Artificial Intelligence in Process Engineering

In recent years, the field of Artificial Intelligence (AI) is experiencing a boom, caused by recent breakthroughs in computing power, AI techniques, and software architectures. Among the many fields being impacted by this paradigm shift, process engineering has experienced the benefits caused by AI. However, the published methods and applications in process engineering are diverse, and there is still much unexploited potential. Herein, the goal of providing a systematic overview of the current state of AI and its applications in process engineering is discussed. Current applications are described and classified according to a broader systematic. Current techniques, types of AI as well as pre- and postprocessing will be examined similarly and assigned to the previously discussed applications. Given the importance of mechanistic models in process engineering as opposed to the pure black box nature of most of AI, reverse engineering strategies as well as hybrid modeling will be highlighted. Furthermore, a holistic strategy will be formulated for the application of the current state of AI in process engineering

Viscosity Model for Nanoparticulate Suspensions Based on Surface Interactions

In this paper, a widely mechanistic model was developed to depict the rheological behaviour of nanoparticulate suspensions with solids contents up to 20 wt.%, based on the increase in shear stress caused by surface interaction forces among particles. The rheological behaviour is connected to drag forces arising from an altered particle movement with respect to the surrounding fluid. In order to represent this relationship and to model the viscosity, a hybrid modelling approach was followed, in which mechanistic relationships were paired with heuristic expressions. A genetic algorithm was utilized during model development, by enabling the algorithm to choose among several hard-to-assess model options. By the combination of the newly developed model with existing models for the various physical phenomena affecting viscosity, it can be applied to model the viscosity over a broad range of solids contents, shear rates, temperatures and particle sizes. Due to its mechanistic nature, the model even allows an extrapolation beyond the limits of the data points used for calibration, allowing a prediction of the viscosity in this area. Only two parameters are required for this purpose. Experimental data of an epoxy resin filled with boehmite nanoparticles were used for calibration and comparison with modelled values

The Depth-Dependent Mechanical Behavior of Anisotropic Native and Cross-Linked HheG Enzyme Crystals

Enzymes are able to catalyze various specific reactions under mild conditions and can, therefore, be applied in industrial processes. To ensure process profitability, the enzymes must be reusable while ensuring their enzymatic activity. To improve the processability and immobilization of the biocatalyst, the enzymes can be, e.g., crystallized, and the resulting crystals can be cross-linked. These mechanically stable and catalytically active particles are called CLECs (cross-linked enzyme crystals). In this study, the influence of cross-linking on the mechanical and catalytic properties of the halohydrin dehalogenase (HheG) crystals was investigated using the nanoindentation technique. Considering the viscoelastic behavior of protein crystals, a mechanical investigation was performed at different indentation rates. In addition to the hardness, for the first time, depth-dependent fractions of elastic and plastic deformation energies were determined for enzyme crystals. The results showed that the hardness of HheG enzyme crystals are indentation-rate-insensitive and decrease with increases in penetration depth. Our investigation of the fraction of plastic deformation energy indicated anisotropic crystal behavior and higher irreversible deformation for prismatic crystal faces. Due to cross-linking, the fraction of elastic energy of anisotropic crystal faces increased from 8% for basal faces to 68% for prismatic crystal faces. This study demonstrates that mechanically enhanced CLECs have good catalytic activity and are, therefore, suitable for industrial use

Effect of Different Shear Rates on Particle Microstructure of Cementitious Materials in a Wide Gap Vane-in-cup Rheometer

Rheological properties of cementitious suspensions are affected not only by their mixture composition but also by process-related factors such as shear history. To enable a model-based description, investigations were carried out on the effect of shear history (shear rate variation over time) on the cement paste agglomeration state. Therefore, a Focused Beam Reflectance Measurement (FBRM) system and a wide gap rheometer were coupled to study the relation between shear history and in-situ chord length distribution simultaneously, indicating particle agglomeration. Hence, the effect of average shear rates (resulting from the applied shear profile), as well as shear rate distribution within the gap (local shear rates) on the particle agglomeration state have been investigated. The rheological properties of cement paste were evaluated with the Reiner-Riwlin approach. Furthermore, the agglomeration state of the particles was compared for different average shear rates and local shear rates at various positions of the FBRM probe. The results show that the median chord length increases in all positions when the average shear rate is decreased, indicating increasing particle agglomeration. Moreover, due to variable local shear rates at different FBRM probe positions, different agglomeration states are observed, resulting from two factors, shear rate dependent particle agglomeration and shear-induced particle migration

Grinding Media Motion and Collisions in Different Zones of Stirred Media Mills

Product fineness during grinding in stirred media mills is mainly influenced by the specific energy input, the stress energy transferred by the colliding grinding media and the stress frequency. The stress energy from grinding media collisions is heterogeneously distributed in stirred media mills. Herein, in order to characterize the stress energy distribution and the local grinding media collision frequencies, the grinding media motion was calculated using discrete element method (DEM) simulations coupled with computational fluid dynamics (CFD). The local grinding media concentration, velocity profiles, grinding media collisions and stress energies were compared for varied total grinding media fillings and stirrer speeds. It was confirmed that the normalized grinding media velocity profile can be used to divide the grinding chamber into four types of zones that allow the modeling of the stress energy distribution. However, the collision frequency showed very different distributions for varied stirrer velocities and grinding media fillings

Structure-Properties Correlation of Cross-Linked Penicillin G Acylase Crystals

In biocatalytic processes, the use of free enzymes is often limited due to the lack of long-term stability and reusability. To counteract this, enzymes can be crystallized and then immobilized, generating cross-linked enzyme crystals (CLECs). As mechanical stability and activity of CLECs are crucial, different penicillin G acylases (PGAs) from Gram-positive organisms have proven to be promising candidates for industrial production of new semisynthetic antibiotics, which can be crystallized and cross-linked to characterize the resulting CLECs regarding their mechanical and catalytic properties. The greatest hardness and Young’s modulus determined by indentation with an atomic force microscope were observed for CLECs of Bacillus species FJAT-PGA CLECs (26 MPa/1450 MPa), followed by BmPGA (Priestia megaterium PGA, 23 MPa/1170 MPa) and BtPGA CLECs (Bacillus thermotolerans PGA, 11 MPa/614 MPa). In addition, FJAT- and BtPGA CLECs showed up to 20-fold higher volumetric activities compared to BmPGA CLECs. Correlation to structural characteristics indicated that a high solvent content and low number of cross-linking residues might lead to reduced stability. Furthermore, activity seems to be restricted by small water channels due to severe diffusion limitations. To the best of our knowledge, we show for the first time in this study that the entire process chain for the characterization of diverse industrially relevant enzymes can be performed at the microliter scale to discover the most important relationships and limitation

Biological Surface Coating and Molting Inhibition as Mechanisms of TiO2 Nanoparticle Toxicity in Daphnia magna

The production and use of nanoparticles (NP) has steadily increased within the last decade; however, knowledge about risks of NP to human health and ecosystems is still scarce. Common knowledge concerning NP effects on freshwater organisms is largely limited to standard short-term (≤48 h) toxicity tests, which lack both NP fate characterization and an understanding of the mechanisms underlying toxicity. Employing slightly longer exposure times (72 to 96 h), we found that suspensions of nanosized (∼100 nm initial mean diameter) titanium dioxide (nTiO2) led to toxicity in Daphnia magna at nominal concentrations of 3.8 (72-h EC50) and 0.73 mg/L (96-h EC50). However, nTiO2 disappeared quickly from the ISO-medium water phase, resulting in toxicity levels as low as 0.24 mg/L (96-h EC50) based on measured concentrations. Moreover, we showed that nTiO2 (∼100 nm) is significantly more toxic than non-nanosized TiO2 (∼200 nm) prepared from the same stock suspension. Most importantly, we hypothesized a mechanistic chain of events for nTiO2 toxicity in D. magna that involves the coating of the organism surface with nTiO2 combined with a molting disruption. Neonate D. magna (≤6 h) exposed to 2 mg/L nTiO2 exhibited a “biological surface coating” that disappeared within 36 h, during which the first molting was successfully managed by 100% of the exposed organisms. Continued exposure up to 96 h led to a renewed formation of the surface coating and significantly reduced the molting rate to 10%, resulting in 90% mortality. Because coating of aquatic organisms by manmade NP might be ubiquitous in nature, this form of physical NP toxicity might result in widespread negative impacts on environmental health

Quantification and modeling of macroparticle-induced mechanical stress for varying shake flask cultivation conditions

In biotechnological processes, filamentous microorganisms are known for their broad product spectrum and complex cellular morphology. Product formation and cellular morphology are often closely linked, requiring a well-defined level of mechanical stress to achieve high product concentrations. Macroparticles were added to shake flask cultures of the filamentous actinomycete Lentzea aerocolonigenes to find these optimal cultivation conditions. However, there is currently no model concept for the dependence of the strength and frequency of the bead-induced stress on the process parameters. Therefore, shake flask simulations were performed for combinations of bead size, bead concentration, bead density and shaking frequency. Contact analysis showed that the highest shear stresses were caused by bead-bottom contacts. Based on this, a newly generated characteristic parameter, the stress area ratio (SAR), was defined, which relates the bead wall shear and normal stresses to the total shear area. Comparison of the SAR with previous cultivation results revealed an optimum pattern for product concentration and mean product-to-biomass related yield coefficient. Thus, this model is a suitable tool for future optimization, comparison and scaling up of shear-sensitive microorganism cultivation. Finally, the simulation results were validated using high-speed recordings of the bead motion on the bottom of the shake flask