Processes

19 pages, 968 KiB

Open AccessArticle

Development of Maintenance Plan for Power-Generating Unit at Gas Plant of Sirte Oil Company Using Risk-Based Maintenance (RBM) Approach

by Abdelnaser Elwerfalli, Salih Alsadaie and Iqbal M. Mujtaba

Processes 2025, 13(8), 2533; https://doi.org/10.3390/pr13082533 (registering DOI) - 11 Aug 2025

Abstract

This paper presents a novel risk-based maintenance (RBM) approach for the development of a structured maintenance strategy for the power-generating (PG) unit at the gas plant of the Sirte Oil Company (SOC). The proposed approach comprises three key aspects: estimated risk (ER), risk [...] Read more.

This paper presents a novel risk-based maintenance (RBM) approach for the development of a structured maintenance strategy for the power-generating (PG) unit at the gas plant of the Sirte Oil Company (SOC). The proposed approach comprises three key aspects: estimated risk (ER), risk evaluation (RV), and maintenance planning (MP). To identify and prioritize critical components, the methodology integrates fault tree analysis (FTA) with Monte Carlo simulations, enabling the probabilistic modeling of failure scenarios and the accurate quantification of risk. High-pressure (HP) water systems were selected as a case study due to their significant role and failure consequences within the PG unit. Through this RBM methodology, risk levels—based on the probability of failure (PoF) and consequence of failure (CoF)—were quantified, and maintenance tasks were rescheduled to target the most vulnerable components. The results demonstrate that implementing the RBM strategy reduced unplanned shutdowns and optimized uptime, achieving 348 operational days per year, compared to the baseline 365-day mean time to failure (MTTF) cycle (reduction in downtime of around 4.65%). This translated into a measurable improvement in system reliability and operational efficiency. The approach is especially applicable to processing units operating under harsh conditions, offering a preventive tool for the reduction of risk exposure and improvements in asset performance. Full article

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

14 pages, 740 KiB

Open AccessArticle

Power Effectiveness Factor: A Method for Evaluating Photovoltaic Enhancement Techniques

by Sakhr M. Sultan and C. P. Tso

Processes 2025, 13(8), 2532; https://doi.org/10.3390/pr13082532 - 11 Aug 2025

Abstract

Photovoltaic (PV) module enhancers, such as coolers and reflectors, are advanced technologies aimed at improving PV performance. The conventional approach for selecting the optimal PV enhancer relies on the observation of the highest power. While effective in comparing different enhancer designs, this method [...] Read more.

Photovoltaic (PV) module enhancers, such as coolers and reflectors, are advanced technologies aimed at improving PV performance. The conventional approach for selecting the optimal PV enhancer relies on the observation of the highest power. While effective in comparing different enhancer designs, this method does not determine the maximum performance that the PV enhancer can achieve. To address this limitation, a new methodology is introduced that overcomes this drawback. It relies on three essential parameters: the net power gain with an enhancer, the power output of a PV module without an enhancer, and the maximum power of a PV module under standard test conditions. The impact of each parameter on the proposed method is analyzed, and enhancers are classified based on the method’s output. Maximum or minimum performance is observed when the method’s value is either in unity with or matches the ratio of a PV module’s power output (without an enhancer) to its maximum power under standard conditions. To validate this approach in practical applications, experimental data from previous studies are examined. The results confirm that this technique can be applied for real-world cases and can effectively categorize PV enhancers, offering valuable insights for researchers, designers, and manufacturers. Full article

(This article belongs to the Special Issue Advancements in Photovoltaic Technologies: Innovations for Enhanced Energy Conversion and Efficiency)

15 pages, 904 KiB

Open AccessArticle

Low-Carbon and Economic-Oriented Dispatch Method for Multi-Microgrid Considering Green Certificate: Carbon Trading Mechanism Driven by AI Reinforcement Learning-Enhanced Genetic Algorithm

by Yiqiao Cheng, Hongbo Zou and Fei Wang

Processes 2025, 13(8), 2531; https://doi.org/10.3390/pr13082531 (registering DOI) - 11 Aug 2025

Abstract

Aiming at the problem that the existing research mostly focuses on a single microgrid or an independent optimization goal and lacks the cooperative scheduling of multi-microgrids and the deep integration with the green certificate (GC) and carbon trading (CT) mechanisms, this paper proposes [...] Read more.

Aiming at the problem that the existing research mostly focuses on a single microgrid or an independent optimization goal and lacks the cooperative scheduling of multi-microgrids and the deep integration with the green certificate (GC) and carbon trading (CT) mechanisms, this paper proposes a low-carbon and economic-oriented dispatch method for multi-microgrids considering a GC-CT mechanism driven by an artificial intelligence (AI) reinforcement learning-enhanced genetic algorithm (GA). First of all, under the constructed architecture model of the GC-CT mechanism and multi-microgrid, this method constructs an optimal objective model that incorporates economic revenue and GC-CT costs. Secondly, regarding the two key parameters, crossover rate and mutation rate, which seriously influence the performance of the GA, this paper utilizes an AI reinforcement learning algorithm to adaptively adjust them and solves the constructed model based on the AI reinforcement learning-enhanced GA. Finally, based on a regional multi-microgrid system, the simulation results show that the proposed method can significantly improve the operating efficiency of the microgrid system after integrating the GC-CT mechanism into the microgrid system, which provides a theoretical framework and technical path for low-carbon and economic-oriented dispatch of multi-microgrids and helps the power system to evolve into a zero-carbon smart energy system. Full article

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

► Show Figures

Figure 1

21 pages, 1141 KiB

Open AccessArticle

Simulation and Optimization of a Novel FLNG Liquefaction Process Based on Supersonic Swirling Separation and Nitrogen Expansion Refrigeration

by Lei Gao, Zhaoxi Wang, Guodong Qiu, Yihuai Hua, Jiang Bian and Weihua Cai

Processes 2025, 13(8), 2530; https://doi.org/10.3390/pr13082530 - 11 Aug 2025

Abstract

To meet the high standards required for the liquefaction process by the Floating Liquefied Natural Gas System (FLNG), including low power consumption, compact footprint, high safety, resistance to waves, and portability, this paper proposes a novel FLNG liquefaction process which combines the supersonic [...] Read more.

To meet the high standards required for the liquefaction process by the Floating Liquefied Natural Gas System (FLNG), including low power consumption, compact footprint, high safety, resistance to waves, and portability, this paper proposes a novel FLNG liquefaction process which combines the supersonic swirling separation technology with pressurized liquefaction technology. The process is simulated and optimized using Aspen HYSYS V10 software and genetic algorithms. The results indicate that the specific power consumption of this liquefaction process is only 0.208 kWh/m³, with the cooler, expander, and compressor being the main equipment responsible for exergy losses, accounting for 28.85%, 26.48%, and 21.70%, respectively. This liquefaction process is relatively adaptable to changes in feed gas pressure, temperature, and methane content. The specific power consumption slightly increases with the increasing feed gas pressure and temperature, while it exhibits some fluctuations with the increasing methane content. The process requires a low CO₂ removal rate, possesses moisture pretreatment capability, has fewer pieces of equipment, and saves a significant amount of valuable space. It combines low specific power consumption, minimal impact from swaying, and high safety, providing considerable application potential in future offshore natural gas development. Full article

(This article belongs to the Special Issue Experiments and Numerical Simulations for Heat Transfer and Flow of Supercritical Fluids)

19 pages, 2298 KiB

Open AccessArticle

Reservoir Characterization and 3D Geological Modeling of Fault-Controlled Karst Reservoirs: A Case Study of the Typical Unit of the TP12CX Fault Zone in the Tuoputai Area, Tahe Oilfield

by Bochao Tang, Chenggang Li, Chunying Geng, Bo Liu, Wenrui Li, Chen Guo, Lihong Song, Chao Yu and Binglin Li

Processes 2025, 13(8), 2529; https://doi.org/10.3390/pr13082529 - 11 Aug 2025

Abstract

This study presents an integrated workflow for the characterization of fault-controlled fractured–vuggy reservoirs, demonstrated through a comprehensive analysis of the TP12CX fault zone in the Tahe Oilfield. The methodology establishes a four-element structural model—comprising the damage zone, fault core, vuggy zone, and cavern [...] Read more.

This study presents an integrated workflow for the characterization of fault-controlled fractured–vuggy reservoirs, demonstrated through a comprehensive analysis of the TP12CX fault zone in the Tahe Oilfield. The methodology establishes a four-element structural model—comprising the damage zone, fault core, vuggy zone, and cavern system—coupled with a multi-attribute geophysical classification scheme integrating texture contrast, deep learning, energy envelope, and residual impedance attributes. This framework achieves a validation accuracy of 91.2%. A novel structural element decomposition–integration approach is proposed, combining deterministic structural reconstruction with facies-constrained petrophysical modeling to quantify reservoir properties. The resulting models identify key heterogeneities, including caverns (Φ = 17.8%, K = 587 mD), vugs (Φ = 3.5%, K = 25 mD), and fractures (K = 1400 mD), with model reliability verified through production history matching. Field application of an optimized nitrogen foam flooding strategy, guided by this workflow, resulted in an incremental oil recovery of 3292 tons. The proposed methodology offers transferable value by addressing critical challenges in karst reservoir characterization, including seismic resolution limits, complex heterogeneity, and late-stage development optimization in fault-controlled carbonate reservoirs. It provides a robust and practical framework for enhanced oil recovery in structurally complex carbonate reservoirs, particularly those in mature fields with a high water cut. Full article

(This article belongs to the Special Issue Multiphase Flow, and Efficient Development Methodology and Technology in Unconventional Reservoirs (2nd Edition))

26 pages, 3122 KiB

Open AccessArticle

Sustainable Adsorption of Amoxicillin and Sulfamethoxazole onto Activated Carbon Derived from Food and Agricultural Waste: Isotherm Modeling and Characterization

by Arzum Işıtan

Processes 2025, 13(8), 2528; https://doi.org/10.3390/pr13082528 - 11 Aug 2025

Abstract

This study investigates the adsorption performance of activated carbon (AC) derived from food and agricultural waste, specifically coffee grounds, coffee skin, bamboo, and palm leaves, for the removal of two antibiotics: amoxicillin (AMX) and sulfamethoxazole (SMX). The ACs were synthesized via KOH and [...] Read more.

This study investigates the adsorption performance of activated carbon (AC) derived from food and agricultural waste, specifically coffee grounds, coffee skin, bamboo, and palm leaves, for the removal of two antibiotics: amoxicillin (AMX) and sulfamethoxazole (SMX). The ACs were synthesized via KOH and ZnCl₂ chemical activation and characterized through BET surface area analysis, thermal stability, electrical conductivity, SEM, EDS, and FTIR. Among all samples, bamboo-derived AC (B-AC) exhibited superior properties, such as the highest surface area (860 m²/g), thermal stability (855 °C), conductivity (0.063 S/cm), and adsorption capacities (292.6 mg/g for AMX and 195.7 mg/g for SMX). SEM and EDS analyses confirmed successful antibiotic adsorption with morphological and elemental changes, while FTIR spectra indicated interaction with surface functional groups. Adsorption data were best described by the Langmuir and Dubinin–Radushkevich isotherm models, suggesting a monolayer physical adsorption process dominated by micropore filling (E < 8 kJ/mol). In contrast, BET and Flory–Huggins models exhibited poor fit, confirming the absence of multilayer or partition-based adsorption mechanisms. Kinetic modeling showed that AMX followed a pseudo-second-order model, while SMX exhibited a more complex adsorption behavior. Thermodynamic studies confirmed that both processes were spontaneous, with AMX adsorption being endothermic and entropy-driven and SMX being exothermic but favorable. These findings demonstrate the high potential of B-AC as a low-cost, eco-friendly, and efficient adsorbent for pharmaceutical removal from water, supporting circular economy and sustainability goals. Full article

(This article belongs to the Special Issue Sustainable Adsorbent Materials for Wastewater Treatment)

► Show Figures

Graphical abstract

22 pages, 3845 KiB

Open AccessReview

Improving Biodiesel Atomization Performance in CI Engines: A Review of Spray Behavior, Droplet Impingement, and Advanced Techniques

by Zehao Feng, Junlong Zhang, Jiechong Gu, Xianyin Leng, Zhixia He and Keiya Nishida

Processes 2025, 13(8), 2527; https://doi.org/10.3390/pr13082527 - 11 Aug 2025

Abstract

The escalating challenges of greenhouse gas emissions, coupled with the severe depletion of oil reserves and the surging global energy demand, have emerged as critical concerns requiring urgent attention. Against this backdrop, biodiesel has been recognized as a viable alternative fuel for compression [...] Read more.

The escalating challenges of greenhouse gas emissions, coupled with the severe depletion of oil reserves and the surging global energy demand, have emerged as critical concerns requiring urgent attention. Against this backdrop, biodiesel has been recognized as a viable alternative fuel for compression ignition (CI) engines. The primary objective of this research is to review the application of biodiesel in CI engines, with a focus on enhancing fuel properties and improving atomization performance. This article examines the spray and atomization characteristics of biodiesel fuels and conducts a comparative analysis with diesel fuel. The results show that biodiesel has a longer spray tip penetration, smaller spray cone angle, larger Sauter mean diameter (SMD) and faster droplet velocity due to its higher viscosity and surface tension. Blending with other fuels, such as ethanol, butanol, dimethyl ether (DME) and di-n-butyl ether, results in reduced viscosity and surface tension in these mixed fuels, representing a simple and effective approach for improving biodiesel atomization performance. A comprehensive analysis of spray and droplet impingement is also conducted. The findings reveal that biodiesel exhibits a higher probability of fuel–wall impingement, suggesting that future research should focus on two key directions: first, developing combined strategies to enhance impact-induced secondary atomization while minimizing fuel deposition; and second, investigating single-droplet impingement, specifically that of microscale biodiesel droplets and blended fuel droplets under real engine operating conditions. This paper also presents several advanced techniques, including air-assisted atomization, dual-fuel impingement, nano-biodiesel, and water-emulsified biodiesel, aimed at mitigating the atomization limitations of biodiesel, thereby facilitating the broader adoption of biodiesel in compression ignition engines. Full article

(This article belongs to the Special Issue Low/Zero Carbon Fuels Production, Transportation, Storage and Utilization)

► Show Figures

Figure 1

26 pages, 2753 KiB

Open AccessArticle

Intelligent Impedance Strategy for Force–Motion Control of Robotic Manipulators in Unknown Environments via Expert-Guided Deep Reinforcement Learning

by Hui Shao, Weishi Hu, Li Yang, Wei Wang, Satoshi Suzuki and Zhiwei Gao

Processes 2025, 13(8), 2526; https://doi.org/10.3390/pr13082526 - 11 Aug 2025

Abstract

In robotic force–motion interaction tasks, ensuring stable and accurate force tracking in environments with unknown impedance and time-varying contact dynamics remains a key challenge. Addressing this, the study presents an intelligent impedance control (IIC) strategy that integrates model-based insights with deep reinforcement learning [...] Read more.

In robotic force–motion interaction tasks, ensuring stable and accurate force tracking in environments with unknown impedance and time-varying contact dynamics remains a key challenge. Addressing this, the study presents an intelligent impedance control (IIC) strategy that integrates model-based insights with deep reinforcement learning (DRL) to improve adaptability and robustness in complex manipulation scenarios. The control problem is formulated as a Markov Decision Process (MDP), and the Deep Deterministic Policy Gradient (DDPG) algorithm is employed to learn continuous impedance policies. To accelerate training and improve convergence stability, an expert-guided initialization strategy is introduced based on iterative error feedback, providing a weak-model-based demonstration to guide early exploration. To rigorously assess the impact of contact uncertainties on system behavior, a comprehensive performance analysis is conducted by utilizing a time- and frequency-domain approach, offering deep insights into how impedance modulation shapes both transient dynamics and steady-state accuracy across varying environmental conditions. A high-fidelity simulation platform based on MATLAB (version 2021b) multi-toolbox co-simulation is developed to emulate realistic robotic contact conditions. Quantitative results show that the IIC framework significantly reduces settling time, overshoot, and undershoot under dynamic contact conditions, while maintaining stability and generalization across a broad range of environments. Full article

(This article belongs to the Special Issue Process Optimization, Diagnosis, and Control for Complex Industrial Processes)

► Show Figures

Figure 1

6 pages, 186 KiB

Open AccessEditorial

Special Issue on “10th Anniversary of Processes: Recent Advances in Food Processing Processes”

by Dariusz Dziki

Processes 2025, 13(8), 2525; https://doi.org/10.3390/pr13082525 - 11 Aug 2025

Abstract

It is a great pleasure to present this Special Issue of Processes, dedicated to celebrating the journal’s 10th anniversary and showcasing the latest advances in the field of food processing [...] Full article

(This article belongs to the Special Issue 10th Anniversary of Processes: Recent Advances in Food Processing Processes)

16 pages, 1511 KiB

Open AccessArticle

A Network Partition-Based Optimal Reactive Power Allocation and Sizing Method in Active Distribution Network

by Deshu Gan, Huabao Ling, Zhijian Mao, Ran Gu, Kangxin Zhou and Keman Lin

Processes 2025, 13(8), 2524; https://doi.org/10.3390/pr13082524 - 11 Aug 2025

Abstract

To address the node voltage fluctuation and over-limit caused by the high penetration of distributed photovoltaic (PV) generation connected to distribution networks, this paper proposes a network partition-based optimal reactive power allocation and sizing method in the active distribution network (ADN). A network [...] Read more.

To address the node voltage fluctuation and over-limit caused by the high penetration of distributed photovoltaic (PV) generation connected to distribution networks, this paper proposes a network partition-based optimal reactive power allocation and sizing method in the active distribution network (ADN). A network index incorporating network partition and critical node identification is introduced to obtain the optimal location for the reactive power compensation. A singular value entropy-based adaptive spectral clustering algorithm is applied to obtain the initial zones and obtain the critical nodes of each zone on the basis of the proposed network indexes. This method avoids the unreasonable scheme and enhances the efficiency and clarity of partitioning. The improved decimal coding method is proposed to improve the efficiency of the proposed method. A case study on the IEEE 33-node distribution system is carried out to verify the feasibility and effectiveness of the proposed method. The results show that compared with the conventional methods, the proposed method can effectively reduce voltage variations and control the voltage within the safe limit. Full article

(This article belongs to the Special Issue Advances in Smart Grids and Microgrids: Distributed Generation and Energy Storage Systems)

► Show Figures

Figure 1

16 pages, 2888 KiB

Open AccessArticle

Research on Methods to Improve Liquefaction Efficiency of Supersonic Cyclone Devices

by Yuan Tian, Huang Qian, Huirong Huang and Xueyuan Long

Processes 2025, 13(8), 2523; https://doi.org/10.3390/pr13082523 - 11 Aug 2025

Abstract

This research explores supersonic cyclonic separation for natural gas liquefaction (LNG). A 3D computational model was developed using the Eulerian–Eulerian two-fluid framework to simulate spontaneous gas condensation. The model tracks droplet formation/growth mechanisms and employs Reynolds stress modeling (RSM) for turbulence, implemented in [...] Read more.

This research explores supersonic cyclonic separation for natural gas liquefaction (LNG). A 3D computational model was developed using the Eulerian–Eulerian two-fluid framework to simulate spontaneous gas condensation. The model tracks droplet formation/growth mechanisms and employs Reynolds stress modeling (RSM) for turbulence, implemented in Fluent via user-defined functions (UDFs). Validated against experimental data, it accurately predicted condensation onset and shock wave behavior. A prototype separator designed for a natural gas peak-shaving station demonstrated lower temperatures than throttling valves but modest liquefaction efficiency (4.28% at 5 MPa inlet pressure). Two enhancement strategies were tested: (1) injecting submicron LNG condensation nuclei (radius < 1 × 10⁻⁹ m) significantly boosted liquefaction by reducing nucleation energy barriers and suppressing condensation shocks; (2) a multi-stage configuration increased total liquefaction by 156% versus single-stage operation. These findings highlight the technology’s potential for energy-efficient gas processing. Full article

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

► Show Figures

Figure 1

27 pages, 5201 KiB

Open AccessReview

Geomechanical and Geochemical Considerations for Hydrogen Storage in Shale and Tight Reservoirs

by Sarath Poda and Gamadi Talal

Processes 2025, 13(8), 2522; https://doi.org/10.3390/pr13082522 - 11 Aug 2025

Abstract

Underground hydrogen storage (UHS) in shale and tight reservoirs offers a promising solution for large-scale energy storage, playing a critical role in the transition to a hydrogen-based economy. However, the successful deployment of UHS in these low-permeability formations depends on a thorough understanding [...] Read more.

Underground hydrogen storage (UHS) in shale and tight reservoirs offers a promising solution for large-scale energy storage, playing a critical role in the transition to a hydrogen-based economy. However, the successful deployment of UHS in these low-permeability formations depends on a thorough understanding of the geomechanical and geochemical factors that affect storage integrity, injectivity, and long-term stability. This review critically examines the geomechanical aspects, including stress distribution, rock deformation, fracture propagation, and caprock integrity, which govern hydrogen containment under subsurface conditions. Additionally, it explores key geochemical challenges such as hydrogen-induced mineral alterations, adsorption effects, microbial activity, and potential reactivity with formation fluids, to evaluate their impact on storage feasibility. A comprehensive analysis of experimental studies, numerical modeling approaches, and field applications is presented to identify knowledge gaps and future research directions. Full article

(This article belongs to the Special Issue Recent Developments in Low-Carbon and Efficient Extraction Technologies of Deep Unconventional Reservoirs)

► Show Figures

Figure 1

30 pages, 2320 KiB

Open AccessFeature PaperArticle

Effect of Different Amine Solutions on Performance of Post-Combustion CO₂ Capture

by Sara Elmarghni, Meisam Ansarpour and Tohid N. Borhani

Processes 2025, 13(8), 2521; https://doi.org/10.3390/pr13082521 - 10 Aug 2025

Abstract

Carbon dioxide (CO₂) is the primary component contributing to anthropogenic greenhouse gas emissions, necessitating the adoption of effective mitigation strategies to promote environmental sustainability. Among the various carbon capture methodologies, chemical absorption is acknowledged as the most scalable solution for post-combustion [...] Read more.

Carbon dioxide (CO₂) is the primary component contributing to anthropogenic greenhouse gas emissions, necessitating the adoption of effective mitigation strategies to promote environmental sustainability. Among the various carbon capture methodologies, chemical absorption is acknowledged as the most scalable solution for post-combustion applications. This investigation presents a thorough, comparative, and scenario-based evaluation of both singular and blended amine solvents for CO₂ capture within packed absorption–desorption columns. A validated rate-based model employing monoethanolamine (MEA) functions as the benchmark for executing process simulations. Three sequential scenarios are meticulously examined to switch the solvents and see the results. In the preliminary scenario, baseline performance is assessed by applying MEA to achieve the designated 73% removal target. Then the implementation of alternative solvents is examined—piperazine (PZ), a combination of methyldiethanolamine (MDEA) and PZ, and a blend of MEA and PZ—under uniform design parameters to ascertain their relative effectiveness and performance. In the second scenario, the design of the system is changed to reach a CO₂ removal efficiency for MEA of 90%, and then MEA is switched to other solvents. In the final scenario, critical design parameters, including column height and diameter, are adjusted for each solvent system that did not meet the 90% capture efficiency in Scenario 2 to achieve 90% CO₂ capture. A comprehensive sensitivity analysis is subsequently conducted on the adjusted systems to evaluate the influence of critical operational variables such as temperature, flue gas and solvent flow rates, and concentrations. Importantly, the MEA + PZ blend also demonstrated the lowest specific reboiler duty, as low as 4.28 MJ/kg CO₂, highlighting its superior energy efficiency compared to other solvents in the condition that the system in this study is pilot-scale, not commercial-scale, and due to this reason, the energy consumption of the system is slightly higher than the reported value for the commercial-scale systems. The results yield invaluable insights into the performance trade-offs between singular and blended amines, thereby facilitating the development of more efficient CO₂ capture systems that function within practical constraints. Full article

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

► Show Figures

Figure 1

12 pages, 1712 KiB

Open AccessArticle

Selective and Efficient Separation of No-Carrier-Added 161Tb from Gd/Dy Matrix Using P350@Resin for Radiopharmaceutical Applications

by Jiuquan Qi, Qianwen Chen, Shuainan Ni and Chuanying Liu

Processes 2025, 13(8), 2520; https://doi.org/10.3390/pr13082520 - 10 Aug 2025

Abstract

Terbium-161 (¹⁶¹Tb) is an emerging β⁻-emitting radionuclide of high interest for targeted radionuclide therapy. However, its reactor-based production presents significant challenges in the efficient separation of ¹⁶¹Tb from target ¹⁶⁰Gd and co-produced ¹⁶¹Dy. In this study, [...] Read more.

Terbium-161 (¹⁶¹Tb) is an emerging β⁻-emitting radionuclide of high interest for targeted radionuclide therapy. However, its reactor-based production presents significant challenges in the efficient separation of ¹⁶¹Tb from target ¹⁶⁰Gd and co-produced ¹⁶¹Dy. In this study, the separation of ¹⁶¹Tb by a solvent-impregnated resin P350@resin has been evaluated. A combination of static adsorption and dynamic column experiments was conducted to investigate the separation behavior of Gd³⁺, Tb³⁺, and Dy³⁺. Optimal separation performance was achieved at 0.4–0.6 mol/L HNO₃, using a column bed height of 20–28 cm and flow rates of 0.5–1.0 mL/min. A two-step elution protocol enabled near-baseline resolution between Tb and Gd, Dy within 3 h, ensuring high-purity and fast product recovery. Comprehensive characterization using SEM-EDS, FT-IR, and XPS confirmed that metal ion uptake occurs via coordination with phosphoryl groups on the resin. The P350@resin thus enables a simple and selective separation platform for the production of no-carrier-added ¹⁶¹Tb, with high potential for clinical radiopharmaceutical manufacturing. Full article

(This article belongs to the Section Separation Processes)

► Show Figures

Figure 1

22 pages, 4801 KiB

Open AccessArticle

Research on the Process for Removing Heat-Stable Salts from Organic Amine Absorbents via Electrodialysis

by Guang Chen, Qian Liu, Li Liu, Shilong Zhang, Guixian Li, Hongwei Li and Dongliang Wang

Processes 2025, 13(8), 2519; https://doi.org/10.3390/pr13082519 - 10 Aug 2025

Abstract

The use of organic amine absorbents in CO₂ capture technologies is highly significant. The widespread application of this technique is limited by the heat-stable salts (HSSs) produced during the cyclic absorption–desorption process. This research focused on the HSS removal process using electrodialysis [...] Read more.

The use of organic amine absorbents in CO₂ capture technologies is highly significant. The widespread application of this technique is limited by the heat-stable salts (HSSs) produced during the cyclic absorption–desorption process. This research focused on the HSS removal process using electrodialysis technology and systematically examined the effects of operating voltage, initial concentration, pH, current density, the ratio of liquid volume in the enriched chamber to that in the diluting chamber, and the type of ion-exchange membrane on desalination efficiency, energy consumption, and amine loss. An increase in both voltage and initial concentration significantly enhances the rate of water migration. The rate of ion migration is observed to follow the order of Cl⁻ >

{S O}_{4}^{2 -}

> F⁻ in a homogeneous membrane, while in a heterogeneous membrane, the order is

{SO}_{4}^{2 -}

> Cl⁻ > F⁻. The optimal operating voltage is 10 V, with a pH level of 8 resulting in the highest

{SO}_{4}^{2 -}

removal efficiency. An industrial scenario validated the optimized process conditions, which balanced energy consumption with desalination efficiency. This methodology is essential not only for providing a viable solution for the industrial purification of organic amines but also for promoting the environmentally sustainable development of carbon capture technologies. Full article

(This article belongs to the Special Issue Advances in Process Systems Engineering: Selected Papers from China PSE Annual Meeting)

► Show Figures

Figure 1

20 pages, 3862 KiB

Open AccessArticle

BlueberryNet: A Lightweight CNN for Real-Time Ripeness Detection in Automated Blueberry Processing Systems

by Bojian Yu, Hongwei Zhao and Xinwei Zhang

Processes 2025, 13(8), 2518; https://doi.org/10.3390/pr13082518 - 10 Aug 2025

Abstract

Blueberries are valued for their flavor and health benefits, but inconsistent ripeness at harvest complicates post-harvest food processing such as sorting and quality control. To address this, we propose a lightweight convolutional neural network (CNN) to detect blueberry ripeness in complex field environments, [...] Read more.

Blueberries are valued for their flavor and health benefits, but inconsistent ripeness at harvest complicates post-harvest food processing such as sorting and quality control. To address this, we propose a lightweight convolutional neural network (CNN) to detect blueberry ripeness in complex field environments, supporting efficient and automated food processing workflows. To meet the low-power and low-resource demands of embedded systems used in smart processing lines, we introduce a Grouped Large Kernel Reparameterization (GLKRep) module. This design reduces computational cost while enhancing the model’s ability to recognize ripe blueberries under complex lighting and background conditions. We also propose a Unified Adaptive Multi-Scale Fusion (UMSF) detection head that adaptively integrates multi-scale features using a dynamic receptive field. This enables the model to detect blueberries of various sizes accurately, a common challenge in real-world harvests. During training, a Semantics-Aware IoU (SAIoU) loss function is used to improve the alignment between predicted and ground truth regions by emphasizing semantic consistency. The model achieves 98.1% accuracy with only 2.6M parameters, outperforming existing methods. Its high accuracy, compact size, and low computational load make it suitable for real-time deployment in embedded sorting and grading systems, bridging field detection and downstream food-processing tasks. Full article

(This article belongs to the Section AI-Enabled Process Engineering)

► Show Figures

Figure 1

15 pages, 2045 KiB

Open AccessArticle

Characterization of Hydrogen-in-Oxygen Changes in Alkaline Electrolysis Hydrogen Production System and Analysis of Influencing Factors

by Shuiyong Wang, Huabin Chen, Song Hu, Wanxiang Zhao, Mingya Chen, Dongfang Chen and Xiaoming Xu

Processes 2025, 13(8), 2517; https://doi.org/10.3390/pr13082517 - 10 Aug 2025

Abstract

Industrial alkaline water electrolysis systems face challenges in maintaining hydrogen-in-oxygen impurity within safe limits under fluctuating operating conditions. This study aims to characterize the dynamic response of hydrogen-in-oxygen concentration in an industrial 10 kW alkaline water electrolysis test platform (2 Nm³/h [...] Read more.

Industrial alkaline water electrolysis systems face challenges in maintaining hydrogen-in-oxygen impurity within safe limits under fluctuating operating conditions. This study aims to characterize the dynamic response of hydrogen-in-oxygen concentration in an industrial 10 kW alkaline water electrolysis test platform (2 Nm³/h hydrogen output at 1.6 MPa and 90 °C) and to identify how operating parameters influence hydrogen-in-oxygen behavior. We systematically varied the cell current, system pressure, and electrolyte flow rate while monitoring real-time hydrogen-in-oxygen levels. The results show that hydrogen-in-oxygen exhibits significant inertia and delay: during startup, hydrogen-in-oxygen remained below the 2% safety threshold and stabilized at 0.9% at full load, whereas a step decrease to 60% load caused hydrogen-in-oxygen to rise to 1.6%. Furthermore, reducing the pressure from 1.4 to 1.0 MPa lowered the hydrogen-in-oxygen concentration by up to 15%, and halving the alkaline flow rate suppressed hydrogen-in-oxygen by over 20% compared to constant conditions. These findings provide new quantitative insights into hydrogen-in-oxygen dynamics and offer a basis for optimizing control strategies to keep gas purity within safe limits in industrial-scale alkaline water electrolysis systems. Full article

(This article belongs to the Special Issue Recent Advances in Green Hydrogen Production and Hydrogen-Based Energy Storage Technology)

► Show Figures

Figure 1

24 pages, 2791 KiB

Open AccessArticle

Short-Term Wind Power Forecasting Based on Improved Modal Decomposition and Deep Learning

by Bin Cheng, Wenwu Li and Jie Fang

Processes 2025, 13(8), 2516; https://doi.org/10.3390/pr13082516 - 9 Aug 2025

Abstract

With the continued growth in wind power installed capacity and electricity generation, accurate wind power forecasting has become increasingly critical for power system stability and economic operations. Currently, short-term wind power forecasting often employs deep learning models following modal decomposition of wind power [...] Read more.

With the continued growth in wind power installed capacity and electricity generation, accurate wind power forecasting has become increasingly critical for power system stability and economic operations. Currently, short-term wind power forecasting often employs deep learning models following modal decomposition of wind power time series. However, the optimal length of the time series used for decomposition remains unclear. To address this issue, this paper proposes a short-term wind power forecasting method that integrates improved modal decomposition with deep learning techniques. First, the historical wind power series is segmented using the Pruned Exact Linear Time (PELT) method. Next, the segmented series is decomposed using an enhanced Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) to extract multiple modal components. High-frequency oscillatory components are then further decomposed using Variational Mode Decomposition (VMD), and the resulting modes are clustered using the K-means algorithm. The reconstructed components are subsequently input into a Long Short-Term Memory (LSTM) network for prediction, and the final forecast is obtained by aggregating the outputs of the individual modes. The proposed method is validated using historical wind power data from a wind farm. Experimental results demonstrate that this approach enhances forecasting accuracy, supports grid power balance, and increases the economic benefits for wind farm operators in electricity markets. Full article

(This article belongs to the Section Energy Systems)

► Show Figures

Figure 1

18 pages, 5474 KiB

Open AccessArticle

Dynamics Study of Liquid Water Transport in GDL with Different Wettability Distributions: Pore-Scale Simulation Based on Multi-Component and Multi-Phase LBM

by Nan Xie, Hongyu Chang, Jie Li and Chenchong Zhou

Processes 2025, 13(8), 2515; https://doi.org/10.3390/pr13082515 - 9 Aug 2025

Abstract

This study proposes a MPL (microporous layer)–GDL (gas diffusion layer) microstructure reconstruction method based on a novel random reconstruction algorithm. Then the Shan–Chen multi-component and multi-phase lattice Boltzmann method (SC-LBM) is used to systematically describe the influence of different contact angle distributions on [...] Read more.

This study proposes a MPL (microporous layer)–GDL (gas diffusion layer) microstructure reconstruction method based on a novel random reconstruction algorithm. Then the Shan–Chen multi-component and multi-phase lattice Boltzmann method (SC-LBM) is used to systematically describe the influence of different contact angle distributions on the drainage characteristics of the GDL of proton exchange membrane fuel cells (PEMFCs). Meanwhile, the breakthrough time of liquid water, steady-state time, and liquid water saturation are compared. The results show that with the increase in contact angle, the time for the first droplet breakthrough and the steady-state time are significantly shortened, and the saturation of liquid water gradually decreases at the steady state, indicating that increasing hydrophobicity can effectively improve the drainage capacity of the GDL. Several double-gradient and three-gradient contact angle distribution schemes are studied, and it is found that the gradient structure with increasing contact angles along the direction of water flow will lead to prolonged steady-state time and elevated water saturation, which is not conducive to drainage. This study analyzes the drainage process under different wettability gradients considering aspects such as the droplet morphology evolution, flow path, and water distribution mechanism, clarifying the key role of gradient design in GDL water management. This work also provides a theoretical basis and design guidelines for wettability optimization in the GDL of PEMFCs. Full article

(This article belongs to the Special Issue Structure Optimization and Transport Characteristics of Porous Media)

► Show Figures

Figure 1

22 pages, 7743 KiB

Open AccessArticle

A Coordinated Operation Optimization Model for Multiple Microgrids and Shared Energy Storage Based on Asymmetric Bargaining Negotiations

by Yao Wang, Zhongfu Tan, Xiaotong Zhou, Jia Li, Yingying Hu, Huimin Wu and Liwei Ju

Processes 2025, 13(8), 2514; https://doi.org/10.3390/pr13082514 - 9 Aug 2025

Viewed by 51

Abstract

The promotion of local renewable energy consumption and stable power gird (the latter is referred to as PG) operation have emerged as the primary objectives of power system reform. The integration of multiple microgrids with distinct characteristics through the utilization of shared energy [...] Read more.

The promotion of local renewable energy consumption and stable power gird (the latter is referred to as PG) operation have emerged as the primary objectives of power system reform. The integration of multiple microgrids with distinct characteristics through the utilization of shared energy storage (the following is referred to as SES) facilitates coordinated operation. This approach enables the balancing of energy across temporal and spatial domains, contributing to the overall reliability and security of the energy network. The proposed model outlines a methodology for the coordinated operation of multiple microgrids and SES, with a focus on asymmetric price negotiation. Initially, cost and revenue models for microgrids and SES power plants are established. Secondly, an asymmetric pricing method based on the magnitude of each entity’s energy contribution is proposed. A profit optimization model is also established. The model can be decomposed into two distinct subproblems: the maximization of overall profit and the negotiation of transaction prices. The model can be solved by employing the alternating direction method of multipliers (ADMM). Finally, a series of case studies were conducted for the purpose of validating the operation optimization model that was previously constructed. These studies demonstrate that the model enhances collective operational efficiency by 44.69%, with each entity’s efficiency increasing by at least 12%. At the same time, cooperative benefits are distributed fairly according to each entity’s energy contribution. Full article

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

► Show Figures

Figure 1

16 pages, 1119 KiB

Open AccessArticle

An Integrated Synthesis Approach for Emergency Logistics System Optimization of Hazardous Chemical Industrial Parks

by Daqing Ma, Fuming Yang, Zhongwang Chen, Fengyi Liu, Haotian Ye and Mingshu Bi

Processes 2025, 13(8), 2513; https://doi.org/10.3390/pr13082513 - 9 Aug 2025

Viewed by 61

Abstract

The rapid clustering of Chemical Industrial Parks (CIPs) has escalated the risk of cascading disasters (e.g., toxic leaks and explosions), underscoring the need for resilient emergency logistics systems. However, traditional two-stage optimization models often yield suboptimal outcomes due to decoupled facility location and [...] Read more.

The rapid clustering of Chemical Industrial Parks (CIPs) has escalated the risk of cascading disasters (e.g., toxic leaks and explosions), underscoring the need for resilient emergency logistics systems. However, traditional two-stage optimization models often yield suboptimal outcomes due to decoupled facility location and routing decisions. To address this issue, we propose a unified mixed-integer nonlinear programming (MINLP) model that integrates site selection and routing decisions in a single framework. The model accounts for multi-source supply allocation, enforces minimum safety distance constraints, and incorporates heterogeneous economic factors (e.g., regional land costs) to ensure risk-aware, cost-efficient planning. Two deployment scenarios are considered: (1) incremental augmentation of an existing emergency network and (2) full network reconstruction after a systemic failure. Simulations on a regional CIP cluster (2400 × 2400 km) were conducted to validate the model. The integrated approach reduced facility and operational costs by 9.77% (USD 13.68 million saved) in the incremental scenario and achieved a 15.10% (USD 21.13 million saved) total cost reduction over decoupled planning in the reconstruction scenario while maintaining an 8 km minimum safety distance. This integrated approach can enhance cost-effectiveness and strengthen the resilience of high-risk industrial emergency response networks. Overall, the proposed modeling framework, which integrates spatial constraints, time-sensitive supply mechanisms, and disruption risk considerations, is not only tailored for hazardous chemical zones but also exhibits strong potential for adaptation to a variety of high-risk scenarios, such as natural disasters, industrial accidents, or critical infrastructure failures. Full article

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

► Show Figures

Figure 1

32 pages, 7126 KiB

Open AccessArticle

Switchable Building-Integrated Photovoltaic–Thermal Curtain Wall for Building Integration

by Masoud Valinejadshoubi, Anna-Maria Sigounis, Andreas K. Athienitis and Ashutosh Bagchi

Processes 2025, 13(8), 2512; https://doi.org/10.3390/pr13082512 - 9 Aug 2025

Viewed by 74

Abstract

This study presents a novel switchable multi-inlet Building integrated photovoltaic/thermal (BIPV/T) curtain wall system designed to enhance solar energy utilization in commercial buildings. The system integrates controllable air inlets and motorized dampers that dynamically adjust airflow patterns in response to real-time environmental conditions [...] Read more.

This study presents a novel switchable multi-inlet Building integrated photovoltaic/thermal (BIPV/T) curtain wall system designed to enhance solar energy utilization in commercial buildings. The system integrates controllable air inlets and motorized dampers that dynamically adjust airflow patterns in response to real-time environmental conditions such as solar irradiance, ambient air temperature, and PV panel temperature. A steady-state energy balance model, developed using a thermal network analogy and implemented in Python, was used to simulate winter operation in Montréal, Canada. Three operating modes with different air inlet configurations were assessed to evaluate system performance across variable air velocities and solar conditions. Results indicate that the switchable system improves combined thermal and electrical generation by 2% to 25% compared to fixed one- or two-inlet systems. Under low irradiance and air velocity, one-inlet operation is dominant, while higher solar gain and airflow favor two-inlet configurations. The system demonstrates effective temperature control and enhanced energy yield through optimized airflow management. This work highlights the potential of integrated control strategies and modular façade design in improving the efficiency of solar building envelope systems and offers practical implications for scalable deployment in energy-efficient, heating-dominated climates. Full article

(This article belongs to the Special Issue Design and Optimisation of Solar Energy Systems)

► Show Figures

Figure 1

15 pages, 1925 KiB

Open AccessArticle

Ultrasound-Assisted Extraction Enhances Enzymatic Activity and Thermal Stability of Bovine Pancreatin: Effect of pH and Temperature

by Gulmira Kenenbay, Urishbay Chomanov and Alibek Tursunov

Processes 2025, 13(8), 2511; https://doi.org/10.3390/pr13082511 - 9 Aug 2025

Viewed by 110

Abstract

The extraction of enzyme preparations from bovine pancreas is a key step in the production of pancreatin used for pharmaceutical and food industry applications. However, conventional methods (CMs) often fail to preserve enzymatic activity (EA) during processing, particularly under variable temperature and pH [...] Read more.

The extraction of enzyme preparations from bovine pancreas is a key step in the production of pancreatin used for pharmaceutical and food industry applications. However, conventional methods (CMs) often fail to preserve enzymatic activity (EA) during processing, particularly under variable temperature and pH conditions. This study investigates the potential of ultrasound-assisted extraction (UAM) as an alternative to CMs for improving the recovery, stability, and performance of two essential pancreatic enzymes—α-amylase (AA) and protease (PA). EA was assessed over a broad temperature range (10–50 °C) and pH spectrum (5.5–8.0), with both methods evaluated under identical conditions. UAM consistently yielded higher EA across all tested parameters, with optimal AA and PA observed at pH 6.0 and 38 °C. Notably, UAM-extracted enzymes retained significant activity even at elevated temperatures (46–50 °C), whereas CM-derived samples showed a marked loss of function. These findings demonstrate that UAM enhances enzyme release and thermal resilience by minimizing denaturation and structural degradation during extraction. UAM showed improved apparent thermal tolerance under the tested conditions, which may indicate enhanced applicability in temperature-sensitive processing environments. Full article

(This article belongs to the Special Issue Application and Development of Ultrasonic Technology in Food Processing)

► Show Figures

Figure 1

17 pages, 807 KiB

Open AccessArticle

Effect of Acetylation on the Behavior of Hyperbranched Polyglycerols in Supercritical CO₂

by Lígia Passos Maia-Obi and Reinaldo Camino Bazito

Processes 2025, 13(8), 2510; https://doi.org/10.3390/pr13082510 - 8 Aug 2025

Viewed by 100

Abstract

Processes using CO₂ either as a solvent or as a reactant, for example, in catalyzed chemical reactions, are increasing in interest due to their green characteristics. Hyperbranched polyglycerols have the potential to be used as support for catalysts in these processes, allowing [...] Read more.

Processes using CO₂ either as a solvent or as a reactant, for example, in catalyzed chemical reactions, are increasing in interest due to their green characteristics. Hyperbranched polyglycerols have the potential to be used as support for catalysts in these processes, allowing for an efficient separation of the products and the reutilization of the catalyst, but this requires them to absorb CO₂. Acetylating hydroxylated compounds has shown to be an efficient way to increase their CO₂-philicity, and this work aims to understand how acetylation increases the interaction of hyperbranched polyglycerols with different cores with supercritical CO₂. This involves the study of their kinetics of expansion in this media (from 10 to 25 MPa and at 35 °C and 45 °C) and, eventually, their solubility when it happens. The expansion of the acetylated polyglycerols reached up to 66% in volume, while that of non-acetylated ones, in general, do not exceed 10%. Acetylation plays an important role in increasing the expansion of these polymers in the presence of CO₂ and, therefore, in increasing their CO₂-philicity and CO₂ absorption, making them potential materials to be used in biphasic (polymer/CO₂) reaction systems. Full article

(This article belongs to the Special Issue Phase Equilibrium in Chemical Processes: Experiments and Modeling)

► Show Figures

Graphical abstract

20 pages, 2073 KiB

Open AccessArticle

Tomato Seed Inoculation with Bacillus subtilis Biofilm Mitigates Toxic Effects of Excessive Copper in the Substrate

by Gabriela Cristina Sarti, Antonio Paz-González, Josefina Ana Eva Cristóbal-Míguez, Gonzalo Arnedillo, Ana Rosa García and Mirta Esther Galelli

Processes 2025, 13(8), 2509; https://doi.org/10.3390/pr13082509 - 8 Aug 2025

Viewed by 122

Abstract

Accumulation of copper (Cu) in soils devoted to intensive agriculture due to anthropogenic additions is becoming a significant threat to plant productivity. Biological inoculants may play an important role in alleviating toxic effects of heavy metals on plants. The plant-growth-promoting rhizobacteria (PGPR) Bacillus [...] Read more.

Accumulation of copper (Cu) in soils devoted to intensive agriculture due to anthropogenic additions is becoming a significant threat to plant productivity. Biological inoculants may play an important role in alleviating toxic effects of heavy metals on plants. The plant-growth-promoting rhizobacteria (PGPR) Bacillus subtilis subsp. spizizenii has demonstrated the ability to reduce harmful impacts of heavy metals on crops. This study aimed to evaluate the suitability of seed inoculation with biofilm produced by this bacterium to mitigate the severity of Cu toxicity on tomato. In the laboratory, first, B. subtilis was cultivated under increased Cu concentrations. Then, germination of inoculated and non-inoculated tomato seeds was tested for Cu concentrations of 0, 50, 100, 150, and 200 ppm. Next, a greenhouse experiment was conducted for four months to assess the effects of both inoculation and excess 150 ppm Cu in the substrate. The studied treatments included control, no inoculation and Cu surplus, inoculation and no Cu surplus, and inoculation plus Cu surplus. In the laboratory, first, the bacterium’s ability to grow in a liquid medium containing Cu was confirmed. Thereafter, we verified that the germination of non-inoculated seeds was negatively affected by Cu, with higher concentrations leading to a more detrimental effect. However, seed inoculation with biofilm mitigated the adverse impact of Cu on germination. Under greenhouse conditions, excess Cu significantly reduced root dry weight, tomato number, and tomato yield compared with the control, whereas shoot dry weight, plant height, leaf area, and soluble solid concentration (Brix index) did not experience significant changes (p < 0.05). However, seed inoculation mitigated the toxic effects of excess Cu, significantly enhancing all the aforementioned plant parameters, except plant height. Seed inoculation also significantly reduced the Cu contents in the fruits of tomato plants growing in the metal contaminated substrate. The biofilm of the B. subtilis strain used demonstrated its effectiveness as a bioinoculant, attenuating the detrimental effects induced by a substrate with excess Cu. Full article

(This article belongs to the Special Issue Processes in 2025)

► Show Figures

Figure 1

25 pages, 3348 KiB

Open AccessArticle

An AI-Assisted Thermodynamic Equilibrium Simulator: A Case Study on Steam Methane Reforming in Isothermal and Adiabatic Reactors

by Julles Mitoura dos Santos Junior, Antonio Carlos Daltro de Freitas and Adriano Pinto Mariano

Processes 2025, 13(8), 2508; https://doi.org/10.3390/pr13082508 - 8 Aug 2025

Viewed by 195

Abstract

This study presents TeS v.3, a thermodynamic equilibrium simulator integrated with an artificial intelligence agent (AI), ThermoAgent, to enhance the analysis of complex chemical systems. Developed in Python, the simulator employs Gibbs energy minimization for isothermal reactors and entropy maximization for [...] Read more.

This study presents TeS v.3, a thermodynamic equilibrium simulator integrated with an artificial intelligence agent (AI), ThermoAgent, to enhance the analysis of complex chemical systems. Developed in Python, the simulator employs Gibbs energy minimization for isothermal reactors and entropy maximization for adiabatic reactors. ThermoAgent leverages the LangChain framework to interpret natural language commands, autonomously execute simulations, and query a scientific knowledge base through a Retrieval-Augmented Generation (RAG) approach. The validation of TeS v.3 demonstrated high accuracy, with coefficients of determination (R² > 0.95) compared to reference simulation data and strong correlation (R² > 0.88) with experimental data from the steam methane reforming (SMR) process. The SMR analysis correctly distinguished the high conversions in isothermal reactors from the limited conversions in adiabatic reactors, due to the reaction temperature drop. ThermoAgent successfully executed simulations and provided justified analyses, combining generated data with information from reference publications. The successful integration of the simulator with the AI agent represents a significant advancement, offering a powerful tool that accurately calculates equilibrium and accelerates knowledge extraction through intuitive interaction. Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) and Automation-Driven Innovations in Chemical Engineering)

► Show Figures

Figure 1

15 pages, 2982 KiB

Open AccessArticle

CFD-Based Lagrangian Multiphase Analysis of Particulate Matter Transport in an Operating Room Environment

by Ahmet Çoşgun and Onur Gündüztepe

Processes 2025, 13(8), 2507; https://doi.org/10.3390/pr13082507 - 8 Aug 2025

Viewed by 163

Abstract

Maintaining air quality in operating rooms is critical for infection control and patient safety. Particulate matter, originating from surgical instruments, personnel, and external sources, is influenced by airflow patterns and ventilation efficiency. This study employs Computational Fluid Dynamics (CFD) simulations using Simcenter STAR-CCM+ [...] Read more.

Maintaining air quality in operating rooms is critical for infection control and patient safety. Particulate matter, originating from surgical instruments, personnel, and external sources, is influenced by airflow patterns and ventilation efficiency. This study employs Computational Fluid Dynamics (CFD) simulations using Simcenter STAR-CCM+ 2410 to analyze airflow and particulate behavior in a surgical-grade operating room. A steady-state solver with the k–ε turbulence model was used to replicate airflow, while the Lagrangian multiphase method simulated particle trajectories (0.5 µm, 1 µm, and 5 µm). The simulation results demonstrated close agreement with the experimental data, with average errors of 17.3%, 17.7%, and 39.7% for 0.5 µm, 1 µm, and 5 µm particles, respectively. These error margins are considered acceptable given the device’s 10% measurement sensitivity and the observed experimental asymmetry—attributable to equipment placement—which resulted in variations of 17.2%, 18.0%, and 26.5% at corresponding symmetric points. Collectively, these findings support the validity of the simulation model in accurately predicting particulate transport and deposition within the operating room environment. Findings confirm that optimizing airflow can achieve ISO Class 7 cleanroom standards and highlight the potential for future studies incorporating dynamic elements, such as personnel movement and equipment placement, to further improve contamination control in critical environments. Full article

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

► Show Figures

Figure 1

31 pages, 9785 KiB

Open AccessArticle

An Improved XGBoost Model for Development Parameter Optimization and Production Forecasting in CO₂ Water-Alternating-Gas Processes: A Case Study of Low Permeability Reservoirs in China

by Bin Su, Junchao Li, Jixin Li, Changjian Han and Shaokang Feng

Processes 2025, 13(8), 2506; https://doi.org/10.3390/pr13082506 - 8 Aug 2025

Viewed by 111

Abstract

The pronounced heterogeneity and geological complexity of low-permeability reservoirs pose significant challenges to parameter optimization and performance prediction during the development of CO₂ water-alternating-gas (CO₂-WAG) injection processes. This study introduces a predictive model based on the Extreme Gradient Boosting (XGBoost) [...] Read more.

The pronounced heterogeneity and geological complexity of low-permeability reservoirs pose significant challenges to parameter optimization and performance prediction during the development of CO₂ water-alternating-gas (CO₂-WAG) injection processes. This study introduces a predictive model based on the Extreme Gradient Boosting (XGBoost) algorithm, trained on 1225 multivariable numerical simulation cases of CO₂-WAG injection. To enhance the model’s performance, four advanced metaheuristic algorithms—Collective Parallel Optimization (CPO), Grey Wolf Optimization (GWO), Artificial Hummingbird Algorithm (AHA), and Black Kite Algorithm (BKA)—were applied for hyperparameter tuning. Among these, the CPO algorithm demonstrated superior performance due to its ability to balance global exploration with local exploitation in high-dimensional, complex optimization problems. Additionally, the integration of Chebyshev chaotic mapping and Elite Opposition-Based Learning (EOBL) strategies further improved the algorithm’s efficiency and adaptability, leading to the development of the ICPO (Improved Crowned Porcupine Optimization)-XGBoost model. Rigorous evaluation of the model, including comparative analyses, cross-validation, and real-case simulations, demonstrated its exceptional predictive capacity, with a coefficient of determination of 0.9894, a root mean square error of 2.894, and errors consistently within ±2%. These results highlight the model’s robustness, reliability, and strong generalization capabilities, surpassing traditional machine learning methods and other state-of-the-art boosting-based ensemble algorithms. In conclusion, the ICPO-XGBoost model represents an efficient and reliable tool for optimizing the CO₂-WAG process in low-permeability reservoirs. Its exceptional predictive accuracy, robustness, and generalization capability make it a highly valuable asset for practical reservoir management and strategic decision-making in the oil and gas industry. Full article

(This article belongs to the Special Issue Applications of Intelligent Models in the Petroleum Industry)

11 pages, 1278 KiB

Open AccessFeature PaperArticle

Investigation of Low-Toxicity Azoic Direct Dyes Synthesized from 4,4′-Diaminobenzanilide

by Maria Elena Radulescu-Grad, Simona Popa, Giannin Mosoarca and Vasile Daniel Gherman

Processes 2025, 13(8), 2505; https://doi.org/10.3390/pr13082505 - 8 Aug 2025

Viewed by 139

Abstract

In this paper, a toxicological investigation was carried out on a series of azoic direct dyes generally with an affinity for cellulosic fibers, presenting symmetrical and asymmetrical structures having as a central component a non-carcinogenic, mutagenic, or teratogenic and accessible precursor potential substitute [...] Read more.

In this paper, a toxicological investigation was carried out on a series of azoic direct dyes generally with an affinity for cellulosic fibers, presenting symmetrical and asymmetrical structures having as a central component a non-carcinogenic, mutagenic, or teratogenic and accessible precursor potential substitute for benzidine, namely 4,4′-diaminobenzanilide, and, as coupling components, 2-hydroxybenzoic acid, 2-hydroxy-3,6-naphthalenesulfonic acid, 2-amino-8-hydroxynaphthalene-6-sulfonic acid, 1-amino-8-hydroxynaphthalene-3,6-disulfonic acid, 1-(4′-sulfophenyl)-3-methyl-5-pyrazolone, and 2-hydroxy-6-naphthalenesulfonic acid, respectively. For the purpose of their safe use, this study shows the results regarding the toxicity of the above-mentioned dyes, obtained through biological tests on colonies of Hydractinia echinata (H. echinata). The toxicity tests were performed on heterotrophic bacteria cultures obtained from the Bega River. The minimum toxic concentration was monitored using the dilutions 0.6 g/L, 24 g/L, and 48 g/L, obtained by dilution of a stock solution of 60 g/L. The symmetric dye with the coupling component 2-hydroxybenzoic acid presents the highest degree of toxicity, the lowest being shown by dyes with symmetric and asymmetric structures with the following coupling components: 2-amino-8-hydroxynaphthalene-6-sulfonic acid, 1-amino-8-hydroxynaphthalene-3,6-disulfonic acid, 1-(4′-sulfophenyl)-3-methyl-5-pyrazolone, and 2-hydroxy-6-naphthalenesulfonic acid. Full article

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

► Show Figures

Figure 1

18 pages, 10772 KiB

Open AccessArticle

Mg/Fe Layered Double Hydroxide Modified Biochar for Synergistic Removal of Phosphate and Ammonia Nitrogen from Chicken Farm Wastewater: Adsorption Performance and Mechanisms

by Tao Li, Jinping Li, Zengpeng Li and Xiuwen Cheng

Processes 2025, 13(8), 2504; https://doi.org/10.3390/pr13082504 - 8 Aug 2025

Viewed by 145

Abstract

The development of an economical and efficient method for recovering phosphate (PO₄³⁻-P) and ammonium nitrogen (NH₄⁺-N) is of paramount importance for environmental remediation. The preparation of Mg/Fe-loaded biochar (Mg/Fe-BC) was achieved through chemical precipitation followed by pyrolysis [...] Read more.

The development of an economical and efficient method for recovering phosphate (PO₄³⁻-P) and ammonium nitrogen (NH₄⁺-N) is of paramount importance for environmental remediation. The preparation of Mg/Fe-loaded biochar (Mg/Fe-BC) was achieved through chemical precipitation followed by pyrolysis in this study. Single solution adsorption studies indicated that temperature significantly affected how effectively Mg/Fe-BC could adsorb and remove NH₄⁺-N, whereas PO₄³⁻-P adsorption showed minimal temperature sensitivity. In mixed simulated solutions, In the mixed simulated solution, the maximum adsorption capacities of Mg/Fe-BC for PO₄³⁻-P and NH₄⁺-N were 145.97–153.05 mg/g and 112.63–121.51 mg/g, respectively. The optimal dosage for synergistic adsorption was determined to be 3 g/L, while pH values ranging from 3 to 9 exhibited negligible effects on the adsorption of both contaminants. The presence of Ca²⁺ and HCO₃⁻ in the solution may interfere with the simultaneous adsorption of PO₄³⁻-P and NH₄⁺-N. SEM-EDS and XPS analyses revealed that the primary adsorption mechanisms of PO₄³⁻-P and NH₄⁺-N by Mg/Fe-BC involved electrostatic attraction, ion exchange, and hydrogen bonding. In practical applications using chicken manure biogas slurry, Mg/Fe-BC demonstrated synergistic adsorption effects, achieving removal efficiencies of 86.86% for PO₄³⁻-P and 36.86% for NH₄⁺-N, thereby confirming its potential application value in wastewater treatment. Full article

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

► Show Figures

Graphical abstract

Journal Menu

Journal Browser

Processes, Volume 13, Issue 8 (August 2025) – 212 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI