Processes

22 pages, 1315 KiB

Open AccessFeature PaperReview

Freeze and Spray Drying Technologies to Produce Solid Microbial Formulations for Sustainable Agriculture

by Luciana Luft and Marcio A. Mazutti

Processes 2025, 13(7), 2188; https://doi.org/10.3390/pr13072188 (registering DOI) - 9 Jul 2025

Different techniques that require specific conditions are used to increase long-term stability and facilitate the transportation of products. Solid microbial formulation gained significant attention in the scientific world for several applications due to its benefits, mainly for agriculture. The extensive applications in the [...] Read more.

Different techniques that require specific conditions are used to increase long-term stability and facilitate the transportation of products. Solid microbial formulation gained significant attention in the scientific world for several applications due to its benefits, mainly for agriculture. The extensive applications in the agricultural area, especially in the protection as a biopesticide and in the nutrition as a biofertilizer, have expanded knowledge on the production of solid bioproducts to keep up with developments in the community. Recent scientific works have disclosed different techniques, increased yields, and optimized parameters and other related procedures to produce solid microbial formulations with quality. However, the optimal protocol for solid microbial preparations differs between species and strains. The mechanisms underlying the protection and damage during drying methods and storage are, unfortunately, not clearly understood. Therefore, the current review highlights the state of the art of freeze and spray drying, both physical methods that are applied in microorganism formulations. Additionally, the study highlights the stresses these systems are exposed to during the drying process, as well as the strategies employed to ensure their stability throughout processing and storage. In summary, the information in this review provides a theoretical basis for the selection of these relevant technologies, according to the requirements demanded to obtain a sustainable bioinput. Full article

(This article belongs to the Special Issue Applications of Non-Thermal and Thermal Technologies in Food Processing, 2nd Edition)

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27 pages, 4818 KiB

Open AccessArticle

Instance Selection Strategies to Improve the Performance of Data-Driven Regression Models Applied to Industrial Systems

by Thiago K. Anzai, Gabriel Marcal de Brito, Tiago S. M. Lemos, Jaqueline Sousa Santos, Pedro H. T. Furtado and José Carlos Pinto

Processes 2025, 13(7), 2187; https://doi.org/10.3390/pr13072187 - 8 Jul 2025

Abstract

The present study originally addresses the data reduction problem in industrial settings through the lens of instance selection procedures, aiming to enhance the quality of data-driven models by preserving only the most relevant characteristics from the available datasets. Unlike traditional approaches, the proposed [...] Read more.

The present study originally addresses the data reduction problem in industrial settings through the lens of instance selection procedures, aiming to enhance the quality of data-driven models by preserving only the most relevant characteristics from the available datasets. Unlike traditional approaches, the proposed Instance Selection Library (ISLib) is specifically designed to handle the unique challenges of industrial datasets, such as operational variability, sensor inaccuracies, and the need for interpretable results. ISLib introduces a novel methodology tailored for regression tasks, an underexplored area in instance selection research. Additionally, the paper explores the statistical characteristics of the reduced datasets, the impact of training data size and distribution, and the performance of models across various fault and anomaly types. ISLib was validated using three datasets, including the Tennessee Eastman Process and two real-world oil and gas applications. The findings emphasize, for the first time, the significance of employing a well-designed instance selection approach to achieve successful outcomes in practical industrial applications, particularly in regression machine learning problems. By bridging literature gaps and offering a user-friendly tool, this work advances data-driven process monitoring in industrial environments. Full article

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

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22 pages, 4046 KiB

Open AccessArticle

Research on the Adsorption Characteristics and Adsorption Capacity Predictions of Supercritical Methane in Deep Coal Seams

by Xuan Chen, Chao Wu, Hua Zhang, Shiqi Liu, Xinggang Wang, Hongwei Li, Zongsen Yao, Kaisaer Wureyimu, Fansheng Huang and Zhongliang Cao

Processes 2025, 13(7), 2186; https://doi.org/10.3390/pr13072186 - 8 Jul 2025

Abstract

In the development of deep coalbed methane (CBM) resources, the adsorption behavior of supercritical methane is a key factor restricting reserve evaluation and development efficiency. This study integrates scanning electron microscopy (SEM), low-temperature CO₂ adsorption (LTCO₂A), mercury intrusion porosimetry (MIP), [...] Read more.

In the development of deep coalbed methane (CBM) resources, the adsorption behavior of supercritical methane is a key factor restricting reserve evaluation and development efficiency. This study integrates scanning electron microscopy (SEM), low-temperature CO₂ adsorption (LTCO₂A), mercury intrusion porosimetry (MIP), high-temperature and high-pressure CH₄ adsorption experiments (HTHP-CH₄A), and theoretical models to reveal the pore–fracture structure of deep coal seams and the adsorption characteristics of supercritical methane. Based on a predictive model for supercritical methane adsorption capacity, the adsorption capacity of deep methane was predicted. Results show that micro-pores are well-developed in deep coal rocks, but pore connectivity is generally poor, predominantly consisting of fine bottleneck pores and semi-closed pores, with a certain proportion of open pores. The fractal dimension (D_m) of micro-pore structures in deep coal samples ranges from 2.0447 to 2.2439, indicating high micro-pore surface roughness and a large specific surface area, which provide favorable sites for methane adsorption. Pores larger than 100 nm exhibit fractal values between 2.6459 and 2.8833, suggesting that the pore surfaces in deep coal seams approach a three-dimensional pore space with rough surfaces and complex pore structures. As temperature and pressure enter the supercritical region, the adsorption capacity shows an abnormal trend of “first increasing and then decreasing” with increasing pressure. The deep coal rock–supercritical methane adsorption system exhibits two scenarios in low-pressure and high-pressure regions, corresponding to self-adsorption driven by strong methane adsorption potential and external force adsorption or overpressure micro-pore adsorption, respectively. The supercritical adsorption prediction model considering temperature and methane adsorption phase density has extremely low deviation (1.11–1.25%) and high accuracy. The average dispersion between predicted and actual values ranges from 0.44 cm³/g to 0.48 cm³/g, with small error fluctuations and no significant deviation. This study provides theoretical support for the recoverability evaluation and efficient development of deep CBM resources. Full article

(This article belongs to the Section Energy Systems)

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16 pages, 1731 KiB

Open AccessArticle

Research on the Mechanism of Wellbore Strengthening Influence Based on Finite Element Model

by Erxin Ai, Qi Li, Zhikun Liu, Liupeng Wang and Chengyun Ma

Processes 2025, 13(7), 2185; https://doi.org/10.3390/pr13072185 - 8 Jul 2025

Abstract

Wellbore strengthening is a widely applied technique to mitigate wellbore leakage during drilling operations in complex formations characterized by narrow mud weight windows. This method enhances the wellbore’s pressure-bearing capacity by using lost circulation materials (LCMs) to bridge natural or induced fractures. In [...] Read more.

Wellbore strengthening is a widely applied technique to mitigate wellbore leakage during drilling operations in complex formations characterized by narrow mud weight windows. This method enhances the wellbore’s pressure-bearing capacity by using lost circulation materials (LCMs) to bridge natural or induced fractures. In recent years, advanced sealing technologies such as wellbore reinforcement have gradually been applied and developed, but their related influencing factors and mechanisms have not been deeply revealed. This article uses the Cohesive module of ABAQUS to establish a wellbore fracture sealing model. By establishing a porous elastic finite element model, the elastic mechanics theory of porous media is combined with finite element theory. Under the influence of factors such as anisotropy of geostress, reservoir elastic modulus, Poisson’s ratio, and fracturing fluid viscosity, the circumferential stress distribution of the wellbore after fracture sealing is simulated. The simulation results show that stress anisotropy has a significant impact on Mises stress. The greater the stress anisotropy, the more likely the wellbore sealing is to cause wellbore rupture or instability. Therefore, it is necessary to choose a suitable wellbore direction to avoid high stress concentration areas. The elastic modulus of the reservoir is an important parameter that affects wellbore stability and fracturing response, especially in high modulus reservoirs where the effect is more pronounced. Poisson’s ratio has a relatively minor impact. In fracturing and plugging design, the viscosity of fracturing fluid should be reasonably selected to balance the relationship between plugging efficiency and wellbore mechanical stability. In the actual drilling process, priority should be given to choosing the wellbore direction that avoids high stress concentration areas to reduce the risk of wellbore rupture or instability induced by plugging, specify targeted wellbore reinforcement strategies for high elastic modulus reservoirs; using models to predict fracture response characteristics can guide the use of sealing materials, achieve efficient bridging and stable sealing, and enhance the maximum pressure bearing capacity of the wellbore. By simulating the changes in circumferential stress distribution of the wellbore after fracture sealing, the mechanism of wellbore reinforcement was explored to provide guidance for mechanism analysis and on-site application. Full article

(This article belongs to the Section Energy Systems)

17 pages, 986 KiB

Open AccessArticle

Safety-Oriented Coordinated Operation Algorithms for Natural Gas Pipeline Networks and Gas-Fired Power Generation Facilities

by Xinyi Wang, Feng Wang, Qin Bie, Wenlong Jia, Yong Jiang, Ying Liu, Yuanyuan Tian, Yuxin Zheng and Jie Sun

Processes 2025, 13(7), 2184; https://doi.org/10.3390/pr13072184 (registering DOI) - 8 Jul 2025

Abstract

The natural gas pipeline network transmission system involved in the coordinated operation of pipeline networks and gas-fired power generation facilities is complex. It consists of multiple components, such as gas sources, users, valves, compressor stations, and pipelines. The addition of natural gas-fired power [...] Read more.

