Processes

32 pages, 9156 KB

Open AccessArticle

Ultrasound-Assisted Extraction of Antioxidant Compounds from Pomegranate Peels and Simultaneous Machine Learning Optimization Study

by Martha Mantiniotou, Vassilis Athanasiadis, Konstantinos G. Liakos, Eleni Bozinou and Stavros I. Lalas

Processes 2025, 13(11), 3700; https://doi.org/10.3390/pr13113700 (registering DOI) - 16 Nov 2025

Abstract

The pomegranate, a widely consumed fruit, produces large quantities of waste, mainly from its peel. Pomegranate peels (PPs) contain high amounts of antioxidant compounds, such as polyphenols, flavonoids, and anthocyanins, which can be isolated from them and used for the benefit of humans [...] Read more.

The pomegranate, a widely consumed fruit, produces large quantities of waste, mainly from its peel. Pomegranate peels (PPs) contain high amounts of antioxidant compounds, such as polyphenols, flavonoids, and anthocyanins, which can be isolated from them and used for the benefit of humans and the environment. In the present work, a study of recovery of these compounds by ultrasound-assisted extraction (UAE) was carried out, whose parameters were optimized. The optimal results were a total polyphenol content of 195.55 mg gallic acid equivalents/g, total flavonoid content of 74.78 mg rutin equivalents/g, total anthocyanin content of 992.87 μg cyanidin 3-O-glucoside equivalents/g, and ascorbic acid content of 15.68 mg/g, while the antioxidant activity determined through ferric-reducing antioxidant power and DPPH assays was 2366.89 and 1755.17 μmol ascorbic acid equivalents/g, respectively. In parallel, an artificial intelligence (AI)-based framework was developed to model and predict antioxidant and phytochemical responses from UAE parameters. Six machine learning models were implemented on the experimental dataset, with the Random Forest (RF) regressor consistently achieving the best predictive accuracy. Partial dependence analysis revealed ethanol concentration as the dominant factor influencing outcomes, while ultrasonic power and extraction time exerted comparatively minor effects. Although dataset size limited model generalizability, the RF model reproduced experimental outcomes within experimental variability, underscoring its suitability for predictive extraction optimization. These findings demonstrate the complementary role of machine learning in accelerating antioxidant compound recovery research and its potential to guide future industrial-scale applications of AI-assisted extraction. Full article

(This article belongs to the Special Issue Advanced Separation and Extraction Processes for Effective Resource Utilization)

16 pages, 1629 KB

Open AccessArticle

Dried Sourdough as a Functional Tool for Enhancing Carob-Enriched Wheat Bread

by Jana Zahorec, Dragana Šoronja-Simović, Jovana Petrović, Ljubica Dokić, Ivana Lončarević and Ivana Nikolić

Processes 2025, 13(11), 3699; https://doi.org/10.3390/pr13113699 (registering DOI) - 16 Nov 2025

Abstract

Functional bread development with clean-label ingredients remains a technological challenge due to the negative effects of certain functional additives on dough rheology and bread quality. The aim of this study was to evaluate the effectiveness of dried sourdough as a natural improver in [...] Read more.

Functional bread development with clean-label ingredients remains a technological challenge due to the negative effects of certain functional additives on dough rheology and bread quality. The aim of this study was to evaluate the effectiveness of dried sourdough as a natural improver in carob-enriched bread. Dough formulations included 10–20% carob flour as a partial replacement of wheat flour, with dried sourdough added as a dough improver at 5–10%. The results demonstrated that the addition of 10% dried sourdough increased maximum creep compliance of dough with 10% and 15% carob flour by 26% and 56%, respectively. The addition of 5% and 10% dried sourdough to dough with 10% carob flour decreased its Newtonian viscosity by 24% and 36%, resulting in improved dough handling. Crumb pore structure was enhanced by the addition of 5% dried sourdough, with average pore surface area increasing around 2.5 times in breads with 15% and 20% carob flour. Incorporation of dried sourdough reduced bread hardness and chewiness by up to 40% in samples with 15% carob flour and by 20–30% in samples with 20% carob flour. Sensory properties of crumb structure (crumb development, pore fineness, elasticity and crumbliness), which were adversely affected by carob flour addition, showed varying levels of improvement by the addition of dried sourdough. These results demonstrate the feasibility of using dried sourdough as a natural improver in functional bakery formulations, supporting the development of clean-label products without synthetic additives. Full article

(This article belongs to the Section Food Process Engineering)

21 pages, 2624 KB

Open AccessArticle

Hypersphere-Guided Reciprocal Point Learning for Open-Set Industrial Process Fault Diagnosis

by Shipeng Li, Qi Wen, Binbin Zheng and Xinhua Wang

Processes 2025, 13(11), 3698; https://doi.org/10.3390/pr13113698 (registering DOI) - 16 Nov 2025

Abstract

Deep neural networks (DNNs) have achieved superior performance in diagnosing process faults, but they lack robustness when encountering novel fault types absent from training sets. Such unknown faults commonly appear in industrial settings, and conventional DNNs often misclassify them as one of the [...] Read more.

Deep neural networks (DNNs) have achieved superior performance in diagnosing process faults, but they lack robustness when encountering novel fault types absent from training sets. Such unknown faults commonly appear in industrial settings, and conventional DNNs often misclassify them as one of the known fault types. To address this limitation, we formulate the concept of open-set fault diagnosis (OSFD), which seeks to distinguish unknown faults from known ones while correctly classifying the known faults. The primary challenge in OSFD lies in minimizing both the empirical classification risk associated with known faults and the open space risk without access to training data for unknown faults. In order to mitigate these risks, we introduce a novel approach called hypersphere-guided reciprocal point learning (SRPL). Specifically, SRPL preserves a DNN for feature extraction while constraining features to lie on a unit hypersphere. To reduce empirical classification risk, it applies an angular-margin penalty that explicitly increases intra-class compactness and inter-class separation for known faults on the hypersphere, thereby improving discriminability among known faults. Additionally, SRPL introduces reciprocal points on the hypersphere, with each point acting as a classifier by occupying the extra-class region associated with a particular known fault. The interactions among multiple reciprocal points, together with the deliberate synthesis of unknown fault features on the hypersphere, serve to lower open-space risk: the reciprocal-point interactions provide an indirect estimate of unknowns, and the synthesized unknowns provide a direct estimate, both of which enhance distinguishability between known and unknown faults. Extensive experimental results on the Tennessee Eastman process confirm the superiority of the proposed method compared to state-of-the-art OSR algorithms, e.g., an 82.32% AUROC score and a 71.50% OSFDR score. Full article

(This article belongs to the Special Issue Fault Detection Based on Deep Learning)

► Show Figures

Figure 1

22 pages, 6001 KB

Open AccessArticle

Fabrication and Characterization of Poly(Lactic Acid) (PLA)/Ethylene Vinyl Acetate (EVA)/Graphene Oxide (GO) Polymer Composites for the Purpose of Removing Lead Ions (Pb(II)) from Water

by Lesia Sydney Mokoena, Khotso Mpitso and Julia Puseletso Mofokeng

Processes 2025, 13(11), 3697; https://doi.org/10.3390/pr13113697 (registering DOI) - 16 Nov 2025

Abstract

The contamination of water by heavy metals is a global problem with distressing health consequences, and researchers have proposed various methods to remove these ions. This study explored poly (lactic acid) (PLA)/ethylene vinyl acetate (EVA)/graphene oxide (GO) composites as possible adsorbents of lead [...] Read more.

The contamination of water by heavy metals is a global problem with distressing health consequences, and researchers have proposed various methods to remove these ions. This study explored poly (lactic acid) (PLA)/ethylene vinyl acetate (EVA)/graphene oxide (GO) composites as possible adsorbents of lead ions from water. GO was synthesized using modified Hummer’s method, and melt mixing was used to prepare the polymer blends and composites. Morphology investigations showed that PLA and EVA were immiscible, GO preferred to settle on the interface between the two polymers, and GO had a partial miscibility and compatibility effect on the polymers, even though cracks and voids were observed with increasing GO content. In water absorption studies, the early hydrolytic degradation of PLA was avoided by incorporating EVA, resulting in reasonable water absorption rates. The 50/50 w/w PLA/EVA blend and its composites showed a high-water intake. In Pb(II) adsorption studies using AAS, all the analyzed samples had very high Pb(II) adsorption capacities, and the 66.5/28.5/5 w/w PLA/EVA/GO composite adsorbed the most lead ions, under basic media, and a 5 h contact time. Adsorption kinetic modeling suggested that a homogenous adsorption process took place, with a precise Langmuir isotherm. The developed materials are promising commercial lead ion adsorbents that are environmentally friendly. Full article

(This article belongs to the Section Materials Processes)

► Show Figures

Figure 1

26 pages, 846 KB

Open AccessArticle

Technical Evaluation of BTEX Emission Mitigation from Gas Dehydration Unit by Revamping and Using Alternative Glycols

by Ahmed A. Bhran and Abeer M. Shoaib

Processes 2025, 13(11), 3696; https://doi.org/10.3390/pr13113696 (registering DOI) - 15 Nov 2025

Abstract

Water removal is crucial in natural gas processing to minimize water content, ensure safe transmission, and prevent operational issues like equipment corrosion and hydrate formation. Glycol absorption could be considered as one of the most effective methods used for natural gas dehydration and [...] Read more.

Water removal is crucial in natural gas processing to minimize water content, ensure safe transmission, and prevent operational issues like equipment corrosion and hydrate formation. Glycol absorption could be considered as one of the most effective methods used for natural gas dehydration and dew point control. However, during solvent regeneration, some pollutants, like benzene, toluene, ethylbenzene, and xylene (BTEX), are released to the atmosphere, resulting in catastrophic physical and mental health problems. Minimizing such pollutants that have negative impacts is highly needed to avoid the related negative environmental consequences. The objective of the current work is to investigate alternative strategies targeted to minimize BTEX emissions and guarantee efficient control of the dew point. Two strategies are introduced and investigated in this work; the first strategy is based on revamping an existing unit by adding a new cooler upstream glycol inlet separator, while the second strategy is based on using alternative glycols. The proposed strategies are applied to an Egyptian natural gas dehydration unit to select the optimum scenario that achieves the minimum BTEX emissions with efficient dew point control. It is found that natural gas dehydration using monoethylene glycol (MEG) is the best scenario in reducing BTEX emissions with efficient dew point control. The impact of operating conditions on BTEX emissions, along with natural gas water content, is also investigated. Lingo optimization software, v. 18, as well as HYSYS, v. 14, are used to find the optimum operating conditions for efficient dew point control with minimum BTEX emissions. It is demonstrated that stripping gas, MEG circulation rate, and inlet feed gas temperature have remarkable effects on BTEX emissions. Two quadratic correlations are also introduced in this study to efficiently relate BTEX emissions and water dew point to the influencing operating conditions. Full article

(This article belongs to the Special Issue Innovative Processes and Technologies for Energy Applications Towards Sustainability)

20 pages, 1021 KB

Open AccessArticle

Combined Effects of Taro Starch-Based Edible Coating, Osmotic Dehydration, and Ultrasonication on Drying Kinetics and Quality Attributes of Pears

by Betül Aslan Yılmaz, Dilek Demirbüker Kavak and Hande Demir

Processes 2025, 13(11), 3695; https://doi.org/10.3390/pr13113695 (registering DOI) - 15 Nov 2025

Abstract

The pursuit of efficient drying methods that preserve fruit quality remains a major challenge in food processing. Non-thermal pre-treatments such as ultrasonication (U), edible film coating (F), and osmotic dehydration (O) can improve drying performance but show limited effectiveness when applied individually. This [...] Read more.

The pursuit of efficient drying methods that preserve fruit quality remains a major challenge in food processing. Non-thermal pre-treatments such as ultrasonication (U), edible film coating (F), and osmotic dehydration (O) can improve drying performance but show limited effectiveness when applied individually. This study investigates a combined pre-treatment strategy for pear drying, evaluating a taro starch-based edible coating used alone and in combination with U and O. Pear slices received individual and combined pre-treatments (F, OF, UF, and UOF) prior to drying at temperatures of 60, 70, and 80 °C. The drying kinetics were modeled, and quality parameters such as effective moisture diffusivity (D_eff), rehydration capacity, microstructure, color, total phenolic content (TPC), antioxidant activity, and vitamin C, were assessed. The Page model fitted the drying data the best (R² > 0.9935). UF achieved the shortest drying time and a porous microstructure, thereby enhancing rehydration. OF showed the highest D_eff and best color retention, but the lowest rehydration. Conversely, UOF caused the greatest losses in bioactive compounds (TPC: 54.29 mg GAE/100 g; antioxidant activity: 15.39%; 0.48 mg vitamin C/100 g). Unlike single-technology studies, this sequential pre-treatment strategy for pears uniquely tailors the final quality, targeting efficiency, color, bioactivity, or structural properties. Full article

(This article belongs to the Special Issue Feature Papers in the "Food Process Engineering" Section)

► Show Figures

Figure 1

15 pages, 5222 KB

Open AccessArticle

A Numerical Simulation Method for Cyclic Steam Stimulation Development of Heavy Oil Reservoirs with Multi-Layer Radial Horizontal Wells

by Tiantian Yu, Zhaoxiang Zhang, Yipu Li, Yongge Liu, Aifen Li, Dechun Chen and Liyuan Chen

Processes 2025, 13(11), 3694; https://doi.org/10.3390/pr13113694 (registering DOI) - 15 Nov 2025

Abstract

Radial drilling technology, which involves drilling multiple micro-horizontal wellbores radially from a main wellbore, can effectively expand the contact area between the wellbore and the reservoir, as well as the swept volume of thermal fluid. It is a promising technology for enhancing the [...] Read more.

Radial drilling technology, which involves drilling multiple micro-horizontal wellbores radially from a main wellbore, can effectively expand the contact area between the wellbore and the reservoir, as well as the swept volume of thermal fluid. It is a promising technology for enhancing the efficiency of heavy oil thermal recovery. However, a systematic numerical simulation study on the application of this technology in the cyclic steam stimulation (CSS) development of heavy oil reservoirs is currently lacking. This paper establishes a numerical thermal recovery model for heavy oil reservoirs based on an unstructured grid modeling method, which can accurately describe the complex geometry of multi-layer, multi-branch radial wells. The model is discretized using the finite volume method and solved with a fully implicit method. Then, based on the geological parameters of a typical heavy oil reservoir, a comparative study was conducted on the production dynamics and physical field evolution of horizontal wells, single-layer radial wells, and dual-layer radial wells during the CSS process. The results indicate that, compared to conventional well types, dual-layer multi-branch radial wells can simultaneously inject steam into the upper and lower parts of the reservoir. This forms a more balanced and extensive three-dimensional heated body, significantly improving the planar sweep efficiency of heat and the uniformity of reserve recovery, thereby substantially increasing crude oil production and recovery factor. Compared to the horizontal well scenario, using dual-layer radial wells for CSS can increase cumulative oil production by 44.8%. Full article

(This article belongs to the Special Issue New Insights into Enhanced Oil Recovery Process Analysis and Application, 2nd Edition)

► Show Figures

Figure 1

18 pages, 3749 KB

Open AccessArticle

Performance Analysis of Integrated Energy System Driven by Solar Energy for Hydrogen Production and Cogeneration Application

by Qing Zhu, Huijie Lin, Hongjuan Zheng and Zeting Yu

Processes 2025, 13(11), 3693; https://doi.org/10.3390/pr13113693 (registering DOI) - 15 Nov 2025

Abstract

The accelerating deterioration of the global environment underscores the urgent need to transition from the conventional fossil fuels to renewable energy, particularly the abundant solar energy. However, large-scale solar power integration could cause the severe grid fluctuations and compromise the operational stability. Existing [...] Read more.

The accelerating deterioration of the global environment underscores the urgent need to transition from the conventional fossil fuels to renewable energy, particularly the abundant solar energy. However, large-scale solar power integration could cause the severe grid fluctuations and compromise the operational stability. Existing studies have attempted to address this issue using hydrogen-based energy storage for peak shaving, but most suffer from low system efficiency. To overcome these limitations, this study proposes a novel solar-driven integrated energy system (IES) for hydrogen production and combined heat and power (CHP) generation, in which advanced hydrogen storage technologies are employed to achieve the efficient system operation. The system couples four subsystems: parabolic trough solar collector (PTSC), transcritical CO₂ power cycle (TCPC), Kalina cycle (KC) and proton exchange membrane electrolytic cell (PEMEC). Thermodynamic analysis of the proposed IES was conducted, and the effects of key parameters on system performance were investigated in depth. Simulation results show that under design conditions, the PEMEC produces 0.514 kg/h of hydrogen with an energy efficiency of 54.09% and an exergy efficiency of 51.59%, respectively. When the TCPC evaporator outlet temperature is 430.35 K, the IES achieves maximum energy and exergy efficiencies of 46.52% and 18.62%, respectively, with a hydrogen production rate of 0.51 kg/h. The findings highlight the importance of coordinated parameter optimization to maximize system efficiency and hydrogen productivity, providing theoretical guidance for practical design and operation of solar-based hydrogen integrated energy system. Full article

(This article belongs to the Special Issue Advances in Detection, Control and Optimization of Low-Carbon Energy Systems)

14 pages, 4689 KB

Open AccessArticle

Scaling-Up the Growth of TiO₂ Nanostructures on Ti Arc-PVD Coatings Deposited at a Semi-Industrial Scale

by Nancy C. Aguirre De Paz, Aurora M. Estrada-Murillo, Rafael Huirache-Acuña, Nayeli Camacho and Guillermo César Mondragón-Rodríguez

Processes 2025, 13(11), 3692; https://doi.org/10.3390/pr13113692 (registering DOI) - 15 Nov 2025

Abstract

The anodization of Ti° enables the formation of well-ordered TiO₂ nanotubes, a highly promising nanomaterial with exceptional photochemical properties and potential applications in the energy and environmental sectors. This study addresses the growth of TiO₂ nanotubes on large-scale surfaces applied for [...] Read more.

The anodization of Ti° enables the formation of well-ordered TiO₂ nanotubes, a highly promising nanomaterial with exceptional photochemical properties and potential applications in the energy and environmental sectors. This study addresses the growth of TiO₂ nanotubes on large-scale surfaces applied for photocatalytic processes. The present investigation approaches the scaling up of the reactor for anodizing Ti°-coated flat surfaces and thus connecting the TiO₂-nano-structure with real-world applications. For this, 316 stainless steel sheets were coated with a uniform Ti° layer using the arc cathodic method. The results indicate that the (~3 µm) thick Ti° arc-PVD coatings are well anodized, despite the inherent amount of µm-sized droplets produced during the deposition. The results reported here highlight the effects of the anodization process parameters—voltage, current, and time—on nanotube growth. At 60 V, the nanotubes exhibited a highly uniform cylindrical morphology, homogeneous walls contributing to an ordered, stable, and open nanostructure at large Ti-coated surfaces. The scaling up of the reactor for the controlled anodization process of Ti° coating is addressed. This approach validates Ti°-based PVD coatings at a semi-industrial scale on commercial stainless steel, thus enabling affordable production costs. Lastly, the anodization of Ti° coatings is a viable, scalable manufacturing process for producing photocatalytic nanostructured surfaces. Full article

(This article belongs to the Special Issue Advances in Synthesis and Applications of Supported Nanocatalysts)

► Show Figures

Figure 1

13 pages, 4667 KB

Open AccessArticle

Phytotoxicity Evaluation of Leaf Extracts and Isolation of Phytotoxic Compounds from Trewia nudiflora Linn. for Natural Weed Control

by Mst. Rokeya Khatun, Shunya Tojo, Toshiaki Teruya and Hisashi Kato-Noguchi

Processes 2025, 13(11), 3691; https://doi.org/10.3390/pr13113691 (registering DOI) - 15 Nov 2025

Abstract

This research focuses on examining the phytotoxic effect of leaf extracts of T. nudiflora on the growth of one dicot, Lepidium sativum L. (cress), and one monocot, Lolium multiflorum Lam. (Italian ryegrass), plant. Significant shoot and root growth suppression occurred in both plants [...] Read more.

This research focuses on examining the phytotoxic effect of leaf extracts of T. nudiflora on the growth of one dicot, Lepidium sativum L. (cress), and one monocot, Lolium multiflorum Lam. (Italian ryegrass), plant. Significant shoot and root growth suppression occurred in both plants treated with different concentrations of T. nudiflora leaf extracts (p ≤ 0.05). An increase in T. nudiflora leaf extracts was associated with a progressive decline in the root and shoot development of both plants. The half maximum inhibitory doses (I₅₀ values) for cress and Italian ryegrass root growth were 0.00037 and 0.00071 g dry weight (DW), while concentrations of 0.00129 and 0.006 g DW equivalent T. nudiflora leaf extract in mL^–1 were needed for a similar reduction in shoot growth. According to these values, root development exhibited a greater sensitivity than shoot development to the applied extract, and dicot plants were more susceptible to T. nudiflora extracts than monocot plants. Chromatographic fractionation of the extracts led to the successful isolation of two phenolic acids; protocatechuic acid and gallic acid. Bioassays of T. nudiflora leaf extract-derived two phenolic acids against treated plants demonstrated significant toxic action that correlated with the concentrations of the compounds, which varied between the two plants. These results suggest that these two phenolic acids are key contributors to the phytotoxic activity observed in extracts from T. nudiflora leaves and might contribute to the development of sustainable agricultural practices, including the design of allelopathy-based weed management strategies. Full article

(This article belongs to the Special Issue Extraction, Separation, and Purification of Bioactive Compounds)

► Show Figures

Figure 1

20 pages, 2266 KB

Open AccessArticle

Numerical Study of Pulsation-Controlled Droplet Generation in a Microfluidic T-Junction

by Alibek Kuljabekov, Darezhat Bolysbek, Zhibek Akasheva and Zhumabek Zhantayev

Processes 2025, 13(11), 3690; https://doi.org/10.3390/pr13113690 (registering DOI) - 15 Nov 2025

Abstract

Droplet generation in microfluidic T-junctions is a key process in various chemical and biomedical applications requiring precise size and frequency control. This study presents a numerical investigation of pulsation-controlled droplet formation using a two-phase incompressible laminar flow model with constant surface tension and [...] Read more.

Droplet generation in microfluidic T-junctions is a key process in various chemical and biomedical applications requiring precise size and frequency control. This study presents a numerical investigation of pulsation-controlled droplet formation using a two-phase incompressible laminar flow model with constant surface tension and defined wettability. Simulations were conducted in COMSOL Multiphysics employing the Level Set method, and the model was validated against the benchmark data of Bashir et al., accurately reproducing droplet pinch-off time and morphology under steady co-flow conditions. Pulsatile inlet velocity was then introduced to analyze its influence on droplet dynamics. Results show that at frequencies between 35 and 60 Hz, droplet generation becomes synchronized with the pulsation cycle, producing one droplet per period. Beyond 60 Hz, synchronization is lost, leading to irregular breakup and loss of droplet size control. The droplet length exhibited an approximately linear dependence on pulsation frequency, indicating predictable and tunable droplet formation. These findings demonstrate that simple modulation of the dispersed-phase velocity enables droplet-on-demand operation and robust control of droplet size and generation rate in standard microfluidic T-junctions. Full article

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

► Show Figures

Figure 1

19 pages, 2593 KB

Open AccessArticle

A Ghost Wave Suppression Method for Towed Cable Data Based on the Hybrid LSMR

by Zhaoqi Wang, Ya Li, Zhixue Sun, Zhonghua Li and Dongsheng Ge

Processes 2025, 13(11), 3689; https://doi.org/10.3390/pr13113689 (registering DOI) - 15 Nov 2025

Abstract

In marine seismic exploration, ghost waves distort reflection waveforms and narrow the frequency band of seismic records. Traditional deghosting methods are susceptible to practical limitations from sea surface fluctuations and velocity variations. This paper proposes a τ-p domain deghosting method based on the [...] Read more.

In marine seismic exploration, ghost waves distort reflection waveforms and narrow the frequency band of seismic records. Traditional deghosting methods are susceptible to practical limitations from sea surface fluctuations and velocity variations. This paper proposes a τ-p domain deghosting method based on the Hybrid Least Squares Residual (HyBR LSMR) algorithm. We first establish a linear forward model in the τ-p domain that describes the relationship between the total wavefield and upgoing wavefield, transforming deghosting into a linear inverse problem. The method then employs the hybrid LSMR algorithm with Tikhonov regularization to address the inherent ill-posedness. A key innovation is the integration of the Generalized Cross Validation (GCV) criterion to adaptively determine regularization parameters and iteration stopping points, effectively avoiding the semi-convergence phenomenon and enhancing solution stability. Applications to both synthetic and field data demonstrate that the proposed method effectively suppresses ghost waves under various acquisition conditions, significantly improves the signal-to-noise ratio and resolution, broadens the effective frequency band, and maintains good computational efficiency, providing a reliable solution for high-precision seismic data processing in complex marine environments. Full article

(This article belongs to the Special Issue Advances in Evaluation, Development, Simulation and Utilization of Geo-Energy Resources and Underground Space)

► Show Figures

Figure 1

13 pages, 2874 KB

Open AccessArticle

Microstructure and Dry-Sliding Tribology of Thermal-Spray Coatings on Cu for Continuous Casting Molds

by Indira Abizhanova, Saule Abdulina, Dastan Buitkenov, Małgorzata Rutkowska-Gorczyca, Arystanbek Kussainov and Dauir Kakimzhanov

Processes 2025, 13(11), 3688; https://doi.org/10.3390/pr13113688 (registering DOI) - 15 Nov 2025

Abstract

The low hardness of copper alloys, which are the substrate material used for continuous casting molds, makes them prone to plastic deformation, wear, and high-temperature oxidation, leading to premature failure and the formation of surface defects on billets. In this work, the microstructure, [...] Read more.

The low hardness of copper alloys, which are the substrate material used for continuous casting molds, makes them prone to plastic deformation, wear, and high-temperature oxidation, leading to premature failure and the formation of surface defects on billets. In this work, the microstructure, phase composition, mechanical, and tribological properties of Cr₃C₂–NiCr coatings deposited by high-velocity oxy-fuel (HVOF) spraying onto copper substrates used in molds were investigated. This research was driven by the need to extend the service life of copper molds in continuous steel casting processes. It was established that spraying parameters have a decisive influence on porosity, coating thickness, microhardness, and friction behavior under conditions simulating billet contact with the working surface of the mold. Among the investigated regimes, the coating deposited at a powder feed rate of 11.39 m/s exhibited a dense lamellar structure and the highest level of microhardness. Tribological tests confirmed that this coating exhibited the lowest coefficient of friction, whereas the other coatings were characterized by higher porosity and poorer wear resistance. Thus, the results emphasize the necessity of optimizing spraying parameters to develop highly effective HVOF protective coatings for copper molds operating under extreme thermomechanical loads during steel casting. Full article

(This article belongs to the Special Issue Microstructure Properties and Characterization of Metallic Material)

► Show Figures

Figure 1

19 pages, 4138 KB

Open AccessArticle

Machinability Analysis of LPBF-AlSi10Mg: A Study on SL-MQL Efficiency and ML Prediction Models

by Zhenhua Dou, Kai Guo, Jie Sun and Xiaoming Huang

Processes 2025, 13(11), 3687; https://doi.org/10.3390/pr13113687 - 14 Nov 2025

Abstract

Because of their exceptional strength, corrosion resistance, and low weight, materials such as titanium, aluminum, and others are becoming increasingly popular. The application scope of additive manufacturing (AM) in the aerospace sector continues to expand. Because of its high performance and low coefficient [...] Read more.

Because of their exceptional strength, corrosion resistance, and low weight, materials such as titanium, aluminum, and others are becoming increasingly popular. The application scope of additive manufacturing (AM) in the aerospace sector continues to expand. Because of its high performance and low coefficient of thermal expansion, AlSi10Mg processed by laser-based powder bed fusion (LPBF) is becoming increasingly popular in lightweight aerospace component design. Nonetheless, the AM technique has a number of benefits; poor surface quality is the only drawback, necessitating post-processing. This study aims to focus on the machinability of AlSi10Mg under three distinct environmental conditions (dry, minimum quantity lubrication (MQL), and SL-MQL). The experimental investigations were centered on chip morphology, flank wear (Vb), surface roughness (Ra), and cutting temperature (Tc). SL-MQL reduced the roughness by 53–57% over dry machining and 23–29% over MQL condition, and in a similar way lessened the flank wear by 36–40% over dry machining and 12–15% over MQL condition. In addition, to check the predictive accuracy and optimize machining parameters, four machine learning models were used: Gaussian Process Regression (GPR), Bagging, Multilayer Perceptron (MLP), and Random Forest (RF). In both the training and testing stages, MLP consistently demonstrated superior performance across all parameters in comparison to other algorithms, achieving high levels of accuracy and low error rates. Full article

(This article belongs to the Special Issue Machine Learning for Predictive Modeling and Optimization of Manufacturing Processes)

► Show Figures

Figure 1

23 pages, 3369 KB

Open AccessArticle

Performance and Emissions Optimization of a Diesel Engine Using Biodiesel–Diesel Blends with Amine-Modified Nanobiochar

by Mahtab Yarveysi, Behdad Shadidi, Maryam Hajjami, Seyed Mohammad Safieddin Ardebili and Hossein Haji Agha Alizade

Processes 2025, 13(11), 3686; https://doi.org/10.3390/pr13113686 - 14 Nov 2025

Abstract

Utilizing bio-based nano-fuel additives presents a promising path towards improved engine performance and reduced emissions. The response surface method is used in this investigation to predict and optimize the performance parameters and exhaust emissions of a single-cylinder diesel engine. The engine operates with [...] Read more.

Utilizing bio-based nano-fuel additives presents a promising path towards improved engine performance and reduced emissions. The response surface method is used in this investigation to predict and optimize the performance parameters and exhaust emissions of a single-cylinder diesel engine. The engine operates with B20 at 2900, 3100, and 3300 rpm and nanobiochar concentrations of 30, 60, and 90 ppm. The results showed a declining trend in all of the engine-out emissions when the nanobiochar additive was used. Based on the optimization results, an engine speed of 3108 rpm and a nanobiochar ratio of 90 ppm were found to be the optimal conditions within the defined range of the input parameters. At this point, the engine power, torque, BSFC, and emissions of NOx, CO, and UHC were measured at 5.78 kW, 17.96 Nm, and 309 g/kW·h, 104.9 ppm, 1.25 (%Vol.), and 104.9 ppm, respectively. These values represent significant improvements compared to the baseline B20 fuel. The modeling results showed that RSM could effectively predict engine performance and emissions when running on a green-based fuel like B20, with a 90 ppm nanobiochar additive. Full article

(This article belongs to the Special Issue Combustion Processes and Emissions Assessment of Internal Combustion Engines)

17 pages, 1001 KB

Open AccessArticle

Process-Oriented Modeling and Performance Optimization of Intelligent Traffic Systems Using Stochastic Petri Nets

by Shumei Chai, Feng Ni, Jiang Liu, Rui Fu and Yubo Dou

Processes 2025, 13(11), 3685; https://doi.org/10.3390/pr13113685 - 14 Nov 2025

Abstract

To address the dynamic characteristics of data collection, risk assessment, and response execution in intelligent traffic warning systems, this study proposes a modeling and performance analysis framework based on Stochastic Petri Nets (SPN). An SPN model of the warning-information evolution process is constructed [...] Read more.

To address the dynamic characteristics of data collection, risk assessment, and response execution in intelligent traffic warning systems, this study proposes a modeling and performance analysis framework based on Stochastic Petri Nets (SPN). An SPN model of the warning-information evolution process is constructed and transformed into a continuous-time Markov chain (CTMC), for which the steady-state probability equations are derived to quantify system performance. The transition rates in the model are assigned according to national technical specifications and practical operational scenarios. A sensitivity analysis is conducted on several key rates (λ₂, λ₃, λ₉, λ₁₀, λ₁₁, λ₁₂) to examine their influence on the steady-state distribution. The simulation results indicate that increasing λ₂ (data-cleaning rate) improves processing efficiency in the data-fusion stage, while insufficient values of λ₁₀ or λ₁₁ may lead to system congestion or delayed responses. To further evaluate system behavior, performance indicators such as the average number of tokens and transition utilization are introduced to assess resource occupancy and process activation frequency. These measures help identify potential bottlenecks and guide targeted optimization. The findings demonstrate that appropriate adjustment of critical transition rates can enhance operational efficiency and warning accuracy, providing theoretical support and practical insights for the modeling, optimization, and resource allocation of intelligent traffic systems. Full article

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

32 pages, 797 KB

Open AccessReview

Molecular Simulation in Phosphate Ore Interfacial Separation: Research Progress, Innovations, and Industrial Prospects

by Wenquan Yang, Zhongjun Cai, Hua Zhang, Lingpan Du, Menglai Wang and Dongsheng He

Processes 2025, 13(11), 3684; https://doi.org/10.3390/pr13113684 - 14 Nov 2025

Abstract

Phosphate ore is essential for global food security and industry. However, the depletion of high-grade deposits necessitates processing complex low-grade ores, posing significant separation challenges. Flotation, the main beneficiation method, exploits minor differences in surface properties, yet conventional approaches offer limited molecular-level insight, [...] Read more.

