine can automatically find a feasible design with a reasonable tradeoff between the objectives. All elements of the framework are implemented in open source software. A highlight of this research is that a very comprehensive and detailed simulation model is employed in the optimization framework. Thus, the presented method can be easily adjusted to fit the needs of other engineering tasks.

Currently, various industrial processes are carried out in fluidized bed reactors. Knowing its internal dynamics is fundamental for the intensification of these processes. This work assesses the motion of fluidized calcium alginate spheres under the influence of an upward fluid flow within a 1.2 m high and 0.1 m inner diameter acrylic column. The liquid–solid fluidized bed was compared with a gas–liquid–solid fluidized bed operation mode in terms of mixing behavior. The radioactive particle tracking technique is a proper methodology to study the internal dynamics of these kinds of equipment. Data gathered were analyzed with Shannon entropy as a dynamic mixing measure. Mixing times were found to be between 1 and 2.5 seconds for both fluidization modes. The liquid–solid fluidized bed presents a rather smooth mixing time profile along the column. On the other hand, the gas–liquid–solid fluidized bed showed high sensitivity of entropy production with height, reaching a sharp tendency break at the second quartile of the column. The Glansdorff–Prigogine stability measure can accurately capture flow regime transitions of the gas–liquid–solid fluidized bed, allowing it to be used to construct reliable operative windows for fluidization equipment.

The unique properties of graphene oxide (GO) have attracted the attention of the research community and cost-effective routes for its production are studied. The type and percentage of the oxygen groups that decorate a GO sheet are dependent on the synthesis path, and this path specifies the carbon content of the sheet. The chemical reduction of GO results in reduced graphene oxide (rGO) while the removal of the oxygen groups is also achievable with thermal processes (tpGO). This review article introduces the reader to the carbon allotropes, provides information about graphene which is the backbone of GO and focuses on GO synthesis and properties. The last part covers some characterization techniques of GO (XRD, FTIR, AFM, SEM-EDS, N2 porosimetry and UV-Vis) with a view to the fundamental principles of each technique. Some critical aspects arise for GO synthesized and characterized from our group.

Stenting is a common method for treating atherosclerosis. A metal or polymer stent is deployed to open the stenosed artery or vein. After the stent is deployed, the blood flow dynamics influence the mechanics by compressing and expanding the structure. If the stent does not respond properly to the resulting stress, vascular wall injury or re-stenosis can occur. In this work, a Discrete Multiphysics modelling approach is used to study the mechanical deformation of the coronary stent and its relationship with the blood flow dynamics. The major parameters responsible for deforming the stent are sorted in terms of dimensionless numbers and a relationship between the elastic forces in the stent and pressure forces in the fluid is established. The blood flow and the stiffness of the stent material contribute significantly to the stent deformation and affect its rate of deformation. The stress distribution in the stent is not uniform with the higher stresses occurring at the nodes of the structure. From the relationship (correlation) between the elastic force and the pressure force, depending on the type of material used for the stent, the model can be used to predict whether the stent is at risk of fracture or not after deployment.

Microscale photobioreactors for microalgae growth represent an interesting technology for fast data production and biomass characterization; however, the small scale poses severe monitoring challenges, as traditional methods cannot be used. Non-invasive techniques are therefore needed to quantify biomass concentration and other culture properties, for example, pigment composition. To this purpose, a soft sensing approach based on multivariate image regression is proposed to exploit RGB images and/or PAM-imaging chlorophyll fluorescence. Different PLS (Partial Least Squares) regression models are used to estimate: (a) biomass concentration from the features extracted by RGB indices and/or PAM-imaging chlorophyll fluorescence measurements; and (b) Chlorophyll a content per cell from the features extracted by RGB indices and biomass concentration measurements. Every single model is aimed at characterizing the microalgae culture at different light intensities during batch growth. Results show that the proposed monitoring approach is as accurate as traditional measurement approaches and may represent a promising methodology for fast and inexpensive monitoring of microscale photobioreactors.

Group contribution (GC) methods to predict thermochemical properties are of eminent importance to process design. Compared to previous works, we present an improved group contribution parametrization for the heat of formation of organic molecules exhibiting chemical accuracy, i.e., a maximum 1 kcal/mol (4.2 kJ/mol) difference between the experiment and model, while, at the same time, minimizing the number of parameters. The latter is extremely important as too many parameters lead to overfitting and, therewith, to more or less serious incorrect predictions for molecules that were not within the data set used for parametrization. Moreover, it was found to be important to explicitly account for common chemical knowledge, e.g., geminal effects or ring strain. The group-related parameters were determined step-wise: first, alkanes only, and then only one additional group in the next class of molecules. This ensures unique and optimal parameter values for each chemical group. All data will be made available, enabling other researchers to extend the set to other classes of molecules.

Currently, we assist the emergence of sensors and low-cost information and communication technologies applied to food products, in order to improve food safety and quality along the food chain. Thus, it is relevant to implement predictive mathematical modeling tools in order to predict changes in the food quality and allow decision-making for expiration dates. To perform that, the Baranyi and Roberts model and the online tool Combined Database for Predictive Microbiology (Combase) were used to determine the factors that define the growth of different bacteria. These factors applied to the equation that determines the maximum specific growth rate establish a relation between the bacterial growth and the intrinsic and extrinsic factors that define the bacteria environment. These models may be programmed in low-cost wireless biochemical sensor devices applied to packaging and food supply chains to promote food safety and quality through real time traceability.

This work added semi-Lagrangian convected air particles to the Intermediate Complexity Atmospheric Research (ICAR) model. The ICAR model is a simplified atmospheric model using quasi-dynamical downscaling to gain performance over more traditional atmospheric models. The ICAR model uses Fortran coarrays to split the domain amongst images and handle the halo region communication of the image’s boundary regions. The newly implemented convected air particles use trilinear interpolation to compute initial properties from the Eulerian domain and calculate humidity and buoyancy forces as the model runs. This paper investigated the performance cost and scaling attributes of executing unsaturated and saturated air particles versus the original particle-less model. An in-depth analysis was done on the communication patterns and performance of the semi-Lagrangian air particles, as well as the performance cost of a variety of initial conditions such as wind speed and saturation mixing ratios. This study found that given a linear increase in the number of particles communicated, there is an initial decrease in performance, but that it then levels out, indicating that over the runtime of the model, there is an initial cost of particle communication, but that the computational benefits quickly offset it. The study provided insight into the number of processors required to amortize the additional computational cost of the air particles.

In this study, we aimed to enhance the catalytic activity of perovskite catalysts and elucidate their catalytic behavior in the oxidative coupling of methane (OCM), using alkali-added LaAlO3 perovskite catalysts. We prepared LaAlO3_XY (X = Li, Na, K, Y = mol %) catalysts and applied them to the OCM reaction. The results showed that the alkali-added catalysts’ activities were promoted compared to the LaAlO3 catalyst. In this reaction, ethane was first synthesized through the dimerization of methyl radicals, which were produced from the reaction of methane and oxygen vacancy in the perovskite catalysts. The high ethylene selectivity of the alkali-added catalysts originated from their abundance of electrophilic lattice oxygen species, facilitating the selective formation of C2 hydrocarbons from ethane. The high COx (carbon monoxide and carbon dioxide) selectivity of the LaAlO3 catalyst originated from its abundance of nucleophilic lattice oxygen species, favoring the selective production of COx from ethane. We concluded that electrophilic lattice oxygen species play a significant role in producing ethylene. We obtained that alkali-adding could be an effective method for improving the catalytic activity of perovskite catalysts in the OCM reaction.

Properties of emulsions such as stability, viscosity or color can be influenced by the droplet size distribution. High-pressure homogenization (HPH) is the method of choice for emulsions with a low to medium viscosity with a target mean droplet diameter of less than 1 µm. During HPH, the droplets of the emulsion are exposed to shear and extensional stresses, which cause them to break up. Ongoing work is focused on better understanding the mechanisms of droplet breakup and relevant parameters. Since the gap dimensions of the disruption unit (e.g., flat valve or orifice) are small (usually below 500 µm) and the droplet breakup also takes place on small spatial and time scales, the resolution limit of current measuring systems is reached. In addition, the high velocities impede time resolved measurements. Therefore, a five-fold and fifty-fold magnified optically accessible coaxial orifice were used in this study while maintaining the dimensionless numbers characteristic for the droplet breakup (Reynolds and Weber number, viscosity and density ratio). Three matching material systems are presented. In order to verify their similarity, the local velocity profiles of the emerging free jet were measured using both a microparticle image velocimetry (µ-PIV) and a particle image velocimetry (PIV) system. Furthermore, the influence of the outlet geometry on the velocity profiles is investigated. Similar relationships were found on all investigated scales. The areas with the highest velocity fluctuations were identified where droplets are exposed to the highest turbulent forces. The Reynolds number had no influence on the normalized velocity fluctuation field. The confinement of the jet started to influence the velocity field if the outlet channel diameter is smaller than 10 times the diameter of the orifice. In conclusion, the scaling approach offers advantages to study very fast processes on very small spatial scales in detail. The presented scaling approach also offers chances in the optimization of the geometry of the disruption unit. However, the results also show challenges of each size scale, which can come from the respective production, measurement technology or experimental design. Depending on the problem to be investigated, we recommend conducting experimental studies at different scales.