ChemEngineering

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

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

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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

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)

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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

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

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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

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)

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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

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

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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

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

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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

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

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20 pages, 1654 KiB

Open AccessArticle

Environmental Dispersion of Toxic Effluents from Waste Polyethylene Fires: Simulations with ALOFT

by Giulia De Cet and Chiara Vianello

ChemEngineering 2025, 9(2), 41; https://doi.org/10.3390/chemengineering9020041 - 17 Apr 2025

Abstract

In recent years, the Italian peninsula has frequently been affected by fires in waste storage facilities, both accidental and malicious. Waste storage activities must comply with a series of regulations that require the employer to carefully assess the risks associated with the operation [...] Read more.

In recent years, the Italian peninsula has frequently been affected by fires in waste storage facilities, both accidental and malicious. Waste storage activities must comply with a series of regulations that require the employer to carefully assess the risks associated with the operation of the plant. All prevention and protection measures must be taken to reduce the risk of fires in order to safeguard both people and the environment. In addition, with new regulations coming into force in November 2022, efforts are being made to regulate waste treatment and storage facilities in terms of fire safety. This work presents simulations of the dispersion into the environment of toxic effluents produced during a polyethylene fire at a storage site, with the aid of dedicated software. Simulations were carried out using ALOFT, varying the parameters of the simulations (e.g., the burnt area, environmental characteristics, and toxic effluent investigated). In total, 24 simulations were carried out to investigate the emissions of particulate matter and volatile organic compounds in the case of polyethylene fires. The simulations showed that atmospheric stability class and wind speed had a significant impact on the dispersion. The proposed methodology can be applied both in the risk assessment and emergency phases and, eventually, as a valuable tool in post-accident analysis. Full article

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32 pages, 3317 KiB

Open AccessArticle

Recycling of Walnut Shell Biomass for Adsorptive Removal of Hazardous Dye Alizarin Red from Aqueous Solutions Using Magnetic Nanocomposite: Process Optimization, Kinetic, Isotherm, and Thermodynamic Investigation

by Vairavel Parimelazhagan, Palak Sharma, Yashaswini Tiwari, Alagarsamy Santhana Krishna Kumar and Ganeshraja Ayyakannu Sundaram

ChemEngineering 2025, 9(2), 40; https://doi.org/10.3390/chemengineering9020040 - 11 Apr 2025

Abstract

Dye wastewater poses significant risks to human health and aquatic ecosystems, necessitating efficient remediation strategies. This study developed a magnetic Fe₂O₃ nanocomposite (MNC) derived from phosphoric acid-treated walnut shell biomass carbon to remove Alizarin red S (AR) dye from polluted [...] Read more.

Dye wastewater poses significant risks to human health and aquatic ecosystems, necessitating efficient remediation strategies. This study developed a magnetic Fe₂O₃ nanocomposite (MNC) derived from phosphoric acid-treated walnut shell biomass carbon to remove Alizarin red S (AR) dye from polluted water. Characterization techniques confirmed the nanocomposite’s mesoporous structure, superparamagnetic properties (61.5 emu/g), and high crystallinity. Optimization using Response Surface Methodology (RSM) revealed a maximum adsorption efficiency of 94.04% under the following optimal conditions: A pH of 2, AR dye concentration of 85 mg/L, adsorbent dose of 1.5 g/L, and particle size of 448.1 nm. Adsorption followed pseudo-second-order (PSO) kinetics (R² = 0.9999) and Langmuir isotherm models (R² = 0.9983), with thermodynamic studies indicating spontaneous and endothermic chemisorption. The intra-particle diffusion model, Bangham, and Boyd plots describe the adsorption process, and external boundary layer diffusion of AR dye molecules in the aqueous phase limits the adsorbate removal rate. Regeneration tests demonstrated reusability over three cycles, with a desorption efficiency of 50.52% using 30 mM HCl. The MNC exhibited a maximum adsorption capacity (Q_max) of 115.35 mg/g, outperforming other adsorbents, making it an efficient and sustainable alternative solution for AR dye removal from water bodies. Full article

(This article belongs to the Special Issue Chemical Engineering in Wastewater Treatment)

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15 pages, 2620 KiB

Open AccessArticle

Research of the Process of Obtaining Monocalcium Phosphate from Unconditional Phosphate Raw Materials

by Abibulla Anarbayev, Balzhan Kabylbekova, Zhakhongir Khussanov, Bakyt Smailov, Nurlan Anarbaev and Yevgeniy Kulikov

ChemEngineering 2025, 9(2), 39; https://doi.org/10.3390/chemengineering9020039 - 2 Apr 2025

Abstract

The article presents methods for processing low-grade phosphate raw materials from the Chilisay deposit using a circulation method to produce mineral fertilizers and feed monocalcium phosphate. A study was conducted on the process of obtaining high-quality monocalcium phosphate, and optimal parameters for the [...] Read more.

The article presents methods for processing low-grade phosphate raw materials from the Chilisay deposit using a circulation method to produce mineral fertilizers and feed monocalcium phosphate. A study was conducted on the process of obtaining high-quality monocalcium phosphate, and optimal parameters for the decomposition of low-grade phosphate raw materials were determined. Based on the research, it was established that for the decomposition of phosphate raw materials, phosphoric acid with a concentration of 36–42% P₂O₅ should be used; the recycle phosphoric acid rate should be 540–560% of the stoichiometric amount required for the formation of monocalcium phosphate (MCP); the decomposition temperature should be 95–100 °C; the decomposition duration should be 40–50 min; the filtration temperature of the insoluble residue should be 85–90 °C; the crystallization temperature of MCP should be 40–45 °C; and the crystallization duration should be 85–90 min. For the sulfation of the mother solution and the production of recycle phosphoric acid, sulfuric acid with a concentration of 86–93% H₂SO₄ should be used; the sulfuric acid rate should be 95–100% of the stoichiometric amount required for the decomposition of dissolved Ca(H₂PO₄)₂. After drying the wet residue, monocalcium phosphate was obtained with the following composition: P₂O₅—55%, Ca—18.01%, H₂O—4.0%, F—0.01%, As—0.004%, Pb—0.002%. The obtained monocalcium phosphate is used in agriculture as a mineral fertilizer and feed monocalcium phosphate. Full article

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19 pages, 6273 KiB

Open AccessArticle

Enhanced Efficiency of CZTS Solar Cells with Reduced Graphene Oxide and Titanium Dioxide Layers: A SCAPS Simulation Study

by Dounia Fatihi, Giorgio Tseberlidis, Vanira Trifiletti, Simona Binetti, Eleonora Isotta, Paolo Scardi, Abderrafi Kamal, R’hma Adhiri and Narges Ataollahi

ChemEngineering 2025, 9(2), 38; https://doi.org/10.3390/chemengineering9020038 - 1 Apr 2025

Abstract

Copper zinc tin sulfide (commonly known as CZTS) solar cells (SCs) are gaining attention as a promising technology for sustainable electricity generation owing to their cost-effectiveness, availability of materials, and environmental advantages. The goal of this study is to enhance CZTS SC performance [...] Read more.

Copper zinc tin sulfide (commonly known as CZTS) solar cells (SCs) are gaining attention as a promising technology for sustainable electricity generation owing to their cost-effectiveness, availability of materials, and environmental advantages. The goal of this study is to enhance CZTS SC performance by adding a back surface field (BSF) layer. SC capacitance simulator software (SCAPS) was used to examine three different configurations. Another option is to replace the cadmium sulfide (CdS) buffer layer with a titanium dioxide (TiO₂) layer. The results demonstrate that the reduced graphene oxide (rGO) BSF layer increases the conversion efficiency by 25.68% and significantly improves the fill factor, attributed to lowering carrier recombination and creating a quasi-ohmic contact at the interface between the metal and semiconductor. Furthermore, replacing the CdS buffer layer with TiO₂ offers potential efficiency gains and mitigates environmental concerns associated with the toxicity of CdS. The results of this investigation could enhance the efficiency and viability of CZTS SCs for future energy applications. However, it is observed that BSF layers may become less effective at elevated temperatures due to increased recombination, leading to reduced carrier lifetime. This study underlines valuable insights into optimizing CZTS SC performance through advanced material choices, highlighting the dual benefits of improved efficiency and reduced environmental impact. Full article

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

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14 pages, 3431 KiB

Open AccessArticle

Drilling Optimization Using Artificial Neural Networks and Empirical Models

by Mohammed F. Al Dushaishi, Ahmed K. Abbas, Mortadha T. Al Saba and Jarrett Wise

ChemEngineering 2025, 9(2), 37; https://doi.org/10.3390/chemengineering9020037 - 31 Mar 2025

Cited by 1

Abstract

A key role of drilling optimization is reducing the cost and non-productive time (NPT) for drilling operations. The rate of penetration (ROP) directly affects the overall cost and cost per foot of drilling operations and could lead to significant cost savings or expenses. [...] Read more.

A key role of drilling optimization is reducing the cost and non-productive time (NPT) for drilling operations. The rate of penetration (ROP) directly affects the overall cost and cost per foot of drilling operations and could lead to significant cost savings or expenses. Traditionally, empirical ROP modeling is used to predict bit response or estimate ROP using nearby offset data. Due to the complexity and nonlinearity of ROP, data-driven modeling, such as machine learning (ML), became more attractive. The objective of this paper is to develop an ROP data-driven artificial neural network (ANN) model using drilling and formation data collected from three nearby wells. Additionally, drilling optimization was conducted and compared with traditional empirical ROP models. The advantages and disadvantages of both methods are discussed, and the direction of future data-driven modeling is highlighted. The data-driven ANN model demonstrated strong performance when compared to the field data. The ANN model showed an RMSE and R² of 3.89 m/h and 0.93 for the training data and an RMSE and R² of 4.16 m/h and 0.92 for the testing dataset. The sensitivity analysis showed that the ANN model predicted higher ROP than the empirical models in the selected interval. Due to the limited bit wear data compared to the operational parameters, coupled simultaneous data-driven and empirical modeling is believed to be the future direction for data-driven drilling optimization. Full article

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32 pages, 3637 KiB

Open AccessReview

Comparison of Dispersing Processes of Bio-Based and Synthetic Materials: A Review

by Leah Jalowy, Dominik Nemec and Oguzhan Ilhan

ChemEngineering 2025, 9(2), 36; https://doi.org/10.3390/chemengineering9020036 - 26 Mar 2025

Abstract

The ever-growing environmental and sustainability awareness as well as the associated increased independence from petroleum has led to bio-based materials increasingly replacing synthetic, non-renewable materials in various applications, including food packaging, coatings, adhesives, and energy storage devices. Although bio-based materials offer advantages such [...] Read more.

The ever-growing environmental and sustainability awareness as well as the associated increased independence from petroleum has led to bio-based materials increasingly replacing synthetic, non-renewable materials in various applications, including food packaging, coatings, adhesives, and energy storage devices. Although bio-based materials offer advantages such as reduced toxicity and harmfulness for humans and the environment, as well as contributing to the conservation of important resources, these aspects are usually not sufficient for commercialization. Integrating bio-based materials into existing technologies is challenging due to inherent disadvantages, such as difficult processability and low moisture resistance, making it difficult to readily substitute them for synthetic materials. Consequently, surface modifications are often necessary to make bio-based materials suitable for the intended applications. This review highlights the critical role of processing methods in the successful substitution of synthetic materials with bio-based alternatives. While previous studies have primarily concentrated on material combinations and formulations of bio-based applications, often considering processing methods as secondary, this review explores the influence and importance of dispersion quality. It examines how varying dispersing methods and process parameters can impact the performance of bio-based materials, alongside addressing the specific requirements for both the materials and the dispersing processes. Furthermore, it focuses on bio-based dispersions based on lignin and polysaccharides, particularly in applications such as bio-based adhesives and binders for battery technologies. By addressing these aspects, this review aims to reveal existing research gaps and provide insights into optimizing the processing of bio-based materials for diverse applications. Full article

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22 pages, 3886 KiB

Open AccessArticle

Development of New Xanthan-Aldehyde/Gelatin Nanogels for Enhancement of Ibuprofen Transdermal Delivery: In-Vitro/Ex-Vivo/In-Vivo Evaluation

by Yacine Nait Bachir, Ramdane Mohamed Said, Mohamed Lamine Abdelli, Walid Namaoui, Meriem Medjkane, Nouara Boudjema, Halima Meriem Issaadi and Elisabeth Restrepo Parra

ChemEngineering 2025, 9(2), 35; https://doi.org/10.3390/chemengineering9020035 - 20 Mar 2025

Abstract

The aim of this study was to prepare nanogels based on gelatin and xanthan-aldehyde for the enhancement of ibuprofen transdermal delivery. Firstly, the process of formulating nanogels using the reaction of Schiff’s base was optimized using experimental designs. Secondly, the structural characterization of [...] Read more.

The aim of this study was to prepare nanogels based on gelatin and xanthan-aldehyde for the enhancement of ibuprofen transdermal delivery. Firstly, the process of formulating nanogels using the reaction of Schiff’s base was optimized using experimental designs. Secondly, the structural characterization of nanogels was performed using laser particle size, zetometry, FTIR (Fourier Transform Infrared Spectroscopy), XRD (X-Ray Diffraction), SEM (scanning electron microscopy), and thermogravimetric analysis. Finally, the evaluation of pharmacological characteristics and formulation therapeutic efficacy were achieved using in vitro dissolution kinetics, ex vivo transdermal diffusion studies, and an evaluation of in vivo anti-inflammatory activity. The results of the experimental plan show that the formulations containing a ratio of 15:10 ibuprofen/polymer and a ratio of 1:2 gelatin/xanthan-aldehyde with a gelling time of 2 h exhibited the best results; the formulations showed a mean diameter of 179.9 ± 6.2 nm, a polydispersity index of 0.193, which confirms monodispersed particles, a zeta potential of 24.7 mV, denoting a high degree of particle stability, and an encapsulation rate of 93.78%. The FTIR spectroscopy analysis showed the formation of imine function in the nanogel, and scanning electron microscopy showed the globular and porous form of the formulation. The incorporation of ibuprofen into nanogels improved their in vitro dissolution kinetics and ex vivo transdermal diffusion. The incorporation of nanogels into a patch system for its in vivo anti-inflammatory activity has shown excellent efficiency with a percentage of edema inhibition at a dose of 25 mg and 50 mg of 38.77 ± 1.6% and 82.03 ± 9.03%, respectively, while the commercial reference gel presented inhibition values at a dose of 25 mg and 50 mg of 10.61 ± 1.71% and 37.03 ± 11.43%, respectively. Thus, the innovative pharmaceutical form of ibuprofen offers a promising model for enhancing drug bioavailability and therapeutic effects while reducing adverse effects. Full article

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20 pages, 17704 KiB

Open AccessArticle

Soft Actor-Critic Reinforcement Learning Improves Distillation Column Internals Design Optimization

by Dhan Lord B. Fortela, Holden Broussard, Renee Ward, Carly Broussard, Ashley P. Mikolajczyk, Magdy A. Bayoumi and Mark E. Zappi

ChemEngineering 2025, 9(2), 34; https://doi.org/10.3390/chemengineering9020034 - 18 Mar 2025

Abstract

Amid the advancements in computer-based chemical process modeling and simulation packages used in commercial applications aimed at accelerating chemical process design and analysis, there are still certain tasks in design optimization, such as distillation column internals design, that become bottlenecks due to inherent [...] Read more.

Amid the advancements in computer-based chemical process modeling and simulation packages used in commercial applications aimed at accelerating chemical process design and analysis, there are still certain tasks in design optimization, such as distillation column internals design, that become bottlenecks due to inherent limitations in such software packages. This work demonstrates the use of soft actor-critic (SAC) reinforcement learning (RL) in automating the task of determining the optimal design of trayed multistage distillation columns. The design environment was created using the AspenPlus^® software (version 12, Aspen Technology Inc., Bedford, Massachusetts, USA) with its RadFrac module for the required rigorous modeling of the column internals. The RL computational work was achieved by developing a Python package that allows interfacing with AspenPlus^® and by implementing in OpenAI’s Gymnasium module (version 1.0.0, OpenAI Inc., San Francisco, California, USA) the learning space for the state and action variables. The results evidently show that (1) SAC RL works as an automation approach for the design of distillation column internals, (2) the reward scheme in the SAC model significantly affects SAC performance, (3) column diameter is a significant constraint in achieving column internals design specifications in flooding, and (4) SAC hyperparameters have varying effects on SAC performance. SAC RL can be implemented as a one-shot learning model that can significantly improve the design of multistage distillation column internals by automating the optimization process. Full article

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

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15 pages, 2739 KiB

Open AccessArticle

Performance Assessment of Novel Soda Ash Adsorbent Biogas Sweetening: Fixed Bed Studies, Adsorption Kinetics, and Adsorption Isotherms

by Register Mrosso and Cleophas Achisa Mecha

ChemEngineering 2025, 9(2), 33; https://doi.org/10.3390/chemengineering9020033 - 17 Mar 2025

Abstract

The reliance on greenhouse gas-emitting unrenewable energy sources such as coal, natural gas, and oil, increases climate change. Transitioning to renewable energy, such as biogas, is crucial to reducing environmental degradation and global warming. The existence of impurities such as hydrogen sulfide hampers [...] Read more.

The reliance on greenhouse gas-emitting unrenewable energy sources such as coal, natural gas, and oil, increases climate change. Transitioning to renewable energy, such as biogas, is crucial to reducing environmental degradation and global warming. The existence of impurities such as hydrogen sulfide hampers the application of biogas. Utilizing natural resources for biogas purification is essential to improve access to clean energy for low-income communities. This study used soda ash derived from Lake Natron in Tanzania as a sorbent for H₂S removal. Effects of sorbent mass, flow rate, and particle size were investigated. Experimental data were analyzed using kinetic models, adsorption isotherms, and breakthrough curves. Soda ash of 280 μm particle size, a flow rate of 0.03 m³/h, and a mass of 75 g demonstrated the best performance, achieving an efficiency of 94% in removal and a sorption capacity of 0.02 g per 100 g in five repeated cycles. Freundlich and Jovanovich’s isotherms match the data with n = 0.4 and K_j = 0.003, respectively. Adsorption kinetics were best described by the intra-particle model (k_id = 0.14, c = 0.59 mg/g, and R² = 0.972). A breakthrough analysis indicated that the Yoon–Nelson model provided the best fit with an R² of 0.95. Soda ash from Lake Natron demonstrated great potential in biogas desulphurization, thus contributing to the production and access to clean energy. Full article

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16 pages, 2398 KiB

Open AccessArticle

Source Tracing of Raw Material Components in Wood Vinegar Distillation Process Based on Machine Learning and Aspen Simulation

by Siqi Liao, Wanting Sun, Haoran Zheng and Qiyang Xu

ChemEngineering 2025, 9(2), 32; https://doi.org/10.3390/chemengineering9020032 - 13 Mar 2025

Abstract

As a kind of high-oxygen organic liquid produced during biomass pyrolysis, wood vinegar possesses significant industrial value due to its rich composition of acetic acid, phenols, and other bioactive compounds. In this study, we explore the application of advanced machine learning models in [...] Read more.

As a kind of high-oxygen organic liquid produced during biomass pyrolysis, wood vinegar possesses significant industrial value due to its rich composition of acetic acid, phenols, and other bioactive compounds. In this study, we explore the application of advanced machine learning models in optimizing the dual-column distillation process for wood vinegar production, such as Random Forest algorithms. Through the integration of Aspen Plus simulation and deep learning, an adaptive control strategy is proposed to enhance the separation efficiency of key components under varying feed conditions. The experimental results demonstrate that the Random Forest model exhibits superior predictive accuracy to traditional decision tree methods, and an R² of 0.9728 can be achieved for phenol concentration prediction. This AI-driven system can provide real-time process optimization, enhancing energy efficiency, stabilizing component yields, and contributing to the advancement of sustainable practices within the biomass chemical industry. These findings are anticipated to offer valuable insights into the integration of green chemistry principles with intelligent control systems to facilitate the achievement of Industry 4.0 objectives in bio-based production. Full article

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14 pages, 2125 KiB

Open AccessArticle

Phytochemical Profiling and Antioxidant Activity of True Leaves and Cotyledons of Adenocaulon himalaicum

by Sang-Yun Lee, Nari Yoon, Neil Patrick Uy, Chung-Ho Choi and Sanghyun Lee

ChemEngineering 2025, 9(2), 31; https://doi.org/10.3390/chemengineering9020031 - 10 Mar 2025

Abstract

Adenocaulon himalaicum is widely distributed across Asia. In its early growth stages, A. himalaicum is traditionally consumed as a food source in Korea. Although previous research has identified the presence of bioactive compounds in A. himalaicum extract, suggesting its potential as a medicinal [...] Read more.

Adenocaulon himalaicum is widely distributed across Asia. In its early growth stages, A. himalaicum is traditionally consumed as a food source in Korea. Although previous research has identified the presence of bioactive compounds in A. himalaicum extract, suggesting its potential as a medicinal resource, the phytochemical profile of A. himalaicum extract has not been extensively determined. This investigation aimed to identify the phytochemicals present in the true leaf and cotyledon of A. himalaicum (TLA and CLA, respectively) and evaluate their radical-scavenging activity. By performing LC-MS/MS and HPLC, varying amounts of isochlorogenic acid A, cryptochlorogenic acid, isochlorogenic acid B, rutin, chlorogenic acid, hyperin, and neochlorogenic acid were detected in the TLA and CLA extracts. Chlorogenic acid (9.002 mg/g DW), isochlorogenic acid A (28.512 mg/g DW), and isochlorogenic acid B (12.223 mg/g DW) were the most abundant in TLA. TLA exhibited higher phytochemical content (49.737 mg/g DW), total phenolic content (45.51 mg tannic acid equivalent/g extract), and total flavonoid content (16.24 mg quercetin equivalent/g extract) than CLA. Moreover, the radical-scavenging activity of TLA was two times higher than that of CLA. The young leaf of A. himalaicum has a rich phytochemical profile and robust antioxidant activity; hence, it has potential as natural antioxidant sources for human health and valuable pharmacognosy raw materials for pharmaceutical and functional food applications. Full article

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17 pages, 4636 KiB

Open AccessArticle

Preparation and Characterization of Unactivated, Activated, and γ-Fe₂O₃ Nanoparticle-Functionalized Biochar from Rice Husk via Pyrolysis for Dyes Removal in Aqueous Samples: Comparison, Performance, and Mechanism

by Diego Barzallo, Edwuin Carrasquero, Mónica Andrade, Daniel Alejandro Heredia Jara and Paúl Palmay

ChemEngineering 2025, 9(2), 30; https://doi.org/10.3390/chemengineering9020030 - 10 Mar 2025

Abstract

This study aimed at preparing three types of biochar derived from rice husk via pyrolysis, including unactivated biochar, biochar chemically activated after with H₃PO₄, and biochar impregnated with γ-Fe₂O₃ nanoparticles. These materials were subsequently characterized using [...] Read more.

This study aimed at preparing three types of biochar derived from rice husk via pyrolysis, including unactivated biochar, biochar chemically activated after with H₃PO₄, and biochar impregnated with γ-Fe₂O₃ nanoparticles. These materials were subsequently characterized using Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), and Brunauer–Emmett–Teller (BET) analysis, which revealed favorable textural properties, such as an increased surface area and porosity, as well as the presence of functional groups that facilitate the adsorption of methylene blue and malachite green in aqueous solutions. Several factors that affect the adsorption capacity, including the type of material, pH effect, and adsorbent dosage, were evaluated and optimized. The adsorption behavior was analyzed using isotherm and kinetic models to better understand the mechanisms involved. Under optimal conditions, biochar@γ-Fe₂O₃ NPs emerged as the most effective material due to its high surface area, functionalized surface, and magnetic properties, allowing easy water recovery without the need for complex instrumentation. Among the kinetic models evaluated, the pseudo-second-order model exhibited the highest linear regression coefficient (R² = 0.99), supporting a chemisorption process driven by strong interactions and stable chemical bond formation between the adsorbate and the adsorbent, while equilibrium data fit well with the Sips isotherm model, indicating a combination of monolayer and multilayer adsorption mechanisms. This magnetic biochar achieved removal efficiencies of 97% for methylene blue and 95% for malachite green, demonstrating a high performance and reusability over four cycles. Moreover, a possible adsorption mechanism of MB on the magnetic biochar was proposed to explain the interaction between the dye and the adsorbent surface. Thus, this work demonstrates that magnetic biochar is a sustainable and cost-effective adsorbent for wastewater treatment, integrating circular economy principles by transforming rice husk into a high-value material. The incorporation of γ-Fe₂O₃ nanoparticles enhances adsorption while enabling magnetic recovery, providing an eco-friendly and scalable solution for dye removal. Full article

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

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