Phosphate ore is essential for global food security and industry. However, the depletion of high-grade deposits necessitates processing complex low-grade ores, posing significant separation challenges. Flotation, the main beneficiation method, exploits minor differences in surface properties, yet conventional approaches offer limited molecular-level insight, resulting in inefficiency, high reagent use, and pollution. Molecular simulation has emerged as a transformative solution, integrating quantum chemistry, molecular dynamics, and mesoscale modeling to accurately predict electronic structures and optimize flotation systems. This review systematically examines its applications in phosphate ore processing, highlighting four key advances: a multi-scale framework linking atomic mechanisms to macro-performance; structure–activity models for rational reagent design; insights into interfacial micro-environments for intelligent control; and machine learning integration for high-throughput screening. Key challenges such as force field accuracy and simulation scalability are addressed, along with emerging directions like in situ dynamic simulation and integration with process engineering. This review aims to support the development of efficient, sustainable, and intelligently optimized phosphate beneficiation technologies. Full article

(This article belongs to the Special Issue Molecular Simulation in Mineral Flotation Processes)

21 pages, 2999 KB

Open AccessArticle

Particulate Matter Characteristics from a Gasification Cookstove: Implications of Operating Conditions Using Densified Wood Biomass

by Jonatan Gutiérrez, Alexander Santamaría and Juan F. Pérez

Processes 2025, 13(11), 3683; https://doi.org/10.3390/pr13113683 - 14 Nov 2025

Abstract

Biomass is commonly used for cooking in developing countries, but traditional cookstoves emit pollutants (CO, NO_x, PM), which harm indoor air quality. Improvements and solutions are essential for achieving Sustainable Development Goal 7 (SDG 7). This study assesses the impact of [...] Read more.

Biomass is commonly used for cooking in developing countries, but traditional cookstoves emit pollutants (CO, NO_x, PM), which harm indoor air quality. Improvements and solutions are essential for achieving Sustainable Development Goal 7 (SDG 7). This study assesses the impact of the combustion chamber design, the combustion-air/gasification-air ratio (CA/GA = 2.8, 3.0, and 3.2), and the start type of water boiling test (WBT) protocol (cold and hot starts) on the chemical and morphological characteristics of the total suspended particulate matter (TSPM) emitted from a biomass gasification-based cookstove using densified biomass as feedstock. TSPM was characterized using Fourier-Transform Infrared Spectroscopy (FTIR), X-ray Photoelectron Spectroscopy (XPS), Raman Spectroscopy, and Transmission Electron Microscopy (TEM) to evaluate their chemical composition and morphological features under the above operational conditions. Under the modified WBT protocol, the cookstove achieved CO levels ranging from 1.52 to 2.13 g/MJ_d, and efficiency between 26.56% and 27.81%. TSPM emissions ranged between ~74 and 122.70 mg/MJ_d. The chemical characteristics of TSPM surface functional groups weren’t affected by the start condition, except for decreased intensities as CA/GA increased, promoting oxidation and removal as CO/CO₂. While cold start produced TSPM with higher structural order at higher CA/GA levels, no significant differences were observed among samples from both start conditions at CA/GA ³ 3.0, indicating chemical and structural similarity. Morphology and particle size were mainly unaffected, with only slight increases in particle size during hot start due to higher biomass-to-air ratios. Full article

(This article belongs to the Special Issue Biomass Pretreatment for Thermochemical Conversion)

19 pages, 4490 KB

Open AccessArticle

Classification of Tight Sandstone Gas Reservoirs and Evaluation of Aqueous-Phase Trapping Damage Using Mercury Intrusion Porosimetry

by Yuanyuan Tian, Yu Lu, Xin Zhou, Ying Liu, Qin Bie and Nan Zhang

Processes 2025, 13(11), 3682; https://doi.org/10.3390/pr13113682 - 14 Nov 2025

Abstract

Diagnosing water-phase damage remains challenging because routine petrophysical parameters do not capture capillary hysteresis and pressure-transmission effects. In this study, a standardized, auditable workflow was established to link laboratory descriptors to field-relevant cleanup. Full-curve mercury injection capillary pressure data were acquired and converted [...] Read more.

Diagnosing water-phase damage remains challenging because routine petrophysical parameters do not capture capillary hysteresis and pressure-transmission effects. In this study, a standardized, auditable workflow was established to link laboratory descriptors to field-relevant cleanup. Full-curve mercury injection capillary pressure data were acquired and converted using consistent Washburn parameters, from which withdrawal efficiency was computed on the withdrawal branch. A pressure-transmission coefficient was evaluated under unified boundary conditions to complement permeability and porosity. After preprocessing and partial least-squares regression (PLSR) screening, MICP descriptors were clustered by k-means (k = 5) to obtain reservoir Types I–V. Regressions relating WE to permeability and flowback behavior were then used to assess engineering relevance. The results indicate that WE capture hysteretic trapping/back-pressure not contained in permeability or porosity and, when interpreted jointly with PTC, differentiates reservoir types by cleanup propensity. This framework provides a reproducible bridge from laboratory MICP hysteresis to field-scale flowback interpretation. Practical implications include prioritization of gas–wet wettability modification, low-surface-tension systems, and minimized early liquid loading for clusters exhibiting higher WE and lower PTC. Full article

(This article belongs to the Section Energy Systems)

► Show Figures

Figure 1

Journal Description

Processes

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Topical Collections

Further Information

Guidelines

MDPI Initiatives

Follow MDPI