Processes

26 pages, 5269 KB

Open AccessArticle

Development and Optimization of Resveratrol-Loaded NLCs via Low-Energy Methods: A Promising Alternative to Conventional High-Energy or Solvent-Based Techniques

by Nicoly T. R. Britto, Lilian R. S. Montanheri, Juliane N. B. D. Pelin, Raquel A. G. B. Siqueira, Matheus de Souza Alves, Tereza S. Martins, Ian W. Hamley, Patrícia S. Lopes, Vânia R. Leite-Silva and Newton Andreo-Filho

Processes 2026, 14(2), 393; https://doi.org/10.3390/pr14020393 - 22 Jan 2026

Cited by 1 | Viewed by 592

Abstract

High-energy methods dominate the development of lipid nanoparticles but often require specialized equipment that increases production costs. Low-energy approaches, particularly those free of organic solvents, offer a promising alternative. This study aimed to obtain nanostructured lipid carriers (NLCs) using a solvent-free, low-energy process [...] Read more.

High-energy methods dominate the development of lipid nanoparticles but often require specialized equipment that increases production costs. Low-energy approaches, particularly those free of organic solvents, offer a promising alternative. This study aimed to obtain nanostructured lipid carriers (NLCs) using a solvent-free, low-energy process combining microemulsification and phase inversion. Cetearyl alcohol and PEG-40 hydrogenated castor oil were selected as the solid lipid and surfactant, respectively; the formulation and process were optimized through a Box–Behnken Design. Incorporation of the ionic surfactant extended colloidal stability, while the poloxamer in the aqueous phase enhanced steric stabilization. Resveratrol was efficiently encapsulated (E.E. = 98%), contributing to reduced particle size (291 nm), improved homogeneity (PDI = 0.25), and positive surface charge (+43 mV). Scale-up yielded stable particles carrying resveratrol with a mean size of 507 nm, PDI = 0.24, and ZP = +52 mV. The optimized formulation remained stable for 90 days at 8 °C. In vitro release demonstrated a sustained and controlled release profile, with significantly lower resveratrol release compared to the free compound. Thermal analysis confirmed drug incorporation within the lipid matrix, while transmission electron microscopy (TEM) revealed spherical particles (~200 nm) and SAXS indicated a nanostructure of ~50 nm. Overall, this study demonstrates that solvent-free, low-energy processing can produce stable and scalable NLC formulations, successfully encapsulating resveratrol with favorable physicochemical properties and controlled release behavior. These findings highlight a simple, cost-effective strategy for developing lipid-based nanocarriers with potential applications in drug delivery. Full article

(This article belongs to the Special Issue Studies of the Dosage Form and Stability of the Drug by Various Techniques, 2nd Edition)

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21 pages, 8423 KB

Open AccessArticle

Effects of Fin Configuration and Structural Parameters on the Exothermic Performance of a CaCO₃/CaO Thermochemical Energy Storage Reactor

by Shuai Luo, Zhengyue Zhu, Zhenming Liu, Yajun Deng, Wei Zhang and Bo Yu

Processes 2026, 14(2), 392; https://doi.org/10.3390/pr14020392 - 22 Jan 2026

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Abstract

Thermochemical energy storage technology offers an effective approach to address the intermittency and instability of solar energy supply, thereby enhancing its utilization efficiency and reducing dependence on fossil fuels. The CaCO₃/CaO system provides a low-cost, abundant, and safe thermal energy storage [...] Read more.

Thermochemical energy storage technology offers an effective approach to address the intermittency and instability of solar energy supply, thereby enhancing its utilization efficiency and reducing dependence on fossil fuels. The CaCO₃/CaO system provides a low-cost, abundant, and safe thermal energy storage solution with high energy density, suitable for large-scale use. However, the low effective thermal conductivity of the storage material in fixed-bed reactors often leads to limited heat transfer performance. To address this issue, this study investigates the internal temperature distribution and reaction field in a finned reactor, with a focus on the effects of fin geometry (including layout, number, and dimensions) on the carbonation reaction performance. The results demonstrate that the incorporation of fins significantly enhances heat transfer within the reactor. Hor-izontal fins increased the reaction rate by 11.81%, while vertical fins resulted in a more pronounced improvement of 41.17%. Furthermore, variations in fin structural parameters markedly influenced the carbonation process. Increasing the number of vertical fins from four to eight improved the reaction rate by 24.23%. Under the conditions studied, the optimal fin configuration, with a thickness of 0.002 m, a length of 0.03 m, and a total of eight fins, achieved the shortest carbonation time. This study provides valuable insights into the design of efficient reactor structures for enhanced thermochemical energy storage. Full article

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17 pages, 979 KB

Open AccessArticle

Holistic Estuarine Monitoring: Data-Driven and Process-Based Coupling of Biogeochemical Cycles of Per- and Polyfluoroalkyl Substances

by Fatih Evrendilek and Gulsun Akdemir Evrendilek

Processes 2026, 14(2), 391; https://doi.org/10.3390/pr14020391 - 22 Jan 2026

Cited by 1 | Viewed by 298 | Correction

Abstract

Better understanding the fate and transport of estuarine per- and polyfluoroalkyl substances (PFASs) requires coupling multiple matrix-specific biogeochemical roles, rather than relying on a single-matrix approach. We therefore evaluated sediment and biological matrices (blue mussels (BMs), Mytilus edulis; and hardshell clams (HSCs), [...] Read more.

Better understanding the fate and transport of estuarine per- and polyfluoroalkyl substances (PFASs) requires coupling multiple matrix-specific biogeochemical roles, rather than relying on a single-matrix approach. We therefore evaluated sediment and biological matrices (blue mussels (BMs), Mytilus edulis; and hardshell clams (HSCs), Mercenaria mercenaria) as complementary indicators of PFAS contamination across three locations over a 240-day period following a spill event. A three-tiered analytical approach was applied: Tier 1 used non-parametric statistics to assess the broad-spectrum detection patterns for a total of 40 PFASs (n = 47 samples); Tier 2 employed generalized regression (adaptive Elastic Net), random forest, and artificial neural networks to model the concentrations of the most frequently detected PFASs (PFOS, PFOA, PFHxA, and PFOSA) (n = 188 observations); and Tier 3 implemented a system dynamics model to mechanistically couple the PFOS and 5:3 FTCA fate. The results suggest that the sediment acted as a long-term sink for legacy long-chain compounds (99.3%, primarily PFOS), while the biota, particularly BMs, acted as sensitive recorders of acute pulses and hydrophilic precursors, uniquely accumulating 5:3 FTCA during spring pulses (p < 0.001). All the models identified the matrix type as the dominant driver of the most prevalent PFAS concentrations. A reliance on sediment monitoring alone may fail to capture the majority of the active contamination burden sequestered in the biota, suggesting that effective risk assessment necessitates an integrated view. Full article

(This article belongs to the Special Issue Advances in Water Resource Pollution Mitigation Processes)

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16 pages, 1974 KB

Open AccessArticle

Edible Oil Adulteration Analysis via QPCA and PSO-LSSVR Based on 3D-FS

by Si-Yuan Wang, Qi-Yang Liu, Ai-Ling Tan and Linan Liu

Processes 2026, 14(2), 390; https://doi.org/10.3390/pr14020390 - 22 Jan 2026

Viewed by 278

Abstract

A method utilizing quaternion principal component analysis (QPCA) for three-dimensional fluorescence spectral (3D FS) feature extraction is employed to identify frying oil in edible oil. Particle swarm optimization partial least squares support vector machine (PSO-LSSVR) is utilized for detecting frying oil concentration. The [...] Read more.

A method utilizing quaternion principal component analysis (QPCA) for three-dimensional fluorescence spectral (3D FS) feature extraction is employed to identify frying oil in edible oil. Particle swarm optimization partial least squares support vector machine (PSO-LSSVR) is utilized for detecting frying oil concentration. The study includes rapeseed oil, soybean oil, peanut oil, blending oil, and corn oil samples. Adulteration involves adding frying oil to these edible oils at concentrations of 0%, 5%, 10%, 30%, 50%, 70%, and 100%. Firstly, the F7000 fluorescence spectrometer is employed to measure the 3D FS of the adulterated edible oil samples, resulting in the generation of contour maps and 3D FS projections. The excitation wavelengths utilized in these measurements are 360 nm, 380 nm, and 400 nm, while the emission wavelengths span from 220 nm to 900 nm. Secondly, leveraging the automatic peak-finding function of the spectrometer, a quaternion parallel representation model of the 3D FS data for frying oil in edible oil is established using the emission spectra data corresponding to the aforementioned excitation wavelengths. Subsequently, in conjunction with the K-nearest neighbor classification (KNN), three feature extraction methods—summation, modulus, and multiplication quaternion feature extraction—are compared to identify the optimal approach. Thirdly, the extracted features are input into KNN, particle swarm optimization support vector machine (PSO-SVM), and genetic algorithm support vector machine (GA-SVM) classifiers to ascertain the most effective discriminant model for adulterated edible oil. Ultimately, a quantitative model for adulterated edible oil is developed based on partial least squares regression, PSO-SVR and PSO-LSSVR. The results indicate that the classification accuracy of QPCA features combined with PSO-SVM achieved 100%. Furthermore, the PSO-LSSVR quantitative model exhibited the best performance. Full article

(This article belongs to the Special Issue Feature Reviews in Food Processing Technologies: Present Innovations and Future Opportunities (2nd Edition))

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26 pages, 11043 KB

Open AccessArticle

Disintegration of Liquid Jets in Grinding Cooling

by Sheikh Ahmad Sakib and Alex Povitsky

Processes 2026, 14(2), 389; https://doi.org/10.3390/pr14020389 - 22 Jan 2026

Viewed by 274

Abstract

Liquid coolant jets are commonly used to remove excess heat from workpieces during grinding. There is a pressing need to reduce energy waste that contributes to environmental heat pollution and to limit the spread of oil-based coolants and mist formation. As a liquid [...] Read more.

Liquid coolant jets are commonly used to remove excess heat from workpieces during grinding. There is a pressing need to reduce energy waste that contributes to environmental heat pollution and to limit the spread of oil-based coolants and mist formation. As a liquid jet issues from a nozzle and enters the surrounding air, surface instabilities develop, causing the jet to break into droplets. This breakup diminishes the jet’s ability to deliver maximum momentum to the workpiece and grinding wheel in grinding operations, thereby reducing cooling efficiency. The presence of moving ambient air near the workpiece and rotating grinding wheel further complicates cooling. First, the study investigates jet breakups in stationary air, predicting breakup lengths with reasonable agreement to experiments at varying jet velocities using the Reynolds Averaged Navier–Stokes (RANS) method equipped with Shear Stress Transport (SST) k-ω model of turbulence. The coolant jet breakup length for a jet normal to the grinding wheel is different from that for a free jet and affected by the proximity of grinding wheel to nozzle that was not evaluated in prior studies. Simulations were performed using Ansys Fluent software 2023R1, with careful tuning of numerical schemes and selection of breakup criteria. The results include analysis of jet breakup phenomena in presence of rotating grinding wheel and workpieces, determination of breakup lengths across a range of Weber numbers, and effects of nozzle design. Full article

(This article belongs to the Section Energy Systems)

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26 pages, 485 KB

Open AccessArticle

An Integrated Methodology and Novel Index for Assessing Distributed Photovoltaic Deployment in Energy Transition Pathways: Evidence from Ecuador

by Alfonso Gunsha-Morales, Marcos A. Ponce-Jara, G. Jiménez-Castillo, J. L. Sánchez-Jiménez and Catalina Rus-Casas

Processes 2026, 14(2), 388; https://doi.org/10.3390/pr14020388 - 22 Jan 2026

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Abstract

This study aims to develop and apply a novel methodology to assess the scope, benefits and challenges of distributed photovoltaic generation (DG-PV). The research provides a replicable framework applicable to any country, as long as official energy consumption data are available and the [...] Read more.

This study aims to develop and apply a novel methodology to assess the scope, benefits and challenges of distributed photovoltaic generation (DG-PV). The research provides a replicable framework applicable to any country, as long as official energy consumption data are available and the nation is seeking to modify its energy matrix as part of a sustainable transition through the design of renewable-energy-based policies. To support the viability of the proposal, data from the Ecuadorian electrical system for the period between 2014 and 2024 were analyzed using technical, operational and socio-economic indicators defined in the methodology. These include renewable participation, energy diversification, DG-PV, technical efficiency, regulatory index, operational resilience and electrical coverage. The investigation concludes with the definition of a Distributed Photovoltaic Integration Index (DPII), which can be used to measure a country’s progress toward the proper implementation of renewable energy. The DPII supports informed decision-making by allowing utilities and policymakers to prioritize distributed photovoltaic integration and compare alternative energy transition scenarios. In the case of Ecuador, a DPII of 0.170 is obtained for 2024 compared to a value of 0 for 2014. This result is mainly due to an increase in renewable energy participation (P1), which rose from 0.49 to 0.76 during this period, largely supported by hydropower expansion. This value was obtained because over the last ten years, Ecuador has committed to implementing active policies that incorporate renewable energies, as well as other aspects such as technical efficiency and the expansion of electrical coverage. This approach offers a replicable quantitative tool for evaluating the integration of DG-PV, providing key information for energy planning and for the formulation of policies that promote the decarbonization, decentralization and digitalization of the national electrical system. Full article

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

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24 pages, 9651 KB

Open AccessArticle

H₂/CH₄ Competitive Adsorption of LTA Zeolite: Effects of Cations, Si/Al Ratio, Adsorption Temperature, and Pressure

by Xue Zhang, Jianfeng Tang and Hui Liu

Processes 2026, 14(2), 387; https://doi.org/10.3390/pr14020387 - 22 Jan 2026

Viewed by 382

Abstract

The efficient separation of H₂ from CH₄ is crucial for hydrogen purification from industrial off-gases using pressure swing adsorption (PSA). In this study, the competitive adsorption behavior of H₂/CH₄ on LTA zeolites was systematically investigated via grand canonical [...] Read more.

The efficient separation of H₂ from CH₄ is crucial for hydrogen purification from industrial off-gases using pressure swing adsorption (PSA). In this study, the competitive adsorption behavior of H₂/CH₄ on LTA zeolites was systematically investigated via grand canonical Monte Carlo (GCMC) simulations, with a focus on the effects of cation type (Na⁺, Li⁺, Ca²⁺, Mg²⁺), Si/Al ratio (1–1.5), temperature (298–318 K), and pressure (0.2–2 MPa). The results reveal that CH₄ favors β-cages as excellent adsorption sites with high population density, followed by the regions adjacent to the cations or framework oxygen atoms of the eight-membered rings. In contrast, H₂ is uniformly distributed throughout all the channels. Cations with higher valence and smaller ionic radii (e.g., Mg²⁺) enhance CH₄ adsorption capacity and diffusion more effectively than monovalent or larger cations. Increasing the Si/Al ratio reduces cation content and exposes more framework oxygen atoms, particularly those in Si–O–Si environments, which improve CH₄ adsorption. Elevated temperature weakens CH₄ adsorption while promoting H₂ diffusion and pore occupancy. Although higher pressure increases the uptake of both gases, H₂ adsorption rises more substantially and distributes more widely, leading to a decrease in CH₄/H₂ selectivity. Full article

(This article belongs to the Special Issue Advanced Research on Marine and Deep Oil & Gas Development)

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23 pages, 4205 KB

Open AccessArticle

A Novel Predictive Model for Drilling Fluid Rheological Parameters Across Wide Temperature–Pressure Ranges Using Symbolic Regression Algorithm

by Wang Chen, Jun Li, Hongwei Yang, Geng Zhang, Biao Wang, Gonghui Liu, Zhaoyu Shen and Hui Ji

Processes 2026, 14(2), 386; https://doi.org/10.3390/pr14020386 - 22 Jan 2026

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Abstract

Accurate prediction of drilling fluid rheological parameters under high-temperature and high-pressure (HTHP) conditions is critical for reliable drilling hydraulics and wellbore pressure control in deep and ultra-deep wells. However, most existing empirical and semi-empirical rheological models are developed for limited temperature–pressure ranges and [...] Read more.

Accurate prediction of drilling fluid rheological parameters under high-temperature and high-pressure (HTHP) conditions is critical for reliable drilling hydraulics and wellbore pressure control in deep and ultra-deep wells. However, most existing empirical and semi-empirical rheological models are developed for limited temperature–pressure ranges and specific fluid formulations, which restrict their applicability and accuracy under HTHP conditions. In this study, systematic rheological experiments were conducted on multiple drilling fluid systems over wide temperature–pressure ranges (20–200 °C and 0.1–200 MPa). Based on the experimental data, a unified predictive model for key rheological parameters was developed using a symbolic regression (SR) algorithm. The model performance was evaluated using standard statistical metrics and compared with commonly used conventional models. Compared with conventional models, the proposed model shows stronger applicability for predicting the rheological parameters of the investigated oil-based and water-based drilling fluids over a wider temperature–pressure range. It effectively overcomes the limitations of existing models under HTHP conditions (150–200 °C and 80–200 MPa) and demonstrates improved prediction accuracy and robustness for both high- and low-density drilling fluids. The overall prediction errors are generally within approximately 10%. The results indicate that the proposed unified model provides a reliable and computationally efficient tool for predicting drilling fluid rheological parameters under HTHP conditions, facilitating its integration into wellbore hydraulics, wellbore pressure, and equivalent circulating density calculations in deep and ultra-deep well applications. Full article

(This article belongs to the Special Issue Advanced Research on Marine and Deep Oil & Gas Development)

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17 pages, 3395 KB

Open AccessArticle

Performance Analysis and Mix Proportion Optimization of Coal Gangue Concrete Under Sulfate Dry–Wet Cycling Conditions

by Mingtao Gao, Chengyang Guo, Zhenhua Hu, Minhui Li, Zihao Guo, Hongyun Ren and Jiaxin Cui

Processes 2026, 14(2), 385; https://doi.org/10.3390/pr14020385 - 22 Jan 2026

Cited by 1 | Viewed by 197

Abstract

The performance degradation of concrete structures in underground water sumps within the Ordos mining area has become increasingly prominent due to environmental factors, particularly the sulfate-induced dry–wet cycles. These conditions lead to the development of cracks, spalling, and structural instability, which poses significant [...] Read more.

The performance degradation of concrete structures in underground water sumps within the Ordos mining area has become increasingly prominent due to environmental factors, particularly the sulfate-induced dry–wet cycles. These conditions lead to the development of cracks, spalling, and structural instability, which poses significant safety risks. This issue must be addressed with consideration of the regional hydrogeological characteristics and the current requirements for safe, sustainable, and environmentally responsible coal mining practices. The study investigates the concrete employed in the underground central water reservoir of Bulianta Coal Mine in the Ordos mining area. A novel approach is proposed for developing sulfate-resistant concrete capable of withstanding dry–wet cyclic conditions in underground environments through the utilization of coal gangue sourced from the same mining operation. Considering concrete performance, cost-effectiveness, and coal gangue utilization, a laboratory mix optimization study was conducted and the optimal mixture proportion was determined to be a 60% gangue content, a 30% fly ash content, a water–binder ratio of 0.38, which produced concrete with a compressive strength of 31 MPa. Sulfate resistance tests were conducted on the optimal mixture of dry–wet cycle-resistant concrete. The effect of different dry–wet cycle counts on the compressive strength of the coal gangue concrete was investigated, and the evolution patterns of the ascending segment shape coefficient a and descending segment shape coefficient b under sulfate-induced dry–wet cycling were analyzed. Combining the Guo Zhenhai concrete constitutive model, a concrete constitutive model suitable for the dry–wet cycle conditions of sulfate was established. Based on the proposed constitutive model, the uniaxial compressive mechanical behavior of coal gangue concrete subjected to sulfate attack was investigated through numerical simulations using the Abaqus (2020) software. The simulation results are basically consistent with the laboratory results, which proves the applicability of the constitutive model and confirms the performance of the optimal proportioning scheme for preparing sulfate-resistant dry–wet cycle concrete using coal gangue from underground mines. This study provides a new type of concrete for similar underground conditions in this mining area and offers a new approach for the comprehensive utilization of coal gangue. Full article

(This article belongs to the Section Energy Systems)

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19 pages, 59527 KB

Open AccessFeature PaperArticle

Hierarchical Control System for a Multi-Port, Bidirectional MMC-Based EV Charging Station: A Model-in-the-Loop Validation

by Tomas Ravet, Cristobal Rodriguez, Matias Diaz, Daniel Velasquez, Roberto Cárdenas and Pat Wheeler

Processes 2026, 14(2), 384; https://doi.org/10.3390/pr14020384 - 22 Jan 2026

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Abstract

The increasing demand for high-power electric vehicle charging systems with Vehicle-to-Grid (V2G) capability highlights the need for modular, scalable power converters. This paper proposes a hierarchical control strategy for a high-power, multi-port electric vehicle charging station. The system, based on a Series-Parallel Modular [...] Read more.

The increasing demand for high-power electric vehicle charging systems with Vehicle-to-Grid (V2G) capability highlights the need for modular, scalable power converters. This paper proposes a hierarchical control strategy for a high-power, multi-port electric vehicle charging station. The system, based on a Series-Parallel Modular Multilevel Converter (SP-MMC) with isolated modules, is managed by a coordinated control strategy that integrates proportional-integral-resonant regulators, nearest-level control with voltage sorting, and single-phase-shifted modulation. The proposed system enables simultaneous, independent regulation of multiple bidirectional, isolated direct current ports while maintaining grid-side power quality and internal variables of the SP-MMC. The proposed control is validated using real-time Model-In-the-Loop (MIL) simulations that include sequential port activation, bidirectional power flow, and charging operation. MIL results demonstrate stable operation with controlled DC-link voltage ripple, accurate per-port current tracking, and near-unity grid power factor under multi-port operation. Full article

(This article belongs to the Special Issue Power Electronics, Control, and Energy Systems for the Energy Transition and Renewable Energy Conversion Processes)

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25 pages, 8863 KB

Open AccessArticle

A Multi-Scale Residual Convolutional Neural Network for Fault Diagnosis of Progressive Cavity Pump Systems in Coalbed Methane Wells with Imbalanced and Differentiated Data

by Jiaojiao Yu, Yajie Ou, Ying Gao, Youwu Li, Feng Gu, Jinhuang You, Bin Liu, Xiaoyong Gao and Chaodong Tan

Processes 2026, 14(2), 383; https://doi.org/10.3390/pr14020383 - 22 Jan 2026

Viewed by 276

Abstract

Coalbed methane, an abundant clean energy resource in China, is gaining significant attention. Electric submersible progressive cavity pumps, ideal for downhole extraction with high solids content, are vital in coalbed methane operations. Current fault diagnosis research for these pumps mainly relies on machine [...] Read more.

Coalbed methane, an abundant clean energy resource in China, is gaining significant attention. Electric submersible progressive cavity pumps, ideal for downhole extraction with high solids content, are vital in coalbed methane operations. Current fault diagnosis research for these pumps mainly relies on machine learning algorithms to identify fault features, but complex working conditions and imbalanced sample distributions challenge these models’ ability to perceive multi-scale and multi-dimensional features. To enhance the model’s perception of deep abnormal data in complex multi-case industrial datasets, this study proposes a deep learning model based on a multi-scale extraction and residual module convolutional neural network. Innovatively, a cross-attention module using global autocorrelation and local cross-correlation is introduced to constrain the multi-scale feature extraction process, making the model better suited to specific and differentiated data environments. Post feature extraction, the model employs Borderline-SMOTE to augment minority class samples and uses Tomek Links for noise removal. These enhancements improve the comprehensive perception of fault types with significant differences in period, amplitude, and dimension, as well as the learning capability for rare faults. Based on field-collected fault data and using enhanced and cleaned features for classifier training, tests on a real industrial dataset show the proposed model achieves an F1 Measure of 90.7%—an improvement of 13.38% over the unimproved model and 9.15–31.64% over other common fault diagnosis models. Experimental results confirm the method’s effectiveness in adapting to extremely imbalanced sample distributions and complex, variable field data characteristics. Full article

(This article belongs to the Special Issue Coalbed Methane Development Process)

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20 pages, 1190 KB

Open AccessArticle

Compositional Group Analysis of Biocrude Oils Obtained from Swine Manure by Slow Pyrolysis

by Lenia Gonsalvesh, Stefan Marinov, Maya Stefanova, Jan Czech, Robert Carleer and Jan Yperman

Processes 2026, 14(2), 382; https://doi.org/10.3390/pr14020382 - 22 Jan 2026

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Abstract

The study comprises an in-depth characterization of compositional groups of the liquid by-products obtained from the pyrolysis of swine manure at 500 °C, with the aim of providing an alternative and efficient approach for the valorisation of this waste stream, alongside with the [...] Read more.

The study comprises an in-depth characterization of compositional groups of the liquid by-products obtained from the pyrolysis of swine manure at 500 °C, with the aim of providing an alternative and efficient approach for the valorisation of this waste stream, alongside with the production of biogas and char, the latter of which can be further converted into activated carbon. Two samples were considered: de-watered cake and solid product from anaerobic digestion of swine manure. Biocrude oils were fractionated into weak acidic, strong acidic, alkaline and neutral oil fractions. Subsequently, the neutral oil fraction was separated into paraffinic–naphthenic, slightly polar and polar fractions. All fractions were analyzed by GC–MS. The major identified compositional groups were: (i) for de-watered cake: steroids (40.7%), fatty acids, FAs (23.7%) and n-alkenes/n-alkanes (23.3%); (ii) for solid product from anaerobic digestion: FAs (31.0%), phenols/methoxy phenols (26.6%), n-alkenes/n-alkanes (10.8%) and steroids (10.6%). A variety of short-chain FAs (i.e., linear saturated, mono- and di-unsaturated, cis (i-), trans (ai-), isoprenoid, phenyl alkanoic, amongst others) and methyl esters (FAMEs) were identified as well. FA distribution, nC₁₂–nC₂₀, was similar for both manures studied with nC₁₆ and nC₁₈ as major compounds. FAMEs (nC₁₄–nC₂₈, with even carbon number dominance) in the slightly polar fraction of both samples were accompanied by considerable amounts of oleic (nC_18:1) and linoleic (nC_18:2) acids, and corresponding methyl esters. Hydrocarbons, i.e., n-alkenes/n-alkanes, were in the range of nC₁₅–nC₃₄, with nC₁₈ maximizing. Anaerobically digested manure has resulted in (i) an increase in the portion of longer homologues of hydrocarbons and FAMEs and (ii) the appearance of new FAs series of long chain members nC_22:1–nC_26:1, ω-9. The comprehensive analysis of the biocrude oils obtained from the slow pyrolysis of swine manure indicates their potential for use as biodiesel additives or as feedstock to produce value-added materials. Full article

(This article belongs to the Special Issue Biomass Pyrolysis Characterization and Energy Utilization)

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17 pages, 3775 KB

Open AccessArticle

Genomic Insights into a Thermophilic Bacillus licheniformis Strain Capable of Degrading Polyethylene Terephthalate Intermediate

by Pedro Eugenio Sineli, Fernando Gabriel Martínez, Federico Zannier, Luciana Costas, José Horacio Pisa, Analía Álvarez and Cintia Mariana Romero

Processes 2026, 14(2), 381; https://doi.org/10.3390/pr14020381 - 22 Jan 2026

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Abstract

Bacillus licheniformis Mb1, a thermophilic strain isolated from the Yungas rainforest in northwestern Argentina, was analyzed through genomic and experimental approaches to explore its biotechnological potential. Phylogenomic analysis confirmed its close relationship with B. licheniformis reference strains. The genome revealed multiple genes associated [...] Read more.

Bacillus licheniformis Mb1, a thermophilic strain isolated from the Yungas rainforest in northwestern Argentina, was analyzed through genomic and experimental approaches to explore its biotechnological potential. Phylogenomic analysis confirmed its close relationship with B. licheniformis reference strains. The genome revealed multiple genes associated with hydrolytic, oxidative, carbohydrate-active, and polyester-degrading activities, indicating a wide enzymatic capacity. Experimental assays demonstrated strong extracellular hydrolytic activities and efficient degradation of bis(2-hydroxyethyl) terephthalate (BHET), a key polyethylene terephthalate (PET) intermediate. In liquid cultures with 3 mg/mL BHET, B. licheniformis Mb1 achieved 99.9% depletion within four days, with transient BHET dimer accumulation and progressive terephthalic acid (TPA) production, reaching 1.17 mg/mL after 15 days. Mono (2-hydroxyethyl) terephthalate (MHET) and vanillic acid were not detected. Complete BHET and dimer degradation suggests the presence of versatile hydrolases acting on short-chain polyester intermediates. Sequence and molecular docking analyses identified a BHETase-like carboxylesterase as the main enzyme candidate, featuring a truncated lidC region that generates a more open catalytic cleft. This structural trait, not previously reported in bacterial BHETases, enables the accommodation of bulkier substrates such as BHET dimer. These findings highlight B. licheniformis Mb1 as a promising biocatalyst for polyester depolymerization and a valuable microbial resource for future enzyme discovery and plastic bioremediation strategies. Full article

(This article belongs to the Special Issue Chemical and Microbiological Analyses of Wastes, Effluents and Materials)

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15 pages, 1013 KB

Open AccessArticle

Innovations and Sustainability Metrics for Nitric Acid Production: Emission Control and Process Optimization

by Filippo Buttignol, Pierdomenico Biasi and Alberto Garbujo

Processes 2026, 14(2), 380; https://doi.org/10.3390/pr14020380 - 22 Jan 2026

Viewed by 668

Abstract

Nitric acid production is a cornerstone of the chemical industry, yet it presents considerable environmental challenges, primarily due to greenhouse gas emissions such as nitrous oxide (N₂O) and nitrogen oxides (NO_x). This manuscript critically examines the key performance indicators [...] Read more.

Nitric acid production is a cornerstone of the chemical industry, yet it presents considerable environmental challenges, primarily due to greenhouse gas emissions such as nitrous oxide (N₂O) and nitrogen oxides (NO_x). This manuscript critically examines the key performance indicators (KPIs) that define the gate-to-gate environmental sustainability of nitric acid plants. Quantitative metrics and related benchmarks achieved in modern plants, e.g., energy efficiency (ca. 2 GJ exported per ton of HNO₃) and NO_x/N₂O reduction (95–99%), are presented. Strategies to enhance these KPIs are discussed, including process integration, intensification, advanced emission control technologies, and operational optimization. Special attention is given to the chemical conversion processes of NO_x and N₂O, highlighting their roles in minimizing overall emissions. The review also synthesizes recent literature to showcase emerging trends, regulatory developments, and technological innovations that facilitate the transition toward more sustainable nitric acid production. Finally, the article identifies current research gaps and outlines future directions for the field. Full article

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

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14 pages, 1317 KB

Open AccessArticle

Cost-Engineering Analysis of Radio Frequency Plus Heat for In-Shell Egg Pasteurization

by Daniela Bermudez-Aguirre, Joseph Sites, Sudarsan Mukhopadhyay and Brendan A. Niemira

Processes 2026, 14(2), 379; https://doi.org/10.3390/pr14020379 - 22 Jan 2026

Viewed by 262

Abstract

Salmonella spp. is a pathogenic microorganism linked to eggs and egg products. In-shell eggs are not required to be pasteurized in any country before they reach the consumer. The use of an emerging technology known as radio frequency has been successfully used to [...] Read more.

Salmonella spp. is a pathogenic microorganism linked to eggs and egg products. In-shell eggs are not required to be pasteurized in any country before they reach the consumer. The use of an emerging technology known as radio frequency has been successfully used to inactivate this pathogen inside in-shell eggs and claim pasteurization standards (5 - log reduction). The objective of this manuscript was to conduct the engineering cost of egg processing using a radio frequency pasteurizer and compare the processing cost to conventional thermal pasteurization for in-shell eggs. The ARS-patented radio frequency pasteurizer was used (40.68 MHz, 35 W) to pasteurize eggs in 24.5 min. The conventional thermal pasteurization (56.7 °C) required 60 min for the same level of inactivation. The techno-economic analysis (TEA) included information from stakeholders, egg processors and equipment manufacturers and was used together with energy balances and some key assumptions. Calculations for the engineering cost were made based on the required energy for each system, showing that the radio frequency required a third of the total cost of electricity to pasteurize eggs in a year compared with thermal, based on utilities costs in PA. Other utilities such as water and steam were also minor for radio frequency pasteurization. After two years of operation, the projected additional cost of processing is ~USD 0.19 per egg for the radio frequency system, compared with USD 0.22 per egg for conventional thermal treatment, largely due to volume-based amortization of capital costs and lower annual operating costs for the RF process. Radio frequency thus could be an option to pasteurize eggs in farms from PA and potentially in other states, using the system developed by our research team, while reducing energy consumption and increasing return on investment. Full article

(This article belongs to the Special Issue Emerging Thermal and Non-Thermal Technologies for Food Preservation and Sustainable Food Processing)

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23 pages, 7133 KB

Open AccessArticle

Energy Transfer Characteristics of Surface Vortex Heat Flow Under Non-Isothermal Conditions Based on the Lattice Boltzmann Method

by Qing Yan, Lin Li and Yunfeng Tan

Processes 2026, 14(2), 378; https://doi.org/10.3390/pr14020378 - 21 Jan 2026

Cited by 6 | Viewed by 324

Abstract

During liquid drainage from intermediate vessels in various industrial processes such as continuous steel casting, aircraft fuel supply, and chemical separation, free-surface vortices commonly occur. The formation and evolution of these vortices not only entrain surface slag and gas, but also lead to [...] Read more.

During liquid drainage from intermediate vessels in various industrial processes such as continuous steel casting, aircraft fuel supply, and chemical separation, free-surface vortices commonly occur. The formation and evolution of these vortices not only entrain surface slag and gas, but also lead to deterioration of downstream product quality and abnormal equipment operation. The vortex evolution process exhibits notable three-dimensional unsteadiness, multi-scale turbulence, and dynamic gas–liquid interfacial changes, accompanied by strong coupling effects between temperature gradients and flow field structures. Traditional macroscopic numerical models show clear limitations in accurately capturing these complex physical mechanisms. To address these challenges, this study developed a mesoscopic numerical model for gas-liquid two-phase vortex flow based on the lattice Boltzmann method. The model systematically reveals the dynamic behavior during vortex evolution and the multi-field coupling mechanism with the temperature field while providing an in-depth analysis of how initial perturbation velocity regulates vortex intensity and stability. The results indicate that vortex evolution begins near the bottom drain outlet, with the tangential velocity distribution conforming to the theoretical Rankine vortex model. The vortex core velocity during the critical penetration stage is significantly higher than that during the initial depression stage. An increase in the initial perturbation velocity not only enhances vortex intensity and induces low-frequency oscillations of the vortex core but also markedly promotes the global convective heat transfer process. With regard to the temperature field, an increase in fluid temperature reduces the viscosity coefficient, thereby weakening viscous dissipation effects, which accelerates vortex development and prolongs drainage time. Meanwhile, the vortex structure—through the induction of Taylor vortices and a spiral pumping effect—drives shear mixing and radial thermal diffusion between fluid regions at different temperatures, leading to dynamic reconstruction and homogenization of the temperature field. The outcomes of this study not only provide a solid theoretical foundation for understanding the generation, evolution, and heat transfer mechanisms of vortices under industrial thermal conditions, but also offer clear engineering guidance for practical production-enabling optimized operational parameters to suppress vortices and enhance drainage efficiency. Full article

(This article belongs to the Section Energy Systems)

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21 pages, 2691 KB

Open AccessArticle

Interturn Short-Circuit Fault Diagnosis in a Permanent Magnet Synchronous Generator Using Wavelets and Binary Classifiers

by Jose Antonio Alvarez-Salas, Francisco Javier Villalobos-Pina, Mario Arturo Gonzalez-Garcia and Ricardo Alvarez-Salas

Processes 2026, 14(2), 377; https://doi.org/10.3390/pr14020377 - 21 Jan 2026

Viewed by 262

Abstract

Condition monitoring and diagnosis in a permanent magnet synchronous generator (PMSG) are crucial for ensuring its service continuity and reliability. Recent advancements have introduced innovative, non-invasive techniques for detecting mechanical and electrical faults in this machine. This paper proposes a novel application of [...] Read more.

Condition monitoring and diagnosis in a permanent magnet synchronous generator (PMSG) are crucial for ensuring its service continuity and reliability. Recent advancements have introduced innovative, non-invasive techniques for detecting mechanical and electrical faults in this machine. This paper proposes a novel application of the discrete wavelet transform and binary classifiers for diagnosing interturn short-circuit faults in a PMSG with high accuracy and low computational burden. The objective of fault diagnosis is to detect the presence of an interturn short-circuit fault (fault vs. no-fault) under different fault severities and operating speeds. Multiple binary models were trained separately for each fault scenario. The three-phase currents from the PMSG are processed using the discrete wavelet transform to extract features, which are then fed into a binary classifier based on a Random Forest algorithm. Optimization techniques are used to improve the performance of the binary classifiers. Experimental results obtained under various stator fault conditions in the PMSG are presented. Metrics such as accuracy and confusion matrices are used to evaluate the performance of binary classifiers. Full article

(This article belongs to the Special Issue Fault Diagnosis of Equipment in the Process Industry)

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27 pages, 9070 KB

Open AccessArticle

Research on the Prediction of Pressure, Temperature, and Hydrate Inhibitor Addition Amount After Surface Mining Throttling

by Dake Peng, Yuxin Wu, Yiyun Wang, Hong Wang, Junji Wei, Guojing Fu, Wei Luo and Jihan Wang

Processes 2026, 14(2), 376; https://doi.org/10.3390/pr14020376 - 21 Jan 2026

Viewed by 224

Abstract

During the trial mining process, ground horizontal pipes are prone to generating hydrates due to pressure and temperature changes, leading to ice blockage. Hydrate inhibitors are usually added on-site to prevent freezing blockage. However, existing addition methods have limitations, including poor real-time performance, [...] Read more.

During the trial mining process, ground horizontal pipes are prone to generating hydrates due to pressure and temperature changes, leading to ice blockage. Hydrate inhibitors are usually added on-site to prevent freezing blockage. However, existing addition methods have limitations, including poor real-time performance, insufficient accuracy in the addition amount, and dependence on manual adjustment. In view of this, this paper aims to develop models to predict the throttling pressure and temperature for horizontal ground pipes, and to indicate the amount of ethylene glycol needed to prevent freezing blockage, thereby laying the foundation for accurate, real-time prediction of fluid pressure and temperature and for controlling the addition amount. By integrating data-driven technologies and mechanism models, this study developed intelligent prediction systems for ground horizontal pipe throttling pressure and temperature, and for suppression of freeze-blocking ethylene glycol addition. First, a three-phase throttling mechanism model for oil, gas, and water is established using the energy conservation equation to accurately predict the pressure and temperature at the throttling points along the process. At the same time, HYSYS software is used to simulate various operating conditions and to fit the ethylene glycol addition amount prediction model. Finally, edge computing equipment is integrated to enable real-time data collection, prediction, and dynamic adjustment and optimization. The field measurement data of Well A showed that the model’s prediction error of pressure and temperature before and after throttling is less than 6%, and the prediction error of the ethylene glycol addition amount is less than 5%, which provides key technical support for safe and efficient operation of the trial mining process as well as for cost reduction and efficiency improvement. Full article

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

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18 pages, 1702 KB

Open AccessArticle

Dynamic Modeling and Calibration of an Industrial Delayed Coking Drum Model for Digital Twin Applications

by Vladimir V. Bukhtoyarov, Ivan S. Nekrasov, Alexey A. Gorodov, Yadviga A. Tynchenko, Oleg A. Kolenchukov and Fedor A. Buryukin

Processes 2026, 14(2), 375; https://doi.org/10.3390/pr14020375 - 21 Jan 2026

Viewed by 493

Abstract

The increasing share of heavy and high-sulfur crude oils in refinery feed slates worldwide highlights the need for models of delayed coking units (DCUs) that are both physically meaningful and computationally efficient. In this study, we develop and calibrate a simplified yet dynamic [...] Read more.

The increasing share of heavy and high-sulfur crude oils in refinery feed slates worldwide highlights the need for models of delayed coking units (DCUs) that are both physically meaningful and computationally efficient. In this study, we develop and calibrate a simplified yet dynamic one-dimensional model of an industrial coke drum intended for integration into digital twin frameworks. The model includes a three-phase representation of the drum contents, a temperature-dependent global kinetic scheme for vacuum residue cracking, and lumped descriptions of heat transfer and phase holdups. Only three physically interpretable parameters—the kinetic scaling factors for distillate and coke formation and an effective wall temperature—were calibrated using routinely measured plant data, namely the overhead vapor and drum head temperatures and the final coke bed height. The calibrated model reproduces the temporal evolution of the top head and overhead temperatures and the final bed height with mean relative errors of a few percent, while capturing the more complex bottom-head temperature dynamics qualitatively. Scenario simulations illustrate how the coking severity (represented here by the effective wall temperature) affects the coke yield, bed growth, and cycle duration. Overall, the results indicate that low-order dynamic models can provide a practical balance between physical fidelity and computational speed, making them suitable as mechanistic cores for digital twins and optimization tools in delayed coking operations. Full article

(This article belongs to the Special Issue Development and Implementation of Digital Twins for Industrial Processes)

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18 pages, 2084 KB

Open AccessArticle

Electronic Activation and Inhibition of Natural Rubber Biosynthesis Catalyzed by a Complex Heterologous Membrane-Bound Complex

by J. Parker Evans, Vishnu Baba Sundaresan and Katrina Cornish

Processes 2026, 14(2), 374; https://doi.org/10.3390/pr14020374 - 21 Jan 2026

Viewed by 293

Abstract

Natural rubber biosynthesis is catalyzed by a unilamella membrane-bound heterologous complex with multiple different subunits (rubber transferase, RTase). Two substrates and divalent metal cation activators are required, and their concentrations affect biosynthetic rate and polymer molecular weight. Rate, molecular weight, and complex stability [...] Read more.

Natural rubber biosynthesis is catalyzed by a unilamella membrane-bound heterologous complex with multiple different subunits (rubber transferase, RTase). Two substrates and divalent metal cation activators are required, and their concentrations affect biosynthetic rate and polymer molecular weight. Rate, molecular weight, and complex stability are highly sensitive to Mg²⁺ and Mn²⁺ concentration, but studies are challenging because methods to control ion concentration may dislodge the elongating rubber polymers from the RTase complexes, halting synthesis and producing low-molecular-weight polymer. Here, programmable chemical actuators (PCAs) are used to electrochemically control rubber biosynthetic rate and subsequent molecular weight in enzymatically active rubber particles purified from Ficus elastica (Indian rubber tree). RTase activity was assayed using ³H-FPP (initiator) and ¹⁴C-IPP (monomer). Since only one FPP molecular is needed to initiate a new rubber polymer, the ratio of incorporated ³H-FPP to ¹⁴C-IPP was used to calculate the mean molecular weight of newly synthesized polymers. PCAs exchange ions in solution through REDOX reactions which we show control cation concentration without dislodging the elongating rubber polymers from the RTase. PCAs demonstrated highly tunable control over monomer incorporation and molecular weight in both Mg²⁺ and Mn²⁺ cations. REDOX cycling PCAs did not irreversibly inhibit the rubber transferase complex, and no indication of enzymatic damage was observed. Precise PCA control of RTase activity may pave the way for rubber eventually to be produced in bioreactors. Full article

(This article belongs to the Section Catalysis Enhanced Processes)

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16 pages, 7138 KB

Open AccessArticle

Characteristics of Plasma-Assisted Ammonia Jet Flame Under High-Pressure Conditions

by Zhicong Lv, Zhiwei Wang, Qifu Lin, Jiawei Gong, Yong Li, Yuchen Zhang and Longwei Chen

Processes 2026, 14(2), 373; https://doi.org/10.3390/pr14020373 - 21 Jan 2026

Viewed by 328

Abstract

A plasma-assisted ammonia jet flame igniter was developed in this study to address the limitations of conventional spark ignition at high pressures. The effect of pressure on plasma discharge characteristics, optical emission spectra, and exhaust gas emission was systematically investigated, providing new insights [...] Read more.

A plasma-assisted ammonia jet flame igniter was developed in this study to address the limitations of conventional spark ignition at high pressures. The effect of pressure on plasma discharge characteristics, optical emission spectra, and exhaust gas emission was systematically investigated, providing new insights into the mechanisms of plasma-assisted ammonia ignition under high-pressure conditions. The results indicate that increased chamber pressure elevates gas density, which in turn raises the voltage required to sustain an arc discharge at 0.4 MPa and markedly reduces the frequency of arc drift. Spectral analysis shows that higher pressure inhibits atomic oxygen lines (777.2 nm and 844.6 nm) while intensifying the molecular nitrogen bands between 350–450 nm. A corresponding decrease in electron excitation temperature is also observed. In terms of exhaust composition, hydrogen concentration demonstrates a bifurcated behavior, rising with pressure under fuel-rich conditions (the equivalence ratio φ > 1.2) and falling under fuel-lean conditions (φ ≤ 1). Conversely, NO concentration consistently decreases with increasing pressure across all test conditions. The ammonia concentration in the exhaust gas shows opposite pressure dependencies at different equivalence ratios. It increases with rising pressure for φ ≥ 1, while it decreases with increasing pressure for φ < 1. Full article

(This article belongs to the Special Issue Synthesis and Utilization of Clean Ammonia as Fuel)

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15 pages, 8711 KB

Open AccessArticle

Microwave-Only Heating Concepts for Industrial CO₂ Regeneration System Design

by Hassan Al-Khalifah and Arvind Narayanaswamy

Processes 2026, 14(2), 372; https://doi.org/10.3390/pr14020372 - 21 Jan 2026

Viewed by 337

Abstract

This study presents various microwave reactor designs specifically engineered for continuous microwave CO₂ desorption, marking a significant advancement in microwave-heating systems. This study explored both horizontal and vertical continuous microwave reactor configurations. The horizontal design incorporates a modified conveyor belt system with [...] Read more.

This study presents various microwave reactor designs specifically engineered for continuous microwave CO₂ desorption, marking a significant advancement in microwave-heating systems. This study explored both horizontal and vertical continuous microwave reactor configurations. The horizontal design incorporates a modified conveyor belt system with cleated belts and Teflon sidewalls, rendering it particularly suitable for the regeneration of gas. Conversely, the vertical design utilizes a cascade gate opening mechanism, facilitating precise control over the microwave intensity and exposure duration. The efficiency of microwave power utilization was enhanced through the numerical modeling and optimization of the reactor dimensions. This study assessed the impact of waveguide placement, cavity size, and sorbent material thickness on power absorption and heating. The findings indicate that strategic waveguide positioning and optimal cavity dimensions significantly influence the microwave energy distribution and absorption, leading to reduced hotspots and more uniform heating. This study offers valuable insights into the design and optimization of microwave reactors for CO₂ desorption, contributing to more efficient and effective commercial applications of this technology. These results underscore the potential of microwave technology to revolutionize desorption processes and pave the way for further advancements in this domain. Design 2 exhibited more uniform heating owing to its slower and controlled temperature increase, making it more suitable for applications requiring consistent thermal performance over extended periods. Full article

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

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14 pages, 844 KB

Open AccessArticle

Knowledge-Enhanced Time Series Anomaly Detection for Lithium Battery Cell Screening

by Zhenjie Liu, Yudong Wang and Jianjun He

Processes 2026, 14(2), 371; https://doi.org/10.3390/pr14020371 - 21 Jan 2026

Viewed by 419

Abstract

The increasing application of lithium-ion batteries in manufacturing and energy storage systems necessitates high-precision screening of abnormal cells during manufacturing, so as to ensure safety and performance. Existing methods struggle to break down the barrier between prior knowledge and data, suffering from limitations [...] Read more.

The increasing application of lithium-ion batteries in manufacturing and energy storage systems necessitates high-precision screening of abnormal cells during manufacturing, so as to ensure safety and performance. Existing methods struggle to break down the barrier between prior knowledge and data, suffering from limitations such as insufficient detection accuracy and poor interpretability. This becomes even more prominent when facing distributional shifts in data. In this study, we propose a knowledge-enhanced anomaly detection framework for cell screening. This framework integrates domain knowledge, such as electrochemical principles, expert heuristic rules, and manufacturing constraints, into data-driven models. By combining features extracted from charging/discharging curves with rule-based prior knowledge, the proposed framework not only improves detection accuracy but also enables a traceable reasoning process behind anomaly identification. Experiments based on real-world battery production data demonstrate that the proposed framework outperforms baseline models in both precision and recall, making it a promising preferred solution for quality control in intelligent battery manufacturing. Full article

(This article belongs to the Special Issue Process Safety and Control Strategies for Urban Clean Energy Systems)

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15 pages, 4702 KB

Open AccessArticle

Alkaline Element Leaching from Fly Ash for Direct CO₂ Fixation

by Lingjin Zhu, Yahu Yao, Chuncheng Cai, Rongqiang Qiao, Xilin Ji, Yazhou Zhang, Zhennan Niu, Shengqi Zhou, Yingshuang Zhang, Baiye Li and Zhiyi Zhang

Processes 2026, 14(2), 370; https://doi.org/10.3390/pr14020370 - 21 Jan 2026

Viewed by 395

Abstract

Fly ash (FA), a major by-product of coal combustion, has long been regarded as a challenging industrial solid waste. Its inherent abundance of alkaline-earth oxides positioned it as a promising candidate for CO₂ sequestration through mineral carbonation. This study systematically investigated the [...] Read more.

Fly ash (FA), a major by-product of coal combustion, has long been regarded as a challenging industrial solid waste. Its inherent abundance of alkaline-earth oxides positioned it as a promising candidate for CO₂ sequestration through mineral carbonation. This study systematically investigated the effects of key operational parameters, including time, stirring rate, ultrasonic treatment, and solid-to-liquid ratio, on the leaching efficiency of calcium ions and subsequent CO₂ fixation. Ultrasonic treatment, a solid-to-liquid ratio of 1:7, a stirring speed of 600 rpm, and 7% monoethanolamine (MEA) collectively enhanced the calcium leaching efficiency (χ_e) to 16.7%, thereby supplying a substantial reservoir of calcium ions for CO₂ fixation. Additionally, the CO₂ injection into fly ash slurry and the slurry spraying into CO₂ gas were investigated to optimize reactor configurations. The latter method demonstrated superior performance, attaining a CO₂ fixation efficiency of 7.23%. This corresponds to a carbonation conversion efficiency (ηc) of approximately 44.5%, indicating that nearly half of the leached calcium ions were successfully converted into stable carbonates. Advanced characterization techniques (SEM-EDS, XRD, FTIR) confirmed the formation of stable carbonates and highlighted the role of additives in enhancing reactivity. The environmental benefit of this approach is addressing fly ash wastes and transforming fly ash into a CO₂ fixation material. These findings provided critical insights for calcium leaching and CO₂ fixation of fly ash. Full article

(This article belongs to the Section Petroleum and Low-Carbon Energy Process Engineering)

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19 pages, 2023 KB

Open AccessArticle

Chemical Composition, Antioxidant, Analgesic, and Wound-Healing Effects of Pinus pinaster Aiton and Pinus halepensis Mill Needles: A Natural Approach to Pain and Oxidative Stress Management

by Widad Tbatou, Hassan Laaroussi, Beybeti Ishagh, Karima El Yagoubi, Akissi Zachée Louis Evariste, Bruno Eto, Badiaa Lyoussi and Zineb Benziane Ouaritini

Processes 2026, 14(2), 369; https://doi.org/10.3390/pr14020369 - 21 Jan 2026

Viewed by 760

Abstract

Pine needles are traditional herbal remedies used for centuries to treat various ailments, including rheumatism, bronchitis, burns, inflammation, and infections. This study aimed to evaluate the antioxidant, analgesic (peripheral and central), and wound-healing activities of Pinus pinaster (PPN) and Pinus halepensis (PAN) needles [...] Read more.

Pine needles are traditional herbal remedies used for centuries to treat various ailments, including rheumatism, bronchitis, burns, inflammation, and infections. This study aimed to evaluate the antioxidant, analgesic (peripheral and central), and wound-healing activities of Pinus pinaster (PPN) and Pinus halepensis (PAN) needles while identifying the bioactive compounds responsible for these effects. Phytochemical analysis revealed several phenolic compounds, including p-coumaroylquinic acid, quercetin, narcissin, and myricetin-3-O-glucoside. Both extracts showed strong antioxidant activity, with high total phenolic content (TPC: 384.84 ± 0.84 and 524.46 mg GAE/g DM for PPN and PAN, respectively) and flavonoid content (TFC: 109.44 ± 0.62 and 111.64 ± 0.62 mg QE/g DM, respectively). Peripheral analgesic activity, assessed using the acetic acid-induced writhing test, revealed that PAN (300 mg/kg) significantly reduced pain by 72.3%, while central analgesic effects, evaluated by the tail immersion test, were comparable to the reference drug for both extracts. In vivo wound-healing tests showed accelerated wound contraction and complete closure by day 21, indicating strong regenerative potential. Overall, this study demonstrates that PPN and PAN needle extracts possess significant antioxidant, analgesic, and wound-healing activities, supporting their traditional use and highlighting their potential as natural therapeutic agents for managing oxidative stress, pain, and skin injuries. Full article

(This article belongs to the Special Issue Analysis and Processes of Bioactive Components in Natural Products)

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17 pages, 8979 KB

Open AccessArticle

Study on Physical Simulation of Shale Gas Dissipation Behavior: A Case Study for Northern Guizhou, China

by Baofeng Lan, Hongqi Liu, Chun Luo, Shaopeng Li, Haishen Jiang and Dong Chen

Processes 2026, 14(2), 368; https://doi.org/10.3390/pr14020368 - 21 Jan 2026

Viewed by 206

Abstract

The Longmaxi from the Anchang Syncline in northern Guizhou exhibits a high degree of thermal evolution of organic matter and significant variation in gas content. Because the synclinal is narrow, steep, and internally faulted, the mechanisms controlling shale gas preservation and escape remain [...] Read more.

The Longmaxi from the Anchang Syncline in northern Guizhou exhibits a high degree of thermal evolution of organic matter and significant variation in gas content. Because the synclinal is narrow, steep, and internally faulted, the mechanisms controlling shale gas preservation and escape remain poorly understood, complicating development planning and engineering design. Research on oil and gas migration and accumulation mechanisms in synclinal structures is therefore essential. To address this issue, three proportionally scaled strata—pure shale, gray shale, and sandy shale—were fabricated, and faults and artificial fractures with different displacements and inclinations were introduced. The simulation system consisted of two glass tanks (No. 1 and No. 2). Each tank had three rows of eight transmitting electrodes on one side, and a row of eight receiving electrodes on the opposite side. Tank 1 remained fixed, while Tank 2 could be hydraulically tilted up to 65° to simulate air and water migration under varying formation inclinations. A gas-water injection device was connected at the base. Gas was first injected slowly into the model. After injecting a measured volume (recorded via the flowmeter), the system was allowed to rest for 24–48 h to ensure uniform gas distribution. Water was then injected to displace the gas. During displacement, Tank 1 remained horizontal, and Tank 2 was inclined at a preset angle. An embedded monitoring program automatically recorded resistivity data from the 48 electrodes, and water-driven gas migration was analyzed through resistivity changes. A gas escape rate parameter (G_d), based on differences in gas saturation, was developed to quantify escape velocity. The simulation results show that gas escape increased with formation inclination. Beyond a critical angle, the escape rate slowed and approached a maximum. Faults and fractures significantly enhanced gas escape. Full article

(This article belongs to the Special Issue Data Acquisition, Processing, Analysis Methods and Process Control in Energy Exploration Systems)

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17 pages, 922 KB

Open AccessArticle

Structural Transformation and Decoupling Strategies in a Carbon-Intensive Catch-Up Economy

by Guozu Hao, Jingjing Wang, Xinfa Tang, Bin Xiao and Musa Dirane Nubea

Processes 2026, 14(2), 367; https://doi.org/10.3390/pr14020367 - 21 Jan 2026

Viewed by 231

Abstract

For less-developed, carbon-dependent regions, achieving carbon decoupling while pursuing economic catch-up presents a fundamental challenge. This study investigates this persistent dilemma through the case of Jiangxi Province, China, a typical coal-reliant inland region. Utilizing data from 2000 to 2022, we estimate carbon emissions [...] Read more.

For less-developed, carbon-dependent regions, achieving carbon decoupling while pursuing economic catch-up presents a fundamental challenge. This study investigates this persistent dilemma through the case of Jiangxi Province, China, a typical coal-reliant inland region. Utilizing data from 2000 to 2022, we estimate carbon emissions following IPCC guidelines and employ the Generalized Divisia Index Method (GDIM) to decompose emission drivers, effectively overcoming the limitation of factor independence in conventional decomposition analyses. The results identify economic scale (cumulative contribution: 97.81%) and energy consumption (51%) as the primary drivers of emission growth, while carbon intensity of output (−47.38%) emerges as the strongest inhibiting factor. The application of the Tapio decoupling model reveals that weak decoupling is the dominant state, prevailing in 91% of the study period. This persistent pattern underscores only a partial and unstable separation between economic growth and emissions, highlighting the region’s entrenched carbon lock-in. Our findings demonstrate that transcending this weak decoupling dilemma necessitates a strategic shift beyond efficiency gains. We propose that the resolution lies in accelerating structural transitions within the energy system and fostering low-carbon industrial upgrading. This study not only elucidates the dynamics of the carbon decoupling challenge in catch-up regions but also offers actionable and context-specific pathways, providing a valuable reference for analogous regions, particularly in developing and transition economies. Full article

(This article belongs to the Special Issue Activated Carbon: Contaminant Removal for Environmental Sustainability)

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21 pages, 7879 KB

Open AccessArticle

Study on Prediction of Particle Migration at Interburden Boundaries in Ore-Drawing Process Based on Improved Transformer Model

by Xinbo Ma, Liancheng Wang, Chao Wu, Xingfan Zhang and Xiaobo Liu

Processes 2026, 14(2), 366; https://doi.org/10.3390/pr14020366 - 21 Jan 2026

Viewed by 222

Abstract

In the process of ore drawing using a caving method under interburden conditions, the key to controlling ore dilution lies in the accurate prediction of boundary particle migration trajectories. To address the challenges of high computational costs and complex modeling in traditional numerical [...] Read more.

In the process of ore drawing using a caving method under interburden conditions, the key to controlling ore dilution lies in the accurate prediction of boundary particle migration trajectories. To address the challenges of high computational costs and complex modeling in traditional numerical simulations, this study designs a dataset construction method. After calibrating parameters using the angle of repose, ore-drawing numerical simulation datasets with interburden (post-defined and pre-defined models) are established. Building upon this foundation, an improved Transformer model is proposed. The model enhances spatiotemporal representation through multi-layer feature fusion embedding, strengthens long-range dependency capture via a reinforced spatiotemporal attention backbone, improves local dynamic modeling capability through optimized decoding at the output stage, and integrates transfer learning to achieve continuous prediction of particle migration. Validation results demonstrate that the model accurately predicts the spatial distribution patterns and collective motion trends of particles, with prediction errors at critical nodes confined to within a single stage and an average estimation error of approximately 4% in interburden regions. The proposed approach effectively overcomes the timeliness bottleneck of traditional interburden ore-drawing simulations, enabling rapid and accurate prediction of boundary particle migration under interburden conditions. Full article

(This article belongs to the Special Issue Sustainable and Advanced Technologies for Mining Engineering)

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40 pages, 7546 KB

Open AccessArticle

Hierarchical Soft Actor–Critic Agent with Automatic Entropy, Twin Critics, and Curriculum Learning for the Autonomy of Rock-Breaking Machinery in Mining Comminution Processes

by Guillermo González, John Kern, Claudio Urrea and Luis Donoso

Processes 2026, 14(2), 365; https://doi.org/10.3390/pr14020365 - 20 Jan 2026

Viewed by 486

Abstract

This work presents a hierarchical deep reinforcement learning (DRL) framework based on Soft Actor–Critic (SAC) for the autonomy of rock-breaking machinery in surface mining comminution processes. The proposed approach explicitly integrates mobile navigation and hydraulic manipulation as coupled subprocesses within a unified decision-making [...] Read more.

This work presents a hierarchical deep reinforcement learning (DRL) framework based on Soft Actor–Critic (SAC) for the autonomy of rock-breaking machinery in surface mining comminution processes. The proposed approach explicitly integrates mobile navigation and hydraulic manipulation as coupled subprocesses within a unified decision-making architecture, designed to operate under the unstructured and highly uncertain conditions characteristic of open-pit mining operations. The system employs a hysteresis-based switching mechanism between specialized SAC subagents, incorporating automatic entropy tuning to balance exploration and exploitation, twin critics to mitigate value overestimation, and curriculum learning to manage the progressive complexity of the task. Two coupled subsystems are considered, namely: (i) a tracked mobile machine with a differential drive, whose continuous control enables safe navigation, and (ii) a hydraulic manipulator equipped with an impact hammer, responsible for the fragmentation and dismantling of rock piles through continuous joint torque actuation. Environmental perception is modeled using processed perceptual variables obtained from point clouds generated by an overhead depth camera, complemented with state variables of the machinery. System performance is evaluated in unstructured and uncertain simulated environments using process-oriented metrics, including operational safety, task effectiveness, control smoothness, and energy consumption. The results show that the proposed framework yields robust, stable policies that achieve superior overall process performance compared to equivalent hierarchical configurations and ablation variants, thereby supporting its potential applicability to DRL-based mining automation systems. Full article

(This article belongs to the Special Issue Advances in the Control of Complex Dynamic Systems)

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27 pages, 7743 KB

Open AccessArticle

Research on High-Temperature Resistant Bridging Composite Cement Slurry Technology for Deep Well Loss Circulation Control

by Biao Ma, Kun Zheng, Bin Feng, Qing Shi, Lei Pu, Chengjin Zhang, Zhengguo Zhao, Shengbin Zeng and Peng Xu

Processes 2026, 14(2), 364; https://doi.org/10.3390/pr14020364 - 20 Jan 2026

Viewed by 368

Abstract

Circulation is one of the most prevalent and severe complications during the drilling and completion of deep and ultra-deep wells, especially in fractured and karstic formations. In regions such as the Sichuan Basin, bottom-hole temperatures exceeding 200 °C, limited formation strength, and frequent [...] Read more.

Circulation is one of the most prevalent and severe complications during the drilling and completion of deep and ultra-deep wells, especially in fractured and karstic formations. In regions such as the Sichuan Basin, bottom-hole temperatures exceeding 200 °C, limited formation strength, and frequent lithological alternations significantly reduce the effectiveness of conventional granular materials under high-temperature and long open-hole conditions. Bridging-type plugging systems based on particle gradation or principles often exhibit low success rates due to fiber softening, rubber aging, and erosion-induced deterioration of the sealing structure. In this study, a high-temperature-resistant bridging composite system was developed to meet the extreme conditions in deep and ultra-deep wells. By incorporating temperature-resistant bridging particles and flexible reinforcing components, the slurry establishes a synergistic “bridging–filling–densification” sealing mechanism. Meanwhile, the combined use of retarders, fluid-loss reducers, and rheology modifiers ensures stable pumpability and adequate curing densification at 200 °C. Overall, the results provide new insights and experimental evidence for the design of high-temperature cement-based plugging materials, offering a promising approach for improving loss-control effectiveness and wellbore strengthening in complex intervals. Full article

(This article belongs to the Special Issue Process Safety and Monitoring of Intelligent and Green Mining Technology (2nd Edition))

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