ChemEngineering

17 pages, 988 KiB

Open AccessTechnical Note

Growth of a Single Bubble Due to Super-Saturation: Comparison of Correlation-Based Modelling with CFD Simulation

by Johannes Manthey, Wei Ding, Hossein Mehdipour, Montadhar Guesmi, Simon Unz, Uwe Hampel and Michael Beckmann

ChemEngineering 2025, 9(3), 63; https://doi.org/10.3390/chemengineering9030063 - 17 Jun 2025

Abstract

This paper investigates and assesses the potential applicability of global mass transfer coefficients derived from large-scale experiments to the bubble growth of a single bubble in a super-saturated flow

(σ = 9)

. Therefore, it presents, for a specific flow velocity [...] Read more.

This paper investigates and assesses the potential applicability of global mass transfer coefficients derived from large-scale experiments to the bubble growth of a single bubble in a super-saturated flow

(σ = 9)

. Therefore, it presents, for a specific flow velocity (

u = 1 \frac{m}{s}, R e = 10,678)

, a comparison between correlation-based modelling and 3D Large Eddy Simulation–Volume of Fluid (LES-VOF) Computational Fluid Dynamics (CFD) simulations (minimum cell size of 10 µm, Δt = 10 µs). After the verification of the CFD with pool nucleation bubbles, two cases are regarded: (1) the bubble flowing in the bulk and (2) a bubble on a wall with a crossflow. The correlation-based modelling results in a nearly linear relationship between bubble radius and time; meanwhile, theoretically, the self-similarity rule offers

r ~ {B t}^{0.5}

. The Avdeev correlation gives the best agreement with the CFD simulation for a bubble in the flow bulk (case 1), while the laminar approach for calculation of the exposure time of the penetration theory shows good agreement with the CFD simulation for the bubble growth at the wall (case 2). This preliminary study provides the first quantitative validation of global mass transfer coefficient correlations at the single-bubble scale, suggesting that computationally intensive CFD simulations may be omitted for rapid estimations. Future work will extend the analysis to a wider range of flow velocities and bubble diameters to further validate these findings. Full article

24 pages, 7924 KiB

Open AccessArticle

Mechanisms and Optimization of Foam Flooding in Heterogeneous Thick Oil Reservoirs: Insights from Large-Scale 2D Sandpack Experiments

by Qingchun Meng, Hongmei Wang, Weiyou Yao, Yuyang Han, Xianqiu Chao, Tairan Liang, Yongxian Fang, Wenzhao Sun and Huabin Li

ChemEngineering 2025, 9(3), 62; https://doi.org/10.3390/chemengineering9030062 - 4 Jun 2025

Viewed by 369

Abstract

To address the challenges of low displacement efficiency and gas channeling in the Lukqin thick oil reservoir, characterized by high viscosity (286 mPa·s) and strong heterogeneity (permeability contrast 5–10), this study systematically investigated water flooding and foam flooding mechanisms using a large-scale 2D [...] Read more.

To address the challenges of low displacement efficiency and gas channeling in the Lukqin thick oil reservoir, characterized by high viscosity (286 mPa·s) and strong heterogeneity (permeability contrast 5–10), this study systematically investigated water flooding and foam flooding mechanisms using a large-scale 2D sandpack model (5 m × 1 m × 0.04 m). Experimental results indicate that water flooding achieves only 30% oil recovery due to a mobility ratio imbalance (M = 128) and preferential channeling. In contrast, foam flooding enhances recovery by 15–20% (final recovery: 45%) through synergistic mechanisms of dynamic high-permeability channel plugging and mobility ratio optimization. By innovatively integrating electrical resistivity tomography with HSV color mapping, this work achieves the first visualization of foam migration pathways in meter-scale heterogeneous reservoirs at a spatial resolution of ≤0.5 cm, reducing monitoring costs by approximately 30% compared to conventional CT techniques. Key controlling factors for gas channeling (injection rate, foam quality, permeability contrast) are identified, and a nonlinear predictive model for plugging strength ((S = 0.70C^0.6 k_r^−0.28) (R² = 0.91)) is established. A composite optimization strategy—combining high-concentration slugs (0.7% AOS), salt-resistant polymer-enhanced foaming, and multi-round profile control—achieves a 67% reduction in gas channeling. This study elucidates the dynamic plugging mechanisms of foam flooding in heterogeneous thick oil reservoirs through large-scale physical simulations and data fusion, offering direct technical guidance for optimizing foam flooding operations in the Lukqin Oilfield and analogous reservoirs. Full article

► Show Figures

Figure 1

19 pages, 1656 KiB

Open AccessArticle

Optimizing Biomethane Production from Industrial Pig Slurry and Wine Vinasse: A Mathematical Approach

by Belén Cañadas, Juana Fernández-Rodríguez, Rosario Solera and Montserrat Pérez

ChemEngineering 2025, 9(3), 61; https://doi.org/10.3390/chemengineering9030061 - 3 Jun 2025

Viewed by 266

Abstract

Pig slurry (PS) and wine vinasse (WV) pose environmental risks if not properly managed. Their composition makes them suitable for anaerobic co-digestion (AcoD), enhancing biomethane production and improving organic matter degradation efficiency. This research applies an innovative Design of Experiments (DoE) approach—specifically the [...] Read more.

Pig slurry (PS) and wine vinasse (WV) pose environmental risks if not properly managed. Their composition makes them suitable for anaerobic co-digestion (AcoD), enhancing biomethane production and improving organic matter degradation efficiency. This research applies an innovative Design of Experiments (DoE) approach—specifically the Box–Behnken design (BBD)—to systematically optimize the AcoD process, surpassing traditional single-factor methods by efficiently evaluating the interactions. Variables such as temperature (35 °C, 52.5 °C, 70 °C), substrate ratio (25PS:75WV, 50PS:50WV, 75PS:25WV) and pH (7, 7.5, 8) were tested using a Box–Behnken design which studied the correlations between the experimental data and the model. In fact, the results showed that temperature, ratio, and their interaction significantly influenced biomethane production, being the pH the factor with the least influence on the response. Optimal conditions—pH of 8, temperature of 35 °C and a 50:50 substrate ratio—achieved a biomethane yield of 487.94 CH₄/gVS (Volatile Solids). These results demonstrate the effectiveness of the DoE methodology in maximizing biomethane production and represent a significant advancement in valorizing wastes from pig farms and wineries, promoting a circular and sustainable economy. Full article

► Show Figures

Figure 1

16 pages, 706 KiB

Open AccessArticle

The Re-Modeling of a Polymeric Drug Delivery System Using Smart Response Surface Designs: A Sustainable Approach for the Consumption of Fewer Resources

by Magdy M. Aly, Shaimaa S. Ibrahim and Rania M. Hathout

ChemEngineering 2025, 9(3), 60; https://doi.org/10.3390/chemengineering9030060 - 1 Jun 2025

Viewed by 271

Abstract

Introduction: The use of response surface designs for drug formulation is highly warranted nowadays. Such smart designs reduce the number of required experiments compared to full-factorial designs, while providing highly accurate and reliable results. Aim: This study compares the effectiveness of [...] Read more.

Introduction: The use of response surface designs for drug formulation is highly warranted nowadays. Such smart designs reduce the number of required experiments compared to full-factorial designs, while providing highly accurate and reliable results. Aim: This study compares the effectiveness of two of the most commonly used response surface designs—Central Composite Design (CCD) and D-optimal Design (DOD)—in modeling a polymer-based drug delivery system. The performance of the two designs was further evaluated under a challenging scenario where a central point was deliberately converted into an outlier. Methods: Both methods were assessed using ANOVA, R-squared values, and adequate precision, and were assessed through an experimental validation point. Results: Both models demonstrated statistical significance (p-value < 0.05), confirming their ability to describe the relationships between formulation variables and critical quality attributes (CQAs). CCD achieved higher R-squared and predicted R-squared values compared to DOD (0.9977 and 0.9846 vs. 0.8792 and 0.7858, respectively), rendering it as the superior approach in terms of modeling complex variables’ interactions. However, DOD proved to be more predictive as it scored a lower percentage relative error. Conclusion: The demonstrated resilience of both models, despite the introduction of an outlier, further validates their utility in real-world applications, instead of the exhaustive full-factorial design. Full article

► Show Figures

Figure 1

15 pages, 2555 KiB

Open AccessArticle

Solving a Challenge in the Tequila Industry: A New Continuous Rectification Process for Reducing Higher Alcohols and Obtaining Products Within the Official Tequila Standard

by Héctor Flores-Martínez, Isaac Guadalupe Tejeda-Arandas, Mirna Estarrón-Espinosa and José Daniel Padilla-de la Rosa

ChemEngineering 2025, 9(3), 59; https://doi.org/10.3390/chemengineering9030059 - 1 Jun 2025

Viewed by 398

Abstract

This work is the first to study the effect of residence time on the volatile composition of distilled fractions of ordinario using a horizontal continuous distiller of our own manufacture. The ordinario used in this research had a high amount of higher alcohols, [...] Read more.

This work is the first to study the effect of residence time on the volatile composition of distilled fractions of ordinario using a horizontal continuous distiller of our own manufacture. The ordinario used in this research had a high amount of higher alcohols, so its adequate distillation is complicated. The fractions rectified by continuous distillation were compared with those obtained by batch distillation. Five distilled fractions were collected, and their combined volume was subjected to gas chromatography (GC) analysis to determine the principal volatile compounds (furfural, aldehyde, higher alcohols, methanol, and ester contents). A variance analysis of each group of volatile compounds was conducted to evaluate the effect of residence time (2 and 4 h) in continuous distillation compared to batch distillation (4 h). Continuous rectification allowed for obtaining a distillate within the permissible limits specified by the Official Mexican Standard (NOM-006-SCFI-2012). For the continuous 2 h, continuous 4 h, and batch 4 h processes, the higher alcohols, esters, and aldehydes showed a decreasing pattern, while methanol and furfural showed an increasing pattern in relation to the fraction number. An analysis of variance showed no statistically significant differences in terms of the regulated volatile composition (higher alcohols, esters, methanol, and furfural) according to process type (continuous 2 h, continuous 4 h, and batch 4 h), except for aldehydes, which presented differences. This new continuous rectification process increases productivity while reducing the processing time by 50%, keeping the composition and volume of the heart fraction. Full article

► Show Figures

Graphical abstract

23 pages, 1013 KiB

Open AccessSystematic Review

Valorization of Lignocellulosic Biomass to Biofuel: A Systematic Review

by Mbuyu Germain Ntunka, Siphesihle Mangena Khumalo, Thobeka Pearl Makhathini, Sphesihle Mtsweni, Marc Mulamba Tshibangu and Joseph Kapuku Bwapwa

ChemEngineering 2025, 9(3), 58; https://doi.org/10.3390/chemengineering9030058 - 29 May 2025

Viewed by 351

Abstract

Lignocellulosic biomass, derived from plant materials, represents a renewable alternative to fossil fuels and plays a crucial role in advancing environmental sustainability. This systematic review investigates recent developments in the conversion of lignocellulosic biomass into biofuels, with a focus on pre-treatment technologies that [...] Read more.