The natural gas pipeline network transmission system involved in the coordinated operation of pipeline networks and gas-fired power generation facilities is complex. It consists of multiple components, such as gas sources, users, valves, compressor stations, and pipelines. The addition of natural gas-fired power generation facilities overlaps with the high and low peak periods of civil gas, imposing dual peak-shaving pressures on pipeline networks and requiring more stringent operational control strategies for maintaining system stability. To address the aforementioned issues and improve the overall operating revenues of the system, we proposed the coordinated optimization model of gas-fired power generation facilities, pipeline networks, gas storage, and compressor stations. The optimization algorithm is written using the penalty function method of the Interior Point OPTimizer (IPOPT) solver. Meanwhile, the basic parameters of the system’s pipeline networks, users, gas storage, natural gas-fired power generation facilities, compressors, and electricity prices were input into the solver. The research results reveal that the algorithm ensures solution accuracy while accounting for computational efficiency and practical applicability. The algorithm can be used to effectively calculate the ideal coordinated operation solution, significantly improve the operating revenues of the system, and achieve safe, stable, coordinated, and efficient operation of the system. Full article

(This article belongs to the Section Energy Systems)

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15 pages, 3286 KiB

Open AccessArticle

Enhanced Sensitivity Microfluidic Microwave Sensor for Liquid Characterization

by Kim Ho Yeap, Kai Bor Tan, Foo Wei Lee, Han Kee Lee, Nuraidayani Effendy, Wei Chun Chin and Pek Lan Toh

Processes 2025, 13(7), 2183; https://doi.org/10.3390/pr13072183 - 8 Jul 2025

Abstract

This paper presents the development and analysis of a planar microfluidic microwave sensor featuring three circular complementary split-ring resonators (CSRRs) fabricated on an RO3035 substrate. The sensor demonstrates enhanced sensitivity in characterizing liquids contained in a fine glass capillary tube by leveraging a [...] Read more.

This paper presents the development and analysis of a planar microfluidic microwave sensor featuring three circular complementary split-ring resonators (CSRRs) fabricated on an RO3035 substrate. The sensor demonstrates enhanced sensitivity in characterizing liquids contained in a fine glass capillary tube by leveraging a novel configuration: a central 5-split-ring CSRR with a drilled hole to suspend the capillary, flanked by two 2-split-ring CSRRs to improve the band-stop filtering effect. The sensor’s performance is benchmarked against another CSRR-based microwave sensor with a similar configuration. High linearity is observed (R² > 0.99), confirming its capability for precise ethanol concentration prediction. Compared to the replicated square CSRR design from the literature, the proposed sensor achieves a 35.22% improvement in sensitivity, with a frequency shift sensitivity of 567.41 kHz/% ethanol concentration versus 419.62 kHz/% for the reference sensor. The enhanced sensitivity is attributed to several key design strategies: increasing the intrinsic capacitance by enlarging the effective area and radial slot width to amplify edge capacitive effects, adding more split rings to intensify the resonance dip, placing additional CSRRs to improve energy extraction at resonance, and adopting circular CSRRs for superior electric field confinement. Additionally, the proposed design operates at a lower resonant frequency (2.234 GHz), which not only reduces dielectric and radiation losses but also enables the use of more cost-effective and power-efficient RF components. This advantage makes the sensor highly suitable for integration into portable and standalone sensing platforms. Full article

(This article belongs to the Special Issue Development of Smart Materials for Chemical Sensing)

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23 pages, 758 KiB

Open AccessArticle

A Study on Ejector Structural and Operational Conditions Based on Numerical Simulation

by Gen Li, Yuan Liu, Dalin Wang, Xing Li, Daqian Liu, Zhongyu Hu, Bingyuan Hong, Xiaoping Li and Jing Gong

Processes 2025, 13(7), 2182; https://doi.org/10.3390/pr13072182 - 8 Jul 2025

Abstract

The Shenfu Gas Field faces challenges with uneven wellhead pressures, where low-pressure wells lose discharge capacity and high-pressure wells require throttling, leading to significant energy waste. Ejectors offer potential for energy recovery by utilizing high-pressure gas to boost low-pressure production. A computational fluid [...] Read more.

The Shenfu Gas Field faces challenges with uneven wellhead pressures, where low-pressure wells lose discharge capacity and high-pressure wells require throttling, leading to significant energy waste. Ejectors offer potential for energy recovery by utilizing high-pressure gas to boost low-pressure production. A computational fluid dynamics (CFD) model was developed using simulation software to simulate ejector performance. Parametric studies analyzed key structural parameters (mixing chamber length L_m, diameter D_m, nozzle spacing L_c, diffuser length L_d) and operational variables (compression ratio, working/entrained fluid pressures). Model validity was confirmed via grid independence tests and experimental comparisons (error < 10%). Network-level efficacy was verified using pipeline simulation software. Entrainment ratio (ε) and isentropic efficiency (η) exhibited non-linear relationships with structural parameters, with distinct optima depending on compression ratio. D_m had the strongest influence on ε. Higher compression ratios reduced ε, while increasing working fluid pressure or entrained fluid pressure improved ε. Optimal configurations were identified. Network simulations confirmed functional effectiveness, though efficiency diminished over production time. Ejector efficiency is highly sensitive to specific structural and operational parameters. Deployment in gas gathering networks is viable but most beneficial in early production stages. Full article

(This article belongs to the Section Energy Systems)

17 pages, 1428 KiB

Open AccessArticle

Three-Dimensional Modeling of Condensing and Superimposing Deltamethrin Droplets on Strawberry Leaf Surface from Dynamic Wetting Process Monitoring Data

by Jun Lu, Zichao Wen, Xueying Wang and Xumin Ding

Processes 2025, 13(7), 2181; https://doi.org/10.3390/pr13072181 - 8 Jul 2025

Abstract

It is imperative to investigate the behavior of the droplet superimposed condensation of deltamethrin reagent on strawberry leaf surface, as well as the dynamic variation rule of its contact angle. A microinjector was utilized to conduct the experiment of droplet superposition and condensation. [...] Read more.

