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Open AccessFeature PaperEditor’s ChoiceArticle
Role of Microalgae in the Recovery of Nutrients from Pig Manure
Processes 2021, 9(2), 203; https://doi.org/10.3390/pr9020203 - 21 Jan 2021
Abstract
Animal production inevitably causes the emission of greenhouse gases and the generation of large amounts of slurry, both representing a serious environmental problem. Photosynthetic microorganisms such as microalgae and cyanobacteria have been proposed as alternative strategies to bioremediate agricultural waste while consuming carbon [...] Read more.
Animal production inevitably causes the emission of greenhouse gases and the generation of large amounts of slurry, both representing a serious environmental problem. Photosynthetic microorganisms such as microalgae and cyanobacteria have been proposed as alternative strategies to bioremediate agricultural waste while consuming carbon dioxide and producing valuable biomass. The current study assessed the potential of the microalga Scenedesmus sp. to remove nutrients from piggery wastewater (PWW) and the influence of the microalga on the microbial consortia. Maximum N-NH4+ consumption was 55.3 ± 3.7 mg·L−1·day−1 while P-PO43− removal rates were in the range 0.1–1.9 mg·L−1·day−1. N-NH4+ removal was partially caused by the action of nitrifying bacteria, which led to the production of N-NO3. N-NO3 production values where lower when microalgae were more active. This work demonstrated that the photosynthetic activity of microalgae allows us to increase nutrient removal rates from PWW and to reduce the coliform bacterial load of the effluent, minimising both their environmental impact and health risks. Microalgae assimilated part of the N-NH4+ present in the media to produce biomass and did not to convert it into N-NO3 as in traditional processes. Full article
(This article belongs to the Special Issue Extraction, Exploitation and Application of Algae Biomass)
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Open AccessFeature PaperEditor’s ChoiceArticle
Population-Based Parameter Identification for Dynamical Models of Biological Networks with an Application to Saccharomyces cerevisiae
Processes 2021, 9(1), 98; https://doi.org/10.3390/pr9010098 - 05 Jan 2021
Abstract
One of the central elements in systems biology is the interaction between mathematical modeling and measured quantities. Typically, biological phenomena are represented as dynamical systems, and they are further analyzed and comprehended by identifying model parameters using experimental data. However, all model parameters [...] Read more.
One of the central elements in systems biology is the interaction between mathematical modeling and measured quantities. Typically, biological phenomena are represented as dynamical systems, and they are further analyzed and comprehended by identifying model parameters using experimental data. However, all model parameters cannot be found by gradient-based optimization methods by fitting the model to the experimental data due to the non-differentiable character of the problem. Here, we present POPI4SB, a Python-based framework for population-based parameter identification of dynamic models in systems biology. The code is built on top of PySCeS that provides an engine to run dynamic simulations. The idea behind the methodology is to provide a set of derivative-free optimization methods that utilize a population of candidate solutions to find a better solution iteratively. Additionally, we propose two surrogate-assisted population-based methods, namely, a combination of a k-nearest-neighbor regressor with the Reversible Differential Evolution and the Evolution of Distribution Algorithm, that speeds up convergence. We present the optimization framework on the example of the well-studied glycolytic pathway in Saccharomyces cerevisiae. Full article
(This article belongs to the Special Issue Bioinformatics Applications Based On Machine Learning)
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Open AccessFeature PaperEditor’s ChoiceArticle
Encapsulation of Lactoferrin for Sustained Release Using Particles from Gas-Saturated Solutions
Processes 2021, 9(1), 73; https://doi.org/10.3390/pr9010073 - 31 Dec 2020
Abstract
The particles from gas saturated solutions (PGSS) process were performed to encapsulate lactofer-rin, an iron-binding milk glycoprotein, using supercritical carbon dioxide (scCO2). A natural en-teric polymer, shellac, was used as a coating material of lactoferrin carried out by the PGSS pro-cess. [...] Read more.
The particles from gas saturated solutions (PGSS) process were performed to encapsulate lactofer-rin, an iron-binding milk glycoprotein, using supercritical carbon dioxide (scCO2). A natural en-teric polymer, shellac, was used as a coating material of lactoferrin carried out by the PGSS pro-cess. Conditions were optimized by applying different temperatures (20–50 °C) and pressures (8–10 MPa) and the particles were evaluated for particle shape and size, lactoferrin encapsulation ef-ficiency, Fourier transform infrared (FTIR) spectroscopy to confirm lactoferrin entrapment and in vitro dissolution studies at different pH values. Particles with an average diameter of 75.5 ± 7 μm were produced with encapsulation efficiency up to 71 ± 2%. Furthermore, particles that showed high stability in low pH (pH 1.2) and a sustained release over time (t2h = 75%) in higher pH (pH 7.4) suggested an effective encapsulation process for the protection of lactoferrin from gastric di-gestion. Full article
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Open AccessFeature PaperEditor’s ChoiceArticle
Biomass-Derived Nitrogen Functionalized Carbon Nanodots and Their Anti-Biofouling Properties
Processes 2021, 9(1), 61; https://doi.org/10.3390/pr9010061 - 29 Dec 2020
Cited by 1
Abstract
The prevalence of the antibiotic resistant bacteria remains a global issue. Cheap, sustainable and multifunctional antibacterial membranes are at the forefront of filtrating materials capable of treating multiple flow streams, such as water cleansing treatments. Carbon nanomaterials are particularly interesting objects shown to [...] Read more.
The prevalence of the antibiotic resistant bacteria remains a global issue. Cheap, sustainable and multifunctional antibacterial membranes are at the forefront of filtrating materials capable of treating multiple flow streams, such as water cleansing treatments. Carbon nanomaterials are particularly interesting objects shown to enhance antibacterial properties of composite materials. In this article, amino-functionalized, photoluminescent carbon nanodots (CNDs) were synthesized from chitosan by bottom-up approach via simple and green hydrothermal carbonization. A chemical model for the CNDs formation during hydrothermal treatment of chitosan is proposed. The use of urea as an additional nitrogen source leads to the consumption of hydroxyl groups of chitosan and higher nitrogen doping level as pyridinic and pyrrolic N-bonding configurations in the final carbonaceous composition. These functionalized carbon nanodots that consist of carbon core and various surface functional groups were used to modify the commercially available membranes in order to enhance their anti-biofouling properties and add possible functionalities, including fluorescent labelling. Incorporation of CNDs to membranes increased their hydrophilicity, surface charge without compromising membranes integrity, thereby increasing the factors affecting bacterial wall disruption. Membranes modified with CNDs effectively stopped the growth of two Gram-negative bacterial colonies: Klebsiella oxytoca (K. oxytoca) and Pseudomonas aeruginosa (P. aeruginosa). Full article
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Open AccessFeature PaperEditor’s ChoiceArticle
Heat Transfer and Rheological Behavior of Fumed Silica Nanofluids
Processes 2020, 8(12), 1535; https://doi.org/10.3390/pr8121535 - 25 Nov 2020
Cited by 1
Abstract
The addition of nanoparticles to liquid media can improve thermomechanical properties of dispersants. This ability gives rise to the development of multiple applications of nanofluids (NF) in branches so different as electronic and photonic devices or cosmetic industry. Logically, these applications require a [...] Read more.
The addition of nanoparticles to liquid media can improve thermomechanical properties of dispersants. This ability gives rise to the development of multiple applications of nanofluids (NF) in branches so different as electronic and photonic devices or cosmetic industry. Logically, these applications require a good control of heat transfer and flow properties. Moreover, if we consider the necessity to optimize industrial processes in which NF take part, it is necessary to obtain possible relationships between both physical mechanisms. Specifically, in this work, a study about thermal conductivity and rheological behavior of fumed silica suspensions in polypropylene glycol (PPG400) and polyethylene glycol (PEG200) was performed. The study of these two suspensions is interesting because the flow behaviors are very dissimilar (while the fumed silica in PEG200 suspension is viscoplastic, the fumed silica in PPG400 suspension shows shear-thickening behavior between two shear-thinning regions), despite the addition of fumed silica producing similar enhancement of the relative thermal conductivity in both liquid phases. The more outstanding contribution of this work lies in the combination of rheological and conductivity measurements to deepen in the understanding of the heat transfer phenomenon in NF. The combination of rheological together with thermal conductivity measurements have permitted establishing the mechanisms of liquid layering and aggregate formation as the more relevant in the heat transfer of these silica fumed suspensions. Full article
(This article belongs to the Special Issue Rheological Study of Nanofluids)
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Open AccessFeature PaperEditor’s ChoiceArticle
Enhancing the Thermal Performance of Slender Packed Beds through Internal Heat Fins
Processes 2020, 8(12), 1528; https://doi.org/10.3390/pr8121528 - 24 Nov 2020
Abstract
Slender packed beds are widely used in the chemical and process industry for heterogeneous catalytic reactions in tube-bundle reactors. Under safety and reaction engineering aspects, good radial heat transfer is of outstanding importance. However, because of local wall effects, the radial heat transport [...] Read more.
Slender packed beds are widely used in the chemical and process industry for heterogeneous catalytic reactions in tube-bundle reactors. Under safety and reaction engineering aspects, good radial heat transfer is of outstanding importance. However, because of local wall effects, the radial heat transport in the vicinity of the reactor wall is hindered. Particle-resolved computational fluid dynamics (CFD) is used to investigate the impact of internal heat fins on the near wall radial heat transport in slender packed beds filled with spherical particles. The simulation results are validated against experimental measurements in terms of particle count and pressure drop. The simulation results show that internal heat fins increase the conductive portion of the radial heat transport close to the reactor wall, leading to an overall increased thermal performance of the system. In a wide flow range (100<Rep<1000), an increase of up to 35% in wall heat transfer coefficient and almost 90% in effective radial thermal conductivity is observed, respectively. Full article
(This article belongs to the Special Issue Process Intensification in Chemical Reaction Engineering)
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Open AccessEditor’s ChoiceArticle
Microwave-Assisted Pyrolysis of Pine Wood Sawdust Mixed with Activated Carbon for Bio-Oil and Bio-Char Production
Processes 2020, 8(11), 1437; https://doi.org/10.3390/pr8111437 - 10 Nov 2020
Cited by 2
Abstract
Pyrolysis of pine wood sawdust was carried out using microwave-heating technology in the presence of activated carbon (AC). Experimental conditions were of 20 min processing time, 10 wt.% of AC, and a microwave power varying from 100 to 800 W. The results obtained [...] Read more.
Pyrolysis of pine wood sawdust was carried out using microwave-heating technology in the presence of activated carbon (AC). Experimental conditions were of 20 min processing time, 10 wt.% of AC, and a microwave power varying from 100 to 800 W. The results obtained showed that the microwave absorber allowed increasing the bio-oil yield up to 2 folds by reducing the charcoal fraction. The maximum temperature reached was 505 °C at 800 W. The higher heating values (HHV) of the solid residues ranged from 17.6 to 30.3 MJ/kg. The highest HHV was obtained for the sample heated at 800 W with 10 wt.% of AC, which was 33% higher than the non-charged sample heated at the same power. Furthermore, the addition of AC allowed showing the probable catalytic effect of the AC in the charged sample pyrolysis bio-oils. Full article
(This article belongs to the Special Issue Microwave Conversion Techniques Intensification)
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Open AccessFeature PaperEditor’s ChoiceArticle
Linear Analysis of a Continuous Crystallization Process for Enantiomer Separation
Processes 2020, 8(11), 1337; https://doi.org/10.3390/pr8111337 - 23 Oct 2020
Abstract
Continuous preferential crystallization is an innovative approach to the separation of chiral substances. The process considered in this work takes place in a gently agitated fluidized bed located in a tubular crystallizer. The feasibility of the process has been shown in previous work, [...] Read more.
Continuous preferential crystallization is an innovative approach to the separation of chiral substances. The process considered in this work takes place in a gently agitated fluidized bed located in a tubular crystallizer. The feasibility of the process has been shown in previous work, but it also turned out that choosing suitable operation conditions is quite delicate. Hence, a model based process design is desirable. Existing models of the process are rather complicated and require long computational times. In this work, a simple linear dynamic model is suggested, which captures the main properties of the process. The model is distributed in space and in a property coordinate. Using the method of characteristics, a semi-analytical solution of the linear model is derived. As a challenge to the solution, there is a recycle loop in the process that causes a feedback and couples the boundary conditions at different boundaries of the computational domain. In order to deal with this, a numerical scheme is suggested. The semi-analytical solution provides a deeper insight into the process dynamics. A comparison with a more detailed mathematical model of the process and with experiments shows strengths and limitations of the linear model. Full article
(This article belongs to the Special Issue Advanced Methods in Process and Systems Engineering)
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Open AccessFeature PaperEditor’s ChoiceArticle
Real-Time Nanoplasmonic Sensor for IgG Monitoring in Bioproduction
Processes 2020, 8(10), 1302; https://doi.org/10.3390/pr8101302 - 16 Oct 2020
Cited by 1
Abstract
Real-time monitoring of product titers during process development and production of biotherapeutics facilitate implementation of quality-by-design principles and enable rapid bioprocess decision and optimization of the production process. Conventional analytical methods are generally performed offline/at-line and, therefore, are not capable of generating real-time [...] Read more.
Real-time monitoring of product titers during process development and production of biotherapeutics facilitate implementation of quality-by-design principles and enable rapid bioprocess decision and optimization of the production process. Conventional analytical methods are generally performed offline/at-line and, therefore, are not capable of generating real-time data. In this study, a novel fiber optical nanoplasmonic sensor technology was explored for rapid IgG titer measurements. The sensor combines localized surface plasmon resonance transduction and robust single use Protein A-modified sensor chips, housed in a flexible flow cell, for specific IgG detection. The sensor requires small sample volumes (1–150 µL) and shows a reproducibility and sensitivity comparable to Protein G high performance liquid chromatography-ultraviolet (HPLC-UV). The dynamic range of the sensor system can be tuned by varying the sample volume, which enables quantification of IgG samples ranging from 0.0015 to 10 mg/mL, without need for sample dilution. The sensor shows limited interference from the sample matrix and negligible unspecific protein binding. IgG titers can be rapidly determined in samples from filtered unpurified Chinese hamster ovary (CHO) cell cultures and show good correlation with enzyme-linked immunosorbent assay (ELISA). Full article
(This article belongs to the Special Issue Measurement Technologies for up- and Downstream Bioprocessing)
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Open AccessFeature PaperEditor’s ChoiceArticle
Synthesis of Peptide-Immobilized Magnetic Beads, and Peptide Reactivity Assay for Assessing Skin Sensitization Utilizing Chromophore
Processes 2020, 8(10), 1257; https://doi.org/10.3390/pr8101257 - 07 Oct 2020
Abstract
DPRA (direct peptide reactivity assay) and ADRA (amino acid derivative reactivity assay), which are based on the biological events of skin sensitization, were developed as alternatives to the controversial animal experiments. These assays are described in the OECD (Organization for Economic Co-operation and [...] Read more.
DPRA (direct peptide reactivity assay) and ADRA (amino acid derivative reactivity assay), which are based on the biological events of skin sensitization, were developed as alternatives to the controversial animal experiments. These assays are described in the OECD (Organization for Economic Co-operation and Development) guideline, Test No. 442C. Although these assays have been endorsed by the industries and internationally accepted as promising and effective tests for in vitro skin sensitization, they suffer from several drawbacks, such as incompatibility with hydrophobic chemicals and complicated sample processing. Here, we demonstrated a chromophore-based solid phase peptide reaction assay in vitro using peptides immobilized on magnetic beads (C-SPRA-MB). We successfully synthesized lysine (Lys) and cysteine (Cys) immobilized on magnetic microbeads. However, Cys immobilized magnetic microbeads showed gradual decomposition of the magnetic beads due to SH oxidation. Using Lys immobilized magnetic microbeads, we demonstrated the capacity of C-SPRA-MB to predict skin sensitization by measuring free amino groups of the Lys after reaction with test chemicals. First, the free amines on the microbeads were reacted with bromophenol blue (BB). Then, by treatment with a saturated solution of Lys, the bound BBs were released and quantified. C-SPRA-MB provides high-throughput and accurate assays for assessments of chemicals, including with low-potency as skin sensitizers and poor water solubility. C-SPRA-MB may be useful for effective prediction of their skin sensitization potential in the process of compound screening, especially in the case of misclassified by DPRA and ADRA. Thus, C-SPRA-MB can be applied to assessing the sensitization potential of medical, pharmaceutical, cosmetics, and industrial compounds. Full article
(This article belongs to the Special Issue Advances of Peptide Engineering)
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Open AccessFeature PaperEditor’s ChoiceArticle
Characterization and Demulsification of the Oil-Rich Emulsion from the Aqueous Extraction Process of Almond Flour
Processes 2020, 8(10), 1228; https://doi.org/10.3390/pr8101228 - 01 Oct 2020
Abstract
The aqueous extraction process (AEP) allows the concurrent extraction of oil and protein from almond flour without the use of harsh solvents. However, the majority of the oil extracted in the AEP is present in an emulsion that needs to be demulsified for [...] Read more.
The aqueous extraction process (AEP) allows the concurrent extraction of oil and protein from almond flour without the use of harsh solvents. However, the majority of the oil extracted in the AEP is present in an emulsion that needs to be demulsified for subsequent industrial utilization. The effects of scaling-up the AEP of almond flour from 0.7 to 7 L and the efficiency of enzymatic and chemical approaches to demulsify the cream were evaluated. The AEP was carried out at pH 9.0, solids-to-liquid ratio of 1:10, and constant stirring of 120 rpm at 50 °C. Oil extraction yields of 61.9% and protein extraction yields of 66.6% were achieved. At optimum conditions, enzymatic and chemical demulsification strategies led to a sevenfold increase (from 8 to 66%) in the oil recovery compared with the control. However, enzymatic demulsification resulted in significant changes in the physicochemical properties of the cream protein and faster demulsification (29% reduction in the incubation time and a small reduction in the demulsification temperature from 55 to 50 °C) compared with the chemical approach. Reduced cream stability after enzymatic demulsification could be attributed to the hydrolysis of the amandin α-unit and reduced protein hydrophobicity. Moreover, the fatty acid composition of the AEP oil obtained from both demulsification strategies was similar to the hexane extracted oil. Full article
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Open AccessFeature PaperEditor’s ChoiceArticle
Calculating the Binary Tortuosity in DEM-Generated Granular Beds
Processes 2020, 8(9), 1105; https://doi.org/10.3390/pr8091105 - 04 Sep 2020
Cited by 1
Abstract
In this paper, a methodology of calculating the tortuosity in three-dimensional granular beds saved in a form of binary geometry with the application of the A-Star Algorithm and the Path Searching Algorithm is presented. The virtual beds serving as examples are prepared with [...] Read more.
In this paper, a methodology of calculating the tortuosity in three-dimensional granular beds saved in a form of binary geometry with the application of the A-Star Algorithm and the Path Searching Algorithm is presented. The virtual beds serving as examples are prepared with the use of the Discrete Element Method based on data of real, existing samples. The obtained results are compared with the results described in other papers (obtained by the use of the Lattice Boltzmann Method and the Path Tracking Method) as well as with the selected empirical formulas found in the literature. It was stated in the paper that the A-Star Algorithm gives values similar (but always slightly underestimated) to the values obtained via approaches based on the Lattice Boltzmann Method or the Path Tracking Method. In turn, the Path Searching Algorithm gives results in the same value range as popular empirical formulas and additionally it is approximately two times faster than the A-Star Algorithm. Full article
(This article belongs to the Special Issue DEM Simulations and Modelling of Granular Materials)
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Open AccessFeature PaperEditor’s ChoiceArticle
Freeze-Drying with Structured Sublimation Fronts—Visualization with Neutron Imaging
Processes 2020, 8(9), 1091; https://doi.org/10.3390/pr8091091 - 02 Sep 2020
Cited by 3
Abstract
The particular structure of the sublimation front in vacuum freeze-drying of porous media is, in most situations, not accessible at the pore scale. The classical measurement techniques access the process only globally. Knowledge about the structure of the front, however, is necessary for [...] Read more.
The particular structure of the sublimation front in vacuum freeze-drying of porous media is, in most situations, not accessible at the pore scale. The classical measurement techniques access the process only globally. Knowledge about the structure of the front, however, is necessary for prescriptive analysis of freeze-drying, as it dictates not only drying velocity, drying time, and overall energy consumption, but also the material properties after drying. This is especially relevant in situations in which the freeze-drying process is carried out close to the collapse temperature of the product. We, therefore, study the sublimation of ice with neutron tomography and analyze the spatial formation of the dry space using the example of frozen cylindrical maltodextrin with drying parameters at the limit of material collapse. We show that the sublimation front forms unique fractal structures that differ strongly from the usual form of a flat front. Distinct dry fingers covering the sample, in addition to a fractal peripheral sublimation front, were observed. The findings are important for the understanding of freeze-drying processes and will serve as a basis for the development of microscale models of freeze-drying. Full article
(This article belongs to the Special Issue Modern Freeze Drying Design for More Efficient Processes)
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Open AccessFeature PaperEditor’s ChoiceArticle
Heat and Mass Transfer during Lignocellulosic Biomass Torrefaction: Contributions from the Major Components—Cellulose, Hemicellulose, and Lignin
Processes 2020, 8(8), 959; https://doi.org/10.3390/pr8080959 - 09 Aug 2020
Abstract
The torrefaction of three representative types of biomass—bamboo, and Douglas fir and its bark—was carried out in a cylindrical-shaped packed bed reactor under nitrogen flow at 573 K of the reactor wall temperature. As the thermal energy for the torrefaction was supplied from [...] Read more.
The torrefaction of three representative types of biomass—bamboo, and Douglas fir and its bark—was carried out in a cylindrical-shaped packed bed reactor under nitrogen flow at 573 K of the reactor wall temperature. As the thermal energy for the torrefaction was supplied from the top and the side of the bed, the propagation of the temperature profile of the bed is a crucial factor for discussing and improving the torrefaction reactor performance. Therefore, the temperature and gas flow rate (vector) profiles throughout the bed were calculated by model simulation so as to scrutinize this point. The measured temperature at a certain representative location (z = 30 mm and r = 38 mm) of the bed was well reproduced by the simulation. The volume faction of the bed at temperatures higher than 500 K at 75 min was 0.89, 0.85, and 0.99 for bamboo, and Douglas fir and its bark, respectively. It was found that the effective thermal conductivity is the determining factor for this difference. The heat of the reactions was found to be insignificant. Full article
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Open AccessFeature PaperEditor’s ChoiceArticle
Hydrogenation of Trans,Trans-Muconic Acid to Bio-Adipic Acid: Mechanism Identification and Kinetic Modelling
Processes 2020, 8(8), 929; https://doi.org/10.3390/pr8080929 - 02 Aug 2020
Abstract
The hydrogenation of trans,trans-muconic acid was investigated on a Pt/C 5% (wt) catalyst in a batch slurry reactor at constant hydrogen pressure (4 bar) and temperature (323, 333 and 343 K), with the purpose of developing a kinetic model able to predict [...] Read more.
The hydrogenation of trans,trans-muconic acid was investigated on a Pt/C 5% (wt) catalyst in a batch slurry reactor at constant hydrogen pressure (4 bar) and temperature (323, 333 and 343 K), with the purpose of developing a kinetic model able to predict conversions and product distributions. A dual-site Langmuir–Hinshelwood–Hougen–Watson (LHHW) model with hydrogen dissociation provided good fitting of the experimental data. The model parameters were regressed by robust numerical methods to overcome the computational challenges of the model parameters’ collinearity. Different reaction mechanisms were tested; the best model involved two subsequent hydrogenation steps. The first step yielded from trans,trans-muconic acid a monounsaturated intermediate (trans-2-hexenedioic acid), which was further hydrogenated to adipic acid in the second step. The intermediate was subjected to an equilibrium isomerization with cis-2-hexenedioic acid. The activation energy values and the rate constants were calculated for the reactions, providing the first reference for trans,trans-muconic acid hydrogenation. Full article
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Open AccessEditor’s ChoiceArticle
Using CFD Simulations to Guide the Development of a New Spray Dryer Design
Processes 2020, 8(8), 932; https://doi.org/10.3390/pr8080932 - 02 Aug 2020
Cited by 1
Abstract
A new spray-drying system has been designed to overcome the limitations caused by existing designs. A key feature of the approach has been the systematic use of Computational Fluid Dynamics (CFD) to guide innovation in the design process. An example of an innovation [...] Read more.
A new spray-drying system has been designed to overcome the limitations caused by existing designs. A key feature of the approach has been the systematic use of Computational Fluid Dynamics (CFD) to guide innovation in the design process. An example of an innovation is the development of a box-shaped transitional feature between the bottom of the main drying chamber and the entrance to the secondary chamber. In physical experiments, the box design performed better in all three representative operating conditions, including the current conditions, a higher feed solids concentration (30% solids rather than 8.8%), and a higher inlet drying temperature (230 °C rather than 170 °C). The current conditions showed a 3% increase in yield (solids recovery) while the 30% feed condition improved the yield by 7.5%, and the higher temperature test increased the yield by 13.5%. Statistical analysis showed that there were significant reductions in the wall flux at the high solids feed concentration. The observed deposition in the box was primarily from the predicted particle impacts by an inertial deposition process on the base of the box, which underwent little degradation due to lower temperatures. There is therefore evidence that the box design is a better design alternative under all operating conditions compared with other traditional designs. Full article
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Open AccessFeature PaperEditor’s ChoiceArticle
Compartment Model of Mixing in a Bubble Trap and Its Impact on Chromatographic Separations
Processes 2020, 8(7), 780; https://doi.org/10.3390/pr8070780 - 03 Jul 2020
Cited by 1
Abstract
Chromatography equipment includes hold-up volumes that are external to the packed bed and usually not considered in the development of chromatography models. These volumes can substantially contribute to band-broadening in the system and deteriorate the predicted performance. We selected a bubble trap of [...] Read more.
Chromatography equipment includes hold-up volumes that are external to the packed bed and usually not considered in the development of chromatography models. These volumes can substantially contribute to band-broadening in the system and deteriorate the predicted performance. We selected a bubble trap of a pilot scale chromatography system as an example for a hold-up volume with a non-standard mixing behavior. In a worst-case scenario, the bubble trap is not properly flushed before elution, thus causing the significant band-broadening of the elution peak. We showed that the mixing of buffers with different densities in the bubble trap device can be accurately modeled using a simple compartment model. The model was calibrated at a wide range of flow rates and salt concentrations. The simulations were performed using the open-source software CADET, and all scripts and data are published with this manuscript. The results illustrate the importance of including external holdup volumes in chromatography modeling. The band-broadening effect of tubing, pumps, valves, detectors, frits, or any other zones with non-standard mixing behavior can be considered in very similar ways. Full article
(This article belongs to the Special Issue Redesign Processes in the Age of the Fourth Industrial Revolution)
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Open AccessEditor’s ChoiceArticle
Plasma Catalytic Conversion of CH4 to Alkanes, Olefins and H2 in a Packed Bed DBD Reactor
Processes 2020, 8(7), 774; https://doi.org/10.3390/pr8070774 - 01 Jul 2020
Abstract
Methane is activated at ambient conditions in a dielectric barrier discharge (DBD) plasma reactor packed with Pd/γ-alumina catalyst containing different loadings of Pd (0.5, 1, 5 wt%). Results indicate that the presence of Pd on γ-alumina substantially abates the formation of deposits, leads [...] Read more.
Methane is activated at ambient conditions in a dielectric barrier discharge (DBD) plasma reactor packed with Pd/γ-alumina catalyst containing different loadings of Pd (0.5, 1, 5 wt%). Results indicate that the presence of Pd on γ-alumina substantially abates the formation of deposits, leads to a notable increase in the production of alkanes and olefins and additionally improves the energy efficiency compared to those obtained for the non-packed reactor and the bare γ-alumina packed reactor. A low amount of Pd (0.5 and 1 wt%) favors achieving a higher production of olefins (mainly C2H4 and C3H6) and a higher yield of H2. Increasing Pd loading to 5 wt% promotes the interaction of H2 and olefins, which consequently intensifies the successive hydrogenation of unsaturated compounds, thus incurring a higher production of alkanes (mainly C2H6 and C3H8). The substantial abatement of the deposits is ascribed to the role of Palladium in moderating the strength of the electric and shifting the reaction pathways, in the way that hydrogenation reactions of deposits’ precursors become faster than their deposition on the catalyst. Full article
(This article belongs to the Special Issue Advances in Methane and CO2 Activation and Conversion)
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Open AccessFeature PaperEditor’s ChoiceArticle
Mechanism, Thermodynamics and Kinetics of Rutile Leaching Process by Sulfuric Acid Reactions
Processes 2020, 8(6), 640; https://doi.org/10.3390/pr8060640 - 27 May 2020
Cited by 3
Abstract
Rutile decomposition by sulfuric acid, including the formation of two salts, Ti(SO4)2/TiOSO4, is thermodynamically modelled. It is shown that TiO2 can spontaneously dissolve in H2SO4 solutions. However, titania is considered as an inert [...] Read more.
Rutile decomposition by sulfuric acid, including the formation of two salts, Ti(SO4)2/TiOSO4, is thermodynamically modelled. It is shown that TiO2 can spontaneously dissolve in H2SO4 solutions. However, titania is considered as an inert (ballast) phase component of titanium-containing raw materials due to the decelerated separate nature of such chemical transformations. It is concluded that the hampered related kinetics of dissolution can be attributed to the lability of Ti(IV) cations/the specific engineered features of the hierarchical crystalline structure. It is suggested that the breaking of Ti–O–Ti bonds without additional mechanical strains in crystal lattice geometry becomes more advantageous when smaller negative anions/fluoride ions can be used. The analysis of sulfate-fluoride extraction leaching of titanium confirmed that a decrease in the Gibbs energy in the presence of F occurs. It is indicated by kinetic research studies that the addition of corrosive sodium reagent (NaF) reduces the activation by 45 kJ/mol, which results in intensification. A mechanism is proposed for the interactions involving the Ti–O–Ti cleavage on the surface/the H2SO4-induced Ti dioxide degradation on the sites of defects. Moreover, F acts as a homogeneous/heterogeneous bifunctional catalyst. Full article
(This article belongs to the Special Issue Advances in Methane and CO2 Activation and Conversion)
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Open AccessFeature PaperEditor’s ChoiceArticle
TLC-Densitometric Determination of Five Coxibs in Pharmaceutical Preparations
Processes 2020, 8(5), 620; https://doi.org/10.3390/pr8050620 - 22 May 2020
Abstract
A class of drugs called coxibs (COX-2 inhibitors) were created to help relieve pain and inflammation of osteoarthritis and rheumatoid arthritis with the lowest amount of side effects possible. The presented paper describes a new developed, optimized and validated thin layer chromatographic (TLC)-densitometric [...] Read more.
A class of drugs called coxibs (COX-2 inhibitors) were created to help relieve pain and inflammation of osteoarthritis and rheumatoid arthritis with the lowest amount of side effects possible. The presented paper describes a new developed, optimized and validated thin layer chromatographic (TLC)-densitometric procedure for the simultaneous assay of five coxibs: celecoxib, etoricoxib, firecoxib, rofecoxib and cimicoxib. Chromatographic separation was conducted on HPTLC F254 silica gel chromatographic plates as a stationary phase using chloroform–acetone–toluene (12:5:2, v/v/v) as a mobile phase. Densitometric detection was carried out at two wavelengths of 254 and 290 nm. The method was tested according to ICH guidelines for linearity, recovery and specificity. The presented method was linear in a wide range of concentrations for all analyzed compounds, with correlation coefficients greater than 0.99. The method is specific, precise (%RSD < 1) and accurate (more than 95%, %RSD < 2). Low-cost, simple and rapid, it can be used in laboratories for drug monitoring and quality control. Full article
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Open AccessFeature PaperEditor’s ChoiceArticle
Catalytic Aquathermolysis of Boca de Jaruco Heavy Oil with Nickel-Based Oil-Soluble Catalyst
Processes 2020, 8(5), 532; https://doi.org/10.3390/pr8050532 - 01 May 2020
Cited by 7
Abstract
This paper investigates aquathermolysis of heavy oil in carbonate reservoir rocks from Boca de Jaruco, which is developed by the cyclic steam stimulation method. The nickel-based catalyst precursor was introduced in order to intensify the conversion processes of heavy oil components. The active [...] Read more.
This paper investigates aquathermolysis of heavy oil in carbonate reservoir rocks from Boca de Jaruco, which is developed by the cyclic steam stimulation method. The nickel-based catalyst precursor was introduced in order to intensify the conversion processes of heavy oil components. The active form of such catalysts—nickel sulfides—are achieved after steam treatment of crude oil at reservoir conditions. The experiments were carried out on a rock sample extracted from the depth of 1900 m. Changes in composition and structure of heavy oil after the conversion were identified using SARA-analysis, Gas Chromatography-Mass Spectroscopy of saturated fractions, FTIR spectroscopy of saturated fractions, and MALDI of resins. It is revealed that catalyst particles provide a reduction in the content of resins and asphaltenes due to the destruction of carbon-heteroatom bonds. Moreover, the destruction of C=Carom. bonds and interactions with aromatic rings are heightened. In contrast, the results of experiments in the absence of catalysts exposed polymerization and condensation of aromatic rings. The most remarkable result to emerge from the thermo-catalytic influence is the irreversible viscosity reduction of produced crude oil enhancing the oil recovery factor. Moreover, the introduction of catalysts increases the gas factor due to additional gas generation as a result of aquathermolysis reactions. The yield of methane gas is significantly high in the experimental runs with oil-saturated rocks rather than crude oil experiments. The gas factor reaches 45 m3/ton. Full article
(This article belongs to the Special Issue Heavy Oils Conversion Processes)
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Open AccessFeature PaperEditor’s ChoiceArticle
Novel Purification Process for Amyloid Beta Peptide(1-40)
Processes 2020, 8(4), 464; https://doi.org/10.3390/pr8040464 - 15 Apr 2020
Cited by 1
Abstract
Amyloid beta peptide (Aβ)-related studies require an adequate supply of purified Aβ peptide. However, Aβ peptides are “difficult sequences” to synthesize chemically, and low yields are common due to aggregation during purification. Here, we demonstrate an easier synthesis, deprotection, reduction, cleavage, and purification [...] Read more.
Amyloid beta peptide (Aβ)-related studies require an adequate supply of purified Aβ peptide. However, Aβ peptides are “difficult sequences” to synthesize chemically, and low yields are common due to aggregation during purification. Here, we demonstrate an easier synthesis, deprotection, reduction, cleavage, and purification process for Aβ(1-40) using standard 9-fluorenylmethyloxycarbonyl (Fmoc)-protected amino acids and solid-phase peptide synthesis (SPPS) resin [HMBA (4-hydroxymethyl benzamide) resin] that provides higher yields of Aβ(1-40) than previous standard protocols. Furthermore, purification requires a similar amount of time as conventional purification processes, although the peptide must be cleaved from the resin immediately prior to purification. The method described herein is not limited to the production of Aβ(1-40), and can be used to synthesize other easily-oxidized and aggregating sequences. Our proposed methodology will contribute to various fields using “difficult sequence” peptides, such as pharmaceutical and materials science, as well as research for the diagnosis and treatment of protein/peptide misfolding diseases. Full article
(This article belongs to the Special Issue Advances of Peptide Engineering)
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Open AccessFeature PaperEditor’s ChoiceArticle
Model-Based Real Time Operation of the Freeze-Drying Process
Processes 2020, 8(3), 325; https://doi.org/10.3390/pr8030325 - 10 Mar 2020
Cited by 3
Abstract
Background: Freeze-drying or lyophilization is a dehydration process employed in high added-value food and biochemical goods. It helps to maintain product organoleptic and nutritional properties. The proper handling of the product temperature during the operation is critical to preserve quality and to reduce [...] Read more.
Background: Freeze-drying or lyophilization is a dehydration process employed in high added-value food and biochemical goods. It helps to maintain product organoleptic and nutritional properties. The proper handling of the product temperature during the operation is critical to preserve quality and to reduce the process duration. Methods: Mathematical models are useful tools that can be used to design optimal policies that minimize production costs while keeping product quality. In this work, we derive an operational mathematical model to describe product quality and stability during the freeze-drying process. Model identification techniques are used to provide the model with predictive capabilities. Then, the model is used to design optimal control policies that minimize process time. Results and conclusion: Experimental measurements suggest splitting the process into two subsystems, product and chamber, to facilitate the calibration task. Both models are successfully validated using experimental data. Optimally designed control profiles are able to reduce the process duration by around 30% as compared with standard policies. The optimization task is introduced into a real time scheme to take into account unexpected process disturbances and model/plant mismatch. The implementation of the real time optimization scheme shows that this approach is able to compensate for such disturbances. Full article
(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing)
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Open AccessFeature PaperEditor’s ChoiceArticle
Biodrying of the Light Fraction from Anaerobic Digestion Pretreatment in Order to Increase the Total Recovery Rate
Processes 2020, 8(3), 276; https://doi.org/10.3390/pr8030276 - 28 Feb 2020
Cited by 3
Abstract
Two pilot-scale tests were carried out to assess if biodrying could be an effective process for the treatment of light fraction produced by an hydromechanical pre-treatment in an anaerobic digestion plant. The trials were performed using two pilot-scale stainless steel cylindrical reactors of [...] Read more.
Two pilot-scale tests were carried out to assess if biodrying could be an effective process for the treatment of light fraction produced by an hydromechanical pre-treatment in an anaerobic digestion plant. The trials were performed using two pilot-scale stainless steel cylindrical reactors of 750 L capacity. Two tests were performed: in Test 1, only the light fraction was used; in Test 2, the light fraction was mixed with a bulking agent composed of garden and pruning waste. In Test 2, the highest temperature (71 °C) in a short time (8 days) was reached. An average water content reduction of 78% in Test 1 and 61% in Test 2 was measured, leading to similar reductions of weight (47–48%) and volume (27–29%). A high biological stability was measured on the final light fraction samples collected from both the tests. Furthermore, the lower heating value obtained after the biodrying treatment complies with the quality specification of the European standard on refuse-derived fuels. Full article
(This article belongs to the Special Issue Anaerobic Digestion Processes)
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Open AccessFeature PaperEditor’s ChoiceArticle
Oxidative Coupling of Methane in Membrane Reactors; A Techno-Economic Assessment
Processes 2020, 8(3), 274; https://doi.org/10.3390/pr8030274 - 27 Feb 2020
Cited by 6
Abstract
Oxidative coupling of methane (OCM) is a process to directly convert methane into ethylene. However, its ethylene yield is limited in conventional reactors by the nature of the reaction system. In this work, the integration of different membranes to increase the overall performance [...] Read more.
Oxidative coupling of methane (OCM) is a process to directly convert methane into ethylene. However, its ethylene yield is limited in conventional reactors by the nature of the reaction system. In this work, the integration of different membranes to increase the overall performance of the large-scale oxidative coupling of methane process has been investigated from a techno-economic point of view. A 1D membrane reactor model has been developed, and the results show that the OCM reactor yield is significantly improved when integrating either porous or dense membranes in packed bed reactors. These higher yields have a positive impact on the economics and performance of the downstream separation, resulting in a cost of ethylene production of 595–625 €/tonC2H4 depending on the type of membranes employed, 25–30% lower than the benchmark technology based on oil as feedstock (naphtha steam cracking). Despite the use of a cryogenic separation unit, the porous membranes configuration shows generally better results than dense ones because of the much larger membrane area required in the dense membranes case. In addition, the CO2 emissions of the OCM studied processes are also much lower than the benchmark technology (total CO2 emissions are reduced by 96% in the dense membranes case and by 88% in the porous membranes case, with respect to naphtha steam cracking), where the high direct CO2 emissions have a major impact on the process. However, the scalability and the issues associated with it seem to be the main constraints to the industrial application of the process, since experimental studies of these membrane reactor technologies have been carried out just on a very small scale. Full article
(This article belongs to the Special Issue Catalysis in Membrane Reactors)
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Open AccessFeature PaperEditor’s ChoiceArticle
Self-Synchronized Oscillatory Metabolism of Clostridium pasteurianum in Continuous Culture
Processes 2020, 8(2), 137; https://doi.org/10.3390/pr8020137 - 21 Jan 2020
Cited by 2
Abstract
By monitoring the real-time gas production (CO2 and H2) and redox potential at high sampling frequency in continuous culture of Clostridium pasteurianum on glycerol as sole carbohydrate, the self-synchronized oscillatory metabolism was revealed and studied. The oscillations in CO2 [...] Read more.
By monitoring the real-time gas production (CO2 and H2) and redox potential at high sampling frequency in continuous culture of Clostridium pasteurianum on glycerol as sole carbohydrate, the self-synchronized oscillatory metabolism was revealed and studied. The oscillations in CO2 and H2 production were in sync with each other and with both redox potential and glycerol in the continuous stirred tank reactor (CSTR). There is strong evidence that the mechanism for this is in the regulation of the oxidative pathway of glycerol metabolism, including glycolysis, and points toward complex, concerted cycles of enzyme inhibition and activation by pathway intermediates and/or redox equivalents. The importance of understanding such an “oscillatory metabolism” is for developing a stable and highly productive industrial fermentation process for butanol production, as unstable oscillations are unproductive. It is shown that the oscillatory metabolism can be eradicated and reinstated and that the period of oscillations can be altered by modification of the operating parameters. Synchronized oscillatory metabolism impacted the product profile such that it lowered the selectivity for butanol and increased the selectivity for ethanol. This elucidates a possible cause for the variability in the product profile of C. pasteurianum that has been reported in many previous studies. Full article
(This article belongs to the Special Issue Bioreactor System: Design, Modeling and Continuous Production Process)
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Open AccessFeature PaperEditor’s ChoiceArticle
Accelerating Biologics Manufacturing by Modeling: Process Integration of Precipitation in mAb Downstream Processing
Processes 2020, 8(1), 58; https://doi.org/10.3390/pr8010058 - 02 Jan 2020
Cited by 8
Abstract
The demand on biologics has been constantly rising over the past decades and has become crucial in modern medicine. Promising approaches to cope with widespread diseases like cancer and diabetes are gene therapy, plasmid DNA, virus-like particles, and exosomes. Due to progress that [...] Read more.
The demand on biologics has been constantly rising over the past decades and has become crucial in modern medicine. Promising approaches to cope with widespread diseases like cancer and diabetes are gene therapy, plasmid DNA, virus-like particles, and exosomes. Due to progress that has been made in upstream processing (USP), difficulties arise in downstream processing and demand for innovative solutions. This work focuses on the integration of precipitation using a quality by design (QbD) approach for process development. Selective precipitation is achieved with PEG 4000 resulting in an HCP depletion of ≥80% respectively to IgG. Dissolution was executed with a sodium phosphate buffer (pH = 5/50 mM) reaching an IgG recovery of ≥95%. However, the central challenge in process development is still an optimal process design, which is transferable for a broad molecular variety of new products. This is where rigorous modeling becomes vital in order to generate digital twins to support early-stage process development and reduce the experimental overhead. Therefore, a model development and validation concept for construction of a process model for precipitation is also presented. Full article
(This article belongs to the Special Issue Processes Accelerating Biologics Manufacturing by Modelling)
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Open AccessFeature PaperEditor’s ChoiceArticle
An Incubation System to Enhance Biogas and Methane Production: A Case Study of an Existing Biogas Plant in Umbria, Italy
Processes 2019, 7(12), 925; https://doi.org/10.3390/pr7120925 - 04 Dec 2019
Cited by 2
Abstract
The pre-incubation of digestate and recycling of microbes inside a continuously stirred tank reactor (CSTR) are effective ways to optimize the anaerobic digestion process and improve the performance of biogas and methane production, also in existing biogas plants. In this study, a digestate [...] Read more.
The pre-incubation of digestate and recycling of microbes inside a continuously stirred tank reactor (CSTR) are effective ways to optimize the anaerobic digestion process and improve the performance of biogas and methane production, also in existing biogas plants. In this study, a digestate incubation system using a nutrient mix to boost the activity of microbes was coupled to a CSTR to boost biogas and methane production. This system has been tested both on a lab scale and on an industrial scale. On a pilot scale, the system achieved an increase of +16.47 v% in biogas production with respect to the conventional anaerobic digestion process, and an increase of +2 v% in methane content (from 65.94 v% to 67.84 v%). On an industrial scale, the use of this incubation reactor with a capacity of 1 m3 has led to an increase in methane yield of 12 v%. This system allows to maintain the syntrophic relationship between acid-producing bacteria and methanogens and contemporary push the development of methanogens. Moreover, it is an economic system to be integrated into an existing biogas plant given the small volume and the simplicity of the incubation reactor. Full article
(This article belongs to the Special Issue Anaerobic Digestion Processes)
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Open AccessFeature PaperEditor’s ChoiceArticle
Splitting Triglycerides with a Counter-Current Liquid–Liquid Spray Column: Modeling, Global Sensitivity Analysis, Parameter Estimation and Optimization
Processes 2019, 7(12), 881; https://doi.org/10.3390/pr7120881 - 26 Nov 2019
Cited by 3
Abstract
In this work we present the model of a counter-current spray column in which a triglyceride (tripalmitic triglyceride) is hydrolyzed by water and leads to fatty acid (palmitic acid) and glycerol. A finite volume model (FVM) of the column was developed to describe [...] Read more.
In this work we present the model of a counter-current spray column in which a triglyceride (tripalmitic triglyceride) is hydrolyzed by water and leads to fatty acid (palmitic acid) and glycerol. A finite volume model (FVM) of the column was developed to describe the reactive extraction process with a two-phase system and validated with an analytical model from the literature with the given data set encompassing six experimental runs. Global, variance-based (Sobol) sensitivity analysis allowed assessment of the sensitivity of the sweet water glycerol content in respect to liquid density, overall mass-transfer coefficient, reaction rate coefficient and the equilibrium ratio to rank them accordingly. Furthermore, parameter estimation with a differential evolution (DE) algorithm was performed to obtain among others the mass transfer, backmixing and reaction rate coefficients. The model was used to formulate and solve a process design problem regarding economic and sustainable performance. Multi-criteria optimization was applied via DE to minimize total annual cost (TAC) and the Eco99 indicator by varying the steam inlet flow rate and distribution over the two steam inlets as the independent variables. The model and analysis was implemented in Fortran and Python where the Fortran model can also be embedded in a process simulator such as PRO/II or Aspen. Full article
(This article belongs to the Special Issue Advanced Methods in Process and Systems Engineering)
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Open AccessFeature PaperEditor’s ChoiceArticle
New Aspects on the Modeling of Dithiolactone-Mediated Radical Polymerization of Vinyl Monomers
Processes 2019, 7(11), 842; https://doi.org/10.3390/pr7110842 - 10 Nov 2019
Abstract
A kinetic model for the dithiolactone-mediated radical polymerization of vinyl monomers based on the persistent radical effect and reversible addition (negligible fragmentation) was used to calculate the polymerization rate and describe molar mass development in the polymerization of methyl methacrylate at 60 °C, [...] Read more.
A kinetic model for the dithiolactone-mediated radical polymerization of vinyl monomers based on the persistent radical effect and reversible addition (negligible fragmentation) was used to calculate the polymerization rate and describe molar mass development in the polymerization of methyl methacrylate at 60 °C, using 2,2-azobisisobutyronitrile (AIBN) as an initiator, as well as dihydro-5-phenyl-2(3H)-thiophenethione (DTL1) and dihydro-2(3H)-thiophenethione (DTL2) as controllers. The model was implemented in the PREDICI commercial software. A good agreement between experimental data and model predictions was obtained. Full article
(This article belongs to the Special Issue Modeling and Simulation of Polymerization Processes)
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Open AccessFeature PaperEditor’s ChoiceArticle
Bioinspired Hybrid Model to Predict the Hydrogen Inlet Fuel Cell Flow Change of an Energy Storage System
Processes 2019, 7(11), 825; https://doi.org/10.3390/pr7110825 - 07 Nov 2019
Cited by 4
Abstract
The present research work deals with prediction of hydrogen consumption of a fuel cell in an energy storage system. Due to the fact that these kind of systems have a very nonlinear behaviour, the use of traditional techniques based on parametric models and [...] Read more.
The present research work deals with prediction of hydrogen consumption of a fuel cell in an energy storage system. Due to the fact that these kind of systems have a very nonlinear behaviour, the use of traditional techniques based on parametric models and other more sophisticated techniques such as soft computing methods, seems not to be accurate enough to generate good models of the system under study. Due to that, a hybrid intelligent system, based on clustering and regression techniques, has been developed and implemented to predict the necessary variation of the hydrogen flow consumption to satisfy the variation of demanded power to the fuel cell. In this research, a hybrid intelligent model was created and validated over a dataset from a fuel cell energy storage system. Obtained results validate the proposal, achieving better performance than other well-known classical regression methods, allowing us to predict the hydrogen consumption with a Mean Absolute Error (MAE) of 3.73 with the validation dataset. Full article
(This article belongs to the Special Issue Bioinformatics Applications Based On Machine Learning)
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Open AccessFeature PaperEditor’s ChoiceArticle
Model Validation and Process Design of Continuous Single Pass Tangential Flow Filtration Focusing on Continuous Bioprocessing for High Protein Concentrations
Processes 2019, 7(11), 781; https://doi.org/10.3390/pr7110781 - 01 Nov 2019
Cited by 3
Abstract
In this study, the continuous Single-Pass Tangential Flow Filtration (SPTFF) concept is adapted for high protein concentrations. The work is based on the previously validated physico-chemical model for low concentrations and high viscosities. The model contains the Stagnant Film Model for concentration polarization, [...] Read more.
In this study, the continuous Single-Pass Tangential Flow Filtration (SPTFF) concept is adapted for high protein concentrations. The work is based on the previously validated physico-chemical model for low concentrations and high viscosities. The model contains the Stagnant Film Model for concentration polarization, as well as the Boundary Layer Model for the mass transfer through the membrane. The pressure drop is calculated as a function of the Reynolds number. By performing preliminary experiments with a single ultrafiltration (UF) cassette, the model parameter are determined. The presented model is validated for a multi-step Single-Pass Tangential Flow Filtration. With subsequent simulation studies, an optimized process is found and confirmed by experiments. The outcome of this work shows the potential to optimize this multi-parameter dependent unit operation. This is reached by a model-based optimization allowing significant reduction of experimental efforts and applying the Quality by Design approach consistently. Furthermore, a comparison between the experimental setup and a commercial module is examined. Full article
(This article belongs to the Special Issue Processes Accelerating Biologics Manufacturing by Modelling)
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Open AccessFeature PaperEditor’s ChoiceArticle
Application of CFD to Analyze the Hydrodynamic Behaviour of a Bioreactor with a Double Impeller
Processes 2019, 7(10), 694; https://doi.org/10.3390/pr7100694 - 03 Oct 2019
Cited by 4
Abstract
Stirred bioreactors are commonly used unit operations in the pharmaceutical industry. In this study, computational fluid dynamics (CFD) was used in order to analyze the influence of the impeller configuration (Segment–Segment and Segment–Rushton impeller configurations) and the impeller rotational speed (an operational parameter) [...] Read more.
Stirred bioreactors are commonly used unit operations in the pharmaceutical industry. In this study, computational fluid dynamics (CFD) was used in order to analyze the influence of the impeller configuration (Segment–Segment and Segment–Rushton impeller configurations) and the impeller rotational speed (an operational parameter) on the hydrodynamic behaviour and mixing performance of a bioreactor equipped with a double impeller. A relatively close agreement between the power values obtained from the CFD model and those measured experimentally was observed. Various parameters such as velocity profiles, stress generated by impellers due to the turbulence and velocity gradient, flow number, and mixing time were used to compare the CFD simulations. It was observed that the impeller’s RPM could change the intensity of the interaction between the impellers when a Segment–Rushton impeller was used. In general, increasing the RPM led to an increase in total power and the stress acting on the cells and to a shorter mixing time. At a constant RPM, the Segment–Rushton impeller configuration had higher total power and stress acting on cells compared to the Segment–Segment impeller configuration. At lower RPM values (i.e., 50 and 100), the Segment–Segment impeller provided a shorter mixing time. Conversely, at the highest RPM (i.e., 150) the Segment–Rushton impeller had a shorter mixing time compared to the Segment–Segment impeller; this was attributed to the high level of turbulence generated with the former impeller configuration at high RPM. Full article
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Open AccessFeature PaperEditor’s ChoiceArticle
Effects of Conventional Flotation Frothers on the Population of Mesophilic Microorganisms in Different Cultures
Processes 2019, 7(10), 653; https://doi.org/10.3390/pr7100653 - 25 Sep 2019
Cited by 2
Abstract
Bioleaching is an environment-friendly and low-investment process for the extraction of metals from flotation concentrate. Surfactants such as collectors and frothers are widely used in the flotation process. These chemical reagents may have inhibitory effects on the activity of microorganisms through a bioleaching [...] Read more.
Bioleaching is an environment-friendly and low-investment process for the extraction of metals from flotation concentrate. Surfactants such as collectors and frothers are widely used in the flotation process. These chemical reagents may have inhibitory effects on the activity of microorganisms through a bioleaching process; however, there is no report indicating influences of reagents on the activity of microorganisms in the mixed culture which is mostly used in the industry. In this investigation, influences of typical flotation frothers (methyl isobutyl carbinol and pine oil) in different concentrations (0.01, 0.10, and 1.00 g/L) were examined on activates of bacteria in the mesophilic mixed culture (Acidithiobacillus ferrooxidans, Leptospirillum ferrooxidans, and Acidithiobacillus thiooxidans). For comparison purposes, experiments were repeated by pure cultures of Acidithiobacillus ferrooxidans and Leptospirillum ferrooxidans in the same conditions. Results indicated that increasing the dosage of frothers has a negative correlation with bacteria activities while the mixed culture showed a lower sensitivity to the toxicity of these frothers in comparison with examined pure cultures. Outcomes showed the toxicity of Pine oil is lower than methyl isobutyl carbinol (MIBC). These results can be used for designing flotation separation procedures and to produce cleaner products for bio extraction of metals. Full article
(This article belongs to the Special Issue Bioprocess Monitoring and Control)
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Open AccessFeature PaperEditor’s ChoiceArticle
BISSO: Biomass Interface for Superstructure Simulation and Optimization
Processes 2019, 7(10), 645; https://doi.org/10.3390/pr7100645 - 21 Sep 2019
Abstract
This paper presents a web-based tool for the optimization of biomass-to-chemicals processing pathways. The tool provides a user-friendly grpahical user interface (GUI) for building a process superstructure, offers the possibility of uploading data from Aspen Plus simulations and generates an optimization code to [...] Read more.
This paper presents a web-based tool for the optimization of biomass-to-chemicals processing pathways. The tool provides a user-friendly grpahical user interface (GUI) for building a process superstructure, offers the possibility of uploading data from Aspen Plus simulations and generates an optimization code to find the pathway that minimizes the annualized costs or maximizes the net present value. A processing pathway from residues to lactic acid is used to discuss and illustrate the main features of the tool. Full article
(This article belongs to the Special Issue Process Systems Engineering à la Canada)
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Open AccessFeature PaperEditor’s ChoiceArticle
Distinct and Quantitative Validation Method for Predictive Process Modelling in Preparative Chromatography of Synthetic and Bio-Based Feed Mixtures Following a Quality-by-Design (QbD) Approach
Processes 2019, 7(9), 580; https://doi.org/10.3390/pr7090580 - 02 Sep 2019
Cited by 6
Abstract
Process development, especially in regulated industries, where quality-by-design approaches have become a prerequisite, is cost intensive and time consuming. A main factor is the large number of experiments needed. Process modelling can reduce this number significantly by replacing experiments with simulations. However, this [...] Read more.
Process development, especially in regulated industries, where quality-by-design approaches have become a prerequisite, is cost intensive and time consuming. A main factor is the large number of experiments needed. Process modelling can reduce this number significantly by replacing experiments with simulations. However, this requires a validated model. In this paper, a process and model development workflow is presented, which focuses on implementing, parameterizing, and validating the model in four steps. The presented methods are laid out to gain, create, or generate the maximum information and process knowledge needed for successful process development. This includes design of experiments and statistical evaluations showing process robustness, sensitivity of target values to process parameters, and correlations between process and target values. Two case studies are presented. An ion exchange capture step for monoclonal antibodies focusing on high accuracy and low feed consumption; and one case study for small molecules focusing on rapid process development, emphasizing speed of parameter determination. Full article
(This article belongs to the Special Issue Processes Accelerating Biologics Manufacturing by Modelling)
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Open AccessFeature PaperEditor’s ChoiceArticle
Pore Network Simulation of Gas-Liquid Distribution in Porous Transport Layers
Processes 2019, 7(9), 558; https://doi.org/10.3390/pr7090558 - 23 Aug 2019
Cited by 7
Abstract
Pore network models are powerful tools to simulate invasion and transport processes in porous media. They are widely applied in the field of geology and the drying of porous media, and have recently also received attention in fuel cell applications. Here we want [...] Read more.
Pore network models are powerful tools to simulate invasion and transport processes in porous media. They are widely applied in the field of geology and the drying of porous media, and have recently also received attention in fuel cell applications. Here we want to describe and discuss how pore network models can be used as a prescriptive tool for future water electrolysis technologies. In detail, we suggest in a first approach a pore network model of drainage for the prediction of the oxygen and water invasion process inside the anodic porous transport layer at high current densities. We neglect wetting liquid films and show that, in this situation, numerous isolated liquid clusters develop when oxygen invades the pore network. In the simulation with narrow pore size distribution, the volumetric ratio of the liquid transporting clusters connected between the catalyst layer and the water supply channel is only around 3% of the total liquid volume contained inside the pore network at the moment when the water supply route through the pore network is interrupted; whereas around 40% of the volume is occupied by the continuous gas phase. The majority of liquid clusters are disconnected from the water supply routes through the pore network if liquid films along the walls of the porous transport layer are disregarded. Moreover, these clusters hinder the countercurrent oxygen transport. A higher ratio of liquid transporting clusters was obtained for greater pore size distribution. Based on the results of pore network drainage simulations, we sketch a new route for the extraction of transport parameters from Monte Carlo simulations, incorporating pore scale flow computations and Darcy flow. Full article
(This article belongs to the Special Issue Electrolysis Processes)
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Open AccessFeature PaperEditor’s ChoiceArticle
Modeling and Simulation of Crystallization of Metal–Organic Frameworks
Processes 2019, 7(8), 527; https://doi.org/10.3390/pr7080527 - 09 Aug 2019
Cited by 5
Abstract
Metal–organic frameworks (MOFs) are the porous, crystalline structures made of metal–ligands and organic linkers that have applications in gas storage, gas separation, and catalysis. Several experimental and computational tools have been developed over the past decade to investigate the performance of MOFs for [...] Read more.
Metal–organic frameworks (MOFs) are the porous, crystalline structures made of metal–ligands and organic linkers that have applications in gas storage, gas separation, and catalysis. Several experimental and computational tools have been developed over the past decade to investigate the performance of MOFs for such applications. However, the experimental synthesis of MOFs is still empirical and requires trial and error to produce desired structures, which is due to a limited understanding of the mechanism and factors affecting the crystallization of MOFs. Here, we show for the first time a comprehensive kinetic model coupled with population balance model to elucidate the mechanism of MOF synthesis and to estimate size distribution of MOFs growing in a solution of metal–ligand and organic linker. The oligomerization reactions involving metal–ligand and organic linker produce secondary building units (SBUs), which then aggregate slowly to yield MOFs. The formation of secondary building units (SBUs) and their evolution into MOFs are modeled using detailed kinetic rate equations and population balance equations, respectively. The effect of rate constants, aggregation frequency, the concentration of organic linkers, and concurrent crystallization of organic linkers are studied on the dynamics of SBU and MOF formation. The results qualitatively explain the longer timescales involved in the synthesis of MOF. The fundamental insights gained from modeling and simulation analysis can be used to optimize the operating conditions for a higher yield of MOF crystals. Full article
(This article belongs to the Special Issue Modeling and Control of Crystallization)
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Open AccessFeature PaperEditor’s ChoiceArticle
Robust Process Design in Pharmaceutical Manufacturing under Batch-to-Batch Variation
Processes 2019, 7(8), 509; https://doi.org/10.3390/pr7080509 - 03 Aug 2019
Cited by 7
Abstract
Model-based concepts have been proven to be beneficial in pharmaceutical manufacturing, thus contributing to low costs and high quality standards. However, model parameters are derived from imperfect, noisy measurement data, which result in uncertain parameter estimates and sub-optimal process design concepts. In the [...] Read more.
Model-based concepts have been proven to be beneficial in pharmaceutical manufacturing, thus contributing to low costs and high quality standards. However, model parameters are derived from imperfect, noisy measurement data, which result in uncertain parameter estimates and sub-optimal process design concepts. In the last two decades, various methods have been proposed for dealing with parameter uncertainties in model-based process design. Most concepts for robustification, however, ignore the batch-to-batch variations that are common in pharmaceutical manufacturing processes. In this work, a probability-box robust process design concept is proposed. Batch-to-batch variations were considered to be imprecise parameter uncertainties, and modeled as probability-boxes accordingly. The point estimate method was combined with the back-off approach for efficient uncertainty propagation and robust process design. The novel robustification concept was applied to a freeze-drying process. Optimal shelf temperature and chamber pressure profiles are presented for the robust process design under batch-to-batch variation. Full article
(This article belongs to the Special Issue Model-Based Tools for Pharmaceutical Manufacturing Processes)
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Open AccessFeature PaperEditor’s ChoiceArticle
Development and Application of a Data-Driven System for Sensor Fault Diagnosis in an Oil Processing Plant
Processes 2019, 7(7), 436; https://doi.org/10.3390/pr7070436 - 10 Jul 2019
Cited by 1
Abstract
Predictive analytics is usually cited as one of the most important pillars of the digital transformation. For the oil industry, specifically, it is a common belief that issues like integrity and maintenance could benefit from predictive analytics. This paper presents the development and [...] Read more.
Predictive analytics is usually cited as one of the most important pillars of the digital transformation. For the oil industry, specifically, it is a common belief that issues like integrity and maintenance could benefit from predictive analytics. This paper presents the development and the application of a process-monitoring tool in a real process facility. The PMA (Predictive Maintenance Application) system is a data-driven application that uses a multivariate analysis in order to predict the system behavior. Results show that the use of a multivariate approach for process monitoring could not only detect an early failure at a metering system days before the operation crew, but could also successfully identify, among hundreds of variables, the root cause of the abnormal situation. By applying such an approach, a better performance of the monitored equipment is expected, decreasing its downtime. Full article
(This article belongs to the Special Issue Modeling, Simulation and Control of Chemical Processes)
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Open AccessFeature PaperEditor’s ChoiceArticle
Predicting the Longitudinally and Radially Varying Gut Microbiota Composition using Multi-Scale Microbial Metabolic Modeling
Processes 2019, 7(7), 394; https://doi.org/10.3390/pr7070394 - 26 Jun 2019
Cited by 6
Abstract
Background: The gut microbiota is a heterogeneous group of microbes that is spatially distributed along various sections of the intestines and across the mucosa and lumen in each section. Understanding the dynamics between the spatially differential microbial populations and the driving forces for [...] Read more.
Background: The gut microbiota is a heterogeneous group of microbes that is spatially distributed along various sections of the intestines and across the mucosa and lumen in each section. Understanding the dynamics between the spatially differential microbial populations and the driving forces for the observed spatial organization will provide valuable insights into important questions such as the nature of colonization of the infant gut and different types of inflammatory bowel disease localized in different regions of the intestines. However, in most studies, the microbiota is sampled only at a single site (often feces) or from a particular anatomical site of the intestines. Differential oxygen availability is putatively a key factor shaping the spatial organization. Results: To test this hypothesis, we constructed a community genome-scale metabolic model consisting of representative organisms for the major phyla present in the human gut microbiome. By solving step-wise optimization problems embedded in a dynamic framework to predict community metabolism and integrate the mucosally-adherent with the luminal microbiome between consecutive sections along the intestines, we were able to capture (i) the essential features of the spatially differential composition of obligate anaerobes vs. facultative anaerobes and aerobes determined experimentally, and (ii) the accumulation of microbial biomass in the lumen. Sensitivity analysis suggests that the spatial organization depends primarily on the oxygen-per-microbe availability in each region. Oxygen availability is reduced relative to the ~100-fold increase in mucosal microbial density along the intestines, causing the switch between aerobes and anaerobes. Conclusion: The proposed integrated dynamic framework is able to predict spatially differential gut microbiota composition using microbial genome-scale metabolic models and test hypotheses regarding the dynamics of the gut microbiota. It can potentially become a valuable tool for exploring therapeutic strategies for site-specific perturbation of the gut microbiota and the associated metabolic activities. Full article
(This article belongs to the Special Issue Microbial Communities in Health and Disease)
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Open AccessFeature PaperEditor’s ChoiceArticle
Microstructure Control of Tubular Micro-Channelled Supports Fabricated by the Phase Inversion Casting Method
Processes 2019, 7(6), 322; https://doi.org/10.3390/pr7060322 - 31 May 2019
Cited by 2
Abstract
Thin-film membrane layers coated onto porous supports is widely considered as an efficient way to obtain high-performance oxygen transport membranes with both good permeability and high mechanical strength. However, conventional preparation methods of membrane supports usually result in highly tortuous channels with high [...] Read more.
Thin-film membrane layers coated onto porous supports is widely considered as an efficient way to obtain high-performance oxygen transport membranes with both good permeability and high mechanical strength. However, conventional preparation methods of membrane supports usually result in highly tortuous channels with high mass transfer resistance. Tubular porous MgO and MgO/CGO supports were fabricated with a simple phase inversion casting method. Long finger-like channels were obtained inside the dual-phase supports by adjusting the ceramic loading, polymer concentration and particle surface area, as well as by introducing ethanol inside the casting slurries. Slurries that exhibit lower viscosity in the zero-shear viscosity region resulted in more pronounced channel growth. These supports were used to produce thin supported CGO membranes for possible application in O2 separation. Similar shrinkage speeds for the different layers during the sintering process are crucial for obtaining dense asymmetric membranes. The shrinkage of the support tube at a high temperature was greatly affected by the polymer/ceramic ratio and compatible shrinkage behaviours of the two layers were realized with polymer/ceramic weight ratios between 0.175 and 0.225. Full article
(This article belongs to the Special Issue Catalysis in Membrane Reactors)
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Open AccessFeature PaperEditor’s ChoiceArticle
Data-Driven Estimation of Significant Kinetic Parameters Applied to the Synthesis of Polyolefins
Processes 2019, 7(5), 309; https://doi.org/10.3390/pr7050309 - 22 May 2019
Cited by 5
Abstract
A data-driven strategy for the online estimation of important kinetic parameters was assessed for the copolymerization of ethylene with 1,9-decadiene using a metallocene catalyst at different diene concentrations and reaction temperatures. An initial global sensitivity analysis selected the significant kinetic parameters of the [...] Read more.
A data-driven strategy for the online estimation of important kinetic parameters was assessed for the copolymerization of ethylene with 1,9-decadiene using a metallocene catalyst at different diene concentrations and reaction temperatures. An initial global sensitivity analysis selected the significant kinetic parameters of the system. The retrospective cost model refinement (RCMR) algorithm was adapted and implemented to estimate the significant kinetic parameters of the model in real time. After verifying stability and robustness, experimental data validated the algorithm performance. Results demonstrate the estimated kinetic parameters converge close to theoretical values without requiring prior knowledge of the polymerization model and the original kinetic values. Full article
(This article belongs to the Special Issue Computational Methods for Polymers)
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Open AccessFeature PaperEditor’s ChoiceArticle
Integrating Genome-Scale and Superstructure Optimization Models in Techno-Economic Studies of Biorefineries
Processes 2019, 7(5), 286; https://doi.org/10.3390/pr7050286 - 15 May 2019
Cited by 1
Abstract
Genome-scale models have become indispensable tools for the study of cellular growth. These models have been progressively improving over the past two decades, enabling accurate predictions of metabolic fluxes and key phenotypes under a variety of growth conditions. In this work, an efficient [...] Read more.
Genome-scale models have become indispensable tools for the study of cellular growth. These models have been progressively improving over the past two decades, enabling accurate predictions of metabolic fluxes and key phenotypes under a variety of growth conditions. In this work, an efficient computational method is proposed to incorporate genome-scale models into superstructure optimization settings, introducing them as viable growth models to simulate the cultivation section of biorefinaries. We perform techno-economic and life-cycle analyses of an algal biorefinery with five processing sections to determine optimal processing pathways and technologies. Formulation of this problem results in a mixed-integer nonlinear program, in which the net present value is maximized with respect to mass flowrates and design parameters. We use a genome-scale metabolic model of Chlamydomonas reinhardtii to predict growth rates in the cultivation section. We study algae cultivation in open ponds, in which exchange fluxes of biomass and carbon dioxide are directly determined by the metabolic model. This formulation enables the coupling of flowrates and design parameters, leading to more accurate cultivation productivity estimates with respect to substrate concentration and light intensity. Full article
(This article belongs to the Special Issue Sustainable Biorefinery Processes)
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Open AccessFeature PaperEditor’s ChoiceArticle
Using a Microfluidics System to Reproducibly Synthesize Protein Nanoparticles: Factors Contributing to Size, Homogeneity, and Stability
Processes 2019, 7(5), 290; https://doi.org/10.3390/pr7050290 - 15 May 2019
Cited by 4
Abstract
The synthesis of Zein nanoparticles (NPs) using conventional methods, such as emulsion solvent diffusion and emulsion solvent evaporation, is often unreliable in replicating particle size and polydispersity between batch-to-batch syntheses. We have systematically examined the parameters for reproducibly synthesizing Zein NPs using a [...] Read more.
The synthesis of Zein nanoparticles (NPs) using conventional methods, such as emulsion solvent diffusion and emulsion solvent evaporation, is often unreliable in replicating particle size and polydispersity between batch-to-batch syntheses. We have systematically examined the parameters for reproducibly synthesizing Zein NPs using a Y-junction microfluidics chip with staggered herringbone micromixers. Our results indicate that the total flow rate of the fluidics system, relative flow rate of the aqueous and organic phase, concentration of the base material and solvent, and properties of the solvent influence the polydispersity and size of the NPs. Trends such as increasing the total flow rate and relative flow rate lead to a decrease in Zein NP size, while increasing the ethanol and Zein concentration lead to an increase in Zein NP size. The solvent property that was found to impact the size of the Zein NPs formed the most was their hydropathy. Solvents that had a hydropathy index most similar to that of Zein formed the smallest Zein NPs. Synthesis consistency was confirmed within and between sample batches. Stabilizing agents, such as sodium caseinate, Tween 80, and Pluronic F-68, were incorporated using the microfluidics system, necessary for in vitro and in vivo use, into Zein-based NPs. Full article
(This article belongs to the Special Issue Biomaterials and Tissue Engineering)
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Open AccessFeature PaperEditor’s ChoiceArticle
Nitroxide-Mediated Copolymerization of Itaconate Esters with Styrene
Processes 2019, 7(5), 254; https://doi.org/10.3390/pr7050254 - 01 May 2019
Cited by 2
Abstract
Replacing petro-based materials with renewably sourced ones has clearly been applied to polymers, such as those derived from itaconic acid (IA) and its derivatives. Di-n-butyl itaconate (DBI) was (co)polymerized via nitroxide mediated polymerization (NMP) to impart elastomeric (rubber) properties. Homopolymerization of DBI by [...] Read more.
Replacing petro-based materials with renewably sourced ones has clearly been applied to polymers, such as those derived from itaconic acid (IA) and its derivatives. Di-n-butyl itaconate (DBI) was (co)polymerized via nitroxide mediated polymerization (NMP) to impart elastomeric (rubber) properties. Homopolymerization of DBI by NMP was not possible, due to a stable adduct being formed. However, DBI/styrene (S) copolymerization by NMP at various initial molar feed compositions fDBI,0 was polymerizable at different reaction temperatures (70–110 °C) in 1,4 dioxane solution. DBI/S copolymerizations largely obeyed first order kinetics for initial DBI compositions of 10% to 80%. Number-average molecular weight (Mn) versus conversion for various DBI/S copolymerizations however showed significant deviations from the theoretical Mn as a result of chain transfer reactions (that are more likely to occur at high temperatures) and/or the poor reactivity of DBI via an NMP mechanism. In order to suppress possible intramolecular chain transfer reactions, the copolymerization was performed at 70 °C and for a longer time (72 h) with fDBI,0 = 50%–80%, and some slight improvements regarding the dispersity (Ð = 1.3–1.5), chain activity and conversion (~50%) were observed for the less DBI-rich compositions. The statistical copolymers produced showed a depression in Tg relative to poly(styrene) homopolymer, indicating the effect of DBI incorporation. Full article
(This article belongs to the Special Issue Renewable Polymers: Processing and Chemical Modifications)
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Open AccessFeature PaperEditor’s ChoiceArticle
Investigating the Molecular Basis of N-Substituted 1-Hydroxy-4-Sulfamoyl-2-Naphthoate Compounds Binding to Mcl1
Processes 2019, 7(4), 224; https://doi.org/10.3390/pr7040224 - 19 Apr 2019
Cited by 2
Abstract
Myeloid cell leukemia-1 (Mcl1) is an anti–apoptotic protein that has gained considerable attention due to its overexpression activity prevents cell death. Therefore, a potential inhibitor that specifically targets Mcl1 with higher binding affinity is necessary. Recently, a series of N-substituted 1-hydroxy-4-sulfamoyl-2-naphthoate compounds [...] Read more.
Myeloid cell leukemia-1 (Mcl1) is an anti–apoptotic protein that has gained considerable attention due to its overexpression activity prevents cell death. Therefore, a potential inhibitor that specifically targets Mcl1 with higher binding affinity is necessary. Recently, a series of N-substituted 1-hydroxy-4-sulfamoyl-2-naphthoate compounds was reported that targets Mcl1, but its binding mechanism remains unexplored. Here, we attempted to explore the molecular mechanism of binding to Mcl1 using advanced computational approaches: pharmacophore-based 3D-QSAR, docking, and MD simulation. The selected pharmacophore—NNRRR—yielded a statistically significant 3D-QSAR model containing high confidence scores (R2 = 0.9209, Q2 = 0.8459, and RMSE = 0.3473). The contour maps—comprising hydrogen bond donor, hydrophobic, negative ionic and electron withdrawal effects—from our 3D-QSAR model identified the favorable regions crucial for maximum activity. Furthermore, the external validation of the selected model using enrichment and decoys analysis reveals a high predictive power. Also, the screening capacity of the selected model had scores of 0.94, 0.90, and 8.26 from ROC, AUC, and RIE analysis, respectively. The molecular docking of the highly active compound—C40; 4-(N-benzyl-N-(4-(4-chloro-3,5-dimethylphenoxy) phenyl) sulfamoyl)-1-hydroxy-2-naphthoate—predicted the low-energy conformational pose, and the MD simulation revealed crucial details responsible for the molecular mechanism of binding with Mcl1. Full article
(This article belongs to the Special Issue Molecular Dynamics Modeling and Simulation)
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Open AccessFeature PaperEditor’s ChoiceArticle
Viscoelastic Properties of Crosslinked Chitosan Films
Processes 2019, 7(3), 157; https://doi.org/10.3390/pr7030157 - 14 Mar 2019
Cited by 12
Abstract
Chitosan films containing citric acid were prepared using a multi-step process called heterogeneous crosslinking. These films were neutralized first, followed by citric acid addition, and then heat treated at 150 °C/0.5 h in order to potentially induce covalent crosslinking. The viscoelastic storage modulus, [...] Read more.
Chitosan films containing citric acid were prepared using a multi-step process called heterogeneous crosslinking. These films were neutralized first, followed by citric acid addition, and then heat treated at 150 °C/0.5 h in order to potentially induce covalent crosslinking. The viscoelastic storage modulus, E′, and tanδ were studied using dynamic mechanical analysis, and compared with neat and neutralized films to elucidate possible crosslinking with citric acid. Films were also prepared with various concentrations of a model crosslinker, glutaraldehyde, both homogeneously and heterogeneously. Based on comparisons of neutralized films with films containing citric acid, and between citric acid films either heat treated or not heat treated, it appeared that the interaction between chitosan and citric acid remained ionic without covalent bond formation. No strong evidence of a glass transition from the tanδ plots was observable, with the possible exception of heterogeneously crosslinked glutaraldehyde films at temperatures above 200 °C. Full article
(This article belongs to the Special Issue Renewable Polymers: Processing and Chemical Modifications)
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Open AccessFeature PaperEditor’s ChoiceArticle
A Glucose-Dependent Pharmacokinetic/ Pharmacodynamic Model of ACE Inhibition in Kidney Cells
Processes 2019, 7(3), 131; https://doi.org/10.3390/pr7030131 - 04 Mar 2019
Abstract
Diabetic kidney disease (DKD) is a major cause of renal failure. Podocytes are terminally differentiated renal epithelial cells that are key targets of damage due to DKD. Podocytes express a glucose-stimulated local renin-angiotensin system (RAS) that produces angiotensin II (ANG II). Local RAS [...] Read more.
Diabetic kidney disease (DKD) is a major cause of renal failure. Podocytes are terminally differentiated renal epithelial cells that are key targets of damage due to DKD. Podocytes express a glucose-stimulated local renin-angiotensin system (RAS) that produces angiotensin II (ANG II). Local RAS differs from systemic RAS, which has been studied widely. Hyperglycemia increases the production of ANG II by podocyte cells, leading to podocyte injury. Angiotensin-converting enzyme (ACE) is involved in the production of ANG II, and ACE inhibitors are drugs used to suppress elevated ANG II concentration. As systemic RAS differs from the local RAS in podocytes, ACE inhibitor drugs should act differently in local versus systemic contexts. Experimental and computational studies have considered the pharmacokinetics (PK) and pharmacodynamics (PD) of ACE inhibition of the systemic RAS. Here, a PK/PD model for ACE inhibition is developed for the local RAS in podocytes. The model takes constant or dynamic subject-specific glucose concentration input to predict the ANG II concentration and the corresponding effects of drug doses locally and systemically. The model is developed for normal and impaired renal function in combination with different glucose conditions, thus enabling the study of various pathophysiological conditions. Parameter uncertainty is also analyzed. Such a model can improve the study of the effects of drugs at the cellular level and can aid in development of therapeutic approaches to slow the progression of DKD. Full article
(This article belongs to the Special Issue Systems Biomedicine )
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Open AccessFeature PaperEditor’s ChoiceArticle
Metabolic Modeling of Clostridium difficile Associated Dysbiosis of the Gut Microbiota
Processes 2019, 7(2), 97; https://doi.org/10.3390/pr7020097 - 15 Feb 2019
Cited by 4
Abstract
Recent in vitro experiments have demonstrated the ability of the pathogen Clostridium difficile and commensal gut bacteria to form biofilms on surfaces, and biofilm development in vivo is likely. Various studies have reported that 3%–15% of healthy adults are asymptomatically colonized with C. [...] Read more.
Recent in vitro experiments have demonstrated the ability of the pathogen Clostridium difficile and commensal gut bacteria to form biofilms on surfaces, and biofilm development in vivo is likely. Various studies have reported that 3%–15% of healthy adults are asymptomatically colonized with C. difficile, with commensal species providing resistance against C. difficile pathogenic colonization. C. difficile infection (CDI) is observed at a higher rate in immunocompromised patients previously treated with broad spectrum antibiotics that disrupt the commensal microbiota and reduce competition for available nutrients, resulting in imbalance among commensal species and dysbiosis conducive to C. difficile propagation. To investigate the metabolic interactions of C. difficile with commensal species from the three dominant phyla in the human gut, we developed a multispecies biofilm model by combining genome-scale metabolic reconstructions of C. difficile, Bacteroides thetaiotaomicron from the phylum Bacteroidetes, Faecalibacterium prausnitzii from the phylum Firmicutes, and Escherichia coli from the phylum Proteobacteria. The biofilm model was used to identify gut nutrient conditions that resulted in C. difficile-associated dysbiosis characterized by large increases in C. difficile and E. coli abundances and large decreases in F. prausnitzii abundance. We tuned the model to produce species abundances and short-chain fatty acid levels consistent with available data for healthy individuals. The model predicted that experimentally-observed host-microbiota perturbations resulting in decreased carbohydrate/increased amino acid levels and/or increased primary bile acid levels would induce large increases in C. difficile abundance and decreases in F. prausnitzii abundance. By adding the experimentally-observed perturbation of increased host nitrate secretion, the model also was able to predict increased E. coli abundance associated with C. difficile dysbiosis. In addition to rationalizing known connections between nutrient levels and disease progression, the model generated hypotheses for future testing and has the capability to support the development of new treatment strategies for C. difficile gut infections. Full article
(This article belongs to the Special Issue Methods in Computational Biology)
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Open AccessFeature PaperEditor’s ChoiceArticle
Scheduling of Energy-Integrated Batch Process Systems Using a Pattern-Based Framework
Processes 2019, 7(2), 103; https://doi.org/10.3390/pr7020103 - 15 Feb 2019
Cited by 2
Abstract
In this paper, a novel pattern-based method is developed for the generation of optimal schedules for energy-integrated batch process systems. The proposed methodology is based on the analysis of available schedules for the identification of repetitive patterns. It is shown that optimal schedules [...] Read more.
In this paper, a novel pattern-based method is developed for the generation of optimal schedules for energy-integrated batch process systems. The proposed methodology is based on the analysis of available schedules for the identification of repetitive patterns. It is shown that optimal schedules of energy-integrated batch processes are composed of several repeating sections (or building blocks), and their sizes and relative positions are dependent on the scheduling horizon and constraints. Based on such a decomposition, the proposed pattern-based algorithm generates an optimal schedule by computing the number and sequence of these blocks. The framework is then integrated with rigorous optimization-based approach wherein it is shown that the learning from the pattern-based solution significantly improves the performance of rigorous optimization. The main advantage of the pattern-based method is the significant reduction in computational time required to solve large scheduling problems, thus enabling the possibility of on-line rescheduling. Three literature examples were considered to demonstrate the presence of repeating patterns in optimal schedules of energy-integrated batch systems. The effectiveness of the proposed methodology was illustrated using an integrated reactor-separator system. Full article
(This article belongs to the Special Issue Design and Control of Sustainable Systems)
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Open AccessFeature PaperEditor’s ChoiceArticle
Multi-Tubular Reactor for Hydrogen Production: CFD Thermal Design and Experimental Testing
Processes 2019, 7(1), 31; https://doi.org/10.3390/pr7010031 - 11 Jan 2019
Cited by 5
Abstract
This study presents the Computational Fluid Dynamics (CFD) thermal design and experimental tests results for a multi-tubular solar reactor for hydrogen production based on the ferrite thermochemical cycle in a pilot plant in the Plataforma Solar de Almería (PSA). The methodology followed for [...] Read more.
This study presents the Computational Fluid Dynamics (CFD) thermal design and experimental tests results for a multi-tubular solar reactor for hydrogen production based on the ferrite thermochemical cycle in a pilot plant in the Plataforma Solar de Almería (PSA). The methodology followed for the solar reactor design is described, as well as the experimental tests carried out during the testing campaign and characterization of the reactor. The CFD model developed for the thermal design of the solar reactor has been validated against the experimental measurements, with a temperature error ranging from 1% to around 10% depending on the location within the reactor. The thermal balance in the reactor (cavity and tubes) has been also solved by the CFD model, showing a 7.9% thermal efficiency of the reactor. CFD results also show the percentage of reacting media inside the tubes which achieve the required temperature for the endothermic reaction process, with 90% of the ferrite pellets inside the tubes above the required temperature of 900 °C. The multi-tubular solar reactor designed with aid of CFD modelling and simulations has been built and operated successfully. Full article
(This article belongs to the Special Issue Hydrogen Production Technologies)
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Open AccessFeature PaperEditor’s ChoiceArticle
Estimation of Pore Size Distribution of Amorphous Silica-Based Membrane by the Activation Energies of Gas Permeation
Processes 2018, 6(12), 239; https://doi.org/10.3390/pr6120239 - 23 Nov 2018
Cited by 1
Abstract
Cobalt oxide silica membranes were prepared and tested to separate small molecular gases, such as He (dk = 2.6 Å) and H2 (dk = 2.89 Å), from other gases with larger kinetic diameters, such as CO2 ( [...] Read more.
Cobalt oxide silica membranes were prepared and tested to separate small molecular gases, such as He (dk = 2.6 Å) and H2 (dk = 2.89 Å), from other gases with larger kinetic diameters, such as CO2 (dk = 3.47 Å) and Ar (dk = 3.41 Å). In view of the amorphous nature of silica membranes, pore sizes are generally distributed in the ultra-microporous range. However, it is difficult to determine the pore size of silica derived membranes by conventional characterization methods, such as N2 physisorption-desorption or high-resolution electron microscopy. Therefore, this work endeavors to determine the pore size of the membranes based on transport phenomena and computer modelling. This was carried out by using the oscillator model and correlating with experimental results, such as gas permeance (i.e., normalized pressure flux), apparent activation energy for gas permeation. Based on the oscillator model, He and H2 can diffuse through constrictions narrower than their gas kinetic diameters at high temperatures, and this was possibly due to the high kinetic energy promoted by the increase in external temperature. It was interesting to observe changes in transport phenomena for the cobalt oxide doped membranes exposed to H2 at high temperatures up to 500 °C. This was attributed to the reduction of cobalt oxide, and this redox effect gave different apparent activation energy. The reduced membrane showed lower apparent activation energy and higher gas permeance than the oxidized membrane, due to the enlargement of pores. These results together with effective medium theory (EMT) suggest that the pore size distribution is changed and the peak of the distribution is slightly shifted to a larger value. Hence, this work showed for the first time that the oscillator model with EMT is a potential tool to determine the pore size of silica derived membranes from experimental gas permeation data. Full article
(This article belongs to the Special Issue Transport of Fluids in Nanoporous Materials)
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Open AccessFeature PaperEditor’s ChoiceArticle
Diagnostics-Oriented Modelling of Micro Gas Turbines for Fleet Monitoring and Maintenance Optimization
Processes 2018, 6(11), 216; https://doi.org/10.3390/pr6110216 - 02 Nov 2018
Cited by 10
Abstract
The market for the small-scale micro gas turbine is expected to grow rapidly in the coming years. Especially, utilization of commercial off-the-shelf components is rapidly reducing the cost of ownership and maintenance, which is paving the way for vast adoption of such units. [...] Read more.
The market for the small-scale micro gas turbine is expected to grow rapidly in the coming years. Especially, utilization of commercial off-the-shelf components is rapidly reducing the cost of ownership and maintenance, which is paving the way for vast adoption of such units. However, to meet the high-reliability requirements of power generators, there is an acute need of a real-time monitoring system that will be able to detect faults and performance degradation, and thus allow preventive maintenance of these units to decrease downtime. In this paper, a micro gas turbine based combined heat and power system is modelled and used for development of physics-based diagnostic approaches. Different diagnostic schemes for performance monitoring of micro gas turbines are investigated. Full article
(This article belongs to the Special Issue Modeling and Simulation of Energy Systems)
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Open AccessFeature PaperEditor’s ChoiceArticle
Eden Model Simulation of Re-Epithelialization and Angiogenesis of an Epidermal Wound
Processes 2018, 6(11), 207; https://doi.org/10.3390/pr6110207 - 25 Oct 2018
Abstract
Among the vital processes of cutaneous wound healing are epithelialization and angiogenesis. The former leads to the successful closure of the wound while the latter ensures that nutrients are delivered to the wound region during and after healing is completed. These processes are [...] Read more.
Among the vital processes of cutaneous wound healing are epithelialization and angiogenesis. The former leads to the successful closure of the wound while the latter ensures that nutrients are delivered to the wound region during and after healing is completed. These processes are regulated by various cytokines and growth factors that subtend their proliferation and migration into the wound region until full healing is attained. Wound epithelialization can be enhanced by the administration of epidermal stem cells (ESC) or impaired by the presence of an infection. This paper uses the Eden model of a growing cluster to independently simulate the processes of epithelialization and angiogenesis in a cutaneous wound for different geometries. Further, simulations illustrating bacterial infection are provided. Our simulation results demonstrate contraction and closure for any wound geometry due to a collective migration of epidermal cells from the wound edge in fractal form and the diffusion of capillary sprouts with the laying down of capillary blocks behind moving tips into the wound area. Full article
(This article belongs to the Special Issue Systems Biomedicine )
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