Lignocellulosic biomass, derived from plant materials, represents a renewable alternative to fossil fuels and plays a crucial role in advancing environmental sustainability. This systematic review investigates recent developments in the conversion of lignocellulosic biomass into biofuels, with a focus on pre-treatment technologies that enhance enzymatic hydrolysis, a critical step in efficient biofuel production. This review addresses two primary questions: (1) What are the most effective pre-treatment methods for enhancing enzymatic hydrolysis in lignocellulosic biomass conversion? (2) How do these pre-treatment methods compare in terms of efficiency, environmental impact, and economic feasibility? Consequently, studies were selected based on inclusion criteria that focus on research investigating these pre-treatment methods and their comparative performance. A structured search of original studies was applied across databases such as Crossref, Google Scholar, Scopus, PubMed, and Semantic Scholar, resulting in the inclusion of 17 peer-reviewed articles published between 2019 and 2024. The findings highlight effective pre-treatment methods that significantly improve enzymatic accessibility and bioethanol yields. However, ongoing challenges such as feedstock variability, process efficiency, and cost-effectiveness remain. These results highlight the need for further research and development to optimize conversion technologies and identify new areas for exploration. Full article

► Show Figures

Graphical abstract

14 pages, 2322 KiB

Open AccessArticle

Effect of Rotation Speed and Powder Bed Volume on Powder Flowability Measured by a Powder Rheometer: Evaluation of the Humidity Effect on Lactose Powder Flowability

by Takamasa Mori, Kanaho Sakurada and Kenta Kitamura

ChemEngineering 2025, 9(3), 57; https://doi.org/10.3390/chemengineering9030057 - 29 May 2025

Viewed by 261

Abstract

Relative humidity during storage is known to affect powder flowability, although its effect on powder flowability remains unclear. Various techniques have been used to evaluate powder flowability, including measurement of the rotational torque of the powder bed, which is a novel method. However, [...] Read more.

Relative humidity during storage is known to affect powder flowability, although its effect on powder flowability remains unclear. Various techniques have been used to evaluate powder flowability, including measurement of the rotational torque of the powder bed, which is a novel method. However, studies investigating the effect of relative humidity on powder flowability using rotational torque measurements are limited. Therefore, this study aimed to examine the influence of relative humidity during storage on the flowability of lactose powder through rotational torque measurement of the powder bed using an Anton Paar powder rheometer. Rotation speed had a minimal effect, except when the powder was stored at a high relative humidity of 99%. The effect of relative humidity was more pronounced at a smaller powder volume (30 mL) than that at the other volumes tested. Of the techniques employed, including the angle of repose and bulk density measurements, the rotational torque measurement of the powder rheometer exhibited the highest sensitivity to variations in relative humidity. It was also found that the measured rotation torque hardly changed when the rotation speed was below a critical value, indicating that the optimal rotation speed exists to measure the representative rotation torque of each powder. Full article

► Show Figures

Figure 1

20 pages, 1490 KiB

Open AccessReview

Liposome-Based Drug Delivery Systems: From Laboratory Research to Industrial Production—Instruments and Challenges

by Suman Basak and Tushar Kanti Das

ChemEngineering 2025, 9(3), 56; https://doi.org/10.3390/chemengineering9030056 - 27 May 2025

Viewed by 456

Abstract

Liposome-based drug delivery systems have revolutionized modern pharmaceutics, offering unparalleled versatility and precision in therapeutic delivery. These lipid vesicles, capable of encapsulating hydrophilic, hydrophobic, and amphiphilic drugs, have demonstrated significant potential in addressing pharmacokinetic challenges such as poor solubility, systemic toxicity, and rapid [...] Read more.

Liposome-based drug delivery systems have revolutionized modern pharmaceutics, offering unparalleled versatility and precision in therapeutic delivery. These lipid vesicles, capable of encapsulating hydrophilic, hydrophobic, and amphiphilic drugs, have demonstrated significant potential in addressing pharmacokinetic challenges such as poor solubility, systemic toxicity, and rapid clearance. This review provides a comprehensive exploration of the evolution of liposomes from laboratory models to clinically approved therapeutics, highlighting their structural adaptability, functional tunability, and transformative impact on modern medicine. We discuss pivotal laboratory-scale preparation techniques, including thin-film hydration, ethanol injection, and reverse-phase evaporation, along with their inherent advantages and limitations. The challenges of transitioning to industrial-scale production are examined, with emphasis on achieving batch-to-batch consistency, scalability, regulatory compliance, and cost-effectiveness. Innovative strategies, such as the incorporation of microfluidic systems and advanced process optimization, are explored to address these hurdles. The clinical success of Food and Drug Administration (FDA)-approved liposomal formulations such as Doxil^® and AmBisome^® underscores their efficacy in treating conditions ranging from cancer to fungal infections. Furthermore, this review delves into emerging trends, including stimuli-responsive and hybrid liposomes, as well as their integration with nanotechnology for enhanced therapeutic precision. As liposomes continue to expand their role in gene therapy, theranostics, and personalized medicine, this review highlights their potential to redefine pharmaceutical applications. Despite existing challenges, ongoing advancements in formulation techniques and scalability underscore the bright future of liposome-based therapeutics in addressing unmet medical needs. Full article

(This article belongs to the Special Issue New Trends in (Bio)chemical Engineering: Biobased Pharmaceutical Processes)

► Show Figures

Figure 1

20 pages, 1922 KiB

Open AccessArticle

Electrification of Compressor in Steam Cracker Plant: A Path to Reduced Emissions and Optimized Energy Integration

by Joana Cordeiro Torcato, Rodrigo Silva and Mário Eusébio

ChemEngineering 2025, 9(3), 55; https://doi.org/10.3390/chemengineering9030055 - 27 May 2025

Viewed by 382

Abstract

Electrification is a highly effective decarbonization and environmental incentive strategy for the chemical industry. Nevertheless, it may lead to downstream challenges in the process. This study analyzes the consequences of electrifying compressors within the steam cracker (SC) condensate system, focusing on the reduction [...] Read more.

Electrification is a highly effective decarbonization and environmental incentive strategy for the chemical industry. Nevertheless, it may lead to downstream challenges in the process. This study analyzes the consequences of electrifying compressors within the steam cracker (SC) condensate system, focusing on the reduction in greenhouse gas (GHG) emissions and energy consumption without compromising the process’s energy efficiency. The aim is to study the impact that the reduction in steam expanded by turbines has on boiler feedwater (BFW) temperature and, subsequently, the behavior it triggers in fuel gas (FG) consumption and carbon dioxide (CO₂) emissions in furnaces. It was concluded that condensate imports from the Energies and Utilities Plant (E&U) would increase by a factor of four, with approximately 60% of the imported condensate being cold condensate. The study revealed a mitigation of CO₂ emissions, resulting in a 1.3% reduction and a reduction in FG consumption of 1.8% preventing an increase in site energy consumption by 795.4 kW in furnaces. Condenser optimization reduces CO₂ emissions by 60%. Energy integration with quench water resulted in heat saving of 1824 kW in hot utility consumption and generating annual savings of EUR 2.3 M. The global carbon dioxide balance can achieve up to a 25% reduction. Full article

► Show Figures

Figure 1

20 pages, 4875 KiB

Open AccessArticle

From Conjugation to Detection: Development of Lateral Flow Assay for Zearalenone

by Vinayak Sharma, Bilal Javed, Hugh J. Byrne and Furong Tian

ChemEngineering 2025, 9(3), 54; https://doi.org/10.3390/chemengineering9030054 - 26 May 2025

Viewed by 364

Abstract

The development of rapid, sensitive and cost-effective lateral flow assays is crucial for the detection of mycotoxins, ideally at the point-of-care level. This study presents the design and optimization of a competitive lateral flow assay based on gold nanoparticles (AuNPs) for the detection [...] Read more.

The development of rapid, sensitive and cost-effective lateral flow assays is crucial for the detection of mycotoxins, ideally at the point-of-care level. This study presents the design and optimization of a competitive lateral flow assay based on gold nanoparticles (AuNPs) for the detection of zearalenone in food samples. Beginning with the synthesis and functionalization of gold nanoparticles, it proceeds to compare the immobilization of antibodies using chemical conjugation and physical adsorption binding strategies, upon optimizing parameters including the pH, antibody concentration and blocking conditions to enhance the stability of the prepared bioconjugates. The bioconjugates are characterized using UV–visible absorption spectroscopy and dynamic light scattering to monitor changes in the spectra and hydrodynamic size of AuNPs upon the addition of antibodies. The assessment of these bioconjugates is based on their ability to bind and manifest a color, developed due to nanoparticle binding with the test zone on the strip with the toxin–protein conjugate. The lateral flow immunochromatographic assay (LFIA) strips are then prepared by dispensing a control line (IgG) and test line (toxin–protein conjugate) on a nitrocellulose membrane using a lateral flow strip dispenser. The sensitivity of the LFIA strips is evaluated after standardizing the conditions by varying the concentration of zearalenone in the spiked samples and optimizing the running buffer solution. The limit of detection and limit of quantification under optimized conditions are determined to be 0.7 ng/mL and 2.37 ng for zearalenone-spiked samples. Furthermore, the mean pixel intensity and RGB values are plotted against the concentration of zearalenone, which can be used in a colorimetric smartphone-based application for the quantification of the amount of mycotoxin in the sample. Full article

► Show Figures

Figure 1

16 pages, 4172 KiB

Open AccessArticle

An Upgraded FOS/TAC Titration Model Integrating Phosphate Effects for Accurate Assessments of Volatile Fatty Acids and Alkalinity in Anaerobic Media

by Xiaojun Liu, André Pauss, Laura André and Thierry Ribeiro

ChemEngineering 2025, 9(3), 53; https://doi.org/10.3390/chemengineering9030053 - 22 May 2025

Viewed by 383

Abstract

The accurate determination of volatile fatty acids (VFAs) and total alkalinity (TAC, mostly carried by bicarbonate ions) is critical for operating anaerobic digesters. The FOS/TAC titration method developed by Nordmann is widely used due to its simplicity and affordability. This method has known [...] Read more.

The accurate determination of volatile fatty acids (VFAs) and total alkalinity (TAC, mostly carried by bicarbonate ions) is critical for operating anaerobic digesters. The FOS/TAC titration method developed by Nordmann is widely used due to its simplicity and affordability. This method has known limitations in dosing VFAs and TAC, since the presence of one interferes with the determination of the other, especially at higher VFA or bicarbonate concentrations. This study builds upon our prior research in 2021 by integrating the influence of phosphate (H₂PO₄⁻/HPO₄²⁻) into numerical models correcting FOS/TAC titration results. A Scilab-based program was used to assess the impact of phosphate on titration results, revealing significant biases at lower concentrations. A revised multivariate regression formula was developed, incorporating phosphate effects, and demonstrating superior accuracy. The mean absolute percentage errors (MAPE) for TAC and VFA estimation were reduced to less than 0.3%. The model maintains compatibility with standard Nordmann’s titration protocols and equipment while significantly improving reliability. These findings highlight the necessity of considering phosphate interference in FOS/TAC titration, particularly in AD systems with variable buffering conditions. The proposed correction model enhances process monitoring and control, providing a more robust tool for both research and industrial practice in anaerobic digestion. Full article

► Show Figures

Figure 1

21 pages, 1914 KiB

Open AccessArticle

Robust Enhanced Auto-Tuning of PID Controllers for Optimal Quality Control of Cement Raw Mix via Neural Networks

by Dimitris Tsamatsoulis

ChemEngineering 2025, 9(3), 52; https://doi.org/10.3390/chemengineering9030052 - 20 May 2025

Viewed by 359

Abstract

Ensuring efficient long-term quality control of the raw mix remains a priority for the cement industry, supporting initiatives to lower the CO₂ footprint by incorporating significant amounts of alternative fuels and raw materials in clinker production. This study presents an effective method [...] Read more.

Ensuring efficient long-term quality control of the raw mix remains a priority for the cement industry, supporting initiatives to lower the CO₂ footprint by incorporating significant amounts of alternative fuels and raw materials in clinker production. This study presents an effective method for creating a robust auto-tuner for proportional–integral–differential (PID) controller control of the lime saturation factor (LSF) of the raw mix using artificial neural networks (ANNs). This auto-tuner, combined with a previously studied robust PID controller, forms an integrated system that adapts to process changes and maintains low long-term variance in LSF. The ANN links each of the three PID gains to the process dynamic parameters, with the three ANNs also interconnected. We employed the Levenberg–Marquardt method to optimize the ANNs’ synaptic weights and applied the weight decay method to prevent overfitting. The industrial implementation of our control system, using the auto-tuner for 16,800 h of raw mill operation, shows an average LSF standard deviation of 2.5, with fewer than 10% of the datasets exceeding a standard deviation of 3.5. Considering that the measurement reproducibility is 1.44 and assuming a low mixing ratio of the raw meal in the silo equal to 2, the LSF standard deviation in the kiln feed approaches the analysis reproducibility, indicating that disturbances in the raw meal largely diminish in the kiln feed. In conclusion, integrating traditional, well-established tools like PID controllers with newer advanced techniques, such as ANNs, can yield innovative solutions. Full article

► Show Figures

Figure 1

49 pages, 6397 KiB

Open AccessArticle

Waste-to-Energy Potential of Petroleum Refinery Sludge, Statistical Optimization, Machine Learning, and Life Cycle Costs Models

by Seyyed Roohollah Masoomi, Mohammad Gheibi, Reza Moezzi, Kourosh Behzadian, Atiyeh Ardakanian, Farzad Piadeh and Andres Annuk

ChemEngineering 2025, 9(3), 51; https://doi.org/10.3390/chemengineering9030051 - 16 May 2025

Viewed by 409

Abstract

Sludge management in petroleum refineries is a costly and complex challenge, posing environmental risks and health hazards for humans. This study explores sludge incineration as a viable energy recovery method, using a case study from an Iranian refinery. Analysis of 15 sludge samples [...] Read more.

Sludge management in petroleum refineries is a costly and complex challenge, posing environmental risks and health hazards for humans. This study explores sludge incineration as a viable energy recovery method, using a case study from an Iranian refinery. Analysis of 15 sludge samples via bomb calorimetry revealed an average heat value of 3100 kcal/kg, which declines with increased moisture content, while higher chemical oxygen demand (COD) enhances energy yield. Over five years, 4000 tonnes of accumulated sludge presented an energy potential of 12,400 Gcal. Statistical modeling, including polynomial regression and response surface methodology (RSM), mapped sludge storage profiles and predicted calorific values based on COD and moisture variations. The results indicate anaerobic digestion at greater depths reduces organic matter, lowering energy potential. Differential scanning calorimetry (DSC) analysis confirmed key thermal transitions, supporting sludge incineration as an effective waste-to-energy strategy. Implementing this approach within a circular economy framework can optimize refinery waste management while reducing pollution, though proper combustion byproduct control is essential for sustainability and regulatory compliance. Full article

(This article belongs to the Special Issue Innovative Approaches for the Environmental Chemical Engineering)

► Show Figures

Figure 1

13 pages, 477 KiB

Open AccessArticle

Decoloration of Waste Cooking Oil by Maghnia Algerian Clays via Ion Exchange and Surface Adsorption

by Abdelhak Serouri, Zoubida Taleb, Alberto Mannu, Chahineze Nawel Kedir, Cherifa Hakima Memou, Sebastiano Garroni, Andrea Mele, Oussama Zinai and Safia Taleb

ChemEngineering 2025, 9(3), 50; https://doi.org/10.3390/chemengineering9030050 - 16 May 2025

Viewed by 296

Abstract

The purification of waste cooking oils (WCOs) through clay-based adsorption is an established recycling method, yet the relationship between clay composition and adsorption efficiency remains an area of active research. The aim of the present research work was to assess the performance of [...] Read more.

The purification of waste cooking oils (WCOs) through clay-based adsorption is an established recycling method, yet the relationship between clay composition and adsorption efficiency remains an area of active research. The aim of the present research work was to assess the performance of Maghnia bentonite in WCO decoloration and to gain information about the specific refining process. Thus, natural bentonite from the Maghnia region (Algeria) was investigated as an adsorbent for WCO refining for biolubricant production. The adsorption efficiency was evaluated under different conditions, achieving up to 70% decolorization at 10 wt% clay after 4 h of treatment. Structural characterization of the bentonite before and after adsorption was conducted using FT-IR spectroscopy, powder X-ray diffraction (XRD), and X-ray fluorescence (XRF) to assess compositional and morphological changes. FT-IR analysis confirmed the adsorption of organic compounds, XRD indicated minor alterations in interlayer spacing, and XRF revealed ion exchange mechanisms, including a reduction in sodium and magnesium and an increase in calcium and potassium. Adsorption kinetics followed a pseudo-second-order model, with desorption effects observed at prolonged contact times. The pHPZC of 8.3 suggested that bentonite adsorption efficiency is enhanced under acidic conditions. The high decoloration capacity of Maghnia bentonite, combined with the availability and the low cost of the material, suggests a possible industrial application of this material for WCO refinement, especially in lubricant production. Full article

► Show Figures

Graphical abstract

20 pages, 15291 KiB

Open AccessArticle

CFD Simulation and Design of Non-Newtonian Fluid Polymer Grinding Pump Under Turbulent Flow

by Hong Du, Chenxi Wang, Jian Zhang, Xianjie Li, Xiujun Wang, Xuecheng Zheng and Xin He

ChemEngineering 2025, 9(3), 49; https://doi.org/10.3390/chemengineering9030049 - 8 May 2025

Viewed by 417

Abstract

The performance of the grinding pump, a device for crushing and stretching conventional polymers, is mainly affected by its stage number, diameter, and tooth count. In this paper, Fluent software was utilized, employing the Eulerian model in conjunction with non-Newtonian fluid models (such [...] Read more.

The performance of the grinding pump, a device for crushing and stretching conventional polymers, is mainly affected by its stage number, diameter, and tooth count. In this paper, Fluent software was utilized, employing the Eulerian model in conjunction with non-Newtonian fluid models (such as the power-law model and Bingham plastic model) and turbulence models (like the k-ε model) to establish a model for CFD (Computational Fluid Dynamics) simulations. These simulations analyzed the turbulence characteristics of non-Newtonian fluids in grinding mixing pumps, as well as the basic performance of the pumps, including pressure, velocity, viscosity, and volume fraction distributions. The effects of different structural parameters (stage number, pump diameter, and tooth count) on the instant dissolving effect of polymers were compared, and the optimal structure was determined. Based on pressure profile, velocity profile analysis, and polymer distribution simulation results, the optimal grinding mixing pump was found to have three stages, with a diameter of d = 140 mm and 60 teeth yielding the best grinding effect. Increasing the stage number and pump diameter can improve the grinding and mixing effect, but an excessively large pump diameter can reduce it. Changes in tooth count have a minor impact on viscosity but affect distribution uniformity. Full article

► Show Figures

Figure 1

25 pages, 3245 KiB

Open AccessArticle

Influence of Substrate Concentrations on the Performance of Fed-Batch and Perfusion Bioreactors: Insights from Mathematical Modelling

by John J. Fitzpatrick, Fionn O'Leary, Ali Hill, James Daly, Fergal Lalor and Edmond P. Byrne

ChemEngineering 2025, 9(3), 48; https://doi.org/10.3390/chemengineering9030048 - 6 May 2025

Viewed by 297

Abstract

Fed-batch and perfusion bioreactors are commonly used in biopharmaceutical production. This study applies mathematical models to investigate the influence of substrate concentration in the media added (

S_{m}

), operating substrate concentration in the bioreactor (

S

), and bioreaction time on [...] Read more.

Fed-batch and perfusion bioreactors are commonly used in biopharmaceutical production. This study applies mathematical models to investigate the influence of substrate concentration in the media added (

S_{m}

), operating substrate concentration in the bioreactor (

S

), and bioreaction time on the performance of both bioreactors. The performance parameters are titer, productivity, product yield, wasted substrate, and mean product residence time. The difference between the substrate concentration in the media and the operating substrate concentration has a major impact on performance parameters. For a fixed

S

, operating at higher values of

S_{m}

is more beneficial to both fed-batch and perfusion performance. Higher productivities are obtained in perfusion, and mean product residence times are shorter. Furthermore, perfusion can obtain titers comparable to fed-batch when operated at similar substrate concentrations. All this suggests that perfusion is more advantageous. It is advantageous to operate the bioreactors over a longer bioreaction time. However, for fed-batch bioreactors, there exists an optimal time after which there is a major progressive reduction in productivity. Full article

► Show Figures

Figure 1

22 pages, 4233 KiB

Open AccessArticle

Steady-State Simulation of a Fixed-Bed Reactor for the Total Oxidation of Volatile Organic Components: Application of the Barkelew Criterion

by Philippe M. Heynderickx and Joris W. Thybaut

ChemEngineering 2025, 9(3), 46; https://doi.org/10.3390/chemengineering9030046 - 30 Apr 2025

Viewed by 279

Abstract

A steady-state tubular reactor for total oxidation reaction under typical industrial conditions in the removal of volatile organic components (VOC) is described using a one-dimensional heterogeneous reactor model with intraparticle diffusion, using a fully developed Langmuir–Hinshelwood reaction rate expression. The effectiveness factor, accounting [...] Read more.

A steady-state tubular reactor for total oxidation reaction under typical industrial conditions in the removal of volatile organic components (VOC) is described using a one-dimensional heterogeneous reactor model with intraparticle diffusion, using a fully developed Langmuir–Hinshelwood reaction rate expression. The effectiveness factor, accounting for these intraparticle diffusion limitations, is calculated with a generalized Thiele modulus. The actual inclusion of this factor shows that higher operational reactor temperatures can be possible, since this diffusion limitation restricts the heat production inside the catalyst particle. Special attention is given to the outlet concentration of propane, taken as the model VOC, and runaway criteria, reported in the literature, are evaluated. Furthermore, the well-known Barkelew criterion (to evaluate runaway for exothermic reactions) is implemented for practical and safe reactor design. This work identifies that the critical couples populating the Barkelew diagram are positioned lower (up to a 50% difference, compared to Barkelew’s original report), so that operation of the reactor under higher hydrocarbon molar inlet fractions is possible while maintaining safe performance. Full article

(This article belongs to the Special Issue Advances in Catalytic Kinetics)

► Show Figures

Figure 1

15 pages, 3644 KiB

Open AccessArticle

Microwave-Mediated Extraction of Critical Metals from LED E-Waste

by Athanasios B. Bourlinos, Christina Papachristodoulou, Anastasios Markou, Nikolaos Chalmpes, Emmanuel P. Giannelis, Dimitrios P. Gournis, Constantinos E. Salmas and Michael A. Karakassides

ChemEngineering 2025, 9(3), 47; https://doi.org/10.3390/chemengineering9030047 - 29 Apr 2025

Viewed by 488

Abstract

This study introduces a microwave-assisted technique for extracting critical minerals from LED electronic waste. The process begins with microwave irradiation, which thermally decomposes the LED’s plastic lens into a brittle, charred residue. During this stage, the LED chip undergoes deflagration—being rapidly ejected from [...] Read more.

This study introduces a microwave-assisted technique for extracting critical minerals from LED electronic waste. The process begins with microwave irradiation, which thermally decomposes the LED’s plastic lens into a brittle, charred residue. During this stage, the LED chip undergoes deflagration—being rapidly ejected from the reflective cavity and becoming embedded within the decomposed lens material. Consequently, the chip is encapsulated in the resulting charred residue. This composite, consisting of the charred lens and the LED chip, can be easily separated from the metallic pins (Fe, Ni, Ag), which remain almost undamaged. Subsequent calcination of the charred material in air exposes the materials making up the LED chip, which contain critical metals (e.g., Ga, As, In, Y, Au). These metals are then extracted through a two-step acid leaching process involving aqua regia followed by hot concentrated hydrochloric acid, yielding them in potentially recoverable forms. The synergistic effect of microwave irradiation and acid treatment achieves an average extraction efficiency of 96% for critical metals. Notably, this approach enables complete and loss-free recovery of the LED chip, offering a practical and efficient solution for LED e-waste recycling. Full article

► Show Figures

Graphical abstract

29 pages, 6667 KiB

Open AccessArticle

Quality Management in Chemical Processes Through Fuzzy Analysis: A Fuzzy C-Means and Predictive Models Approach

by Gabriel Marín Díaz

ChemEngineering 2025, 9(3), 45; https://doi.org/10.3390/chemengineering9030045 - 28 Apr 2025

Viewed by 456

Abstract

Ensuring high levels of quality and efficiency is essential for compliance with ISO standards in chemical manufacturing. Traditional methods, such as Statistical Process Control (SPC) and Six Sigma, often lack adaptability and fail to offer interpretable insights. This study proposes a hybrid quality [...] Read more.

Ensuring high levels of quality and efficiency is essential for compliance with ISO standards in chemical manufacturing. Traditional methods, such as Statistical Process Control (SPC) and Six Sigma, often lack adaptability and fail to offer interpretable insights. This study proposes a hybrid quality control model based on Explainable Artificial Intelligence (XAI), integrating fuzzy C-means clustering (FCM), machine learning (ML), and Fuzzy Inference Systems (FISs) to enhance defect prediction and interpretability in industrial environments. The approach uses fuzzy clusters to segment production batches, improving the understanding of process variability. A supervised ML model (XGBoost) is trained on historical data to predict defect probabilities, while an explainable FIS refines the final assessment using expert-defined rules. XAI techniques (SHAP and LIME) offer transparency and insight into the decision-making process. Experimental validation using a real-world white wine dataset, evaluated in terms of accuracy and interpretability, shows that the proposed model outperforms traditional approaches in both predictive performance and transparency. The results demonstrate the effectiveness of combining unsupervised clustering, predictive analytics, and fuzzy reasoning in an Industry 4.0 framework. This study provides a scalable and adaptable solution for real-time quality control in chemical manufacturing, improving decision support systems and enabling automated and explainable quality assessments. Full article

(This article belongs to the Special Issue New Advances in Chemical Engineering)

► Show Figures

Figure 1

10 pages, 508 KiB

Open AccessArticle

Lagrangian for Real Systems Instead of Entropy for Ideal Isolated Systems

by Nikolai M. Kocherginsky

ChemEngineering 2025, 9(3), 44; https://doi.org/10.3390/chemengineering9030044 - 24 Apr 2025

Viewed by 321

Abstract

The Second Law of Thermodynamics states that entropy S increases in a spontaneous process in an ideal isothermal and isolated system. Real systems are influenced by external forces and fields, including the temperature field. In this case, only entropy is not enough, and [...] Read more.

The Second Law of Thermodynamics states that entropy S increases in a spontaneous process in an ideal isothermal and isolated system. Real systems are influenced by external forces and fields, including the temperature field. In this case, only entropy is not enough, and we suggest using a new function,

L_{s}

, which is analogous to the Lagrangian in classical mechanics. It includes total potential energy but instead of mechanical kinetic energy,

L_{s}

includes the product ST, and the system always evolves towards increasing this modified Lagrangian. It reaches an equilibrium when total potential force is balanced by both entropic and thermal forces. All forces have the same units, Newton/mol, and may be added or subtracted. For condensed systems with friction forces, it is a molecular transport velocity, and not acceleration, which is proportional to the acting force. Our approach has several advantages compared to Onsager’s non-equilibrium thermodynamics with its thermodynamic forces, which may have different units, including 1/T for energy transport. For isolated systems, the description is reduced to Second Law and Clausius inequality. It easily explains diffusion, Dufour effect, and Soret thermodiffusion. The combination of electric, thermal, and entropic forces explains thermoelectric phenomena, including Peltier–Seebeck and Thomson (Lord Kelvin) effects. Gravitational and entropic forces together inside a black hole may lead to a steady state or the black hole evaporation. They are also involved in and influenced by solar atmospheric processes. Full article

► Show Figures

Figure 1

13 pages, 5840 KiB

Open AccessArticle

CrS₂ Supported Transition Metal Single Atoms as Efficient Bifunctional Electrocatalysts: A Density Functional Theory Study

by Ying Wang

ChemEngineering 2025, 9(3), 43; https://doi.org/10.3390/chemengineering9030043 - 23 Apr 2025

Viewed by 357

Abstract

Transition metal dichalcogenides (TMDs) are recognized for their exceptional energy storage capabilities and electrochemical potential, stemming from their unique electronic structures and physicochemical properties. In this study, we focus on chromium disulfide (CrS₂) as the primary research subject and employ a [...] Read more.

Transition metal dichalcogenides (TMDs) are recognized for their exceptional energy storage capabilities and electrochemical potential, stemming from their unique electronic structures and physicochemical properties. In this study, we focus on chromium disulfide (CrS₂) as the primary research subject and employ a combination of density functional theory (DFT) and first-principle calculations to investigate the effects of incorporating transition metal elements onto the surface of CrS₂. This approach aims to develop a class of bifunctional single-atom catalysts with high efficiency and to analyze their catalytic performance in detail. Theoretical calculations reveal that the Au@CrS₂ single-atom catalyst demonstrates outstanding catalytic activity, with a low overpotential of 0.34 V for the oxygen evolution reaction (OER) and 0.37 V for the oxygen reduction reaction (ORR). These results establish Au@CrS₂ as a highly effective bifunctional catalyst. Moreover, the catalytic performance of Au@CrS₂ surpasses that of traditional commercial catalysts, such as Pt (0.45 V) and IrO₂ (0.56 V), suggesting its potential to replace these materials in fuel cells and other energy applications. This study provides a novel approach to the design and development of advanced transition metal-based catalytic materials. Full article

► Show Figures

Figure 1

32 pages, 6834 KiB

Open AccessArticle

Silver-Based Catalysts on Metal Oxides for Diesel Particulate Matter Oxidation: Insights from In Situ DRIFTS

by Punya Promhuad, Boonlue Sawatmongkhon, Thawatchai Wongchang, Ekarong Sukjit, Nathinee Theinnoi and Kampanart Theinnoi

ChemEngineering 2025, 9(3), 42; https://doi.org/10.3390/chemengineering9030042 - 22 Apr 2025

Viewed by 423

Abstract

Diesel particulate matter (DPM) represents a deleterious environmental contaminant that necessitates the development of effective catalytic oxidation methodologies. This research delineates a comparative analysis of silver-supported metal oxide catalysts (Ag/Al₂O₃, Ag/TiO₂, Ag/ZnO, and Ag/CeO₂), with [...] Read more.

Diesel particulate matter (DPM) represents a deleterious environmental contaminant that necessitates the development of effective catalytic oxidation methodologies. This research delineates a comparative analysis of silver-supported metal oxide catalysts (Ag/Al₂O₃, Ag/TiO₂, Ag/ZnO, and Ag/CeO₂), with an emphasis on the effects of silver distribution and the metal-support interaction on the oxidation of DPM. An array of characterization techniques including XRD, HRTEM, XPS, H₂-TPR, TEM, GC-MS, TGA, and in situ DRIFTS was employed. The novelty of this study resides in elucidating the oxidation mechanism through a tripartite pathway and recognizing Ag⁰ as the predominant active species involved in soot oxidation. The Ag/Al₂O₃ catalyst demonstrated superior catalytic performance, achieving a reduction in the ignition temperature by more than 50 °C, attributable to the optimal dispersion of Ag nanoparticles and a balanced metal-support interaction. Conversely, an excessive interaction observed in Ag/ZnO resulted in diminished catalytic activity. The oxidation of DPM transpires through the volatilization of VOCs (<300 °C), the oxidation by reactive oxygen species, and the combustion of soot (>300 °C). This investigation offers significant contributions to the formulation of highly efficient silver-based catalysts for emissions control, with a particular focus on optimizing Ag dispersion and support interactions to enhance catalytic efficacy. Full article

► Show Figures

Graphical abstract

Journal Menu

Journal Browser

ChemEngineering, Volume 9, Issue 3 (June 2025) – 22 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI