Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.1
2.8
Journals
Processes
Editor’s Choice
share announcement

Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Order results
Result details
Results per page
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
17 pages, 474 KiB  
Review
Roles of Drying, Size Reduction, and Blanching in Sustainable Extraction of Phenolics from Olive Leaves
by Fereshteh Safarzadeh Markhali
Processes 2021, 9(9), 1662; https://doi.org/10.3390/pr9091662 - 14 Sep 2021
Cited by 10 | Viewed by 5229
Abstract
It is now known that olive leaves contain a sizable portion of polyphenols and there is much research highlighting that these natural ingredients favorably exhibit bio-functional activities. In this regard, many studies have focused on the exploration of optimum conditions involved directly in [...] Read more.
It is now known that olive leaves contain a sizable portion of polyphenols and there is much research highlighting that these natural ingredients favorably exhibit bio-functional activities. In this regard, many studies have focused on the exploration of optimum conditions involved directly in the extraction process. These investigations, while being highly valuable, may somewhat cast a shadow over other contributing factors such as those involved in the preprocessing of leaves, including size reduction, drying, and blanching. The use of these unit operations under appropriate conditions, together with other benefits, potentially exert improved surface area, homogeneity, and diffusion/mass transfer which may help develop the liberation of target bio-compounds. The research work in this area, particularly size reduction, is relatively limited. Although in various experiments they are incorporated, not many studies have focused on them as the main predictor variables. The performance of further research may help ascertain the magnitude of their effects. Consideration of the operational parameters in preprocessing step is equally important as those in the processing/extraction step that may comparably influence on the extraction efficiency. This review provides an overview of the potential roles of drying, size reduction, and blanching in the extraction efficiency of phenolics from olive leaves. Full article
(This article belongs to the Special Issue Sustainable Development of Waste towards Green Growth)
►▼ Show Figures

Figure 1

17 pages, 1015 KiB  
Review
Bladder Substitution: The Role of Tissue Engineering and Biomaterials
by Martina Casarin, Alessandro Morlacco and Fabrizio Dal Moro
Processes 2021, 9(9), 1643; https://doi.org/10.3390/pr9091643 - 13 Sep 2021
Cited by 17 | Viewed by 4199
Abstract
Tissue engineering could play a major role in the setting of urinary diversion. Several conditions cause the functional or anatomic loss of urinary bladder, requiring reconstructive procedures on the urinary tract. Three main approaches are possible: (i) incontinent cutaneous diversion, such as ureterocutaneostomy, [...] Read more.
Tissue engineering could play a major role in the setting of urinary diversion. Several conditions cause the functional or anatomic loss of urinary bladder, requiring reconstructive procedures on the urinary tract. Three main approaches are possible: (i) incontinent cutaneous diversion, such as ureterocutaneostomy, colonic or ileal conduit, (ii) continent pouch created using different segments of the gastrointestinal system and a cutaneous stoma, and (iii) orthotopic urinary diversion with an intestinal segment with spherical configuration and anastomosis to the urethra (neobladder, orthotopic bladder substitution). However, urinary diversions are associated with numerous complications, such as mucus production, electrolyte imbalances and increased malignant transformation potential. In this context, tissue engineering would have the fundamental role of creating a suitable material for urinary diversion, avoiding the use of bowel segments, and reducing complications. Materials used for the purpose of urinary substitution are biological in case of acellular tissue matrices and naturally derived materials, or artificial in case of synthetic polymers. However, only limited success has been achieved so far. The aim of this review is to present the ideal properties of a urinary tissue engineered scaffold and to examine the results achieved so far. The most promising studies have been highlighted in order to guide the choice of scaffolds and cells type for further evolutions. Full article
(This article belongs to the Section Biological Processes and Systems)
►▼ Show Figures

Figure 1

13 pages, 4853 KiB  
Article
Effects of Geniposide and Geniposidic Acid on Fluoxetine-Induced Muscle Atrophy in C2C12 Cells
by Shang-Ming Huang, Shuan-Ying Lin, Ming-Kai Chen, Chiung-Chi Peng and Chiu-Lan Hsieh
Processes 2021, 9(9), 1649; https://doi.org/10.3390/pr9091649 - 13 Sep 2021
Cited by 3 | Viewed by 3196
Abstract
Fluoxetine, an antidepressant known as a selective 5-hydroxytryptamine reuptake inhibitor (SSRI), can cause side effects such as muscle atrophy with long-term use, but the mechanism is not fully understood. Geniposide (GPS) and geniposidic acid (GPSA), the main components of Gardenia jasminoides fruit, have [...] Read more.
Fluoxetine, an antidepressant known as a selective 5-hydroxytryptamine reuptake inhibitor (SSRI), can cause side effects such as muscle atrophy with long-term use, but the mechanism is not fully understood. Geniposide (GPS) and geniposidic acid (GPSA), the main components of Gardenia jasminoides fruit, have been shown to have biological activity in disease prevention, but their role in preventing FXT-related side effects such as muscle atrophy remains unclear. The process of muscle atrophy is a complex physiological mechanism involving the balance of protein synthesis and catabolism. In this study, we hypothesized that FXT may suppress hypertrophy signaling and activate the atrophy mechanisms, resulting in proteolysis and reduced protein synthesis, while geniposide (GPS) and geniposide acid (GPSA) may be beneficial in improving muscle weakness caused by FXT. The C2C12 cell model was used to examine the expression of hypertrophy signaling (PI3K, Akt, and mTOR) and protein break signals (FOXO, MuRF-1, and MyHC). Our data indicated that FXT inhibited MyHC and promoted MuRF-1 protein expression by downregulating the signaling pathways of p-ERK1/2, p-Akt, p-mTOR, and p-FOXO, resulting in a decrease in differentiation and myotube formation in C2C12 muscle cells, which further resulted in muscle atrophy. However, GPS and GPSA can positively regulate the atrophy mechanism induced by FXT in muscle cells, thereby ameliorating the imbalance in muscle synthesis. In conclusion, GPS and GPSA have the potential to attenuate the muscle loss caused by long-term FXT administration, diseases, or the aging process. Full article
(This article belongs to the Special Issue Food Safety Management and Quality Control Techniques)
►▼ Show Figures

Figure 1

14 pages, 7064 KiB  
Article
Preparation of Microcellular Foams by Supercritical Carbon Dioxide: A Case Study of Thermoplastic Polyurethane 70A
by Yu-Ting Hsiao, Chieh-Ming Hsieh, Tsung-Mao Yang and Chie-Shaan Su
Processes 2021, 9(9), 1650; https://doi.org/10.3390/pr9091650 - 13 Sep 2021
Cited by 4 | Viewed by 2918
Abstract
In this study, a case study to produce microcellular foam of a commercial thermoplastic polyurethane (TPU) through the supercritical carbon dioxide (CO2) foaming process is presented. To explore the feasibility of TPU in medical device and biomedical application, a soft TPU [...] Read more.
In this study, a case study to produce microcellular foam of a commercial thermoplastic polyurethane (TPU) through the supercritical carbon dioxide (CO2) foaming process is presented. To explore the feasibility of TPU in medical device and biomedical application, a soft TPU with Shore hardness value of 70A was selected as the model compound. The effects of saturation temperature and saturation pressure ranging from 90 to 140 °C and 90 to 110 bar on the expansion ratio, cell size and cell density of the TPU foam were compared and discussed. Regarding the expansion ratio, the effect of saturation temperature was considerable and an intermediate saturation temperature of 100 °C was favorable to produce TPU microcellular foam with a high expansion ratio. On the other hand, the mean pore size and cell density of TPU foam can be efficiently manipulated by adjusting the saturation pressure. A high saturation pressure was beneficial to obtain TPU foam with small mean pore size and high cell density. This case study shows that the expansion ratio of TPU microcellular foam could be designed as high as 4.4. The cell size and cell density could be controlled within 12–40 μm and 5.0 × 107–1.3 × 109 cells/cm3, respectively. Full article
(This article belongs to the Special Issue Advanced Polymer Processing Processes)
►▼ Show Figures

Figure 1

15 pages, 6653 KiB  
Article
Automated Compartment Model Development Based on Data from Flow-Following Sensor Devices
by Jonas Bisgaard, Tannaz Tajsoleiman, Monica Muldbak, Thomas Rydal, Tue Rasmussen, Jakob K. Huusom and Krist V. Gernaey
Processes 2021, 9(9), 1651; https://doi.org/10.3390/pr9091651 - 13 Sep 2021
Cited by 9 | Viewed by 2892
Abstract
Due to the heterogeneous nature of large-scale fermentation processes they cannot be modelled as ideally mixed reactors, and therefore flow models are necessary to accurately represent the processes. Computational fluid dynamics (CFD) is used more and more to derive flow fields for the [...] Read more.
Due to the heterogeneous nature of large-scale fermentation processes they cannot be modelled as ideally mixed reactors, and therefore flow models are necessary to accurately represent the processes. Computational fluid dynamics (CFD) is used more and more to derive flow fields for the modelling of bioprocesses, but the computational demands associated with simulation of multiphase systems with biokinetics still limits their wide applicability. Hence, a demand for simpler flow models persists. In this study, an approach to develop data-based flow models in the form of compartment models is presented, which utilizes axial-flow rates obtained from flow-following sensor devices in combination with a proposed procedure for automatic zoning of volume. The approach requires little experimental effort and eliminates the necessity for computational determination of inter-compartmental flow rates and manual zoning. The concept has been demonstrated in a 580 L stirred vessel, of which models have been developed for two types of impellers with varying agitation intensities. The sensor device measurements were corroborated by CFD simulations, and the performance of the developed compartment models was evaluated by comparing predicted mixing times with experimentally determined mixing times. The data-based compartment models predicted the mixing times for all examined conditions with relative errors in the range of 3–27%. The deviations were ascribed to limitations in the flow-following behavior of the sensor devices, whose sizes were relatively large compared to the examined system. The approach provides a versatile and automated flow modelling platform which can be applied to large-scale bioreactors. Full article
(This article belongs to the Special Issue Bioreactor System: Design, Modeling and Continuous Production Process)
►▼ Show Figures

Figure 1

17 pages, 13161 KiB  
Article
Photovoltaic Module Fault Detection Based on a Convolutional Neural Network
by Shiue-Der Lu, Meng-Hui Wang, Shao-En Wei, Hwa-Dong Liu and Chia-Chun Wu
Processes 2021, 9(9), 1635; https://doi.org/10.3390/pr9091635 - 10 Sep 2021
Cited by 16 | Viewed by 3879
Abstract
With the rapid development of solar energy, the photovoltaic (PV) module fault detection plays an important role in knowing how to enhance the reliability of the solar photovoltaic system and knowing the fault type when a system problem occurs. Therefore, this paper proposed [...] Read more.
With the rapid development of solar energy, the photovoltaic (PV) module fault detection plays an important role in knowing how to enhance the reliability of the solar photovoltaic system and knowing the fault type when a system problem occurs. Therefore, this paper proposed the hybrid algorithm of chaos synchronization detection method (CSDM) with convolutional neural network (CNN) for studying PV module fault detection. Four common PV module states were discussed, including the normal PV module, module breakage, module contact defectiveness and module bypass diode failure. First of all, the defects in 16 pieces of 20W monocrystalline silicon PV modules were preprocessed, and there were four pieces of each fault state. When the signal generator delivered high frequency voltage to the PV module, the original signal was measured and captured by the NI PXI-5105 high-speed data acquisition system (DAS) and was calculated by CSDM, to establish the chaos dynamic error map as the image feature of fault diagnosis. Finally, the CNN was employed for diagnosing the fault state of the PV module. The findings show that after entering 400 random fault data (100 data for each fault) into the proposed method for recognition, the recognition accuracy rate of the proposed method was as high as 99.5%, which is better than the traditional ENN algorithm that had a recognition rate of 86.75%. In addition, the advantage of the proposed algorithm is that the mass original measured data can be reduced by CSDM, the subtle changes in the output signals are captured effectively and displayed in images, and the PV module fault state is accurately recognized by CNN. Full article
(This article belongs to the Special Issue Application of Power Electronics Technologies in Power System)
►▼ Show Figures

Figure 1

18 pages, 5408 KiB  
Article
Data Driven Detection of Different Dissolved Oxygen Sensor Faults for Improving Operation of the WWTP Control System
by Alexandra-Veronica Luca, Melinda Simon-Várhelyi, Norbert-Botond Mihály and Vasile-Mircea Cristea
Processes 2021, 9(9), 1633; https://doi.org/10.3390/pr9091633 - 10 Sep 2021
Cited by 16 | Viewed by 3267
Abstract
Sensor faults frequently occur in wastewater treatment plant (WWTP) operation, leading to incomplete monitoring or poor control of the plant. Reliable operation of the WWTP considerably depends on the aeration control system, which is essentially assisted by the dissolved oxygen (DO) sensor. Results [...] Read more.
Sensor faults frequently occur in wastewater treatment plant (WWTP) operation, leading to incomplete monitoring or poor control of the plant. Reliable operation of the WWTP considerably depends on the aeration control system, which is essentially assisted by the dissolved oxygen (DO) sensor. Results on the detection of different DO sensor faults, such as bias, drift, wrong gain, loss of accuracy, fixed value, or complete failure, were investigated based on Principal Components Analysis (PCA). The PCA was considered together with two statistical approaches, i.e., the Hotelling’s T2 and the Squared Prediction Error (SPE). Data used in the study were generated using the previously calibrated first-principle Activated Sludge Model no.1 for the Anaerobic-Anoxic-Oxic (A2O) reactors configuration. The equation-based model was complemented with control loops for DO concentration control in the aerobic reactor and nitrates concentration control in the anoxic reactor. The PCA data-driven model was successfully used for the detection of the six investigated DO sensor faults. The statistical detection approaches were compared in terms of promptness, effectiveness, and accuracy. The obtained results revealed the way faults originating from DO sensor malfunction can be detected and the efficiency of the detection approaches for the automatically controlled WWTP. Full article
(This article belongs to the Special Issue Treatment and Utilization of Waste Materials)
►▼ Show Figures

Figure 1

14 pages, 667 KiB  
Article
Potential for Lager Beer Production from Saccharomyces cerevisiae Strains Isolated from the Vineyard Environment
by Massimo Iorizzo, Francesco Letizia, Gianluca Albanese, Francesca Coppola, Angelita Gambuti, Bruno Testa, Riccardo Aversano, Martino Forino and Raffaele Coppola
Processes 2021, 9(9), 1628; https://doi.org/10.3390/pr9091628 - 9 Sep 2021
Cited by 11 | Viewed by 5397
Abstract
Saccharomyces pastorianus, genetic hybrids of Saccharomyces cerevisiae and the Saccharomyces eubayanus, is one of the most widely used lager yeasts in the brewing industry. In recent years, new strategies have been adopted and new lines of research have been outlined to [...] Read more.
Saccharomyces pastorianus, genetic hybrids of Saccharomyces cerevisiae and the Saccharomyces eubayanus, is one of the most widely used lager yeasts in the brewing industry. In recent years, new strategies have been adopted and new lines of research have been outlined to create and expand the pool of lager brewing starters. The vineyard microbiome has received significant attention in the past few years due to many opportunities in terms of biotechnological applications in the winemaking processes. However, the characterization of S. cerevisiae strains isolated from winery environments as an approach to selecting starters for beer production has not been fully investigated, and little is currently available. Four wild cryotolerant S. cerevisiae strains isolated from vineyard environments were evaluated as potential starters for lager beer production at laboratory scale using a model beer wort (MBW). In all tests, the industrial lager brewing S. pastorianus Weihenstephan 34/70 was used as a reference strain. The results obtained, although preliminary, showed some good properties of these strains, such as antioxidant activity, flocculation capacity, efficient fermentation at 15 °C and low diacetyl production. Further studies will be carried out using these S. cerevisiae strains as starters for lager beer production on a pilot scale in order to verify the chemical and sensory characteristics of the beers produced. Full article
(This article belongs to the Special Issue Control and Optimization of Alcoholic Fermentation and Extraction Technology)
►▼ Show Figures

Figure 1

24 pages, 4946 KiB  
Article
Evaluation of a Combined MHE-NMPC Approach to Handle Plant-Model Mismatch in a Rotary Tablet Press
by Yan-Shu Huang, M. Ziyan Sheriff, Sunidhi Bachawala, Marcial Gonzalez, Zoltan K. Nagy and Gintaras V. Reklaitis
Processes 2021, 9(9), 1612; https://doi.org/10.3390/pr9091612 - 8 Sep 2021
Cited by 17 | Viewed by 3566
Abstract
The transition from batch to continuous processes in the pharmaceutical industry has been driven by the potential improvement in process controllability, product quality homogeneity, and reduction of material inventory. A quality-by-control (QbC) approach has been implemented in a variety of pharmaceutical product manufacturing [...] Read more.
The transition from batch to continuous processes in the pharmaceutical industry has been driven by the potential improvement in process controllability, product quality homogeneity, and reduction of material inventory. A quality-by-control (QbC) approach has been implemented in a variety of pharmaceutical product manufacturing modalities to increase product quality through a three-level hierarchical control structure. In the implementation of the QbC approach it is common practice to simplify control algorithms by utilizing linearized models with constant model parameters. Nonlinear model predictive control (NMPC) can effectively deliver control functionality for highly sensitive variations and nonlinear multiple-input-multiple-output (MIMO) systems, which is essential for the highly regulated pharmaceutical manufacturing industry. This work focuses on developing and implementing NMPC in continuous manufacturing of solid dosage forms. To mitigate control degradation caused by plant-model mismatch, careful monitoring and continuous improvement strategies are studied. When moving horizon estimation (MHE) is integrated with NMPC, historical data in the past time window together with real-time data from the sensor network enable state estimation and accurate tracking of the highly sensitive model parameters. The adaptive model used in the NMPC strategy can compensate for process uncertainties, further reducing plant-model mismatch effects. The nonlinear mechanistic model used in both MHE and NMPC can predict the essential but complex powder properties and provide physical interpretation of abnormal events. The adaptive NMPC implementation and its real-time control performance analysis and practical applicability are demonstrated through a series of illustrative examples that highlight the effectiveness of the proposed approach for different scenarios of plant-model mismatch, while also incorporating glidant effects. Full article
(This article belongs to the Special Issue Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools)
►▼ Show Figures

Figure 1

13 pages, 2505 KiB  
Article
Smart Determination of Gold Content in PCBs of Waste Mobile Phones by Coupling of XRF and AAS Techniques
by Nicolò Maria Ippolito, Gianmaria Belardi, Valentina Innocenzi, Franco Medici, Loris Pietrelli and Luigi Piga
Processes 2021, 9(9), 1618; https://doi.org/10.3390/pr9091618 - 8 Sep 2021
Cited by 4 | Viewed by 3108
Abstract
Quantitative determination of most economic valuable metals in waste is the first fundamental operation of evaluating the feasibility of recycling processes. Field-portable X-ray fluorescence spectrometers (FPXRFs) represent a more practical, efficient, and economic tool in determining the elemental composition of samples with respect [...] Read more.
Quantitative determination of most economic valuable metals in waste is the first fundamental operation of evaluating the feasibility of recycling processes. Field-portable X-ray fluorescence spectrometers (FPXRFs) represent a more practical, efficient, and economic tool in determining the elemental composition of samples with respect to conventional analytical techniques, such as atomic absorption spectrometry (AAS) and inductively coupled plasma emission spectrometry (ICP). In this paper, quick and smart determination of gold content in printed circuit boards (PCBs) of waste mobile phones was studied. The aim of the research was to combine the practicality of FPXRFs with the reliability of quantitative spectrometry analysis and evaluate the error between the two techniques. Several samples (33) of PCBs were ground to a size below 0.5 mm, and then, the powders were analyzed by FPXRFs at different acquisition times with five replications for each sample. The same analyzed samples then underwent chemical attack to determine the quantitative gold content by AAS. The obtained results were associated with FPXRFs response with the purpose of realizing a calibration curve (100–1000 mg/kg Au). The curve was validated for accuracy and precision by other PCBs waste samples; the control samples were added as standards to obtain a more reliable calibration curve. The curve was evaluated with RPD classification, regression linear, and Bolt–Altman analysis. Full article
(This article belongs to the Section Environmental and Green Processes)
►▼ Show Figures

Figure 1

22 pages, 3564 KiB  
Article
Advanced Process Analytical Technology in Combination with Process Modeling for Endpoint and Model Parameter Determination in Lyophilization Process Design and Optimization
by Alex Juckers, Petra Knerr, Frank Harms and Jochen Strube
Processes 2021, 9(9), 1600; https://doi.org/10.3390/pr9091600 - 7 Sep 2021
Cited by 16 | Viewed by 4035
Abstract
Lyophilization is widely used in the preservation of thermolabile products. The main shortcoming is the long processing time. Lyophilization processes are mostly based on a recipe that is not changed, but, with the Quality by Design (QbD) approach and use of Process Analytical [...] Read more.
Lyophilization is widely used in the preservation of thermolabile products. The main shortcoming is the long processing time. Lyophilization processes are mostly based on a recipe that is not changed, but, with the Quality by Design (QbD) approach and use of Process Analytical Technology (PAT), the process duration can be optimized for maximum productivity while ensuring product safety. In this work, an advanced PAT approach is used for the endpoint determination of primary drying. Manometric temperature measurement (MTM) and comparative pressure measurement are used to determine the endpoint of the batch while a modeling approach is outlined that is able to calculate the endpoint of every vial in the batch. This approach can be used for process development, control and optimization. Full article
(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)
►▼ Show Figures

Figure 1

12 pages, 2153 KiB  
Article
Comparison of Two Extraction Procedures, SPE and DLLME, for Determining Plasticizer Residues in Hot Drinks at Vending Machines
by Ivan Notardonato, Sergio Passarella, Alessia Iannone, Cristina Di Fiore, Mario Vincenzo Russo, Carmela Protano, Matteo Vitali and Pasquale Avino
Processes 2021, 9(9), 1588; https://doi.org/10.3390/pr9091588 - 5 Sep 2021
Cited by 8 | Viewed by 3339
Abstract
This paper would like to compare two extraction procedures for analyzing phthalates (PAEs) in hot drinks collected at vending machines, usually coffee and tea. The two analytical procedures are based on Solid Phase Extraction (SPE) using C18 cartridge and on dispersive liquid-liquid microextraction [...] Read more.
This paper would like to compare two extraction procedures for analyzing phthalates (PAEs) in hot drinks collected at vending machines, usually coffee and tea. The two analytical procedures are based on Solid Phase Extraction (SPE) using C18 cartridge and on dispersive liquid-liquid microextraction (DLLME) assisted by ultrasound and vortex for improving the dispersion mechanically, with each followed by a routinary analytical method such as GC-FID. Seven phthalates (DMP, DEP, DiBP, DBP, DEHP, DOP, DDP) have been analyzed and determined. All the analytical parameters (i.e., recovery, limit of detection, limit of quantification, enrichment factors, repeatability, reproducibility) have been investigated and discussed, as has the matrix effect. The entire procedure has been applied to hot drink matrices, e.g., coffee, decaffeinated coffee, barley coffee, ginseng coffee and tea. Full article
(This article belongs to the Special Issue Applications of Chromatographic Separation Techniques in Food and Chemistry)
►▼ Show Figures

Figure 1

11 pages, 979 KiB  
Review
Overview of the Benefits and Challenges Associated with Pelletizing Biochar
by Ali Mohammadi
Processes 2021, 9(9), 1591; https://doi.org/10.3390/pr9091591 - 5 Sep 2021
Cited by 27 | Viewed by 8339
Abstract
Biochar can be derived from a wide variety of organic materials including agricultural wastes and residues, animal wastes, municipal solid wastes, pulp and paper mill wastes, and sewage sludge. Its productivity relies on feedstock type and thermochemical conditions of production. Biochar has many [...] Read more.
Biochar can be derived from a wide variety of organic materials including agricultural wastes and residues, animal wastes, municipal solid wastes, pulp and paper mill wastes, and sewage sludge. Its productivity relies on feedstock type and thermochemical conditions of production. Biochar has many application advantages in several fields and has been widely studied in recent years. However, most of these studies are mainly on the powder form of biochar, while its pelleted form is sparsely reported. Even with the reported studies on biochar pellets, there is still lack of knowledge and awareness of the effects of different feedstock on the densification behavior of biochar. The mechanisms of biochar densification, which appear to be sensitive to the conditions predominating during its thermochemical production, are affected by the material from which the biochar is derived. This partly accounts for why biochar pellets have not been widely adopted in various application fields. Therefore, this paper presents an overview of the benefits associated with the use of biochar pellets and discusses the challenges encountered when pelleting biochars that are derived from different feedstock under various carbonization conditions. Research priority areas needed to overcome the challenges are also identified and discussed. The purpose is to contribute to better understanding on biochar pelletization behavior, and to offer insights useful to comprehend some basic principles that may occur in the pelleting process and to ease further and more thorough investigations. Full article
(This article belongs to the Section Environmental and Green Processes)
►▼ Show Figures

Figure 1

15 pages, 1483 KiB  
Article
Counter-Current Suspension Extraction Process of Lignocellulose in Biorefineries to Reach Low Water Consumption, High Extraction Yields, and Extract Concentrations
by Marc Conrad and Irina Smirnova
Processes 2021, 9(9), 1585; https://doi.org/10.3390/pr9091585 - 4 Sep 2021
Cited by 3 | Viewed by 3710
Abstract
The processing of large quantities of water in biorefining processes can lead to immense costs for heating, evaporation, and wastewater disposal. These costs may prohibit the exploitation of alternative products, e.g., xylooligosaccharides from straw, which are regarded as too costly. A new counter-current [...] Read more.
The processing of large quantities of water in biorefining processes can lead to immense costs for heating, evaporation, and wastewater disposal. These costs may prohibit the exploitation of alternative products, e.g., xylooligosaccharides from straw, which are regarded as too costly. A new counter-current extractions method is proposed that aims at low solvent (water) consumption, as well as high yields and extract concentrations. This process was evaluated with suspension extraction experiments with steam pretreated wheat straw and the process window analysis based on a mass balance for a washing and a leaching scenario. The latter was conducted with two other suspension extraction processes as a comparison. The equilibration time was found to be well below 10 min. While the suspension extraction with and without recycling need to be designed to achieve a high yield or a high concentration and low solvent consumption, the proposed extraction method can reach all three simultaneously. Thus, this new process is evaluated as a potential method to spare water and downstream costs and allow new processing pathways in second-generation biorefineries. Full article
(This article belongs to the Special Issue Recent Advances in Biorefining Processes)
►▼ Show Figures

Figure 1

16 pages, 3446 KiB  
Article
Conjugated Mass Transfer of CO2 Absorption through Concentric Circular Gas–Liquid Membrane Contactors
by Chii-Dong Ho, Hsuan Chang, Yih-Hang Chen, Jun-Wei Lim and Jing-Wei Liou
Processes 2021, 9(9), 1580; https://doi.org/10.3390/pr9091580 - 3 Sep 2021
Cited by 2 | Viewed by 1972
Abstract
A new design of gas absorption that winds the permeable membrane onto an inner concentric tube to conduct a concentric circular gas–liquid membrane module has been studied theoretically in the fully developed region. An analytical formulation, referred to as conjugated Graetz problems, is [...] Read more.
A new design of gas absorption that winds the permeable membrane onto an inner concentric tube to conduct a concentric circular gas–liquid membrane module has been studied theoretically in the fully developed region. An analytical formulation, referred to as conjugated Graetz problems, is developed to predict the concentration distribution and Sherwood numbers for the absorbent fluid flowing in the shell side and CO2/N2 gas mixture flowing in the tube side under various designs and operating parameters. The analytical solutions to the CO2 absorption efficiency were developed by using a two-dimensional mathematical modeling, and the resultant conjugated partial differential equations were solved analytically using the method of separation variables and eigen-function expansion in terms of power series. The predictions of CO2 absorption rate by using Monoethanolamide (MEA) solution in concentric circular membrane contactors under both concurrent- and countercurrent-flow operations are developed theoretically and confirmed with the experimental results. Consistency in both a good qualitative and quantitative sense is achieved between the theoretical predictions and experimental results. The advantage of the present mathematical treatment provides a concise expression for the chemical absorption of CO2 by MEA solution to calculate the absorption rate, absorption efficiency, and average Sherwood number. The concentration profiles with the mass-transfer Graetz number, inlet CO2 concentration, and both gas feed and absorbent flow rates are also emphasized. Both theoretical predictions and experimental results show that the device performance of the countercurrent-flow operation is better than that of the concurrent-flow device operation. The availability of such simplified expressions of the absorption rate and averaged Sherwood as developed directly from the analytical solutions is the value of the present study. Full article
►▼ Show Figures

Figure 1

21 pages, 15858 KiB  
Article
Formation Control of Swarming Vessels Using a Virtual Matrix Approach and ISOT Guidance Algorithm
by Su-Rim Kim, Hyun-Jae Jo, Jung-Hyeon Kim and Jong-Yong Park
Processes 2021, 9(9), 1581; https://doi.org/10.3390/pr9091581 - 3 Sep 2021
Cited by 5 | Viewed by 2713
Abstract
The formation control for the effective operation of multiple vessels is discussed. First, a virtual matrix approach is proposed to improve the formation robustness and transform performance during swarm operations, which is created based on the virtual leader vessel location, and agents composing [...] Read more.
The formation control for the effective operation of multiple vessels is discussed. First, a virtual matrix approach is proposed to improve the formation robustness and transform performance during swarm operations, which is created based on the virtual leader vessel location, and agents composing the formation follow cells in the matrix to maintain formation. This approach is affected by the virtual leader vessel location. The virtual leader vessel location is defined by two cases: matrix center and geometric center; furthermore, robustness and efficiency comparison simulations are performed. The simulation results show that in most formations, the geometric center is better in terms of efficiency and robustness. Second, the isosceles triangle guidance algorithm is proposed to improve the “go-back behavior” of certain agents during excessive maneuvering. Through a waypoint-following simulation, the algorithm is confirmed to be superior to the line-of-sight guidance algorithm. The swarm simulation on the virtual map verifies the performance of the proposed formation control and guidance algorithm. Full article
(This article belongs to the Special Issue Theoretical and Numerical Marine Hydrodynamics)
►▼ Show Figures

Figure 1

18 pages, 886 KiB  
Review
How to Tackle Underdeterminacy in Metabolic Flux Analysis? A Tutorial and Critical Review
by Philippe Bogaerts and Alain Vande Wouwer
Processes 2021, 9(9), 1577; https://doi.org/10.3390/pr9091577 - 2 Sep 2021
Cited by 5 | Viewed by 3449
Abstract
Metabolic flux analysis is often (not to say almost always) faced with system underdeterminacy. Indeed, the linear algebraic system formed by the steady-state mass balance equations around the intracellular metabolites and the equality constraints related to the measurements of extracellular fluxes do not [...] Read more.
Metabolic flux analysis is often (not to say almost always) faced with system underdeterminacy. Indeed, the linear algebraic system formed by the steady-state mass balance equations around the intracellular metabolites and the equality constraints related to the measurements of extracellular fluxes do not define a unique solution for the distribution of intracellular fluxes, but instead a set of solutions belonging to a convex polytope. Various methods have been proposed to tackle this underdeterminacy, including flux pathway analysis, flux balance analysis, flux variability analysis and sampling. These approaches are reviewed in this article and a toy example supports the discussion with illustrative numerical results. Full article
(This article belongs to the Special Issue Mathematical Modeling and Control of Bioprocesses)
►▼ Show Figures

Figure 1

15 pages, 1509 KiB  
Article
Modeling of Continuous PHA Production by a Hybrid Approach Based on First Principles and Machine Learning
by Martin F. Luna, Andrea M. Ochsner, Véronique Amstutz, Damian von Blarer, Michael Sokolov, Paolo Arosio and Manfred Zinn
Processes 2021, 9(9), 1560; https://doi.org/10.3390/pr9091560 - 1 Sep 2021
Cited by 23 | Viewed by 4973
Abstract
Polyhydroxyalkanoates (PHA) are renewable alternatives to traditional oil-derived polymers. PHA can be produced by different microorganisms in continuous culture under specific media composition, which makes the production process both promising and challenging. In order to achieve large productivities while maintaining high yield and [...] Read more.
Polyhydroxyalkanoates (PHA) are renewable alternatives to traditional oil-derived polymers. PHA can be produced by different microorganisms in continuous culture under specific media composition, which makes the production process both promising and challenging. In order to achieve large productivities while maintaining high yield and efficiency, the continuous culture needs to be operated in the so-called dual nutrient limitation condition, where both the nitrogen and carbon sources are kept at very low concentrations. Mathematical models can greatly assist both design and operation of the bioprocess, but are challenged by the complexity of the system, in particular by the dual nutrient-limited growth phenomenon, where the cells undergo a metabolic shift that abruptly changes their behavior. Traditional, non-structured mechanistic models based on Monod uptake kinetics can be used to describe the bioreactor operation under specific process conditions. However, in the absence of a model description of the metabolic phenomena inside the cell, the extrapolation to a broader operation domain (e.g., different feeding concentrations and dilution rates) may present mismatches between the predictions and the actual process outcomes. Such detailed models may require almost perfect knowledge of the cell metabolism and omic-level measurements, hampering their development. On the other hand, purely data-driven models that learn correlations from experimental data do not require any prior knowledge of the process and are therefore unbiased and flexible. However, many more data are required for their development and their extrapolation ability is limited to conditions that are similar to the ones used for training. An attractive alternative is the combination of the extrapolation power of first principles knowledge with the flexibility of machine learning methods. This approach results in a hybrid model for the growth and uptake rates that can be used to predict the dynamic operation of the bioreactor. Here we develop a hybrid model to describe the continuous production of PHA by Pseudomonas putida GPo1 culture. After training, the model with experimental data gained under different dilution rates and medium compositions, we demonstrate how the model can describe the process in a wide range of operating conditions, including both single and dual nutrient-limited growth. Full article
(This article belongs to the Special Issue Advanced Modeling of Biomanufacturing Processes)
►▼ Show Figures

Graphical abstract

31 pages, 4843 KiB  
Article
Estimating the Methane Potential of Energy Crops: An Overview on Types of Data Sources and Their Limitations
by Yue Zhang, Sigrid Kusch-Brandt, Andrew M. Salter and Sonia Heaven
Processes 2021, 9(9), 1565; https://doi.org/10.3390/pr9091565 - 1 Sep 2021
Cited by 18 | Viewed by 7349
Abstract
As the anaerobic digestion of energy crops and crop residues becomes more widely applied for bioenergy production, planners and operators of biogas plants, and farmers who consider growing such crops, have a need for information on potential biogas and methane yields. A rich [...] Read more.
As the anaerobic digestion of energy crops and crop residues becomes more widely applied for bioenergy production, planners and operators of biogas plants, and farmers who consider growing such crops, have a need for information on potential biogas and methane yields. A rich body of literature reports methane yields for a variety of such materials. These data have been obtained with different testing methods. This work elaborates an overview on the types of data source available and the methods that are commonly applied to determine the methane yield of an agricultural biomass, with a focus on European crops. Limitations regarding the transferability and generalisation of data are explored, and crop methane values presented across the literature are compared. Large variations were found for reported values, which can only partially be explained by the methods applied. Most notably, the intra-crop variation of methane yield (reported values for a single crop type) was higher than the inter-crop variation (variation between different crops). The pronounced differences in reported methane yields indicate that relying on results from individual assays of candidate materials is a high-risk approach for planning biogas operations, and the ranges of values such as those presented here are essential to provide a robust basis for estimation. Full article
(This article belongs to the Special Issue New Frontiers in Anaerobic Digestion (AD) Processes)
►▼ Show Figures

Figure 1

67 pages, 6075 KiB  
Review
Computational Fluid Dynamics Modelling of Liquid–Solid Slurry Flows in Pipelines: State-of-the-Art and Future Perspectives
by Gianandrea Vittorio Messa, Qi Yang, Oluwaseun Ezekiel Adedeji, Zdeněk Chára, Carlos Antonio Ribeiro Duarte, Václav Matoušek, Maria Graça Rasteiro, R. Sean Sanders, Rui C. Silva and Francisco José de Souza
Processes 2021, 9(9), 1566; https://doi.org/10.3390/pr9091566 - 1 Sep 2021
Cited by 55 | Viewed by 13181
Abstract
Slurry pipe transport has directed the efforts of researchers for decades, not only for the practical impact of this problem, but also for the challenges in understanding and modelling the complex phenomena involved. The increase in computer power and the diffusion of multipurpose [...] Read more.
Slurry pipe transport has directed the efforts of researchers for decades, not only for the practical impact of this problem, but also for the challenges in understanding and modelling the complex phenomena involved. The increase in computer power and the diffusion of multipurpose codes based on Computational Fluid Dynamics (CFD) have opened up the opportunity to gather information on slurry pipe flows at the local level, in contrast with the traditional approaches of simplified theoretical modelling which are mainly based on a macroscopic description of the flow. This review paper discusses the potential of CFD for simulating slurry pipe flows. A comprehensive description of the modelling methods will be presented, followed by an overview of significant publications on the topic. However, the main focus will be the assessment of the potential and the challenges of the CFD approach, underlying the essential interplay between CFD simulations and experiments, discussing the main sources of uncertainty of CFD models, and evaluating existing models based on their interpretative or predictive capacity. This work aims at providing a solid ground for students, academics, and professional engineers dealing with slurry pipe transport, but it will also provide a methodological approach that goes beyond the specific application. Full article
(This article belongs to the Section Process Control and Monitoring)
►▼ Show Figures

Figure 1

15 pages, 1611 KiB  
Article
Gas to Liquids Techno-Economics of Associated Natural Gas, Bio Gas, and Landfill Gas
by Federico Galli, Jun-Jie Lai, Jacopo De Tommaso, Gianluca Pauletto and Gregory S. Patience
Processes 2021, 9(9), 1568; https://doi.org/10.3390/pr9091568 - 1 Sep 2021
Cited by 18 | Viewed by 5273
Abstract
Methane is the second highest contributor to the greenhouse effect. Its global warming potential is 37 times that of CO2. Flaring-associated natural gas from remote oil reservoirs is currently the only economical alternative. Gas-to-liquid (GtL) technologies first convert natural gas into [...] Read more.
Methane is the second highest contributor to the greenhouse effect. Its global warming potential is 37 times that of CO2. Flaring-associated natural gas from remote oil reservoirs is currently the only economical alternative. Gas-to-liquid (GtL) technologies first convert natural gas into syngas, then it into liquids such as methanol, Fischer–Tropsch fuels or dimethyl ether. However, studies on the influence of feedstock composition are sparse, which also poses technical design challenges. Here, we examine the techno-economic analysis of a micro-refinery unit (MRU) that partially oxidizes methane-rich feedstocks and polymerizes the syngas formed via Fischer–Tropsch reaction. We consider three methane-containing waste gases: natural gas, biogas, and landfill gas. The FT fuel selling price is critical for the economy of the unit. A Monte Carlo simulation assesses the influence of the composition on the final product quantity as well as on the capital and operative expenses. The Aspen Plus simulation and Python calculate the net present value and payback time of the MRU for different price scenarios. The CO2 content in biogas and landfill gas limit the CO/H2 ratio to 1.3 and 0.9, respectively, which increases the olefins content of the final product. Compressors are the main source of capital cost while the labor cost represents 20–25% of the variable cost. An analysis of the impact of the plant dimension demonstrated that the higher number represents a favorable business model for this unit. A minimal production of 7,300,000 kg y−1 is required for MRU to have a positive net present value after 10 years when natural gas is the feedstock. Full article
(This article belongs to the Special Issue Innovation in Chemical Plant Design)
►▼ Show Figures

Figure 1

15 pages, 5510 KiB  
Article
Towards the Circular Economy of Rare Earth Elements: Lanthanum Leaching from Spent FCC Catalyst by Acids
by Corradino Sposato, Enrico Catizzone, Alessandro Blasi, Marilena Forte, Assunta Romanelli, Massimo Morgana, Giacobbe Braccio, Girolamo Giordano and Massimo Migliori
Processes 2021, 9(8), 1369; https://doi.org/10.3390/pr9081369 - 5 Aug 2021
Cited by 11 | Viewed by 4988
Abstract
Rare earth elements (REEs) are strategic materials widely used in different applications from Information and Communication Technologies (ICT) to catalysis, which are expected to grow more in the future. In order to reduce the impact of market price and reduce the environmental effect [...] Read more.
Rare earth elements (REEs) are strategic materials widely used in different applications from Information and Communication Technologies (ICT) to catalysis, which are expected to grow more in the future. In order to reduce the impact of market price and reduce the environmental effect from soil extraction, recovery/purification strategies should be exploited. This paper presents a combined acid-leaching/oxalate precipitation process to recover lanthanum from spent FCC catalyst using nitric acid. Preferred to hydrochloric and sulphuric acid (preliminary assessed), HNO3 showed a good capability to completely leach lanthanum. The combination with an oxalate precipitation step allowed demonstrating that a highly pure (>98% w/w) lanthanum solid can be recovered, with a neglectable amount of poisoning metals (Ni, V) contained into the spent catalyst. This could open a reliable industrial perspective to recover and purify REE in the view of a sustainable recycling strategy. Full article
(This article belongs to the Special Issue Treatment and Utilization of Waste Materials)
►▼ Show Figures

Figure 1

15 pages, 2880 KiB  
Article
Exploring Electrochemically Mediated ATRP of Styrene
by Francesco De Bon, Gian Marco Carlan, Enrico Tognella and Abdirisak Ahmed Isse
Processes 2021, 9(8), 1327; https://doi.org/10.3390/pr9081327 - 30 Jul 2021
Cited by 6 | Viewed by 2976
Abstract
Electrochemically mediated atom transfer radical polymerization (eATRP) of styrene was studied in detail by using CuBr2/TPMA (TPMA = tris(2-pyridylmethyl)amine) as a catalyst. Redox properties of various Cu(II) species were investigated in CH3CN, dimethylformamide (DMF), and dimethyl sulfoxide [...] Read more.
Electrochemically mediated atom transfer radical polymerization (eATRP) of styrene was studied in detail by using CuBr2/TPMA (TPMA = tris(2-pyridylmethyl)amine) as a catalyst. Redox properties of various Cu(II) species were investigated in CH3CN, dimethylformamide (DMF), and dimethyl sulfoxide (DMSO) both in the absence and presence of 50% (v/v) styrene. This investigation together with preliminary eATRP experiments at 80 °C indicated DMF as the best solvent. The effects of catalyst, monomer, and initiator concentrations were also examined. The livingness of the polymerization was studied by chain extension and electrochemical temporal control of polymerization. Full article
(This article belongs to the Special Issue Engineering Reversible Deactivation Radical Polymerization in the Second Century of Macromolecular Science)
►▼ Show Figures

Figure 1

17 pages, 9241 KiB  
Article
Impact of Ballast Fouling on the Mechanical Properties of Railway Ballast: Insights from Discrete Element Analysis
by Luyu Wang, Mohamed Meguid and Hani S. Mitri
Processes 2021, 9(8), 1331; https://doi.org/10.3390/pr9081331 - 30 Jul 2021
Cited by 15 | Viewed by 3637
Abstract
Ballast fouling is a major factor that contributes to the reduction of shear strength of railway ballast, which can further affect the stability of railway supporting structure. The major sources of ballast fouling include infiltration of foreign fines into the ballast material and [...] Read more.
Ballast fouling is a major factor that contributes to the reduction of shear strength of railway ballast, which can further affect the stability of railway supporting structure. The major sources of ballast fouling include infiltration of foreign fines into the ballast material and ballast degradation induced by train movement on the supported tracks. In this paper, a discrete element model is developed and used to simulate the shear stress–strain response of fouled ballast assembly subjected to direct shear loading. A simplified computational approach is then proposed to model the induced ballast fouling and capture the mechanical response of the ballast at various levels of contamination. The approach is based on the assumption that fine particles comprising the fouling material will not only change the interparticle friction angle, but also the contact stiffness between the ballast particles. Therefore, both the interparticle friction coefficient and effective modulus are adjusted based on a fouled ballast model that is validated using experimental results. The effect of ballast degradation is also investigated by gradually changing the particle size distribution of the ballast assembly in the discrete element model to account for the increased range of particle sizes. Using the developed model, the effect of ballast degradation on the shear strength is then evaluated. Conclusions are made to highlight the suitability of these approximate approaches in efficiently modeling ballast assemblies under shear loading conditions. Full article
(This article belongs to the Special Issue Numerical Modeling in Civil and Mining Geotechnical Engineering)
►▼ Show Figures

Figure 1

14 pages, 2837 KiB  
Article
Microbial Fuel Cell as a Bioelectrochemical Sensor of Nitrite Ions
by Arnas Klevinskas, Kristina Kantminienė, Nerita Žmuidzinavičienė, Ilona Jonuškienė and Egidijus Griškonis
Processes 2021, 9(8), 1330; https://doi.org/10.3390/pr9081330 - 30 Jul 2021
Cited by 14 | Viewed by 3207
Abstract
The deteriorating environmental quality requires a rapid in situ real-time monitoring of toxic compounds in environment including water and wastewater. One of the most toxic nitrogen-containing ions is nitrite ion, therefore, it is particularly important to ensure that nitrite ions are completely absent [...] Read more.
The deteriorating environmental quality requires a rapid in situ real-time monitoring of toxic compounds in environment including water and wastewater. One of the most toxic nitrogen-containing ions is nitrite ion, therefore, it is particularly important to ensure that nitrite ions are completely absent in surface and ground waters as well as in wastewater or, at least, their concentration does not exceed permissible levels. However, no selective ion electrode, which would enable continuous measurement of nitrite ion concentration in wastewater by bioelectrochemical sensor, is available. Microbial fuel cell (MFC)-based biosensor offers a sustainable low-cost alternative to the monitoring by periodic sampling for laboratory testing. It has been determined, that at low (0.01–0.1 mg·L−1) and moderate (1.0–10 mg·L−1) concentration of nitrite ions in anolyte-model wastewater, the voltage drop in MFC linearly depends on the logarithm of nitrite ion concentration of proving the potential of the application of MFC-based biosensor for the quantitative monitoring of nitrite ion concentration in wastewater and other surface water. Higher concentrations (100–1000 mg·L−1) of nitrite ions in anolyte-model wastewater could not be accurately quantified due to a significant drop in MFC voltage. In this case MFC can potentially serve as a bioelectrochemical early warning device for extremely high nitrite pollution. Full article
(This article belongs to the Special Issue Advanced Applications, Processes, and Materials in Microbial Electrochemical Technologies)
►▼ Show Figures

Figure 1

13 pages, 5876 KiB  
Article
Effect of  Nb5+ and In3+  Ions on Moisture Sensitivity of Electrospun Titanium/Tungsten Oxide Nanostructures: Microstructural Characterization and Electrical Response
by Georgenes M. G. Silva, Victor N. S. Leão, Michel F. G. Pereira, Pedro M. Faia and Evando S. Araújo
Processes 2021, 9(8), 1336; https://doi.org/10.3390/pr9081336 - 30 Jul 2021
Cited by 2 | Viewed by 2417
Abstract
In this work, Nb5+ and In3+ ions were used as dopants in titanium/tungsten oxide nanostructures that are produced by the electrospinning and sintering process, for relative humidity (RH) detection. The microstructural properties were investigated [...] Read more.
In this work, Nb5+ and In3+ ions were used as dopants in titanium/tungsten oxide nanostructures that are produced by the electrospinning and sintering process, for relative humidity (RH) detection. The microstructural properties were investigated by SEM, EDS, XRD, Raman and FTIR techniques. The electrical response characterization of the samples was performed by electrical impedance spectroscopy in the range of 400 Hz to 40 MHz, at 20 °C. The sensors sensitivity to moisture was evaluated in terms of the impedance variations to RH (10–100%). The combined analysis of the microstructural characterization results confirmed the surface interaction between the oxides and the ions incorporation in Ti crystal lattice. All the studied sensors showed a conduction transition from p- to n-type at around 30–40% RH: besides, they also displayed better sensitivity to moisture than those obtained in a previous work using titanium/tungsten combination using a different fabricationn route. The impedance modulus variation up to 1.1 and 1.3 orders of magnitude for the 4 wt % niobium and indium doped samples, respectively. The results are directly associated with the microstructure and alternative preparation process. Full article
(This article belongs to the Special Issue Design Processes via Manipulation of Nanoparticles and Their Suitability for Gas Sensors)
►▼ Show Figures

Figure 1

16 pages, 2239 KiB  
Article
IP Analytics and Machine Learning Applied to Create Process Visualization Graphs for Chemical Utility Patents
by Amy J. C. Trappey, Charles V. Trappey, Chih-Ping Liang and Hsin-Jung Lin
Processes 2021, 9(8), 1342; https://doi.org/10.3390/pr9081342 - 30 Jul 2021
Cited by 5 | Viewed by 4291
Abstract
Researchers must read and understand a large volume of technical papers, including patent documents, to fully grasp the state-of-the-art technological progress in a given domain. Chemical research is particularly challenging with the fast growth of newly registered utility patents (also known as intellectual [...] Read more.
Researchers must read and understand a large volume of technical papers, including patent documents, to fully grasp the state-of-the-art technological progress in a given domain. Chemical research is particularly challenging with the fast growth of newly registered utility patents (also known as intellectual property or IP) that provide detailed descriptions of the processes used to create a new chemical or a new process to manufacture a known chemical. The researcher must be able to understand the latest patents and literature in order to develop new chemicals and processes that do not infringe on existing claims and processes. This research uses text mining, integrated machine learning, and knowledge visualization techniques to effectively and accurately support the extraction and graphical presentation of chemical processes disclosed in patent documents. The computer framework trains a machine learning model called ALBERT for automatic paragraph text classification. ALBERT separates chemical and non-chemical descriptive paragraphs from a patent for effective chemical term extraction. The ChemDataExtractor is used to classify chemical terms, such as inputs, units, and reactions from the chemical paragraphs. A computer-supported graph-based knowledge representation interface is developed to plot the extracted chemical terms and their chemical process links as a network of nodes with connecting arcs. The computer-supported chemical knowledge visualization approach helps researchers to quickly understand the innovative and unique chemical or processes of any chemical patent of interest. Full article
(This article belongs to the Special Issue Recent Advances in Machine Learning and Applications)
►▼ Show Figures

Figure 1

38 pages, 2821 KiB  
Review
A Bibliometric Survey on Polyisobutylene Manufacture
by Jessica B. Alves, Mateus K. Vasconcelos, Lys H. R. Mangia, Maxmiliano Tatagiba, Juliana Fidalgo, Daniela Campos, Pedro L. Invernici, Marcio V. Rebouças, Marcio Henrique S. Andrade and José Carlos Pinto
Processes 2021, 9(8), 1315; https://doi.org/10.3390/pr9081315 - 29 Jul 2021
Cited by 13 | Viewed by 6281
Abstract
Polyisobutylenes (PIB) constitute a versatile family of polymer materials that have been used mainly as fuel and lubricant additives. Particularly, the current commercial demand for highly reactive polyisobutylene (HR-PIB) products motivates the development of new processes and procedures to produce PIBs with high [...] Read more.
Polyisobutylenes (PIB) constitute a versatile family of polymer materials that have been used mainly as fuel and lubricant additives. Particularly, the current commercial demand for highly reactive polyisobutylene (HR-PIB) products motivates the development of new processes and procedures to produce PIBs with high polymer yields, narrow molar mass distributions and high vinyl contents. For this reason, a bibliometric survey is presented here to map and discuss important technical aspects and technological trends in the field of solution cationic polymerization of isobutylenes. It is shown that investigations in this field are concentrated mainly on developed countries and that industrial initiatives indicate high commercial interest and significant investments in the field. It is also shown that use of catalyst systems based on AlCl3 and ether cocatalysts can be very beneficial for PIB and HR-PIB manufacture. Finally, it is shown that investigations search for cheaper and environmentally friendly catalysts and solvents that can be employed at moderate temperatures, particularly for the production of HR-PIB. Full article
(This article belongs to the Special Issue Feature Review Papers in Advanced Process Systems Engineering)
►▼ Show Figures

Figure 1

22 pages, 6987 KiB  
Article
Microfluidic Network Simulations Enable On-Demand Prediction of Control Parameters for Operating Lab-on-a-Chip-Devices
by Julia Sophie Böke, Daniel Kraus and Thomas Henkel
Processes 2021, 9(8), 1320; https://doi.org/10.3390/pr9081320 - 29 Jul 2021
Cited by 4 | Viewed by 5058
Abstract
Reliable operation of lab-on-a-chip systems depends on user-friendly, precise, and predictable fluid management tailored to particular sub-tasks of the microfluidic process protocol and their required sample fluids. Pressure-driven flow control, where the sample fluids are delivered to the chip from pressurized feed vessels, [...] Read more.
Reliable operation of lab-on-a-chip systems depends on user-friendly, precise, and predictable fluid management tailored to particular sub-tasks of the microfluidic process protocol and their required sample fluids. Pressure-driven flow control, where the sample fluids are delivered to the chip from pressurized feed vessels, simplifies the fluid management even for multiple fluids. The achieved flow rates depend on the pressure settings, fluid properties, and pressure-throughput characteristics of the complete microfluidic system composed of the chip and the interconnecting tubing. The prediction of the required pressure settings for achieving given flow rates simplifies the control tasks and enables opportunities for automation. In our work, we utilize a fast-running, Kirchhoff-based microfluidic network simulation that solves the complete microfluidic system for in-line prediction of the required pressure settings within less than 200 ms. The appropriateness of and benefits from this approach are demonstrated as exemplary for creating multi-component laminar co-flow and the creation of droplets with variable composition. Image-based methods were combined with chemometric approaches for the readout and correlation of the created multi-component flow patterns with the predictions obtained from the solver. Full article
(This article belongs to the Special Issue Microfluidics in Chemical Engineering)
►▼ Show Figures

Figure 1

28 pages, 2622 KiB  
Article
Effects of Dynamic Pricing on the Design and Operation of Distributed Energy Resource Networks
by Tim Sidnell, Bogdan Dorneanu, Evgenia Mechleri, Vassilios S. Vassiliadis and Harvey Arellano-Garcia
Processes 2021, 9(8), 1306; https://doi.org/10.3390/pr9081306 - 28 Jul 2021
Cited by 6 | Viewed by 2761
Abstract
This paper presents a framework for the use of variable pricing to control electricity imported/exported to/from both fixed and unfixed residential distributed energy resource (DER) network designs. The framework shows that networks utilizing much of their own energy, and importing little from the [...] Read more.
This paper presents a framework for the use of variable pricing to control electricity imported/exported to/from both fixed and unfixed residential distributed energy resource (DER) network designs. The framework shows that networks utilizing much of their own energy, and importing little from the national grid, are barely affected by dynamic import pricing, but are encouraged to sell more by dynamic export pricing. An increase in CO2 emissions per kWh of energy produced is observed for dynamic import and export, against a baseline configuration utilizing constant pricing. This is due to feed-in tariffs (FITs) that encourage CHP generation over lower-carbon technologies. Furthermore, batteries are shown to be expensive in systems receiving income from FITs and grid exports, but for the cases when they sell to/buy from the grid using dynamic pricing, their use in the networks becomes more economical. Full article
(This article belongs to the Special Issue Bioinspired Computation for Sustainable Energy Systems)
►▼ Show Figures

Figure 1

15 pages, 2526 KiB  
Article
Fluctuation and Re-Establishment of Aerobic Granules Properties during the Long-Term Operation Period with Low-Strength and Low C/N Ratio Wastewater
by Lijuan Cha, Yong-Qiang Liu, Wenyan Duan, Christain E. W. Sternberg, Qiangjun Yuan and Fangyuan Chen
Processes 2021, 9(8), 1290; https://doi.org/10.3390/pr9081290 - 26 Jul 2021
Cited by 7 | Viewed by 2863
Abstract
Long-term structure stability of aerobic granules is critical to maintaining stable wastewater treatment performance. In this study, granulation and long-term stability of sludge-treating synthetic wastewater with a low chemical oxygen demand to nitrogen (COD/N) ratio of 4:1 and COD concentration of 400 mg/L [...] Read more.
Long-term structure stability of aerobic granules is critical to maintaining stable wastewater treatment performance. In this study, granulation and long-term stability of sludge-treating synthetic wastewater with a low chemical oxygen demand to nitrogen (COD/N) ratio of 4:1 and COD concentration of 400 mg/L in anoxic-oxic conditions were investigated for over 300 days. Inoculated suspended sludge gradually transformed into granules-dominant sludge on day 80. Due to the improved sludge volume index after 30 min settling (SVI30), mixed liquor suspended solids (MLSS) reached 5.2 g/L on day 140. Without any external intervention or disturbance, aerobic granules started to disintegrate from day 140, causing the increase in SVI and the decrease in biomass concentration until day 210, with the average sludge size reduced to 243 µm. From day 210, granular sludge started to be re-established by re-granulation, and the average granule size increased to 500 µm on day 302. During these disintegration and re-granulation periods, there was no obvious difference in terms of COD removal and nitrification, but microbial species were found more diverse after the re-granulation, with Thauera and Sphingomonas dominant. Although there was no external intervention, the food to microorganisms ratio (F/M) varied significantly due to the changes in biomass concentration caused by strong selective pressure and the change of sludge-settling ability in the reactor. F/M ratios should be controlled between 0.3 and 1.0 gCOD/gSS·d to maintain the stable structure of granules to minimize the fluctuation of sludge properties under the conditions used in this study. Although aerobic granular sludge is able to re-establish itself after disintegration, controlling F/M ratios in a certain range would benefit long-term stability. The findings in this study are significant to deepen the understanding of granule stability with low-strength and low COD ratio wastewater and, thus, provide guidance for maintaining the long-term stability of granules. Full article
(This article belongs to the Section Environmental and Green Processes)
►▼ Show Figures

Figure 1

13 pages, 858 KiB  
Article
Evaluation of the PGPR Capacity of Four Bacterial Strains and Their Mixtures, Tested on Lupinus albus var. Dorado Seedlings, for the Bioremediation of Mercury-Polluted Soils
by Daniel González, Carlota Blanco, Agustín Probanza, Pedro A. Jiménez and Marina Robas
Processes 2021, 9(8), 1293; https://doi.org/10.3390/pr9081293 - 26 Jul 2021
Cited by 12 | Viewed by 3311
Abstract
Soil contamination by mercury, which is one of the most toxic heavy metals due to its bioaccumulative capacity, poses a risk to the environment as well as health. The Almadén mining district in Ciudad Real, Spain is one of the most heavily-polluted sites [...] Read more.
Soil contamination by mercury, which is one of the most toxic heavy metals due to its bioaccumulative capacity, poses a risk to the environment as well as health. The Almadén mining district in Ciudad Real, Spain is one of the most heavily-polluted sites in the world, making the soils unusable. Bioremediation, and more specifically phyto-rhizoremediation, based on the synergistic interaction established between plant and Plant Growth Promoting Rhizobacteria (PGPR), improves the plant’s ability to grow, mobilize, accumulate, and extract contaminants from the soil. The objective of this study is to evaluate the plant growth-promoting ability of four PGPR strains (and mixtures), isolated from the bulk soil and rhizosphere of naturally grown plants in the Almadén mining district, when they are inoculated in emerged seeds of Lupinus albus, var. Dorado in the presence of high concentrations of mercury. After 20 days of incubation and subsequent harvesting of the seedlings, biometric measurements were carried out at the root and aerial levels. The results obtained show that the seeds treatment with PGPR strains improves plants biometry in the presence of mercury. Specifically, strain B2 (Pseudomonas baetica) and B1 (Pseudomonas moraviensis) were those that contributed the most to plant growth, both individually and as part of mixtures (CS5 and CS3). Thus, these are postulated to be good candidates for further in situ phyto-rhizoremediation tests of mercury-contaminated soils. Full article
(This article belongs to the Special Issue Innovative Treatments for the Improvement of Bioremediation Processes)
►▼ Show Figures

Figure 1

17 pages, 1715 KiB  
Article
An Imperfect Production–Inventory Model with Mixed Materials Containing Scrap Returns Based on a Circular Economy
by Rung-Hung Su, Ming-Wei Weng, Chih-Te Yang and Hsin-Ting Li
Processes 2021, 9(8), 1275; https://doi.org/10.3390/pr9081275 - 24 Jul 2021
Cited by 15 | Viewed by 3216
Abstract
The implementation of scrap recovery activities has been shown to improve the financial performance of many firms, and this kind of circular economy (CE) is particularly evident in industries with green manufacturing (GM). In this paper, we consider an imperfect multiple-stage production system [...] Read more.
The implementation of scrap recovery activities has been shown to improve the financial performance of many firms, and this kind of circular economy (CE) is particularly evident in industries with green manufacturing (GM). In this paper, we consider an imperfect multiple-stage production system that manufactures paired products made from mixed materials containing scrap returns, in which the scrap returns are converted from defective products. The feed rates of scrap returns for two products are different, and the product with the higher feed rate is placed in the second order of the process to avoid unlimited accumulation of scrap returns. The proposed problem is formulated as a joint economic order quantity (EOQ) and economic production quantity (EPQ) model aimed at cost minimization. The decision variables of the proposed model include the production run time of two products, order quantity of new material, and the extent of investment in converted equipment. We also prove that the optimal solution exists uniquely and provide an algorithm for the computation of the optimal solution. Finally, a numerical example involving the pulp and paper manufacturing industry is provided to illustrate the solution process, and the results of its sensitivity analysis are also presented to show some managerial implications. Full article
(This article belongs to the Collection Tools, Approaches and Modeling in Sustainable Supply Chain Management)
►▼ Show Figures

Figure 1

14 pages, 3718 KiB  
Article
Influence of Freezing Parameters on the Formation of Internal Porous Structure and Its Impact on Freeze-Drying Kinetics
by Patrick Levin, Vincent Meunier, Ulrich Kessler and Stefan Heinrich
Processes 2021, 9(8), 1273; https://doi.org/10.3390/pr9081273 - 23 Jul 2021
Cited by 13 | Viewed by 4015
Abstract
The main objective of this study was firstly to investigate the influence of freezing process parameters on the formation of the internal structure of frozen coffee granules. It was investigated how these frozen internal structures affect the drying kinetics during freeze-drying. A design [...] Read more.
The main objective of this study was firstly to investigate the influence of freezing process parameters on the formation of the internal structure of frozen coffee granules. It was investigated how these frozen internal structures affect the drying kinetics during freeze-drying. A design of experiment study was carried out using the response surface method to quantify the influence of the freezing step that occurs in a scraped surface heat exchanger (SSHE). Therefore, the coffee extract at a concentration of 30% w/w is entering the SSHE as a liquid and gets partially crystallized up to a weight-based ice content of 0.364. During this step, the influence of factors like cooling temperature, scraper rotation speed and temperature cycles on ice crystal structure was investigated. In a second freezing step, the influence of freezing rates during hardening of the product by air-blast freezing is investigated, where the freezing rate is significantly affected by the cake thickness. The produced frozen granules were freeze-dried in single layer experiments. During drying the influence of internal structure on the drying kinetics was investigated. Results show that all factors have a significant impact on structure parameters for 30% w/w coffee solutions. A lower degree of supercooling during freezing in an SSHE, a higher number of temperature cycles (2 to 8 times) and lower freezing rates during hardening (2 °C/min to 10 °C/min) were leading to increased crystal size. This increase accelerates the primary drying rate and decreases the total drying time. A higher number of temperature cycles leads to a significant increase of crystal size and therefore larger pore size at the end of the primary drying. Furthermore, in combination with temperature cycles in the SSHE, it was found that high freezing rates during air blast freezing generally lead to a second nucleation step of ice crystals. Full article
(This article belongs to the Special Issue Modern Freeze Drying Design for More Efficient Processes)
►▼ Show Figures

Graphical abstract

11 pages, 1581 KiB  
Article
Influence of Process Design on the Preparation of Solid Lipid Nanoparticles by an Ultrasonic-Nanoemulsification Method
by Agata Pucek-Kaczmarek
Processes 2021, 9(8), 1265; https://doi.org/10.3390/pr9081265 - 22 Jul 2021
Cited by 16 | Viewed by 4167
Abstract
In recent years, lipid-based nanosystems have emerged as a promising class of nanocarriers for encapsulating many active agents. Solid lipid nanoparticles (SLNs) provide good stability (colloidal as well as physical) and high biocompatibility. Appropriate design of the carrier structure through a selection of [...] Read more.
In recent years, lipid-based nanosystems have emerged as a promising class of nanocarriers for encapsulating many active agents. Solid lipid nanoparticles (SLNs) provide good stability (colloidal as well as physical) and high biocompatibility. Appropriate design of the carrier structure through a selection of components and preparation methods allows us to obtain formulations with desired physicochemical parameters and biological properties. The present contribution has been carried out to investigate SLNs containing biocompatible phosphatidylcholine mixed with non-ionic surfactant Tween 60 as stabilizing agents. The internal lipid phase consisted of glyceryl monostearate was confirmed as safe for drug delivery by the Food and Drug Administration. The SLNs were fabricated by ultrasonic-nanoemulsification method. The preparation process was optimized in regard to variable parameters such as ultrasonication time and used amplitude and number of cycles. The sizes of the studied nanoparticles along with the size distribution were determined by dynamic light scattering (DLS), while shape and morphology were determined by atomic force microscopy (AFM) and transmission electron microscopy (TEM). The colloidal stability was measured by a turbidimetric method. The physical state of SLNs was characterized using differential scanning calorimetry (DSC). The obtained results indicate that the proposed SLNs may provide great potential for design and preparation of novel delivery nanosystems with a variety of possible applications. Full article
(This article belongs to the Special Issue Nanoemulsion Processes Design and Applications)
►▼ Show Figures

Graphical abstract

27 pages, 2158 KiB  
Review
Capture of Acidic Gases from Flue Gas by Deep Eutectic Solvents
by Yan Wang, Shuhang Ren, Yucui Hou and Weize Wu
Processes 2021, 9(8), 1268; https://doi.org/10.3390/pr9081268 - 22 Jul 2021
Cited by 27 | Viewed by 4011
Abstract
Up to now, many kinds of deep eutectic solvents (DESs) were investigated for the capture of acidic gases from flue gases. In this review, non-functionalized and functionalized DESs, including binary and ternary DESs, for SO2, CO2 and NO capture, are [...] Read more.
Up to now, many kinds of deep eutectic solvents (DESs) were investigated for the capture of acidic gases from flue gases. In this review, non-functionalized and functionalized DESs, including binary and ternary DESs, for SO2, CO2 and NO capture, are summarized based on the mechanism of absorption, physical interaction or chemical reaction. New strategies for improving the absorption capacity are introduced in this review. For example, a third component can be introduced to form a ternary DES to suppress the increase in viscosity and improve the CO2 absorption capacity. DESs, synthesized with halogen salt hydrogen bond acceptors (HBAs) and functionalized hydrogen bond donors (HBDs), can be used for the absorption of SO2 and NO with high absorption capacities and low viscosities after absorption, due to physicochemical interaction between gases and DESs. Emphasis is given to introducing the absorption capacities of acidic gases in these DESs, the mechanism of the absorption, and the ways to enhance the absorption capacity. Full article
(This article belongs to the Special Issue Advances in Deep Eutectic Solvents: New Green Solvents)
►▼ Show Figures

Figure 1

11 pages, 2519 KiB  
Article
Aluminum-Free Steelmaking: Desulfurization and Nonmetallic Inclusion Evolution of Si-Killed Steel in Contact with CaO-SiO2-CaF2-MgO Slag
by Stephano P. T. Piva and Petrus Christiaan Pistorius
Processes 2021, 9(8), 1258; https://doi.org/10.3390/pr9081258 - 21 Jul 2021
Cited by 3 | Viewed by 4953
Abstract
In some applications, deep desulfurization and deoxidation of steels without the use of aluminum are required, using Si as a deoxidant instead, with double-saturated slags in the CaO-SiO2-CaF2-MgO system. This work studied the desulfurization and nonmetallic inclusion evolution for [...] Read more.
In some applications, deep desulfurization and deoxidation of steels without the use of aluminum are required, using Si as a deoxidant instead, with double-saturated slags in the CaO-SiO2-CaF2-MgO system. This work studied the desulfurization and nonmetallic inclusion evolution for the system using an induction furnace and compared the results with FactSage kinetic simulations. Steel samples were taken from the steel melt and analyzed with ICP-MS and combustion analysis for chemistry, and SEM/EDS for nonmetallic inclusion quantity, size, and composition. The results indicate that the steel was deeply desulfurized, with a final sulfur partition coefficient of 580; MgO was reduced from the slag, yielding dissolved [Mg] that transformed liquid Mn–silicate inclusions into forsterite and MgO. Intentional reoxidation of the melt with oxidized electrolytic iron demonstrated a significant concentration of dissolved [Mg] in the steel, by the formation of additional forsterite and MgO upon reoxidation. Full article
(This article belongs to the Section Process Control and Monitoring)
►▼ Show Figures

Figure 1

19 pages, 1536 KiB  
Article
Advanced Kinetic Modeling of Bio-co-polymer Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) Production Using Fructose and Propionate as Carbon Sources
by Stefanie Duvigneau, Robert Dürr, Jessica Behrens and Achim Kienle
Processes 2021, 9(8), 1260; https://doi.org/10.3390/pr9081260 - 21 Jul 2021
Cited by 13 | Viewed by 3487
Abstract
Biopolymers are a promising alternative to petroleum-based plastic raw materials. They are bio-based, non-toxic and degradable under environmental conditions. In addition to the homopolymer poly(3-hydroxybutyrate) (PHB), there are a number of co-polymers that have a broad range of applications and are easier to [...] Read more.
Biopolymers are a promising alternative to petroleum-based plastic raw materials. They are bio-based, non-toxic and degradable under environmental conditions. In addition to the homopolymer poly(3-hydroxybutyrate) (PHB), there are a number of co-polymers that have a broad range of applications and are easier to process in comparison to PHB. The most prominent representative from this group of bio-copolymers is poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV). In this article, we show a new kinetic model that describes the PHBV production from fructose and propionic acid in Cupriavidus necator (C. necator). The developed model is used to analyze the effects of process parameter variations such as the CO2 amount in the exhaust gas and the feed rate. The presented model is a valuable tool to improve the microbial PHBV production process. Due to the coupling of CO2 online measurements in the exhaust gas to the biomass production, the model has the potential to predict the composition and the current yield of PHBV in the ongoing process. Full article
(This article belongs to the Special Issue Mathematical Modeling and Control of Bioprocesses)
►▼ Show Figures

Figure 1

16 pages, 1467 KiB  
Article
Prediction of Sugar Content in Port Wine Vintage Grapes Using Machine Learning and Hyperspectral Imaging
by Véronique Gomes, Marco S. Reis, Francisco Rovira-Más, Ana Mendes-Ferreira and Pedro Melo-Pinto
Processes 2021, 9(7), 1241; https://doi.org/10.3390/pr9071241 - 19 Jul 2021
Cited by 19 | Viewed by 4073
Abstract
The high quality of Port wine is the result of a sequence of winemaking operations, such as harvesting, maceration, fermentation, extraction and aging. These stages require proper monitoring and control, in order to consistently achieve the desired wine properties. The present work focuses [...] Read more.
The high quality of Port wine is the result of a sequence of winemaking operations, such as harvesting, maceration, fermentation, extraction and aging. These stages require proper monitoring and control, in order to consistently achieve the desired wine properties. The present work focuses on the harvesting stage, where the sugar content of grapes plays a key role as one of the critical maturity parameters. Our approach makes use of hyperspectral imaging technology to rapidly extract information from wine grape berries; the collected spectra are fed to machine learning algorithms that produce estimates of the sugar level. A consistent predictive capability is important for establishing the harvest date, as well as to select the best grapes to produce specific high-quality wines. We compared four different machine learning methods (including deep learning), assessing their generalization capacity for different vintages and varieties not included in the training process. Ridge regression, partial least squares, neural networks and convolutional neural networks were the methods considered to conduct this comparison. The results show that the estimated models can successfully predict the sugar content from hyperspectral data, with the convolutional neural network outperforming the other methods. Full article
(This article belongs to the Special Issue Emerging Trends in the Wine Ageing Process)
►▼ Show Figures

Figure 1

14 pages, 8598 KiB  
Article
Studies of the Anti-Diabetic Mechanism of Pueraria lobata Based on Metabolomics and Network Pharmacology
by Shu Zhang, Qi Ge, Liang Chen and Keping Chen
Processes 2021, 9(7), 1245; https://doi.org/10.3390/pr9071245 - 19 Jul 2021
Cited by 11 | Viewed by 4062
Abstract
Diabetes mellitus (DM), as a chronic disease caused by insulin deficiency or using obstacles, is gradually becoming a principal worldwide health problem. Pueraria lobata is one of the traditional Chinese medicinal and edible plants, playing roles in improving the cardiovascular system, lowering blood [...] Read more.
Diabetes mellitus (DM), as a chronic disease caused by insulin deficiency or using obstacles, is gradually becoming a principal worldwide health problem. Pueraria lobata is one of the traditional Chinese medicinal and edible plants, playing roles in improving the cardiovascular system, lowering blood sugar, anti-inflammation, anti-oxidation, and so on. Studies on the hypoglycemic effects of Pueraria lobata were also frequently reported. To determine the active ingredients and related targets of Pueraria lobata for DM, 256 metabolites were identified by LC/MS non targeted metabonomics, and 19 active ingredients interacting with 51 DM-related targets were screened. The results showed that puerarin, quercetin, genistein, daidzein, and other active ingredients in Pueraria lobata could participate in the AGE-RAGE signaling pathway, insulin resistance, HIF-1 signaling pathway, FoxO signaling pathway, and MAPK signaling pathway by acting on VEGFA, INS, INSR, IL-6, TNF and AKT1, and may regulate type 2 diabetes, inflammation, atherosis and diabetes complications, such as diabetic retinopathy, diabetic nephropathy, and diabetic cardiomyopathy. Full article
(This article belongs to the Special Issue Network Pharmacology Modelling for Drug Discovery)
►▼ Show Figures

Figure 1

21 pages, 23731 KiB  
Article
Bi-Functional Catalyst/Sorbent for a H2-Rich Gas from Biomass Gasification
by Francesca Micheli, Enrica Mattucci, Claire Courson and Katia Gallucci
Processes 2021, 9(7), 1249; https://doi.org/10.3390/pr9071249 - 19 Jul 2021
Cited by 8 | Viewed by 3044
Abstract
The aim of this work is to identify the effect of the CaO phase as a CO2 sorbent and mayenite (Ca12Al14O33) as a stabilizing phase in a bi-functional material for CO2 capture in biomass syngas [...] Read more.
The aim of this work is to identify the effect of the CaO phase as a CO2 sorbent and mayenite (Ca12Al14O33) as a stabilizing phase in a bi-functional material for CO2 capture in biomass syngas conditioning and cleaning at high temperature. The effect of different CaO weight contents is studied (0, 56, 85, 100 wt%) in sorbents synthesized by the wet mixing method. These high temperature solid sorbents are upgraded to bi-functional compounds by the addition of 3 or 6 wt% of nickel chosen as the metal active phase. N2 adsorption, X-ray diffraction, scanning electronic microscopy, temperature-programmed reduction analyses and CO2 sorption study were performed to characterize structural, textural, reducibility and sorption properties of bi-functional materials. Finally, sorption-enhanced reforming of toluene (chosen as tar model), of methane then of methane and toluene with bi-functional compounds were performed to study the best material to improve H2 content in a syngas, provided by steam biomass gasification. If the catalytic activity on the sorption enhanced reforming of methane exhibits a fast fall-down after 10–15 min of experimental test, the reforming of toluene reaches a constant conversion of 99.9% by using bi-functional materials. Full article
(This article belongs to the Special Issue Methane Reforming Processes)
►▼ Show Figures

Figure 1

13 pages, 2504 KiB  
Article
Ultra-Fast Electrochemical Sensor for Point-of-Care COVID-19 Diagnosis Using Non-Invasive Saliva Sampling
by Ashwin Ramanujam, Sharilyn Almodovar and Gerardine G. Botte
Processes 2021, 9(7), 1236; https://doi.org/10.3390/pr9071236 - 17 Jul 2021
Cited by 25 | Viewed by 5457
Abstract
Point-of-care diagnostic devices that are rapid and reliable remain as an unmet need highlighted by the coronavirus disease (COVID-19) pandemic crisis. The second/third wave of virus spread in various parts of the world combined with new evidence of re-infections and inadequate healthcare facilities [...] Read more.
Point-of-care diagnostic devices that are rapid and reliable remain as an unmet need highlighted by the coronavirus disease (COVID-19) pandemic crisis. The second/third wave of virus spread in various parts of the world combined with new evidence of re-infections and inadequate healthcare facilities demand increased testing rate to diagnose COVID-19 at its core. Although traditional molecular diagnostic tests have served this purpose, there have been shortage of reagents and other supplies at pandemic frontlines. This calls for novel alternate diagnostic processes with potential for obtaining emergency use authorization and that can be deployed in the field at the earliest opportunity. Here, we show an ultra-fast SARS-CoV-2 detection sensor for detecting coronavirus proteins in saliva within 100 milliseconds. Electrochemical oxidation of nickel hydroxide has been controlled using cyclic voltammetry and chronoamperometry techniques for successful detection of SARS-CoV-2. Test results have proven the capability of sensors to quantitatively detect the concentration of virus in blinded analyses. The detection occurs by a process similar to that of SARS-CoV-2 binding onto host cells. The sensor also shows prospects in distinguishing SARS-CoV-2 from other viruses such as HIV. More importantly, the sensor matches the detection limit of the gold standard test for diagnosing early infection. The use of saliva as a non-invasive sampling technique combined with the portability of the instrument has broadened the potential of this sensor. Full article
(This article belongs to the Special Issue Advanced Applications, Processes, and Materials in Microbial Electrochemical Technologies)
►▼ Show Figures

Figure 1

12 pages, 2832 KiB  
Article
Interactive Effects in Two-Droplets Combustion of RP-3 Kerosene under Sub-Atmospheric Pressure
by Hongtao Zhang, Zhihua Wang, Yong He, Jie Huang and Kefa Cen
Processes 2021, 9(7), 1229; https://doi.org/10.3390/pr9071229 - 16 Jul 2021
Cited by 10 | Viewed by 2814
Abstract
To improve our understanding of the interactive effects in combustion of binary multicomponent fuel droplets at sub-atmospheric pressure, combustion experiments were conducted on two fibre-supported RP-3 kerosene droplets at pressures from 0.2 to 1.0 bar. The burning life of the interactive droplets was [...] Read more.
To improve our understanding of the interactive effects in combustion of binary multicomponent fuel droplets at sub-atmospheric pressure, combustion experiments were conducted on two fibre-supported RP-3 kerosene droplets at pressures from 0.2 to 1.0 bar. The burning life of the interactive droplets was recorded by a high-speed camera and a mirrorless camera. The results showed that the flame propagation time from burning droplet to unburned droplet was proportional to the normalised spacing distance between droplets and the ambient pressure. Meanwhile, the maximum normalised spacing distance from which the left droplet can be ignited has been investigated under different ambient pressure. The burning rate was evaluated and found to have the same trend as the single droplet combustion, which decreased with the reduction in the pressure. For every experiment, the interactive coefficient was less than one owing to the oxygen competition, except for the experiment at L/D0 = 2.5 and P = 1.0 bar. During the interactive combustion, puffing and microexplosion were found to have a significant impact on secondary atomization, ignition and extinction. Full article
(This article belongs to the Special Issue Advanced Combustion and Combustion Diagnostic Techniques)
►▼ Show Figures

Figure 1

19 pages, 13452 KiB  
Article
Numerical Study of Electrostatic Desalting Process Based on Droplet Collision Time
by Marco A. Ramirez-Argaez, Diego Abreú-López, Jesús Gracia-Fadrique and Abhishek Dutta
Processes 2021, 9(7), 1226; https://doi.org/10.3390/pr9071226 - 15 Jul 2021
Cited by 5 | Viewed by 4302
Abstract
The desalting process of an electrostatic desalting unit was studied using the collision time of two droplets in a water-in-oil (W/O) emulsion based on force balance. Initially, the model was solved numerically to perform a process analysis and to indicate the effect of [...] Read more.
The desalting process of an electrostatic desalting unit was studied using the collision time of two droplets in a water-in-oil (W/O) emulsion based on force balance. Initially, the model was solved numerically to perform a process analysis and to indicate the effect of the main process parameters, such as electric field strength, water content, temperature (through oil viscosity) and droplet size on the collision time or frequency of collision between a pair of droplets. In decreasing order of importance on the reduction of collision time and consequently on the efficiency of desalting separation, the following variables can be classified such as moisture content, electrostatic field strength, oil viscosity and droplet size. After this analysis, a computational fluid dynamics (CFD) model of a biphasic water–oil flow was developed in steady state using a Eulerian multiphase framework, in which collision frequency and probability of coalescence of droplets were assumed. This study provides some insights into the heterogeneity of a desalination plant which highlights aspects of design performance. This study further emphasizes the importance of two variables as moisture content and intensity of electrostatic field for dehydrated desalination by comparing the simulation with the electrostatic field against the same simulation without its presence. The overall objective of this study is therefore to show the necessity of including complex phenomena such as the frequency of collisions and coalescence in a CFD model for better understanding and optimization of the desalting process from both process safety and improvement. Full article
(This article belongs to the Special Issue Process Design and Sustainable Development)
►▼ Show Figures

Figure 1

29 pages, 12765 KiB  
Article
Influence of Interfacial Force Models and Population Balance Models on the kLa Value in Stirred Bioreactors
by Stefan Seidel and Dieter Eibl
Processes 2021, 9(7), 1185; https://doi.org/10.3390/pr9071185 - 7 Jul 2021
Cited by 11 | Viewed by 4729
Abstract
Optimal oxygen supply is vitally important for the cultivation of aerobically growing cells, as it has a direct influence on cell growth and product formation. A process engineering parameter directly related to oxygen supply is the volumetric oxygen mass transfer coefficient [...] Read more.
Optimal oxygen supply is vitally important for the cultivation of aerobically growing cells, as it has a direct influence on cell growth and product formation. A process engineering parameter directly related to oxygen supply is the volumetric oxygen mass transfer coefficient kLa. It is the influences on kLa and computing time of different interfacial force and population balance models in stirred bioreactors that have been evaluated in this study. For this investigation, the OpenFOAM 7 open-source toolbox was utilized. Firstly, the Euler–Euler model with a constant bubble diameter was applied to a 2L scale bioreactor to statistically examine the influence of different interfacial models on the kLa value. It was shown that the kL model and the constant bubble diameter have the greatest influence on the calculated kLa value. To eliminate the problem of a constant bubble diameter and to take effects such as bubble breakup and coalescence into account, the Euler–Euler model was coupled with population balance models (PBM). For this purpose, four coalescence and five bubble breakup models were examined. Ultimately, it was established that, for all of the models tested, coupling computational fluid dynamics (CFD) with PBM resulted in better agreement with the experimental data than using the Euler–Euler model. However, it should be noted that the higher accuracy of the PBM coupled models requires twice the computation time. Full article
(This article belongs to the Special Issue Computational Fluid Dynamics: Modelling of Industrial Dispersed Systems)
►▼ Show Figures

Figure 1

29 pages, 4073 KiB  
Article
A Real-Time Optimization Strategy for Small-Scale Facilities and Implementation in a Gas Processing Unit
by Pedro A. Delou, Leonardo D. Ribeiro, Carlos R. Paiva, Jacques Niederberger, Marcos Vinícius C. Gomes and Argimiro R. Secchi
Processes 2021, 9(7), 1179; https://doi.org/10.3390/pr9071179 - 7 Jul 2021
Cited by 5 | Viewed by 4195
Abstract
The rise of new digital technologies and their applications in several areas pushes the process industry to update its methodologies with more intensive use of mathematical models—commonly denoted as digital twins—and artificial intelligence (AI) approaches to continuously enhance operational efficiency. In this context, [...] Read more.
The rise of new digital technologies and their applications in several areas pushes the process industry to update its methodologies with more intensive use of mathematical models—commonly denoted as digital twins—and artificial intelligence (AI) approaches to continuously enhance operational efficiency. In this context, Real-time Optimization (RTO) is a strategy that is able to maximize an economic function while respecting the existing constraints, which enables keeping the operation at its optimum point even though the plant is subjected to nonlinear behavior and frequent disturbances. However, the investment related to the project of commercial RTOs may make its application infeasible for small-scale facilities. In this work, an in-house, small-scale RTO is presented and its successful application in a real industrial case—a Natural Gas Processing Unit—is shown. Besides that, a new method for enhancing the efficiency of using sequential-modular simulator inside an optimization framework and a new method to account for the economic return of optimization-based tools are proposed and described. The application of RTO in the industrial case showed an enhancement in the stability of the main variables and an increase in profit of 0.64% when compared to the operation of the regulatory control layer alone. Full article
(This article belongs to the Special Issue Modelling, Monitoring, Control and Optimization for Complex Industrial Processes)
►▼ Show Figures

Graphical abstract

15 pages, 2990 KiB  
Article
Extraction of Added-Value Triterpenoids from Acacia dealbata Leaves Using Supercritical Fluid Extraction
by Vítor H. Rodrigues, Marcelo M. R. de Melo, Inês Portugal and Carlos M. Silva
Processes 2021, 9(7), 1159; https://doi.org/10.3390/pr9071159 - 3 Jul 2021
Cited by 11 | Viewed by 4075
Abstract
Forestry biomass is a by-product which commonly ends up being burnt for energy generation, despite comprising valuable bioactive compounds with valorisation potential. Leaves of Acacia dealbata were extracted for the first time by supercritical fluid extraction (SFE) using different conditions of pressure, temperature [...] Read more.
Forestry biomass is a by-product which commonly ends up being burnt for energy generation, despite comprising valuable bioactive compounds with valorisation potential. Leaves of Acacia dealbata were extracted for the first time by supercritical fluid extraction (SFE) using different conditions of pressure, temperature and cosolvents. Total extraction yield, individual triterpenoids extraction yields and concentrations were assessed and contrasted with Soxhlet extractions using solvents of distinct polarity. The extracts were characterized by gas chromatography coupled to mass spectrometry (GC-MS) and target triterpenoids were quantified. The total extraction yields ranged from 1.76 to 11.58 wt.% and the major compounds identified were fatty acids, polyols, and, from the triterpenoids family, lupenone, α-amyrin and β-amyrin. SFE was selective to lupenone, with higher individual yields (2139–3512 mg kgleaves−1) and concentrations (10.1–12.4 wt.%) in comparison to Soxhlet extractions, which in turn obtained higher yields and concentrations of the remaining triterpenoids. Full article
(This article belongs to the Special Issue Extraction, Utilization and Conversion of Woody Biomass)
►▼ Show Figures

Graphical abstract

17 pages, 4875 KiB  
Article
Storing Energy from External Power Supplies Using Phase Change Materials and Various Pipe Configurations
by Daniel Aprile, Samer Al-Banna, Arraventhan Maheswaran, Joshua Paquette and Mohamad Ziad Saghir
Processes 2021, 9(7), 1160; https://doi.org/10.3390/pr9071160 - 3 Jul 2021
Cited by 2 | Viewed by 2594
Abstract
Phase change materials are commonly used for energy storage. Heat transfer enhancement and heat storage are the two main goals in this paper. A cylindrical pipe covered with phase change material is investigated numerically. Ideally, a high temperature liquid flows through the pipe, [...] Read more.
Phase change materials are commonly used for energy storage. Heat transfer enhancement and heat storage are the two main goals in this paper. A cylindrical pipe covered with phase change material is investigated numerically. Ideally, a high temperature liquid flows through the pipe, resulting in heat transferred to the phase change material. To enhance the heat transfer, various configurations involving the addition of a twisted tape inside of the pipe and the use of helical shape pipes were investigated. A straight pipe with no twisted tape insert was also analyzed and used as a benchmark case. All the configurations had constant properties such as material selection, overall size, pipe diameter and inlet Reynold’s number, so the performance could be compared under similar conditions. All initial configurations were simulated and the heat transfer rate, Nusselt number, friction factor and performance evaluation criterion (PEC) of the designs were determined. It was found that the heat transfer rate and Nusselt number of all the various designs yielded higher results than the reference straight pipe configuration. Additionally, due to the added complexity in the flow caused by the insert, the friction factor of all the configurations was also higher. The helical pipe configuration was the only configuration that had a PEC higher than that of the reference straight pipe. This is because the negative impacts caused by the friction factor outweighed the gains in Nusselt number for the twisted tape designs. It was also hypothesized that lowering the inner diameter of the helical pipe would increase the PEC. Further simulations with modified inner diameters were done to test the hypothesis. The simulations confirmed the hypothesis, as the pipes with inner diameters 0.75 and 0.5 cm led to a 50% and 150% increase in the PEC respectively, when compared to an inner diameter of 1 cm. It was also determined that smaller inner diameters led to lower outlet temperatures meaning a higher percentage of the thermal energy from the fluid was transferred to the phase change material. Full article
(This article belongs to the Special Issue Design, Simulation and Applications of Phase Change Materials in Thermal Energy Storage Systems)
►▼ Show Figures

Figure 1

12 pages, 743 KiB  
Article
Efficacy of Different Waste and By-Products from Forest and Food Industries in the Removal/Retention of the Antibiotic Cefuroxime
by Raquel Cela-Dablanca, Carolina Nebot, Lucia Rodríguez López, David Fernández-Calviño, Manuel Arias-Estévez, Avelino Núñez-Delgado, María J. Fernández-Sanjurjo and Esperanza Álvarez-Rodríguez
Processes 2021, 9(7), 1151; https://doi.org/10.3390/pr9071151 - 1 Jul 2021
Cited by 16 | Viewed by 2958
Abstract
Environmental pollution due to antibiotics is a serious problem. In this work, the adsorption and desorption of the antibiotic cefuroxime (CFX) were studied in four by-products/residues from the forestry and food industries. For this, batch-type experiments were carried out, adding increasing concentrations of [...] Read more.
Environmental pollution due to antibiotics is a serious problem. In this work, the adsorption and desorption of the antibiotic cefuroxime (CFX) were studied in four by-products/residues from the forestry and food industries. For this, batch-type experiments were carried out, adding increasing concentrations of CFX (from 0 to 50 µmol L−1) to 0.5 g of adsorbent. The materials with a pH higher than 9 (mussel shell and wood ash) were those that presented the highest adsorption percentages, from 71.2% (23.1 µmol kg−1) to 98.6% (928.0 µmol kg−1). For the rest of the adsorbents, the adsorption was also around 100% when the lowest concentrations of CFX were added, but the percentage dropped sharply when the highest dose of the antibiotic was incorporated. Adsorption data fitted well to the Langmuir and Freundlich models, with R2 greater than 0.9. Regarding desorption, the materials that presented the lowest values when the highest concentration of CFX was added were wood ash (0%) and mussel shell (2.1%), while pine bark and eucalyptus leaves presented the highest desorption (26.6% and 28.6%, respectively). Therefore, wood ash and mussel shell could be considered adsorbents with a high potential to be used in problems of environmental contamination by CFX. Full article
(This article belongs to the Topic New Research on Detection and Removal of Emerging Pollutants)
►▼ Show Figures

Graphical abstract

15 pages, 3224 KiB  
Article
Residual Life Prediction for Induction Furnace by Sequential Encoder with s-Convolutional LSTM
by Yulim Choi, Hyeonho Kwun, Dohee Kim, Eunju Lee and Hyerim Bae
Processes 2021, 9(7), 1121; https://doi.org/10.3390/pr9071121 - 28 Jun 2021
Cited by 8 | Viewed by 3938
Abstract
Induction furnaces are widely used for melting scrapped steel in small foundries and their use has recently become more frequent. The maintenance of induction furnaces is usually based on empirical decisions of the operator and an explosion can occur through operator error. To [...] Read more.
Induction furnaces are widely used for melting scrapped steel in small foundries and their use has recently become more frequent. The maintenance of induction furnaces is usually based on empirical decisions of the operator and an explosion can occur through operator error. To prevent an explosion, previous studies have utilized statistical models but have been unable to generalize the problem and have achieved a low accuracy. Herein, we propose a data-driven method for induction furnaces by proposing a novel 2D matrix called a sequential feature matrix(s-encoder) and multi-channel convolutional long short-term memory (s-ConLSTM). First, the sensor data and operation data are converted into sequential feature matrices. Then, N-sequential feature matrices are imported into the convolutional LSTM model to predict the residual life of the induction furnace wall. Based on our experimental results, our method outperforms general neural network models and enhances the safe use of induction furnaces. Full article
(This article belongs to the Special Issue Application of Big Data Analysis and Advanced Analytics in Sustainable Production Process)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying article 751-800 on page 16 of 19.
Back to TopTop