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Conversion of Glass Waste into Zeolite A Adsorbent for Efficient Ammonium Ion Adsorption from AqueousSolution: Kinetic and Isotherm Studies
An Investigation of MnO_x and K/MnO_x-Based Catalysts on MnO₂ and Fe₃O₄ Supports for the Deep Oxidation of Cyclohexane
A Two-Level Facility Layout Design Method with the Consideration of High-Risk Facilities in Chemical Industries

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 discounts 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), Ei Compendex, 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 14.9 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the second half of 2024).
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: 2.8 (2023); 5-Year Impact Factor: 3.0 (2023)

Imprint Information Journal Flyer Open Access ISSN: 2227-9717

Latest Articles

19 pages, 4506 KiB

Open AccessArticle

A Novel Triethylammonium Tetrafluoroborate Electrolyte for Enhanced Supercapacitor Performance over a Wide Temperature Range

by Ezgi Yurttas, Yavuz Gokce, Nazife Isik Semerci, Emine Yagmur and Zeki Aktas

Processes 2025, 13(4), 1057; https://doi.org/10.3390/pr13041057 (registering DOI) - 2 Apr 2025

The wide operating temperature and voltage window are favourable properties that increase the practical applications of supercapacitors. Ionic liquids (IL) are suitable electrolytes that allow supercapacitors to be used in wide operating ranges. In this study, triethylammonium tetrafluoroborate (Et₃NHBF₄) [...] Read more.

The wide operating temperature and voltage window are favourable properties that increase the practical applications of supercapacitors. Ionic liquids (IL) are suitable electrolytes that allow supercapacitors to be used in wide operating ranges. In this study, triethylammonium tetrafluoroborate (Et₃NHBF₄) is tested as a new IL to operate supercapacitors in a wide temperature range (−40 °C, 25 °C, and 80 °C) in the presence of commercial activated carbon. The performance of Et₃NHBF₄ is compared to two different commercial ILs. This study also investigates the application of heat treatment to determine suitable activated carbon surface characteristics for ILs. The results indicate that heat treatment enhances the electrode–electrolyte interaction, and the electrochemical performances of the supercapacitors prepared from the heat-treated activated carbon are significantly higher than the original commercial activated carbon. Electrochemical tests show that the synthesised Et₃NHBF₄ (with propylene carbonate) can be used over a wide temperature range and has a better energy storage performance, especially at −40 °C (specific capacitance of 42.12 F/g at 2 A/g), compared to the other two commercial ionic liquids. Full article

(This article belongs to the Special Issue Recent Advances in Conductor Materials for Energy Storage and Electrocaloric Applications)

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15 pages, 1957 KiB

Open AccessArticle

Machine Learning-Based Sizing Model for Tapered Electrical Submersible Pumps Under Multiple Operating Conditions

by Jinsong Yao, Guoqing Han, Xingyuan Liang and Mengyu Wang

Processes 2025, 13(4), 1056; https://doi.org/10.3390/pr13041056 (registering DOI) - 1 Apr 2025

Dewatering gas wells typically exhibit a high gas–liquid ratio, making tapered electrical submersible pump (ESP) systems a common choice. However, the flow rate within the pump varies significantly along its length, and production parameters fluctuate considerably across different stages of operation for a [...] Read more.

Dewatering gas wells typically exhibit a high gas–liquid ratio, making tapered electrical submersible pump (ESP) systems a common choice. However, the flow rate within the pump varies significantly along its length, and production parameters fluctuate considerably across different stages of operation for a gas reservoir. Traditional ESP sizing methods typically consider one single operating case and one single pump model. In contrast, tapered ESP systems require the designer to manually select and combine pump models, stage numbers, and operating frequencies based largely on experience. This process can be cumbersome and time-consuming. To address the limitations of existing ESP sizing methods, this study develops a computational program for ESP operation parameters stage by stage and generates extensive training data. A fully connected neural network (FCNN) based on the backpropagation (BP) algorithm is then trained on these data. The model can predict key parameters such as gas volume fraction (GVF) and flow rate along the pump, operating frequency, and total pump efficiency, using input data such as fluid parameters at the pump’s intake and discharge, as well as pump stage numbers and performance curve data. The model demonstrates high accuracy, with a mean absolute error (MAE) of 0.3431, a mean squared error (MSE) of 0.3231, and a coefficient of determination (R²) of 0.9991. By integrating a wellbore two-phase flow model and leveraging industry experience in pump sizing, a hybrid model for automatic ESP sizing under multiple working conditions is proposed, with the objective of maximizing pump efficiency. This model enables optimal pump sizing, calculates the operating frequency corresponding to given working cases, significantly reduces the workload of designers, and enhances the overall design outcomes. Full article

(This article belongs to the Section Energy Systems)

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25 pages, 6535 KiB

Open AccessArticle

ANN-Based Prediction and RSM Optimization of Radiative Heat Transfer in Couple Stress Nanofluids with Thermodiffusion Effects

by Reima Daher Alsemiry, Sameh E. Ahmed, Mohamed R. Eid and Essam M. Elsaid

Processes 2025, 13(4), 1055; https://doi.org/10.3390/pr13041055 - 1 Apr 2025

This research investigates the impact of second-order slip conditions, Stefan flow, and convective boundary constraints on the stagnation-point flow of couple stress nanofluids over a solid sphere. The nanofluid density is expressed as a nonlinear function of temperature, while the diffusion-thermo effect, chemical [...] Read more.

This research investigates the impact of second-order slip conditions, Stefan flow, and convective boundary constraints on the stagnation-point flow of couple stress nanofluids over a solid sphere. The nanofluid density is expressed as a nonlinear function of temperature, while the diffusion-thermo effect, chemical reaction, and thermal radiation are incorporated through linear models. The governing equations are transformed using appropriate non-similar transformations and solved numerically via the finite difference method (FDM). Key physical parameters, including the heat transfer rate, are analyzed in relation to the Dufour number, velocity, and slip parameters using an artificial neural network (ANN) framework. Furthermore, response surface methodology (RSM) is employed to optimize skin friction, heat transfer, and mass transfer by considering the influence of radiation, thermal slip, and chemical reaction rate. Results indicate that velocity slip enhances flow behavior while reducing temperature and concentration distributions. Additionally, an increase in the Dufour number leads to higher temperature profiles, ultimately lowering the overall heat transfer rate. The ANN-based predictive model exhibits high accuracy with minimal errors, offering a robust tool for analyzing and optimizing the thermal and transport characteristics of couple stress nanofluids. Full article

(This article belongs to the Special Issue Advances in Computational Fluid Dynamics (CFD) Simulation of Thermal Chemical Processes)

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21 pages, 6049 KiB

Open AccessArticle

Sustainable Treatment of Amoxicillin-Contaminated Wastewater Using Fe²⁺/H₂O₂/AC: Performance, Stability, and Environmental Impact

by Sumita, Jibran Ali Ghumro, Jingzhen Su, Cong Li, Zhengming He and Jieming Yuan

Processes 2025, 13(4), 1054; https://doi.org/10.3390/pr13041054 - 1 Apr 2025

This study investigates the activation mechanisms of hydrogen peroxide (H₂O₂) using iron-activated carbon (Fe²⁺/H₂O₂/AC) for the efficient degradation of amoxicillin (AM) in wastewater. The system achieved a high degradation efficiency of 90% under [...] Read more.

This study investigates the activation mechanisms of hydrogen peroxide (H₂O₂) using iron-activated carbon (Fe²⁺/H₂O₂/AC) for the efficient degradation of amoxicillin (AM) in wastewater. The system achieved a high degradation efficiency of 90% under alkaline conditions (pH 9), with singlet oxygen (¹O₂) and hydroxyl radicals (^•OH) identified as the dominant reactive species through scavenger experiments. High-performance liquid chromatography–mass spectrometry (HPLC-MS) analysis revealed degradation by-products and proposed reaction pathways, including the loss of amine groups, ring-opening oxidation, and bond cleavage. The structural and morphological properties of Fe²⁺/H₂O₂/AC were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and Brunauer–Emmett–Teller (BET) analysis. The BET surface area of Fe²⁺/H₂O₂/AC was determined to be 128.36 m²/g, with a mesoporous structure facilitating efficient mass transfer and adsorption. The system was systematically evaluated under varying conditions, including H₂O₂ concentration (25–250 mg/L), catalyst dosage (0.05–1.0 mg/L), and pH (3–10). Kinetic analysis revealed that the degradation process follows pseudo-second-order kinetics (R² = 0.966), while adsorption isotherms were best described by the Langmuir model (R² = 0.98). Ecotoxicity tests indicated that the degradation products are less harmful to aquatic organisms. The system demonstrated excellent stability over three consecutive cycles, highlighting its potential for long-term application in treating pharmaceutical-contaminated wastewater. Full article

(This article belongs to the Section Environmental and Green Processes)

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33 pages, 4777 KiB

Open AccessReview

Biomass-Derived Syngas Chemical Looping Combustion Using Fluidizable Oxygen Carriers: A Review

by Hugo de Lasa and Nicolas Torres Brauer

Processes 2025, 13(4), 1053; https://doi.org/10.3390/pr13041053 - 1 Apr 2025

This critical review evaluates chemical looping combustion using a syngas derived from gasified biomass (BMD Syngas). It is anticipated that establishing such a process will open new opportunities for CO₂ sequestration and the use of highly concentrated CO₂ in the manufacturing [...] Read more.

This critical review evaluates chemical looping combustion using a syngas derived from gasified biomass (BMD Syngas). It is anticipated that establishing such a process will open new opportunities for CO₂ sequestration and the use of highly concentrated CO₂ in the manufacturing and synthesis of fuels from entirely renewable feedstocks. This review focuses on the process conducted through using two interconnected fluidized bed units: a nickel oxide reduction unit (an endothermic Fuel Reactor) and a nickel oxidation unit (an exothermic Air Reactor). In this respect, a high-performance OC (HPOC) with Ni on a γ-Al₂O₃ fluidizable support (20wt% Ni, 1wt% Co, 5wt% La/γ-Al₂O₃) was developed at the CREC (Chemical Reactor Engineering Centre) of the University of Western Ontario, Canada. The HPOC was studied in a CREC Riser Simulator. The benefits of this mini-fluidized unit are that it can be operated at 2–40 s reaction times, 550–650 °C temperatures, 1.3–2.5 H₂/CO ratios, and 0.5–1 biomass/syngas stoichiometric ratios, mimicking the conditions of industrial-scale CLC units. When using a syngas derived from biomass and the HPOC under these operating conditions, 90% CO, 92% H₂, and 88% CH4 conversions, together with a 91% CO₂ yield, were obtained. These results allowed the prediction of a 1.84–3.0 wt% (

g_{O_{2}} / g_{O_{C}}

) oxygen transport capacity, with a 40–70% nickel oxide conversion. The experimental data acquired with the CREC Riser Simulator permitted the development of realistic kinetic models. The resulting kinetics were used in combination with Computational Particle Fluid Dynamics (CPFD) to demonstrate the operability of a large-scale industrial syngas CLC process in a downer fuel unit. In addition, these CPFD simulations were employed to corroborate that high CO₂ yields are achievable in 12–15 m length downer fuel units. Full article

(This article belongs to the Special Issue Bioenergy Production from Biomass Feedstocks)

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19 pages, 3415 KiB

Open AccessArticle

Dynamic Modeling of Heat-Integrated Air Separation Column Based on Nonlinear Wave Theory and Mass Transfer Mechanism

by Hang Zhou, Xinlei Xia and Lin Cong

Processes 2025, 13(4), 1052; https://doi.org/10.3390/pr13041052 - 1 Apr 2025

The air separation process is an important industrial process for the production of high-purity nitrogen and oxygen, representing the level of technological development in a country’s chemical industry. It has high energy consumption but very low energy utilization efficiency. In the overall environment [...] Read more.

The air separation process is an important industrial process for the production of high-purity nitrogen and oxygen, representing the level of technological development in a country’s chemical industry. It has high energy consumption but very low energy utilization efficiency. In the overall environment of increasingly scarce global energy, the application of internal heat coupling technology in the air separation process can effectively reduce energy consumption. However, due to the low-temperature characteristics, ultra-high purity characteristics, and the nature of multi-component systems of the heat-integrated air separation column (HIASC), its modeling process and dynamic characteristic analysis are complex. To solve the disadvantages of overly complex mechanistic models and insufficient accuracy of traditional simplified models, a concentration distribution curve description method based on the mass transfer mechanism is proposed, and combined with the traditional wave theory, a nonlinear wave model of the HIASC is established. Based on this model, static and dynamic analyses were carried out, and the research results prove that the newly established nonlinear wave model maintains high accuracy while simplifying the model complexity. It can not only accurately track the concentration changes of key products but also fully reflect various typical nonlinear characteristics of the system. Compared to the mechanism model, the wave model can reduce the running time by approximately 20%, thereby improving operational efficiency. This method explains various characteristics of the system from a perspective different from that of the mechanistic model. Full article

(This article belongs to the Special Issue Heat and Mass Transfer Phenomena in Energy Systems)

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18 pages, 4317 KiB

Open AccessArticle

Fluorescence-Based Detection of Picric Acid Using Vortex-Assisted Liquid–Liquid Microextraction: An Innovative Analytical Approach

by Sofia Kakalejčíková, Dominik Harenčár, Yaroslav Bazeľ and Maksym Fizer

Processes 2025, 13(4), 1051; https://doi.org/10.3390/pr13041051 (registering DOI) - 1 Apr 2025

A novel design for vortex-assisted liquid–liquid microextraction (VALLME), combined with spectrofluorimetric determination (FLD), was proposed and successfully tested for determining picric acid (PA) in water samples. This fluorescence method is based on the formation of an ion associate (IA) through electrostatic interactions, which [...] Read more.

A novel design for vortex-assisted liquid–liquid microextraction (VALLME), combined with spectrofluorimetric determination (FLD), was proposed and successfully tested for determining picric acid (PA) in water samples. This fluorescence method is based on the formation of an ion associate (IA) through electrostatic interactions, which serves as the analytical species for fluorescence measurement in the presence of the basic polymethine dye Astrafloksin (AF). The approach aims to minimize the volume of the extraction phase, aligning with the principles of green analytical chemistry. The calibration curve was linear from 0.92 to 11.45 µg L⁻¹, with an R² of 0.9930. LOD was 0.40 µg L⁻¹. Density functional theory (DFT) calculations, supported by analysis of van der Waals and electrostatic interionic attraction, helped explain the experimentally observed selectivity of the AF cation for picrate compared to other selected phenols. Theoretical solubility descriptors of the proposed IA provided insight into the extraction of IA from water to the n-amyl acetate phase. This VALLME-FLD method represents a significant advancement in PA determination, characterized by high sensitivity, selectivity, and procedural simplicity. It minimizes the use of organic solvents, facilitates direct sample preparation, and shortens analysis time. The developed method was successfully applied to real samples. Full article

(This article belongs to the Special Issue Advanced Green Analytical Chemistry for Environmental Pollutants Detection)

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14 pages, 2636 KiB

Open AccessArticle

A Similarity Theory-Based Study on Natural Convection Condensation Boundary Layer Characteristics of Vertical Walls

by Jialei Liu, Yuqing Chen, Haifeng Gu, Yinxing Zhang, Wei Wang and Hongguang Xiao

Processes 2025, 13(4), 1050; https://doi.org/10.3390/pr13041050 (registering DOI) - 1 Apr 2025

To address the challenge of heat transfer enhancement in the condensation of steam with non-condensable gases on a vertical wall under natural convection conditions, an improved boundary layer model with coupled multi-physics field was proposed in this paper, and traditional theoretical limitations were [...] Read more.

To address the challenge of heat transfer enhancement in the condensation of steam with non-condensable gases on a vertical wall under natural convection conditions, an improved boundary layer model with coupled multi-physics field was proposed in this paper, and traditional theoretical limitations were broken through by innovations. The particle swarm optimization algorithm was first introduced into the solution of the condensation boundary layer, and the convergence difficulty in the laminar–turbulent transition region under infinite boundary conditions was overcome. A coupled momentum–energy–mass equation system that simultaneously considered temperature–concentration dual-driven gravity terms and liquid film drag–suction dual effects was established, and higher computational efficiency and accuracy were achieved. A new mechanism where the concentration boundary layer dominated heat transfer resistance under the coupled action of the Prandtl number (Pr) and Schmidt number (Sc) was revealed. Experimental validation demonstrated that a prediction error of less than 5% was exhibited by the model under typical operating conditions of passive containment cooling systems (pressures of 1.5–4.5 atm and subcooling temperatures of 14–36 °C), and a theoretical tool for high-precision condensation heat transfer design was provided. Full article

(This article belongs to the Section Chemical Processes and Systems)

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22 pages, 3878 KiB

Open AccessArticle

Precision Prediction Strategy for Renewable Energy Power in Power Systems—A Physical-Knowledge Integrated Model

by Shenbing Hua, Shuanglong Jin, Zongpeng Song, Xiaolin Liu, Shu Wang and Hengrui Ma

Processes 2025, 13(4), 1049; https://doi.org/10.3390/pr13041049 (registering DOI) - 1 Apr 2025

To promote energy transformation and upgrading and achieve the dual carbon strategic goals, the proportion of renewable energy generation in China has been increasing annually. Among them, wind and photovoltaic power generation play a significant role in renewable energy generation due to their [...] Read more.

To promote energy transformation and upgrading and achieve the dual carbon strategic goals, the proportion of renewable energy generation in China has been increasing annually. Among them, wind and photovoltaic power generation play a significant role in renewable energy generation due to their widely distributed energy sources, and their development has been particularly rapid. However, renewable energy generation exhibits strong volatility, and the integration of a large amount of renewable energy into the power grid poses a threat to the stable operation of the power system. Therefore, renewable energy power prediction is of great significance for the safe and stable operation of the power system. This paper proposes a physical-knowledge integrated renewable energy power prediction model. Firstly, the Fuzzy C-Means (FCM) method is used to handle missing data. Then, the variational mode decomposition (VMD) algorithm is applied to decompose the renewable energy power into high-frequency and low-frequency components. The high-frequency components are input into a Convolutional Neural Network (CNN) model, while the low-frequency components are input into a Long Short-Term Memory (LSTM) neural network for training and prediction. Finally, the effectiveness and feasibility of the proposed method in this paper are verified through real data from a certain actual power grid. After analysis, the proposed method demonstrates a prediction accuracy improvement of up to 5.71% compared to conventional approaches. Simultaneously, in high-noise interference environments, the prediction error can be reduced by up to 11.16%. Full article

(This article belongs to the Topic Advanced Operation, Control, and Planning of Intelligent Energy Systems)

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19 pages, 3736 KiB

Open AccessArticle

Radiation and Combustion Effects of Hydrogen Enrichment on Biomethane Flames

by Francisco Elmo Lima Uchoa Filho, Helton Carlos Marques Sampaio, Claudecir Fernandes de Freitas Moura Júnior, Mona Lisa Moura de Oliveira, Jesse Van Griensven Thé, Paulo Alexandre Costa Rocha and André Valente Bueno

Processes 2025, 13(4), 1048; https://doi.org/10.3390/pr13041048 (registering DOI) - 1 Apr 2025

Hydrogen has been presented as a promising energy vector in decarbonized economies. Its singular properties can affect important aspects of industrial flames, such as the temperature, emissions, and radiative/convective energy transfer balance, thus requiring in-depth studies to optimize combustion processes using this fuel [...] Read more.

Hydrogen has been presented as a promising energy vector in decarbonized economies. Its singular properties can affect important aspects of industrial flames, such as the temperature, emissions, and radiative/convective energy transfer balance, thus requiring in-depth studies to optimize combustion processes using this fuel isolate or in combination with other renewable alternatives. This work aims to conduct a detailed numerical analysis of temperatures and gas emissions in the combustion of biomethane enriched with different proportions of hydrogen, with the intent to contribute to the understanding of the impacts of this natural gas surrogate on practical combustion applications. RANS k-

ω

and k-

ϵ

turbulence models were combined with the GRI Mech 3.0, San Diego, and USC mechanisms using the ANSYS-Fluent 2024-R2 softwareto evaluate its performance regarding flame prediction. The Moss–Brookes model was adopted to predict soot formation for the methane flames by solving transport equations for normalized radical nuclei concentration and the soot mass fraction. The Discrete Ordinates (DOs) method with gray band model was applied to solve the Radiation Transfer Equation (RTE). The results of the experiments and numerical simulations highlight the importance of carefully selecting turbulence and chemical kinetics models for an accurate representation of real-scale industrial burners. Relative mean errors of 1.5% and 6.0% were registered for temperature and pollutants predictions, respectively, with the USD kinetics scheme and k-

o m e g a

turbulence model presenting the most accurate results. The operational impacts of hydrogen enrichment of biomethane flames were accessed for a practical combustion system. With 15% of hydrogen blending, the obtained results indicate a 73% penalty in CO emissions, an increase of 6% in NO emissions, and a 34 K flame temperature increase. Also, a reduction in flame radiation due to hydrogen enrichment was observed for hydrogen concentrations above 20%, a behavior that can affect practical combustion systems such as those in glass and other ceramics industries. Full article

(This article belongs to the Special Issue Biomass to Renewable Energy Processes, 2nd Edition)

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19 pages, 1219 KiB

Open AccessArticle

Energy Optimization for Microgrids Based on Uncertainty-Aware Deep Deterministic Policy Gradient

by Tao Wang, Hongchen Liu and Ming Su

Processes 2025, 13(4), 1047; https://doi.org/10.3390/pr13041047 (registering DOI) - 1 Apr 2025

The randomness, volatility, and intermittency of renewable energy sources such as wind and solar energy present significant challenges to energy management in microgrids, resulting in low management efficiency and poor accuracy. This paper proposes an energy optimization method for microgrids based on an [...] Read more.

The randomness, volatility, and intermittency of renewable energy sources such as wind and solar energy present significant challenges to energy management in microgrids, resulting in low management efficiency and poor accuracy. This paper proposes an energy optimization method for microgrids based on an uncertainty-aware deep deterministic policy gradient (DDPG) algorithm. First, considering the uncertainty of renewable energy output, an uncertainty awareness model is constructed based on information gap decision theory (IGDT). Second, the DDPG algorithm is employed to optimize the energy scheduling strategy, incorporating a bidirectional feedback collaborative optimization framework. The uncertainty radius is used for forward feedback adjustment of the optimization step size of the DDPG model, while the risk-aversion coefficient of the IGDT model is adjusted via backward feedback based on the DDPG optimization results. This approach enables adaptive regulation in dynamic and complex environments. The research demonstrates that the proposed algorithm significantly enhances the robustness, convergence, and adaptability of the microgrid in uncertain environments, improving peak shaving and valley filling performance as well as the adaptability to fluctuations in renewable energy sources. The proposed method demonstrates significant improvements in robustness, convergence speed, and adaptability when applied to microgrid energy management. Numerical results show a 5.44% and 70.26% improvement in total microgrid revenue compared to baseline algorithms, highlighting the effectiveness of the uncertainty-aware DDPG algorithm in dynamic and uncertain environments. Full article

(This article belongs to the Topic Intelligent, Flexible, and Effective Operation of Smart Grids with Novel Energy Technologies and Equipment)

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21 pages, 10566 KiB

Open AccessArticle

Analysis of Safe Mud Density Window for Enhanced Wellbore Stability

by Renjun Xie, Jianxiang Feng, Lu Qin, Junliang Yuan, Zhiwei Guo, Yue Yu and Sanyi Yuan

Processes 2025, 13(4), 1046; https://doi.org/10.3390/pr13041046 (registering DOI) - 1 Apr 2025

Deep drilling can lead to the encounter of complex geological conditions, with significant overburden pressure leading to a narrow safety window for mud density. In this study, we deviated wellbore instability conditions using the Mohr–Coulomb and tensile failure criteria, solving for collapse, shear, [...] Read more.

Deep drilling can lead to the encounter of complex geological conditions, with significant overburden pressure leading to a narrow safety window for mud density. In this study, we deviated wellbore instability conditions using the Mohr–Coulomb and tensile failure criteria, solving for collapse, shear, and fracture pressure using Newton’s method. The safe mud density window is defined between the maximum value of pore and collapse pressures and the minimum value of shear and fracture pressures. The analysis of the Anderson fault stress model, utilizing this method, enables a comprehensive investigation of how the safety mud density window varies with wellbore inclination and azimuth angles under various stress conditions. Additionally, applications in Chinese oilfields illustrate that this methodology can accurately calculate and analyze extremely narrow safety mud density windows at depths ranging from 2000 to 3000 m. In conclusion, this method enables rapid and accurate prediction of mud density limits, improving wellbore stability and reducing drilling risks. Full article

(This article belongs to the Section Energy Systems)

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16 pages, 3009 KiB

Open AccessArticle

Preparation of Composite Materials Based on Acrylonitrile–Butadiene–Styrene Flame-Retardant Plastic Obtained from Electronic Waste and Fly Ash Microspheres, with Thermogravimetric/Differential Scanning Calorimetry Analysis and a Study of the Mechanical Characteristics of the Obtained Material

by Natalya Kulenova, Ruslan Sapinov, Marzhan Sadenova and Zhanserik Shoshay

Processes 2025, 13(4), 1045; https://doi.org/10.3390/pr13041045 (registering DOI) - 1 Apr 2025

In this study, we investigate the potential of using acrylonitrile–butadiene–styrene flame-retardant (ABS FR) plastic obtained from electronic waste to create a new composite material through the addition of fly ash microspheres obtained from the combustion of thermal coal at Ekibastuzskaya GRES 1, with [...] Read more.

In this study, we investigate the potential of using acrylonitrile–butadiene–styrene flame-retardant (ABS FR) plastic obtained from electronic waste to create a new composite material through the addition of fly ash microspheres obtained from the combustion of thermal coal at Ekibastuzskaya GRES 1, with the resulting material being suitable for the manufacturing of housings and other elements of electronic equipment. For this purpose, five composite compositions with microsphere/plastic ratios of 10/90, 20/80, 30/70, 40/60, and 50/50 were developed, which were then processed in an extruder at 250 °C to obtain test specimens. The thermal and mechanical properties of the specimens were compared with a control sample developed using ABS FR plastic from electronic waste without the addition of microspheres. The obtained materials, up to a microsphere/plastic ratio of 20/80, demonstrate increased mechanical properties and thermal stability with a simultaneous decrease in material density, while a further increase in the concentration of microspheres leads to a gradual decrease in mechanical properties. These properties make it possible to use the obtained composite for producing housings and other elements of electronic equipment. Full article

(This article belongs to the Section Environmental and Green Processes)

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16 pages, 8022 KiB

Open AccessFeature PaperArticle

Injection-Molded Poly(butylene succinate)/Wheat Flour By-Product Biocomposites: Mechanical, Thermal, and Structural Characterization

by Bianca Peron-Schlosser, Rúbia Martins Bernardes Ramos, Luana Cristina Paludo, Pablo Inocêncio Monteiro, Fabíola Azanha de Carvalho, Samuel Camilo da Silva, Bruno Alexandro Bewzenko Cordova, Benjamim de Melo Carvalho, Fabio Yamashita and Michele Rigon Spier

Processes 2025, 13(4), 1044; https://doi.org/10.3390/pr13041044 - 31 Mar 2025

The increasing concern regarding the environmental impact of conventional plastics has intensified the search for sustainable alternatives. This study investigated the development and characterization of biocomposites produced from glue flour (GF), a wheat milling by-product, and poly(butylene succinate) (PBS) using injection molding. GF/PBS [...] Read more.

The increasing concern regarding the environmental impact of conventional plastics has intensified the search for sustainable alternatives. This study investigated the development and characterization of biocomposites produced from glue flour (GF), a wheat milling by-product, and poly(butylene succinate) (PBS) using injection molding. GF/PBS ratios of 100/0 (PBS0), 80/20 (PBS20), 70/30 (PBS30), and 60/40 (PBS40) (w/w) were evaluated in terms of physical, mechanical, and thermal properties. The results showed that increasing the PBS content significantly enhanced tensile strength from 1.36 MPa (PBS0) to 12.23 MPa (PBS40) and Young’s modulus from 0.12 MPa to 1.54 MPa. Water solubility decreased from 37.03% (PBS0) to 16.08% (PBS40), and linear shrinkage was reduced from 5.5% (PBS0) to around 2.0% (PBS40). Scanning electron microscopy (SEM) analysis revealed improved homogeneity and reduced granule visibility with higher PBS concentration. Fourier transform infrared spectroscopy (FTIR) spectra indicated intensified interactions between starch, proteins, and PBS as its content in the formulation increased. Thermal analysis revealed that biocomposites containing PBS exhibited well-defined melting (Tm ~115 °C) and crystallization (Tc ~80 °C) temperatures, indicating more consistent thermal behavior than the PBS-free sample. These findings suggest that GF/PBS biocomposites have strong potential as sustainable alternatives to conventional plastics, offering viable applications across various industrial sectors. Full article

(This article belongs to the Section Materials Processes)

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26 pages, 4363 KiB

Open AccessArticle

Anomaly Monitoring Model of Industrial Processes Based on Graph Similarity and Applications

by Guoqing Du, Mingyi Yang, Zhigang Xu, Junyi Wang, Cheng Xie, Yuan Lu and Pengfei Yin

Processes 2025, 13(4), 1043; https://doi.org/10.3390/pr13041043 - 31 Mar 2025

Aiming at the strong spatio-temporal coupling relationship between data in the actual industrial production process, which leads to the problem of insufficient reliability and poor timeliness of traditional process anomaly monitoring methods, a time series anomaly monitoring model based on the graph similarity [...] Read more.

Aiming at the strong spatio-temporal coupling relationship between data in the actual industrial production process, which leads to the problem of insufficient reliability and poor timeliness of traditional process anomaly monitoring methods, a time series anomaly monitoring model based on the graph similarity network with multi-scale features is proposed, which can react to the anomalies in the process in a timely and effective manner to guarantee production safety. First, a graph-building method for spatio-temporally coupled time-series data using multidimensional time-varying feature map embedding is designed to capture the dependence of the data on time, while the topology of the graph is utilized to learn the spatial coupling of the data; second, a graph similarity-based anomaly monitoring strategy is innovatively proposed to measure the anomalies of the process using the difference degree index between the standard normal process data and the monitoring data. Finally, the proposed method is validated using the standard normal operating condition data of the Tennessee-Eastman (TE) process as well as the standard fault data. The experimental results show that the proposed model can identify anomalies more quickly and accurately than other typical methods, which significantly improves the reliability and timeliness of industrial process anomaly monitoring. Full article

(This article belongs to the Section Process Control and Monitoring)

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16 pages, 5429 KiB

Open AccessArticle

High Cu-Cu Bonding Strength Achievement Using Micron Copper Particles Under Formic Acid Atmosphere

by Bofu Li, Yinyin Luo, Dejian Li, Dameng Li, Baobin Yang, Baoliang Gong, Shunfeng Han, Siliang He and Miao Cai

Processes 2025, 13(4), 1042; https://doi.org/10.3390/pr13041042 - 31 Mar 2025

This study demonstrates the achievement of robust Cu-Cu bonding strength through thermocompression bonding (TCB) under a formic acid (FA) atmosphere. When subjected to sintering at 300 °C for 1 min under FA, sintering joints exhibit an average shear strength of 50.9 MPa. This [...] Read more.

This study demonstrates the achievement of robust Cu-Cu bonding strength through thermocompression bonding (TCB) under a formic acid (FA) atmosphere. When subjected to sintering at 300 °C for 1 min under FA, sintering joints exhibit an average shear strength of 50.9 MPa. This strength further increases to an average of 131 MPa when the sintering duration is extended to 20 min at the same temperature under FA. Molecular dynamics simulations are employed to model the sintering behavior of copper particles of various sizes and thus understand the diffusion mechanism. The analysis of mean square displacement (MSD) and radial distribution function from these simulations suggests that the presence of small particles aids in the sintering of large ones. A copper paste, formulated by mixing micron-sized copper particles with organic solvents, is utilized in a series of experiments to explore different sintering methodologies aimed at enhancing the mechanical integrity of the sintering joints while simultaneously addressing issues associated with copper particle oxidation. Innovative strategies, including redox processes, are applied to improve the shear strength of the sintering joints and to minimize the detrimental effects of oxidation on the copper particles. Results indicate that preoxidation, which was used to form a nano surface structure, and using an FA atmosphere, remarkably enhance the shear strength of the Cu-Cu joints created via TCB. The findings of this research are pivotal for the advancement of rapid Cu-Cu bonding techniques using micron-scale copper pastes and can have profound implications for the development of future electronic packaging and interconnection technologies. Full article

(This article belongs to the Section Materials Processes)

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20 pages, 8991 KiB

Open AccessArticle

Enhanced Prediction of Muscle Activity Using Wearable Textile Stretch Sensors and Multi-Layer Perceptron

by Gyubin Lee, Sangun Kim and Jooyong Kim

Processes 2025, 13(4), 1041; https://doi.org/10.3390/pr13041041 (registering DOI) - 31 Mar 2025

This study investigates the use of surface electromyography (sEMG) sensors in measuring muscle activity and mapping it onto wearable textile stretch sensors using a basic deep learning model, the Multi-Layer Perceptron (MLP). Wearable sensors are gaining attention for their ability to monitor physiological [...] Read more.

This study investigates the use of surface electromyography (sEMG) sensors in measuring muscle activity and mapping it onto wearable textile stretch sensors using a basic deep learning model, the Multi-Layer Perceptron (MLP). Wearable sensors are gaining attention for their ability to monitor physiological data while maintaining user comfort. A three-stage experimental approach was employed to evaluate the mapping process. In the first stage, the impact of applying a low-pass finite impulse response (FIR) filter was assessed by comparing filtered and unfiltered sEMG data. The results showed minimal impact on accuracy (R-squared ~ 0.77), as RMS preprocessing effectively reduced noise. In the second stage, adding tensile velocity data improved the model’s predictive performance (R-squared ~ 0.80), emphasizing the importance of integrating dynamic variables. In the third stage, data from multiple muscle groups, including the biceps brachii, forearm muscles, and triceps brachii, were incorporated, achieving the highest R-squared value of ~0.94. These findings establish wearable textile stretch sensors as reliable tools for monitoring muscle activity during exercise. By demonstrating improved accuracy with a basic MLP model, this study provides a foundation for advancing wearable health monitoring systems and exploring additional physiological parameters and activities. Full article

(This article belongs to the Special Issue Research on Intelligent Fault Diagnosis Based on Neural Network)

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14 pages, 17757 KiB

Open AccessArticle

Reaction Behavior of Sm and Valence State Evolution of Sm³⁺ During the Reduction of SmF₃

by Donghui Liu, Yuxin Ye, Guisong Li, Kai Sun, Kuifang Zhang and Xiaolin Zhang

Processes 2025, 13(4), 1040; https://doi.org/10.3390/pr13041040 - 31 Mar 2025

SmF₃ cannot be reduced to metallic samarium by aluminum due to variable valence states of Sm. This study investigates the reduction products of SmF₃ via an aluminothermic reduction. The effect of molar ratios of Al/SmF₃ on the morphology, elemental distribution, [...] Read more.

SmF₃ cannot be reduced to metallic samarium by aluminum due to variable valence states of Sm. This study investigates the reduction products of SmF₃ via an aluminothermic reduction. The effect of molar ratios of Al/SmF₃ on the morphology, elemental distribution, crystal structure, and chemical valence of the samples were investigated by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). The thermodynamic results show that it is feasible for SmF₃ reduction by Al to form SmF₂ in 933~1356 K. SmF_2.413, AlF₃, and Sm(AlF)₅ are obtained under the condition of the molar ratio of Al to SmF₃ at 1:3, 2:3, 3:3, 4:3, and 5:3. The samarium of the reduction products exhibits mixed valence states of Sm³⁺ and Sm²⁺, with the ratio δ of F to Sm determined by a(δ) = −0.1794δ + 5.819 (0 ≤ δ ≤ 0.4615). The presence of adsorbed oxygen in the products facilitates the oxidation process from Sm²⁺ to Sm³⁺. These findings may provide a theoretical basis on the development of valence states for other rare earth elements in aluminothermic reduction. Full article

(This article belongs to the Section Materials Processes)

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15 pages, 6746 KiB

Open AccessArticle

Selective Complexation and Leaching of Cobalt Using Histidine in an Alkaline Medium

by Mengying Li, Qingliang Wang, Weiduo Guo, Xu Zhao, Yaolong Zhang, Xiankun Zhou, Zhiwu Lei and Yahui Zhang

Processes 2025, 13(4), 1039; https://doi.org/10.3390/pr13041039 - 31 Mar 2025

Considering the issues of significant ammonia volatilization loss and toxic gas emission associated with the conventional ammonia leaching method used in the resource utilization of cobalt-rich alloy slag, a novel approach involving selective complexation leaching of cobalt in an alkaline histidine solution has [...] Read more.

Considering the issues of significant ammonia volatilization loss and toxic gas emission associated with the conventional ammonia leaching method used in the resource utilization of cobalt-rich alloy slag, a novel approach involving selective complexation leaching of cobalt in an alkaline histidine solution has been proposed. Under conditions of 35 °C temperature, a molar ratio of histidine to cobalt of 1.5, pH of 8, a leaching period of 12 h, and a stirring speed of 300 rpm, the cobalt leaching rate from cobalt-rich alloy slag exceeds 95%. In contrast, the leaching rates for impurity metals such as iron, lead, and copper remain below 3%, demonstrating outstanding leaching selectivity. Leaching kinetics calculations indicate that the rate-controlling step is chemical reaction control, with an apparent activation energy of 64.32 kJ/mol. Through the use of FTIR and XPS characterization techniques, it has been confirmed that histidine molecules form a stable complex with cobalt ions via the dual coordination of the carboxyl (COO⁻) and amino (-NH₂) groups. This distinctive bifunctional synergistic coordination mechanism markedly enhances leaching selectivity and reaction efficiency. Full article

(This article belongs to the Section Separation Processes)

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15 pages, 1964 KiB

Open AccessFeature PaperArticle

Synthesis of 2,3-Dihydrobenzofuran Chalcogenides Under Visible Light: A Sustainable Approach

by Luana S. Gomes, Millena C. Silva, Patrick C. Nobre, Thiago J. Peglow and Vanessa Nascimento

Processes 2025, 13(4), 1038; https://doi.org/10.3390/pr13041038 - 31 Mar 2025

This study introduces a visible light-mediated synthesis of 2,3-chalcogenil-dihydrobenzofuran through the oxyselenocyclization of 2-allylphenols in the presence of chalcogenides. Emphasizing sustainability, this method is notably enhanced by proceeding under mild conditions, facilitated by a straightforward I₂/SnCl₂ as a promoter and [...] Read more.

This study introduces a visible light-mediated synthesis of 2,3-chalcogenil-dihydrobenzofuran through the oxyselenocyclization of 2-allylphenols in the presence of chalcogenides. Emphasizing sustainability, this method is notably enhanced by proceeding under mild conditions, facilitated by a straightforward I₂/SnCl₂ as a promoter and blue LED irradiation to activate the process. A variety of functional groups were effectively tolerated under our developed approach, leading to the desired products with yields ranging from good to excellent, demonstrating in this way the versatility of the method. In addition, the synthesized compounds were characterized using ¹H and ¹³C NMR techniques. Full article

(This article belongs to the Special Issue Advances and Prospects in Organic Synthesis)

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