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Extraction and Recovery of Critical Metals from Electronic Waste Using ISASMELT Technology
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Recovery of Ammonium from Biomass-Drying Condensate Via Ion Exchange and Its Valorization as a Fertilizer
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The Perspective of Using the System Ethanol-Ethyl Acetate in a Liquid Organic Hydrogen Carrier (LOHC) Cycle
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Biological Methanation in an Anaerobic Biofilm Reactor—Trace Element and Mineral Requirements for Stable Operation
Journal Description
Processes
Processes
is an international, peer-reviewed, open access journal on processes/systems in chemistry, biology, material, energy, environment, food, pharmaceutical, manufacturing, automation control, catalysis, separation, particle and allied engineering fields published monthly online by MDPI. The Systems and Control Division of the Canadian Society for Chemical Engineering (CSChE S&C Division) and the Brazilian Association of Chemical Engineering (ABEQ) are affiliated with Processes and their members receive a discount on the article processing charges. Please visit Society Collaborations for more details.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), CAPlus / SciFinder, Inspec, AGRIS, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Chemical) / CiteScore - Q2 (Chemical Engineering (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 12.7 days after submission; acceptance to publication is undertaken in 3.7 days (median values for papers published in this journal in the second half of 2022).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.352 (2021);
5-Year Impact Factor:
3.338 (2021)
Latest Articles
Digital Twin Implementation for Manufacturing of Adjuvants
Processes 2023, 11(6), 1717; https://doi.org/10.3390/pr11061717 (registering DOI) - 03 Jun 2023
Abstract
Pharmaceutical manufacturing processes are moving towards automation and real-time process monitoring with the help of process analytical technologies (PATs) and predictive process models representing the real system. In this paper, we present a digital twin developed for an adjuvant manufacturing process involving a
[...] Read more.
Pharmaceutical manufacturing processes are moving towards automation and real-time process monitoring with the help of process analytical technologies (PATs) and predictive process models representing the real system. In this paper, we present a digital twin developed for an adjuvant manufacturing process involving a microfluidic formation of lipid particles. The twin uses a hybrid model for estimating the current state of the process and predicting system behavior in real time. The twin is used to control the adjuvant particle size, a critical quality attribute, by varying process parameters such as the temperature and inlet flow rates. We describe steps in the design and implementation of the twin, starting from the conception of the mechanistic model, up to the generation of its surrogate model used as state estimator, PATs and the setup of the information technology—Operational technology architecture. We demonstrate the performance of the twin by introducing different disturbances in the process and comparing the effect on the product critical quality attributes with and without the control of the digital twin. Finally, we showcase the digital twin implementation for the process in good manufacturing practice, through an engineering run, which demonstrated the robustness of the process when controlled by the digital twin.
Full article
(This article belongs to the Special Issue Digital Design of Products, Processes and Operations in the (Bio)Pharmaceutical Industry)
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Open AccessArticle
Mechanical Properties of Full-Grouted Prestressed Anchor Bolts under Typical Bed-Separation Conditions
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, , , , , , and
Processes 2023, 11(6), 1716; https://doi.org/10.3390/pr11061716 (registering DOI) - 03 Jun 2023
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For tunnel-support engineering, the bed separation of surrounding rock has a great influence on the support performance of bolts. In order to reveal the mechanical properties of the full-grouted prestressed bolt under the influence of bed separation, three typical working conditions of single-separation,
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For tunnel-support engineering, the bed separation of surrounding rock has a great influence on the support performance of bolts. In order to reveal the mechanical properties of the full-grouted prestressed bolt under the influence of bed separation, three typical working conditions of single-separation, multi-separation and different separation positions were set up, and theoretical models and numerical models were established. Furthermore, the characteristics of bolt axial force and anchorage–interface shear stress were analyzed by numerical method, and the sensitivity based on an orthogonal test was studied by means of range analysis and variance analysis. The results showed that: (1) under the single-separation condition, the separation value has a significant effect on the mechanical properties of the bolt, and with the increase in the separation value, the sliding failure unit of the bolt increases; (2) for multi-separation conditions, if the total separation value is the same, the increase in the number of separation interfaces is beneficial to the force of the bolt; (3) for the case where the separation layer is located at different positions, the separation layer on the right side is more likely to cause the overall slip failure of the bolt; and (4) for the above three influencing factors, the separation value has the greatest influence on the mechanical properties of the bolt, and the separation position has the least influence.
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Open AccessFeature PaperReview
Production of Value-Added Products as Food Ingredients via Microbial Fermentation
Processes 2023, 11(6), 1715; https://doi.org/10.3390/pr11061715 (registering DOI) - 03 Jun 2023
Abstract
Humankind has been unknowingly utilizing food fermentations since the first creation of bread, cheese, and other basic foods. Since the beginning of the last century, microbial fermentation has been extensively utilized for production of commodity chemicals. It has also gained substantial interest in
[...] Read more.
Humankind has been unknowingly utilizing food fermentations since the first creation of bread, cheese, and other basic foods. Since the beginning of the last century, microbial fermentation has been extensively utilized for production of commodity chemicals. It has also gained substantial interest in recent decades due to its underlying applications in the preparation of natural and safe food ingredients including enzymes, antimicrobial agents, vitamins, organic acids, sweeteners, stabilizers, emulsifiers, oligosaccharides, amino acids, and thickening agents. In addition, some novel food ingredients that were conventionally made from some other sources such as plant tissue cultures or animals are now being introduced in the industry as ‘fermentation products.’ Some examples of such novel fermentation food ingredients include flavonoids, cultured meat products, food colorants, antioxidants, lipids, and fatty acids. This review summarizes some of the most prominent food ingredients and novel fermentation food products currently being produced via microbial fermentation as well as the strategies to enhance such fermentation processes. Additionally, economical feedstocks are discussed with their potential to be converted into value-added products with the help of microbial fermentations.
Full article
(This article belongs to the Special Issue Fermentation and Bioprocess Engineering Processes)
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Thermoelectric Generator Design and Characterization for Industrial Pipe Waste Heat Recovery
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, , , , , , , , , and
Processes 2023, 11(6), 1714; https://doi.org/10.3390/pr11061714 (registering DOI) - 03 Jun 2023
Abstract
Thermoelectric technology is an effective strategy to convert low–grade waste heat to electrical energy directly. Thermoelectric generators (TEGs) have been extensively studied in various waste heat scenarios, such as vehicle exhaust, metal casting processes and more. However, industrial pipelines also possess high levels
[...] Read more.
Thermoelectric technology is an effective strategy to convert low–grade waste heat to electrical energy directly. Thermoelectric generators (TEGs) have been extensively studied in various waste heat scenarios, such as vehicle exhaust, metal casting processes and more. However, industrial pipelines also possess high levels of heat and wide distribution, yet there is limited research on TEGs for use in these pipes. The challenge in designing a TEG lies in the heat collector, which is complicated by the distinct structural differences between pipe and plate–shaped TEMs. Ultimately, we propose an arch bridge–shaped heat collector for the pipe to recover wasted thermal energy. The effects of some key factors, such as topology of TEMs, heat source temperature, cooling water temperature and velocity, on the generating performance are studied. The TEG achieved a temperature difference of 65.98 °C across the two ends of the TEM, resulting in an output power of 17.89 W at an open–circuit voltage of 133.35 V. This provides evidence that the designed heat collector is a feasible solution for recovering waste heat from pipes using TEG technology. This work provides reliable experimental data and efficient design for the application of TEGs in industrial pipes.
Full article
(This article belongs to the Special Issue Advances in Waste Heat Recovery Using Thermoelectric Generators)
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Numerical Simulation of the Effect of Heat Conductivity on Proton Exchange Membrane Fuel Cell Performance in Different Axis Directions
Processes 2023, 11(6), 1713; https://doi.org/10.3390/pr11061713 (registering DOI) - 03 Jun 2023
Abstract
In this paper, the effect of changes in the thermal conductivity of porous electrodes in three coordinate directions on the capability of proton exchange membrane fuel cells is investigated on the basis of current density versus voltammetry curves, and the temperature distribution and
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In this paper, the effect of changes in the thermal conductivity of porous electrodes in three coordinate directions on the capability of proton exchange membrane fuel cells is investigated on the basis of current density versus voltammetry curves, and the temperature distribution and water-carrying capacity distribution of the membrane. The results show that when the cell discharge voltage of the PEMFC is 0.3 V, the thermal conductivity in the Z-direction of the porous electrode has a greater effect on the performance of the PEMFC than in the other directions, with the thermal conductivity in the X- and Y-directions of the porous electrode having less than a 5% effect on the performance of the PEMFC, which can therefore be neglected. When the thermal conductivity of the porous electrode in the Z-direction of the PEMFC is 500 W/(m·K) and 1000 W/(m·K), the performance of the PEMFC is improved by 5.78% and 5.87%, respectively, and when the thermal conductivity of the porous electrode in the X-direction of the PEMFC is 500 W/(m·K) and 1000 W/(m·K), the performance of the PEMFC is improved by 2.09% and 2.89%, and the PEMFC performance is improved by 1.51% and 2.00% when the Y-direction thermal conductivity of the porous electrode of the PEMFC is 500 W/(m·K) and 1000 W/(m·K), respectively. The improvement in performance decreases with increasing thermal conductivity, because the thickness of the porous electrode is too thin. Since the side of the model is set to adiabatic heat exchange conditions, while the top and bottom surfaces are set to natural convection heat exchange conditions, the Z-direction thermal conductivity of the porous electrode plays the most important role in the temperature distribution of the PEMFC. The Z-direction thermal conductivity of the porous electrode causes the temperature distribution of the PEMFC assembly to be more uniform, and the Z-direction thermal conductivity of the porous electrode also causes the area of the high-water-content region on the proton exchange membrane to significantly increase.
Full article
(This article belongs to the Special Issue Progresses in Electrochemical Energy Conversion and Storage—Materials, Structures and Simulation)
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Active Disturbance Rejection Control of Five-Phase Motor Based on Parameter Setting of Genetic Algorithm
Processes 2023, 11(6), 1712; https://doi.org/10.3390/pr11061712 (registering DOI) - 03 Jun 2023
Abstract
Five-phase induction motors have the characteristics of high torque density, low torque ripple, and flexible control, making them suitable for medium- and low-voltage power supply situations. However, with the expansion of application scenarios, five-phase motors need to cope with increasingly complex operating conditions.
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Five-phase induction motors have the characteristics of high torque density, low torque ripple, and flexible control, making them suitable for medium- and low-voltage power supply situations. However, with the expansion of application scenarios, five-phase motors need to cope with increasingly complex operating conditions. Five-phase motors for propeller propulsion will face various complex sea conditions during actual use, and five-phase motors for electric vehicles will also face various complex road conditions and operating requirements during use. Therefore, as a propulsion motor, its speed control system must have strong robustness and anti-disturbance performance. The use of traditional PI algorithms has problems, such as poor adaptability and inability to adapt to various complex working conditions, but the use of an active disturbance rejection controller (ADRC) can effectively solve these problems. However, due to the significant coupling between the variables of induction motors and the large number of parameters in the ADRC, tuning the parameters of the ADRC is complex. Traditional empirical tuning methods can only obtain a rough range of parameter values and may have significant errors. Therefore, this paper uses ADRC based on genetic algorithm(GAADRC) to tune the parameters of the control and design an objective function based on multi-objective optimization. The parameters to be adjusted were obtained through multiple iterations. The simulation and experimental results indicate that GAADRC has lower startup overshoot, faster adjustment time, and lower load/unload speed changes compared to the empirically tuned PI controller and ADRC. Meanwhile, using a genetic algorithm for motor ADRC parameter tuning can obtain optimal control parameters while the control parameter range is completely uncertain; therefore, the method proposed in this paper has strong practical value.
Full article
(This article belongs to the Special Issue Adaptive Control: Design and Analysis)
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LC-ESI-QTOF-MS/MS Characterization of Phenolic Compounds in Common Commercial Mushrooms and Their Potential Antioxidant Activities
by
, , , , , and
Processes 2023, 11(6), 1711; https://doi.org/10.3390/pr11061711 (registering DOI) - 03 Jun 2023
Abstract
Mushrooms have a long history of use as food and medicine. They are rich in various nutrients and bioactive compounds, particularly phenolic compounds. In this study, ten mushroom species were selected, and solvent extraction using 80% ethanol was used to extract phenolic compounds.
[...] Read more.
Mushrooms have a long history of use as food and medicine. They are rich in various nutrients and bioactive compounds, particularly phenolic compounds. In this study, ten mushroom species were selected, and solvent extraction using 80% ethanol was used to extract phenolic compounds. Total phenolic content (TPC), total flavonoid content (TFC) and total condensed tannin content (TCT) were measured to evaluate phenolic content in different mushroom varieties. In the mushroom varieties tested, brown portobello mushroom had the highest TPC (396.78 ± 3.12 µg GAE/g), white cup mushroom exhibited the highest TFC (275.17 ± 9.40 μg CE/g), and shiitake mushroom presented the highest TCT (13.80 ± 0.21 µg QE/g). Antioxidant capacity was evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH), ferric reducing antioxidant power (FRAP), 2,2′-azino-bis-3ethylbenzothiazoline-6-sulfonic acid (ABTS) and total antioxidant capacity (TAC) assays. The highest DPPH free radical scavenging ability was found in white cup mushroom (730.14 ± 55.06 µg AAE/g), while the greatest iron-reducing ability (FRAP) was recorded for shiitake mushroom (165.32 ± 10.21 μg AAE/g). Additionally, Swiss brown mushroom showed the highest ABTS antioxidant capacity (321.31 ± 5.7 μg AAE/g), and the maximum TAC value was found in shiitake mushroom (24.52 ± 1.2 μg AAE/g). These results highlight that most of the mushroom varieties studied showed high phenolic contents and demonstrated strong antioxidant activity, with shiitake mushrooms standing out due to their high TCT and FRAP values, and the highest TAC value among the varieties studied. In addition, LC-ESI-QTOF-MS/MS was used to characterize the mushroom samples, and tentatively identified a total of 22 phenolic compounds, including 11 flavonoids, 4 lignans, 3 phenolic acids, 2 stilbenes and 2 other phenolic compounds in all mushroom samples. The research results of this study showed that mushrooms are a good source of phenolic compounds with strong antioxidant potential. The results can provide a scientific basis for the development of mushroom extracts in functional food, health products, and other industries.
Full article
(This article belongs to the Special Issue Extraction and Purification of Bioactive Compounds)
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Preliminary Study on the Feasibility of Radiation Technique for Mural Protection
Processes 2023, 11(6), 1710; https://doi.org/10.3390/pr11061710 (registering DOI) - 02 Jun 2023
Abstract
Murals are a significant cultural heritage of humanity, and one of the conservation studies is to control the growth of microorganisms. General biocide agents can be used to preserve murals while also providing new organic carbon sources and increasing environmental pollution. In recent
[...] Read more.
Murals are a significant cultural heritage of humanity, and one of the conservation studies is to control the growth of microorganisms. General biocide agents can be used to preserve murals while also providing new organic carbon sources and increasing environmental pollution. In recent years, radiation technology has shown promising prospects for use in heritage protection. Five microorganisms often found in murals were irradiated with an electron beam in this study, and six mineral pigments were tested for color change, Raman spectra and pigment layer cohesion after irradiation. The result showed that irradiation at 20 kGy can basically eliminate Pseudomonas citronellolis, Bacillus sporothermodurans, Streptomyces vinaceus, and Streptomyces griseolus from the culture medium, but only inhibited the growth of Penicillium flavigenum. Lead white pigment showed a color difference of 5.56 (∆E*97) after irradiation, but lead tetroxide, azurite, malachite, ferrous oxide, and cinnabar showed no visible changes. The Raman spectra of the irradiated and unirradiated samples were basically the same. E-beam radiation did not affect the surface cohesion of the pigment layer. This preliminary work shows the potential of electron-beam technology in mural protection and provides basic research and relevant experience for the subsequent in situ mural protection work.
Full article
(This article belongs to the Special Issue Advances in Environmental Pollution and Control Processes)
Open AccessFeature PaperArticle
Blank Strip Filling for Logging Electrical Imaging Based on Multiscale Generative Adversarial Network
Processes 2023, 11(6), 1709; https://doi.org/10.3390/pr11061709 (registering DOI) - 02 Jun 2023
Abstract
The Fullbore Formation Micro Imager (FMI) represents a proficient method for examining subterranean oil and gas deposits. Despite its effectiveness, due to the inherent configuration of the borehole and the logging apparatus, the micro-resistivity imaging tool cannot achieve complete coverage. This limitation manifests
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The Fullbore Formation Micro Imager (FMI) represents a proficient method for examining subterranean oil and gas deposits. Despite its effectiveness, due to the inherent configuration of the borehole and the logging apparatus, the micro-resistivity imaging tool cannot achieve complete coverage. This limitation manifests as blank regions on the resulting micro-resistivity logging images, thus posing a challenge to obtaining a comprehensive analysis. In order to ensure the accuracy of subsequent interpretation, it is necessary to fill these blank strips. Traditional inpainting methods can only capture surface features of an image, and can only repair simple structures effectively. However, they often fail to produce satisfactory results when it comes to filling in complex images, such as carbonate formations. In order to address the aforementioned issues, we propose a multiscale generative adversarial network-based image inpainting method using U-Net. Firstly, in order to better fill the local texture details of complex well logging images, two discriminators (global and local) are introduced to ensure the global and local consistency of the image; the local discriminator can better focus on the texture features of the image to provide better texture details. Secondly, in response to the problem of feature loss caused by max pooling in U-Net during down-sampling, the convolution, with a stride of two, is used to reduce dimensionality while also enhancing the descriptive ability of the network. Dilated convolution is also used to replace ordinary convolution, and multiscale contextual information is captured by setting different dilation rates. Finally, we introduce residual blocks on the U-Net network in order to address the degradation problem caused by the increase in network depth, thus improving the quality of the filled logging images. The experiment demonstrates that, in contrast to the majority of existing filling algorithms, the proposed method attains superior outcomes when dealing with the images of intricate lithology.
Full article
(This article belongs to the Special Issue Oil and Gas Well Engineering Measurement and Control)
Open AccessArticle
Influence of Inorganic Salt Additives on the Surface Tension of Sodium Dodecylbenzene Sulfonate Solution
Processes 2023, 11(6), 1708; https://doi.org/10.3390/pr11061708 - 02 Jun 2023
Abstract
In order to study the effect of inorganic salt additives on the surface tension of a sodium dodecylbenzene sulfonate (SDBS) solution, the surface tension of the mixed system of six common inorganic salt additives, NaCl, CaCl2, AlCl3, Na2
[...] Read more.
In order to study the effect of inorganic salt additives on the surface tension of a sodium dodecylbenzene sulfonate (SDBS) solution, the surface tension of the mixed system of six common inorganic salt additives, NaCl, CaCl2, AlCl3, Na2SO4, Na2CO3, and NaHCO3, and SDBS was measured, and the effects of the inorganic salt types, surfactant concentrations and inorganic salt concentrations on the surface tension of the SDBS solution were studied. On this basis, three inorganic salts, NaCl, CaCl2 and Na2SO4, were selected, and their effects on the critical micelle concentration (CMC) of the SDBS solution were studied. The experimental results showed that different inorganic salts had different effects on the surface tension of the SDBS solution. The order of effect of the six inorganic salts on the surface tension of the SDBS solution was CaCl2 > NaCl > Na2SO4 > NaHCO3 > Na2CO3 > AlCl3; when the mass fraction of the SDBS solution is high, the influence of the inorganic salts on the surface tension of the SDBS solution is relatively small; with an increase in the concentration of the preferred inorganic salt additives, the surface tension of the SDBS solution decreases first, then tends to be stable, and then increases; a reduction in the critical micelle concentration by the three selected inorganic salt additives shows the trend of 0.7% NaCl > 0.5% CaCl2 > 0.5% Na2SO4.
Full article
(This article belongs to the Special Issue Mine Ventilation and Dust Control Technology in Safety Management Engineering)
Open AccessArticle
Generalized Functional Observer for Descriptor Nonlinear Systems—A Takagi-Sugeno Approach
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, , , , and
Processes 2023, 11(6), 1707; https://doi.org/10.3390/pr11061707 - 02 Jun 2023
Abstract
This paper concerns the design of a generalized functional observer for Takagi–Sugeno descriptor systems. Furthermore, a generalized structure is herein introduced for purposes of estimating linear functions of the states of descriptor nonlinear systems represented into a Takagi–Sugeno descriptor form. The originality of
[...] Read more.
This paper concerns the design of a generalized functional observer for Takagi–Sugeno descriptor systems. Furthermore, a generalized structure is herein introduced for purposes of estimating linear functions of the states of descriptor nonlinear systems represented into a Takagi–Sugeno descriptor form. The originality of the functional generalized observer structure is that it provides additional degrees of freedom in the observer design, which allows for improvements in the estimation against parametric uncertainties. The effectiveness of the developed design is illustrated by a nonlinear model of a single link robotic arm with a flexible link. A comparison between the functional generalized observer and the functional proportional observer is given to demonstrate the observer performances.
Full article
(This article belongs to the Special Issue Innovative Techniques for Safety, Reliability, and Security in Control Systems)
Open AccessArticle
NN-Based Parallel Model Predictive Control for a Quadrotor UAV
Processes 2023, 11(6), 1706; https://doi.org/10.3390/pr11061706 - 02 Jun 2023
Abstract
A novel neural network (NN)-based parallel model predictive control (PMPC) method is proposed to deal with the tracking problem of the quadrotor unmanned aerial vehicles (Q-UAVs) system in this article. It is well known that the dynamics of Q-UAVs are changeable while the
[...] Read more.
A novel neural network (NN)-based parallel model predictive control (PMPC) method is proposed to deal with the tracking problem of the quadrotor unmanned aerial vehicles (Q-UAVs) system in this article. It is well known that the dynamics of Q-UAVs are changeable while the system is operating in some specific environments. In this case, traditional NN-based MPC methods are not applicable because their model networks are pre-trained and kept constant throughout the process. To solve this problem, we propose the PMPC algorithm, which introduces parallel control structure and experience pool replay technology into the MPC method. In this algorithm, an NN-based artificial system runs in parallel with the UAV system to reconstruct its dynamics model. Furthermore, the experience replay technology is used to maintain the accuracy of the reconstructed model, so as to ensure the effectiveness of the model prediction algorithm. Furthermore, a convergence proof of the artificial system is also given in this paper. Finally, numerical results and analysis are given to demonstrate the effectiveness of the PMPC algorithm.
Full article
(This article belongs to the Special Issue Power Interaction Control Methods among Main Grid, Charging Station and Electric Vehicles)
Open AccessFeature PaperArticle
Evaluation of a Resorcinarene-Based Sorbent as a Solid-Phase Extraction Material for the Enrichment of L-Carnitine from Aqueous Solutions
Processes 2023, 11(6), 1705; https://doi.org/10.3390/pr11061705 - 02 Jun 2023
Abstract
We present five new sorbents for the evaluation of the pre-concentration of L-carnitine. The sorbents were obtained from copolymerization between butylmethacrylate (BuMA) and ethylene dimethacrylate (EDMA), which were physically modified on their surface by each one of the five synthetized resorcinarenes of variable
[...] Read more.
We present five new sorbents for the evaluation of the pre-concentration of L-carnitine. The sorbents were obtained from copolymerization between butylmethacrylate (BuMA) and ethylene dimethacrylate (EDMA), which were physically modified on their surface by each one of the five synthetized resorcinarenes of variable chain length studied, with long-chain resorcinarenes exhibiting better fixation on the copolymer. The characterization of the synthesized resorcinarenes was done using FTIR-ATR, 1H NMR, 13C NMR, and mass spectrometry, while characterization of the sorbents was done using FTIR-ATR and scanning electron micrography (SEM). The molecular interaction between L-carnitine and the synthesized resorcinarenes was studied in DMSO via 1H-NMR spectroscopy and, in the gas phase, via electrospray ionization-mass spectrometry (ESI-MS). The results showed that the short-chain resorcinarenes underwent a stable interaction with the neurotransmitter. Once the sorption of resorcinarenes on the copolymer was accomplished, the best parameters for the evaluation of the L-carnitine preconcentration were established. The solution tests were carried out through LC/MS analysis, obtaining better results for L-carnitine absorption with the short-chain resorcinarenes such as tetra(ethyl)calix[4]resorcinarene and tetra(propyl)calix[4]resorcinarene.
Full article
(This article belongs to the Special Issue Transport Processes in Polymeric Aqueous Systems)
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Molecular Dynamics Simulation of Femtosecond Laser Ablation of Cu50Zr50 Metallic Glass Based on Two-Temperature Model
Processes 2023, 11(6), 1704; https://doi.org/10.3390/pr11061704 - 02 Jun 2023
Abstract
Femtosecond laser machining, characterized by a small heat-affected zone, high precision, and non-contact operation, is ideal for processing metallic glasses. In this study, we employed a simulation method that combines the two-temperature model with molecular dynamics to investigate the effects of fluence and
[...] Read more.
Femtosecond laser machining, characterized by a small heat-affected zone, high precision, and non-contact operation, is ideal for processing metallic glasses. In this study, we employed a simulation method that combines the two-temperature model with molecular dynamics to investigate the effects of fluence and pulse duration on the femtosecond laser ablation of Cu50Zr50 metallic glass. Our results showed that the ablation threshold of the target material was 84 mJ/cm2 at a pulse duration of 100 fs. As the pulse durations increased, the maximum electron temperature at the same position on the target surface decreased, while the electron–lattice temperature coupling time showed no significant difference. As the absorbed fluence increased, the maximum electron temperature at the same position on the target surface increased, while the electron–lattice temperature coupling time became shorter. The surface ablation of the target material was mainly induced by phenomena such as melting, spallation, and phase explosion caused by femtosecond laser irradiation. Overall, our findings provide valuable insights for optimizing the femtosecond laser ablation process for metallic glasses.
Full article
(This article belongs to the Special Issue Micro/Nano Manufacturing Processes: Theories and Optimization Techniques)
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Digital Twinning of a Magnetic Forging Holder to Enhance Productivity for Industry 4.0 and Metaverse
by
, , , , and
Processes 2023, 11(6), 1703; https://doi.org/10.3390/pr11061703 - 02 Jun 2023
Abstract
The concept of digital twinning is essential for smart manufacturing and cyber-physical systems to be connected to the Metaverse. These digital representations of physical objects can be used for real-time analysis, simulations, and predictive maintenance. A combination of smart manufacturing, Industry 4.0, and
[...] Read more.
The concept of digital twinning is essential for smart manufacturing and cyber-physical systems to be connected to the Metaverse. These digital representations of physical objects can be used for real-time analysis, simulations, and predictive maintenance. A combination of smart manufacturing, Industry 4.0, and the Metaverse can lead to sustainable productivity in industries. This paper presents a practical approach to implementing digital twins of a magnetic forging holder that was designed and manufactured in this project. Thus, this paper makes two important contributions: the first contribution is the manufacturing of the holder, and the second significant contribution is the creation of its digital twin. The holder benefits from a special design and implementation, making it a user-friendly and powerful tool in materials research. More specifically, it can be employed for the thermomechanical influencing of the structure and, hence, the final properties of the materials under development. In addition, this mechanism allows us to produce a new type of creep-resistant composite material based on Fe, Al, and Y. The magnetic forging holder consolidates the powder material to form a solid state after mechanical alloying. We produce bars from the powder components using a suitable forging process in which extreme grain coarsening occurs after the final heat treatment. This is one of the conditions for achieving very high resistance to creep at high temperatures.
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(This article belongs to the Special Issue Industry 4.0: Integrating Advanced Manufacturing Technologies, Artificial Intelligence, and Contemporary Information Technology)
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Theoretical and Experimental Analysis of Grinding Stability of Beam Workpiece
by
and
Processes 2023, 11(6), 1702; https://doi.org/10.3390/pr11061702 - 02 Jun 2023
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Grinding chatter is a kind of self-excited vibration in which the grinding system continuously absorbs energy from the grinding machine, increasing the mechanical energy of the system. Grinding chatter can damage the surface of the workpiece and accelerate the abrasion of the grinding
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Grinding chatter is a kind of self-excited vibration in which the grinding system continuously absorbs energy from the grinding machine, increasing the mechanical energy of the system. Grinding chatter can damage the surface of the workpiece and accelerate the abrasion of the grinding wheel. The theoretical analysis of the grinding chatter for the beam surface was launched based on the behavior of a single abrasive grain, whose cutting thickness is a key factor affecting grinding stability. The dynamic grinding force model has been developed, which is the interaction interface between the grinding wheel and the workpiece. In this paper, rail beam grinding was taken as an example. The vibration performance of the rail beam was described with the Timoshenko beam. The characteristics of the frequency domain of the grinding wheel-workpiece system were observed, and the condition of the stability at any position in the longitudinal direction of the beam was gained, which could be quantitatively characterized with the stability limit curve. The grinding experiments of the rail beam surface demonstrated that as chatter developed, the chatter marks could be investigated on the surface of the rail, and the energy of the chatter signal was mainly concentrated around the chatter frequency, which was higher than the natural frequency of the grinding wheel.
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Open AccessArticle
Transport Properties of Carbohydrates: Towards the Minimization Toxicological Risks of Cobalt and Chromium Ions
by
, , , , , , , and
Processes 2023, 11(6), 1701; https://doi.org/10.3390/pr11061701 - 02 Jun 2023
Abstract
The influence of oligosaccharides (α-cyclodextrin, β-cyclodextrin and γ-cyclodextrin), and a polysaccharide, sodium hyaluronate (NaHy), on the diffusion of aqueous solutions of cobalt and chromium chlorides has been investigated. Cobalt and chromium are constituents of metal alloys for biomedical use, including dental prostheses. Thus,
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The influence of oligosaccharides (α-cyclodextrin, β-cyclodextrin and γ-cyclodextrin), and a polysaccharide, sodium hyaluronate (NaHy), on the diffusion of aqueous solutions of cobalt and chromium chlorides has been investigated. Cobalt and chromium are constituents of metal alloys for biomedical use, including dental prostheses. Thus, the release of these ions in the human body can lead to harmful biological effects. The interaction of metal ions with saccharides might have information on the role of mouthwashes in preventing these effects. This interaction has been assessed by measuring multicomponent intermolecular diffusion coefficients at 298.15 K. It has been found that β-cyclodextrin has the highest interaction towards cobalt and chromium ions. This work will contribute to unveiling the mechanisms responsible for transport by diffusion in aqueous solutions, and, therefore, mitigating the potential toxicity inherent to those metal ions.
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(This article belongs to the Special Issue Transport Processes in Polymeric Aqueous Systems)
Open AccessFeature PaperArticle
Research on Pore-Fracture Characteristics and Adsorption Performance of Main Coal Seams in Lvjiatuo Coal Mine
Processes 2023, 11(6), 1700; https://doi.org/10.3390/pr11061700 - 02 Jun 2023
Abstract
Gas prevention and control have always been the focus of coal mine safety. The pore structure characteristics and gas adsorption characteristics of coal seams are the key factors affecting gas adsorption and diffusion in coal seams. Lvjiatuo Mine has the characteristics of a
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Gas prevention and control have always been the focus of coal mine safety. The pore structure characteristics and gas adsorption characteristics of coal seams are the key factors affecting gas adsorption and diffusion in coal seams. Lvjiatuo Mine has the characteristics of a high gas content when it enters deep mining. In order to clarify the influence of the pore-fracture structure characteristics of main coal seams in the research area on coal seam gas adsorption and diffusion, and to study the differences in gas adsorption and diffusion ability in different coal seams, low-temperature nitrogen adsorption (LT-N2GA), high-pressure mercury intrusion (MIP) and computerized tomography (μ-CT) were used as characterization methods, and methane isothermal adsorption experiments were carried out to systematically study the pore structure characteristics of five groups of coal samples, and the pore-fracture structure characteristics and gas adsorption characteristics of each main coal seam were obtained. The results show that: (1) in the LT-N2GA experiment, the adsorption–desorption curves of all coal samples are of type III, and mainly develop cone-shaped pores or wedge-shaped semi-closed pores, with an average pore size of 1.84~4.84 nm, a total pore volume of 0.0010~0.0023 mL/g, a total specific surface area of 0.16~0.24 m2/g, and a fractal dimension D1 of 1.39~1.87 and D2 of 2.44~2.60. The micropores of L12 are more developed, and the mesopores and macropores of L9 are more developed. (2) In the MIP experiment, the porosity of coal samples is 3.79~6.94%. The porosity of L9 is the highest, the macropore ratio is the highest, and the gas diffusion ability is also the strongest. (3) In the μ-CT experiment, the porosity of L8-2 and L12 is 12.12% and 10.41%, the connectivity is 51.22% and 61.59%, and the Df is 2.39 and 2.30, respectively. The fracture of L12 is more developed, the connectivity is better, and the heterogeneity of the pore of L8-2 is higher. (4) In the isothermal adsorption experiment of methane, the gas adsorption capacity basically increases with the increase in the buried depth of the coal seam, and the gas adsorption capacity of the No.12 coal seam is the highest. Based on the pore-fracture structure characteristics and gas adsorption characteristics of the main coal seams in the research area, the gas outburst risk of each coal seam is ranked as follows: No.12 coal seam > No.8 coal seam > No.7 coal seam > No.9 coal seam. The experimental results provide important help for researching the structural characteristics of coal seam pore fractures and preventing gas outbursts during deep coal seam mining.
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(This article belongs to the Special Issue Coal Chemical Structure Evolution, Coal Molecule and Methane Adsorption)
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Open AccessArticle
A Novel Model Prediction and Migration Method for Multi-Mode Nonlinear Time-Delay Processes
Processes 2023, 11(6), 1699; https://doi.org/10.3390/pr11061699 - 02 Jun 2023
Abstract
Most industrial processes have nonlinear and time-delay characteristics leading to difficulty in prediction modeling. In addition, the working conditions of most industrial processes are complex, which results in multiple modes. Testing and modeling for each mode is a waste of time and resources.
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Most industrial processes have nonlinear and time-delay characteristics leading to difficulty in prediction modeling. In addition, the working conditions of most industrial processes are complex, which results in multiple modes. Testing and modeling for each mode is a waste of time and resources. Therefore, it is urgent to complete model migration between different modes. In this work, a new prediction model, a nonlinear autoregressive model with exogenous inputs and back propagation neural network (NARX-BP), is proposed for the nonlinear and time-delay processes, where the input data order of the model is determined by the feedforward neural network (FNN) method, and the nonlinear relation is realized by the BP neural network. For the multi-mode characteristic, a new migration optimization algorithm, input–output slope/bias correction and differential evolution (IOSBC-DE), is provided for using a small amount of data under a new mode to correct the slope and bias of the relationship between the input and output variables through DE. The modeling and migration methods are applied to a wind tunnel system, and the simulation result shows the effectiveness of the proposed method.
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(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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Open AccessArticle
Optimizing Pressure Prediction Models for Pneumatic Conveying of Biomass: A Comprehensive Approach to Minimize Trial Tests and Enhance Accuracy
by
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Processes 2023, 11(6), 1698; https://doi.org/10.3390/pr11061698 - 02 Jun 2023
Abstract
This study investigates pneumatic conveying of four different biomass materials, namely cottonseeds, wood pellets, wood chips, and wheat straw. The performance of a previously proposed model for predicting pressure drop is evaluated using biomass materials. Results indicate that the model can predict pressure
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This study investigates pneumatic conveying of four different biomass materials, namely cottonseeds, wood pellets, wood chips, and wheat straw. The performance of a previously proposed model for predicting pressure drop is evaluated using biomass materials. Results indicate that the model can predict pressure with an error range of 30 percent. To minimize the number of trial tests required, an optimization algorithm is proposed. The findings show that with a combination of three trial tests, there is a 60 percent probability of selecting the right subset for accurately predicting pressure drop for the entire range of tests. Further investigation of different training subsets suggests that increasing the number of tests from 3 to 7 can improve the probability from 60% to 90%. Moreover, thorough analysis of all three-element subsets in the entire series of tests reveals that when considering air mass flow rate as the input, having air mass flow rates that are not only closer in value but also lower increases the likelihood of selecting the correct subset for predicting pressure drop across the entire range. This advancement can help industries to design and optimize pneumatic conveying systems more effectively, leading to significant energy savings and improved operational performance.
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(This article belongs to the Special Issue Biomass Combustion and Energy Production Processes)
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