It is imperative to investigate the behavior of the droplet superimposed condensation of deltamethrin reagent on strawberry leaf surface, as well as the dynamic variation rule of its contact angle. A microinjector was utilized to conduct the experiment of droplet superposition and condensation. The surface tension of deltamethrin droplets was measured by means of an optical contact angle meter, and the wetting parameters, such as contact angle, volume, and spreading diameter, were obtained by observing the leaf surfaces of various parts of strawberries during the dynamic process of superimposed condensation. A model was constructed by establishing the relationship between the contact angle and the coordinates of the observation point and time through the spatial fitting interpolation method. This model is a three-dimensional dynamic trend surface model of contact angle for droplet superposition and condensation. The findings indicated that the surface tension of the deltamethrin drop was 28.92 ± 0.2 mN·m⁻¹. The interval between the superposition of two droplets and the subsequent condensation of a new droplet was found to be within 0.5 s. The time taken for a new droplet to form was found to be between 0.0356 and 0.0476 s. The change in contact angle during the processes of superposition and coalescence can be broadly categorized into three distinct stages: namely, sharp oscillation, slight decrease, and gentle stabilization. The volume of the new droplet formed by the superposition and condensation was found to be 1.05 to 1.93 times that of a lying droplet. The maximum increase in the spreading diameter of the superimposed and condensed droplets was 40.29%. The three-dimensional dynamic trend surface model can reflect the overall spatial–temporal change trend of the contact angle in the process of superposition and coalescence. The model successfully passed the overall significance F-test and each coefficient of the statistical t-test, and demonstrated a satisfactory time interpolation effect. The experimental verification demonstrates that the predicted contact angle value of the model is consistent with the measured value. Full article

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

42 pages, 13901 KiB

Open AccessFeature PaperArticle

Hybrid Explainable AI for Machine Predictive Maintenance: From Symbolic Expressions to Meta-Ensembles

by Nikola Anđelić, Sandi Baressi Šegota and Vedran Mrzljak

Processes 2025, 13(7), 2180; https://doi.org/10.3390/pr13072180 (registering DOI) - 8 Jul 2025

Abstract

Machine predictive maintenance plays a critical role in reducing unplanned downtime, lowering maintenance costs, and improving operational reliability by enabling the early detection and classification of potential failures. Artificial intelligence (AI) enhances these capabilities through advanced algorithms that can analyze complex sensor data [...] Read more.

Machine predictive maintenance plays a critical role in reducing unplanned downtime, lowering maintenance costs, and improving operational reliability by enabling the early detection and classification of potential failures. Artificial intelligence (AI) enhances these capabilities through advanced algorithms that can analyze complex sensor data with high accuracy and adaptability. This study introduces an explainable AI framework for failure detection and classification using symbolic expressions (SEs) derived from a genetic programming symbolic classifier (GPSC). Due to the imbalanced nature and wide variable ranges in the original dataset, we applied scaling/normalization and oversampling techniques to generate multiple balanced dataset variations. Each variation was used to train the GPSC with five-fold cross-validation, and optimal hyperparameters were selected using a Random Hyperparameter Value Search (RHVS) method. However, as the initial Threshold-Based Voting Ensembles (TBVEs) built from SEs did not achieve a satisfactory performance for all classes, a meta-dataset was developed from the outputs of the obtained SEs. For each class, a meta-dataset was preprocessed, balanced, and used to train a Random Forest Classifier (RFC) with hyperparameter tuning via RandomizedSearchCV. For each class, a TBVE was then constructed from the saved RFC models. The resulting ensemble demonstrated a near-perfect performance for failure detection and classification in most classes (0, 1, 3, and 5), although Classes 2 and 4 achieved a lower performance, which could be attributed to an extremely low number of samples and a hard-to-detect type of failure. Overall, the proposed method presents a robust and explainable AI solution for predictive maintenance, combining symbolic learning with ensemble-based meta-modeling. Full article

(This article belongs to the Special Issue Applications of Artificial Intelligence Technologies in Energy, Manufacturing and Automatic Control Processes)

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22 pages, 8995 KiB

Open AccessArticle

Evaluation of the Adsorption Capacity of the BiOX (X = Cl, I) and BiOX-GO Nanomaterials (NMs) for Water Treatment

by Jorge H. Martinez-Montelongo, Martha L. Jiménez-González, Abner González-Pérez, M. Mortimer, F. J. Avelar-González, Jorge E. Macias-Díaz and Iliana E. Medina-Ramírez

Processes 2025, 13(7), 2179; https://doi.org/10.3390/pr13072179 - 8 Jul 2025

Abstract

Water pollution is a global problem that severely impacts human and environmental health, water recycling, and the economy. In Mexico, due to water scarcity, potable water contains significant amounts of heavy metals (i.e., arsenic (As)); thus, there is a need for efficient and [...] Read more.

Water pollution is a global problem that severely impacts human and environmental health, water recycling, and the economy. In Mexico, due to water scarcity, potable water contains significant amounts of heavy metals (i.e., arsenic (As)); thus, there is a need for efficient and sustainable water treatment strategies. Bismuth oxyhalides, BiOX (X = Cl, Br, I), exhibit three-dimensional (3D) porous structures suitable for efficient adsorption activity. In addition, bismuth is an abundant and biocompatible element appropriate for fabricating sustainable environmental remediation technologies, such as adsorptive BiOX nanomaterials (NMs). In this study, we examine the adsorption capacity of BiOX (X = Cl, I), BiOX-GO (GO: graphene oxide) and GO NMs to remove methylene blue (MB), methyl orange (MO) and arsenite (AsO₃³⁻) from aqueous solution. BiOCl-GO 10%, BiOI, BiOI-GO 1%, BiOI-GO 10% and GO have an enhanced adsorption capacity, removing MB (20 ppm) within one hour using a low dose of NMs (1 mg/mL). In addition, BiOX-GO NMs can be easily separated from the solution and regenerated upon visible light activation due to the photocatalytic activity of the materials. The efficiency of the NMs under study for MO removal decreases, with the GO material having the highest efficiency (96%), followed by BiOX-GO 10% (78%). BiOCl-GO 1% removes arsenic from aqueous solution at low doses and short treatment times; 5 mg As/g adsorbent takes five hours; however, at longer adsorption times (24 h), BiOI-GO 1% excels in its arsenic removal capacity. Perlite-supported BiOCl NMs exhibit a weak capacity for water treatment due to the poor mechanical strength of perlite and the amount of surface-exposed BiOCl material. For the photocatalytic removal of arsenic (oxidation–adsorption), BiOI-GO 1% excels in arsenic removal with efficiencies > 70%. Full article

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

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16 pages, 1636 KiB

Open AccessArticle

A Solid-State Nafion-Coated Screen-Printed Electrochemical Sensor for Ultrasensitive and Rapid Detection of Copper Ions in Water

by Yusra M. Obeidat

Processes 2025, 13(7), 2178; https://doi.org/10.3390/pr13072178 - 8 Jul 2025

Abstract

Copper is essential for various biological functions, but elevated levels in water can pose serious health risks. In this work, we introduce a novel electrochemical sensor designed for the highly sensitive and selective detection of copper ions. The sensor is based on a [...] Read more.

Copper is essential for various biological functions, but elevated levels in water can pose serious health risks. In this work, we introduce a novel electrochemical sensor designed for the highly sensitive and selective detection of copper ions. The sensor is based on a screen-printed platinum working electrode coated with a solid-state Nafion layer. Compared to previous platinum-based sensors, this design demonstrates enhanced sensitivity, a wide linear detection range (1 µM to 10 mM), and an exceptionally low limit of detection (1 nM). It also offers a rapid response time of 3–6 s, strong selectivity, and excellent stability. Interference from common metal ions such as Cr²⁺, Zn²⁺, Mn²⁺, Pb²⁺, and Fe²⁺ was minimal, with signal deviations remaining below 2%, and performance remained consistent across varying anion concentrations, showing less than 1% deviation. The use of Nafion as a solid-state electrolyte successfully overcomes challenges typically associated with traditional silver-based reference electrodes. These characteristics make the sensor a reliable and practical tool for the rapid, on-site monitoring of water quality. Full article

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

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16 pages, 2838 KiB

Open AccessFeature PaperArticle

Transcriptomic Response of Azospirillum brasilense Co-Cultured with Green Microalgae Chlorella sp. and Scenedesmus sp. During CO₂ Biogas Fixation

by Carolina Garciglia-Mercado, Oskar A. Palacios, Claudia A. Contreras-Godínez, Jony Ramiro Torres-Velázquez and Francisco J. Choix

Processes 2025, 13(7), 2177; https://doi.org/10.3390/pr13072177 - 8 Jul 2025

Abstract

Microalgal–bacterial consortia are the environmentally sustainable biotechnological strategy to enhance the potential of microalgae. Understanding the regulatory mechanisms that enable bacteria to adapt to culture conditions of each bioprocess is crucial to ensure a successful synergic interaction. Thus, the present study evaluated the [...] Read more.

Microalgal–bacterial consortia are the environmentally sustainable biotechnological strategy to enhance the potential of microalgae. Understanding the regulatory mechanisms that enable bacteria to adapt to culture conditions of each bioprocess is crucial to ensure a successful synergic interaction. Thus, the present study evaluated the transcriptomic response of microalgal growth-promoting bacteria (MGPB) A. brasilense separately co-cultured with both green microalgae Scenedesmus sp. and Chlorella sorokiniana during CO₂ fixation from biogas through a microarray-based approach. The transcriptome profiling revealed a total of 416 differentially expressed genes (DEGs) in A. brasilense: 228 (140 upregulated and 88 downregulated) interacting with Scenedesmus sp. and 188 (40 upregulated and 148 downregulated) associated with C. sorokiniana. These results support the modulation of signal molecules: indole-3-acetic acid (IAA), riboflavin, and biotin, during co-cultivation with both microalgae. The findings suggest that the metabolic A. brasilense adaptation was mainly favored during the mutualistic interaction with Scenedesmus sp. Finally, a valuable contribution is provided to the biotechnological potential of the microalga–Azospirillum consortium as an environmentally sustainable strategy to improve the bio-refinery capacity of these microalgae and biogas upgrading by valorizing CO₂ of these gaseous effluent. Full article

(This article belongs to the Special Issue Development and Application of Microalgae and Microalgae–Bacteria Biotechnologies)

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19 pages, 8170 KiB

Open AccessArticle

Study on Solid and Pore Structures of Borehole Municipal Solid Waste Samples by X-Ray CT Scanning

by Xiaobing Xu, Zhiyu Zhang, Jie Hu, Han Ke, Lei Lang and Changjie Chen

Processes 2025, 13(7), 2176; https://doi.org/10.3390/pr13072176 - 8 Jul 2025

Abstract

The microscale solid and pore structures of waste is crucial for the bio-hydro-mechanical behaviors of landfilled municipal solid waste (MSW). The quantitative analysis of the structural characteristics of MSW is still limited. In this study, borehole MSW samples at different depths (i.e., 0 [...] Read more.

The microscale solid and pore structures of waste is crucial for the bio-hydro-mechanical behaviors of landfilled municipal solid waste (MSW). The quantitative analysis of the structural characteristics of MSW is still limited. In this study, borehole MSW samples at different depths (i.e., 0 m, 2.5 m, 5 m, 7.5 m, 10 m, and 12.5 m) were drilled from a landfill. The waste composition and basic physical properties of these samples were tested in laboratory. Solid and pore structural characteristics were studied through computed tomography (CT) analysis. The results indicate that the ratio of cellulose content to lignin content (i.e., C/L) decreased from 0.85 to 0.47 with increasing depth. For solid particles, two-dimensional (2D) particles constituted the greatest fraction (60.22~72.16%), which showed a decrease with increasing depth. The deeper sample tended to have more fine particles. For pores, the void ratio decreased from 1.68 to 1.10 with increasing depth, with more small pore channels. Meanwhile, the average pore diameter coefficient (λ) decreased from 0.209 to 0.190, the pore angle (θ_e) decreased from 29.6° to 17.8°, the tortuosity (τ) increased from 1.129 to 1.184, and the connectivity (c_e) decreased from 12.0 to 4.1. These quantitative findings can further the understanding of fluid flow behaviors in landfilled waste. Full article

(This article belongs to the Special Issue Emerging Technologies in Solid Waste Recycling and Reuse)

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21 pages, 3369 KiB

Open AccessArticle

Thermal Runaway Critical Threshold and Gas Release Safety Boundary of 18,650 Lithium-Ion Battery in State of Charge

by Jingyu Zhao, Kexin Xing, Xinrong Jiang, Chi-Min Shu and Xiangrong Sun

Processes 2025, 13(7), 2175; https://doi.org/10.3390/pr13072175 - 8 Jul 2025

Abstract

In this study, we systematically investigated the characteristic parameter evolution laws of thermal runaway with respect to 18,650 lithium-ion batteries (LIBs) under thermal abuse conditions at five state-of-charge (SOC) levels: 0%, 25%, 50%, 75%, and 100%. In our experiments, we combined infrared thermography, [...] Read more.

In this study, we systematically investigated the characteristic parameter evolution laws of thermal runaway with respect to 18,650 lithium-ion batteries (LIBs) under thermal abuse conditions at five state-of-charge (SOC) levels: 0%, 25%, 50%, 75%, and 100%. In our experiments, we combined infrared thermography, mass loss analysis, temperature monitoring, and gas composition detection to reveal the mechanisms by which SOC affects the trigger time, critical temperature, maximum temperature, mass loss, and gas release characteristics of thermal runaway. The results showed that as the SOC increases, the critical and maximum temperatures of thermal runaway increase notably. At a 100% SOC, the highest temperature on the positive electrode side reached 1082.1 °C, and the mass loss increased from 6.90 g at 0% SOC to 25.75 g at 100% SOC, demonstrating a salient positive correlation. Gas analysis indicated that under high-SOC conditions (75% and 100%), the proportion of flammable gases such as CO and CH₄ produced during thermal runaway significantly increases, with the CO/CO₂ ratio exceeding 1, indicating intensified incomplete combustion and a significant increase in fire risk. In addition, flammability limit analysis revealed that the lower explosive limit for gases is lower (17–21%) at a low SOC (0%) and a high SOC (100%), indicating greater explosion risks. We also found that the composition of gases released during thermal runaway varies substantially at different SOC levels, with CO, CO₂, and CH₄ accounting for over 90% of the total gas volume, while toxic gases, such as HF, although present in smaller proportions, pose noteworthy hazards. Unlike prior studies that relied on post hoc analysis, this work integrates real-time multi-parameter monitoring (temperature, gas composition, and mass loss) and quantitative explosion risk modeling (flammability limits via the L-C formula). This approach reveals the unique dynamic SOC-dependent mechanisms of thermal runaway initiation and gas hazards. This study provides theoretical support for the source tracing of thermal runaway fires and the development of preventive LIB safety technology and emphasizes the critical influence of the charge state on the thermal safety of batteries. Full article

(This article belongs to the Special Issue Machine Learning Optimization of Chemical Processes)

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16 pages, 1688 KiB

Open AccessArticle

Characterization of Antioxidant and Antimicrobial Activity, Phenolic Compound Profile, and VOCs of Agresto from Different Winegrape Varieties

by Luisa Pozzo, Andrea Raffaelli, Teresa Grande, Stefania Frassinetti, Vincenzo Longo, Francesca Venturi, Chiara Sanmartin, Giuseppe Ferroni, Guido Flamini and Annita Toffanin

Processes 2025, 13(7), 2174; https://doi.org/10.3390/pr13072174 - 8 Jul 2025

Abstract

Agresto is the unfermented juice traditionally obtained from boiled unripe grapes, typically using fruit that would otherwise be discarded, and enriched with spices, herbs, and fruit. In this study, the phenolic profile, antioxidant and antibacterial activity, and volatile organic compounds (VOCs) of Agresto [...] Read more.

Agresto is the unfermented juice traditionally obtained from boiled unripe grapes, typically using fruit that would otherwise be discarded, and enriched with spices, herbs, and fruit. In this study, the phenolic profile, antioxidant and antibacterial activity, and volatile organic compounds (VOCs) of Agresto produced from two grape varieties (Sangiovese, and Vermentino) harvested in Mount Amiata (Tuscany) were evaluated. Agresto from Vermentino showed a higher total phenolic content (TPC), 1.31 mg GAE/mL, as well as a greater total flavonoid and flavonol content and FRAP activity compared to Agresto from Sangiovese. The highest ORAC value was observed in Agresto from Vermentino, 41.01 mg TE/mL, compared to that from Sangiovese. TPC, flavonols, apocarotenes, sulfur derivatives, and non-terpene derivatives were positively correlated with antimicrobial activity against E. coli, FRAP, and ORAC. Overall, our results showed that grape variety significantly influences the chemical composition of Agresto, particularly in terms of both VOCs and phenolic compounds. The observed variations in phenolic composition also affected the antioxidant and antimicrobial activity of Agresto. These experimental findings clearly suggest the utmost importance of identifying the optimal chemical profile of “unripe grapes” used as raw material for Agresto production, considering both variety and the specific ripening degree achievable through vine green harvesting. Full article

(This article belongs to the Special Issue Phytochemicals: Extraction, Optimization, Identification, Biological Activities, and Applications in the Food, Nutraceutical, and Pharmaceutical Industries (2nd Edition))

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11 pages, 2217 KiB

Open AccessFeature PaperArticle

One-Pot Improvement of Stretchable PEDOT/PSS Alginate Conductivity for Soft Sensing Biomedical Processes

by Somayeh Zanganeh, Alberto Ranier Escobar, Hung Cao and Peter Tseng

Processes 2025, 13(7), 2173; https://doi.org/10.3390/pr13072173 - 8 Jul 2025

Abstract

Hydrogels have immense potential in soft electronics due to their similarity to biological tissues. However, for applications in fields like tissue engineering and wearable electronics, hydrogels must obtain electrical conductivity, stretchability, and implantability. This article explores recent advancements in the development of electrically [...] Read more.

Hydrogels have immense potential in soft electronics due to their similarity to biological tissues. However, for applications in fields like tissue engineering and wearable electronics, hydrogels must obtain electrical conductivity, stretchability, and implantability. This article explores recent advancements in the development of electrically conductive hydrogel composites with high conductivity, low Young’s modulus, and remarkable stretchability. By incorporating conductive particles into hydrogels, such as poly(3,4-ethylenedioxythiophene)/poly (styrenesulfonate) (PEDOT/PSS) researchers have enhanced their conductivity. This study presents a one-pot synthesis method for creating electrically conductive hydrogel composites by combining PEDOT/PSS with alginate. The hydrogel reveals changes in chemical composition upon treatment with dimethyl sulfoxide (DMSO). Additionally, surface morphology analysis via Field Emission Scanning Electron Microscopy (FESEM) and Atomic Force Microscopy (AFM) demonstrate the impact of DMSO treatment on PEDOT/PSS/alginate films. Furthermore, electrical conductivity measurements highlighted the effectiveness of the conductive hydrogels in Electromyography (EMG) and human motion detection. This study offers insights into the fabrication and characterization of stretchable, conductive hydrogels, advancing their potential for various soft sensing biomedical applications. The optimized PDOT/PSS/alginate composite under dry condition shows a conductivity of 0.098 S/cm and can be stretched without significant loss in conductivity or mechanical stability. This one-pot method provides a simple and effective way to improve the properties of conductive hydrogel-based sensors. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Industrial Process Modelling and Optimization)

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25 pages, 8033 KiB

Open AccessArticle

Research on the Damage Evolution Law of Branch Wellbore Based on Damage Mechanics

by Qizhong Tian, Chao Han, Yang Meng, Rongdong Dai, Haocai Huang, Jiaao Chen and Chuanliang Yan

Processes 2025, 13(7), 2172; https://doi.org/10.3390/pr13072172 - 8 Jul 2025

Abstract

Multilateral wells can effectively develop complex reservoirs at a lower cost, which, in turn, enhances the overall efficiency of oilfield exploitation. However, drilling branch wells from the main wellbore can disrupt the surrounding formation stresses, leading to secondary stress concentration at the junctions, [...] Read more.

Multilateral wells can effectively develop complex reservoirs at a lower cost, which, in turn, enhances the overall efficiency of oilfield exploitation. However, drilling branch wells from the main wellbore can disrupt the surrounding formation stresses, leading to secondary stress concentration at the junctions, which, in turn, causes wellbore instability. This study established a coupled analysis model for wellbore stability in branch wells by integrating seepage, stress, and damage. The model explained the instability mechanisms of branch wellbores under multi-physics coupling conditions. The results showed that during drilling, the thin, interwall section of branch wells had weak resistance to external loads, with significant stress concentration and a maximum damage factor of 0.267, making it prone to instability. As drilling time progressed, fractures in the surrounding rock mass of the wellbore continuously formed, propagated, and interconnected, causing a sharp increase in the permeability of the damaged area. The seepage direction of drilling fluid in the wellbore tended towards the severely damaged interwall section, leading to a rapid increase in pore pressure there. With increasing distance from the interwall tip, the resistance to external loads strengthened, and the formation damage factor, permeability, pore pressure, and equivalent plastic strain all gradually decreased. When the drilling fluid density increased from 1.0 g/cm³ to 1.5 g/cm³, the maximum equivalent plastic strain around the wellbore decreased from 0.041 to 0.014, a reduction of 65.8%, indicating that appropriately increasing the drilling fluid density can effectively reduce the risk of wellbore instability. Full article

(This article belongs to the Special Issue Geophysical Methods and Processes for Unconventional Reservoir Exploration and Characterization in Petroleum System)

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12 pages, 3179 KiB

Open AccessArticle

Pilot Test of Soil Washing for Arsenic-Contaminated H₂SO₄ Plant Soil Using Discarded H₂SO₄

by Di Wang, Hongbin Xu, Ying Cao, Wei Zhang, Aihua Gao, Yingxu Liu, Haihua Bao, Guangrui Dong, Di Mao and Yunfei Tan

Processes 2025, 13(7), 2171; https://doi.org/10.3390/pr13072171 - 8 Jul 2025

Abstract

This study investigates an innovative soil washing process designed to remediate arsenic (As) contamination in sulfuric acid (H₂SO₄) plant soil by using discarded H₂SO₄ solution in situ. The pilot-scale process comprises five key steps: screening and [...] Read more.

This study investigates an innovative soil washing process designed to remediate arsenic (As) contamination in sulfuric acid (H₂SO₄) plant soil by using discarded H₂SO₄ solution in situ. The pilot-scale process comprises five key steps: screening and rinsing of oversized sand, washing the soil with H₂SO₄, phase separation, recycling the washing solution, and water recovery. This research explored the optimal washing parameters for the process and further researched the reuse of the H₂SO₄ solution across multiple batches. The pH of the washing solution, critical at a threshold of 6.5, was identified as a key factor for effective recycling. Approximately 75% of the H₂SO₄ solution was successfully recycled. In terms of economic analysis, the total operational cost of the soil washing process was significantly lower than in previous studies. Overall, these findings demonstrate the feasibility of using discarded H₂SO₄ as a washing agent for As-contaminated soil. The integration of automated pH-based monitoring technology streamlines the washing process, providing a cost-effective and effective As removal remediation strategy, making it a viable option for large-scale applications in soil remediation. Full article

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

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17 pages, 3329 KiB

Open AccessArticle

Optimization of Intermittent Production Well Strategy in Jingbian Gas Field

by Zhixing Cai, Qinyang Zhao, Hu Chen, Qin Yang, Yongsheng An and Jinpeng Yue

Processes 2025, 13(7), 2170; https://doi.org/10.3390/pr13072170 - 7 Jul 2025

Abstract

As a crucial natural gas production base in China, the Jingbian Gas Field has gradually entered its mid-to-late development stage with prolonged exploitation. The increasing number of intermittent production wells and reliance on empirical settings for single-well opening/shut-in durations have resulted in low [...] Read more.

As a crucial natural gas production base in China, the Jingbian Gas Field has gradually entered its mid-to-late development stage with prolonged exploitation. The increasing number of intermittent production wells and reliance on empirical settings for single-well opening/shut-in durations have resulted in low production efficiency and high energy consumption. Concurrently, concentrated intermittent production across multiple wells frequently triggers severe pressure fluctuations in the pipeline network, jeopardizing overall field production stability. Achieving cost reduction and improved efficiency through single-well intermittent production optimization and staggered production scheduling for multi-well systems has become a critical challenge in this late-development phase. The absence of flow meters in most Jingbian wells introduces substantial difficulties in adjusting both single-well operating durations and multi-well staggered production schedules. This study first introduces a novel coefficient D inspired by the load factor concept, proposing a methodology to adjust opening/shut-in durations using only tubing pressure, casing pressure, and pipeline delivery pressure. Second, a dynamic workflow is developed for staggered multi-well production scheduling to mitigate pressure surges caused by simultaneous well restarts. Field applications demonstrate that optimized single-well operations achieved steady efficiency improvements, with the average tubing–casing pressure differential in severe liquid-loading wells decreasing by 80% post-adjustment. The staggered multi-well scheduling ensures that no two or more wells (n > 1) restart simultaneously, significantly enhancing the stability of the gas transmission network. These findings provide theoretical and technical guidance for the efficient development of similar low-pressure gas fields. Full article

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

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