Abstract: This study investigates the chemical composition, liquefaction behavior, and polyurethane foam (PU) properties of two lignocellulosic biomasses, Red Angico (Anadenanthera colubrina) and Mahogany (Swietenia macrophylla), as potential sources of bio-based polyols. Detailed chemical characterization revealed that Red Angico has high α-cellulose (48.44%) and moderate hemicellulose (25.68%) content, while Mahogany shows the inverse, with high hemicellulose (56.11%) and low cellulose (18.24%), influencing their reactivity during liquefaction. Liquefaction trials using a polyalcohol system (glycerol:ethylene glycol) demonstrated higher conversion efficiency for Mahogany, reaching 93.4% at 180 °C in 60 minutes, compared to 73.9% for Red Angico. Hydroxyl value analysis revealed increasing functionality for Mahogany polyols with time, whereas Red Angico showed declining values, indicating possible recondensation reactions. PU foams were synthesized using the resulting polyols, with compressive strength and modulus increasing with isocyanate index. Red Angico foams, despite lower OH values, displayed superior mechanical performance, attributed to their lower hydroxyl content favoring optimal crosslinking. Water content, used as a chemical blowing agent, negatively impacted compressive strength for both foams due to increased porosity. Results highlight the species-specific influence of chemical composition on liquefaction behavior and foam performance, suggesting tailored processing conditions are essential for maximizing bio-based PU properties.

Abstract: Transitioning to more efficient and digital industrial processes requires plant design methodologies that go beyond traditional approaches and respond to the operational challenges of Industry 4.0. The objective of this study was to integrate Artificial Intelligence (AI) and Augmented Reality (AR) into SLP methodology for the design of a cosmetic emulsion production plant. A case study was developed based on the layout of a previously reported cosmetic plant by creating a preliminary layout using SLP and evaluating it using AI based on technical prompts. Subsequently, the refined model was represented in three dimensions and validated in a real environment using AR. The results show that AI identified opportunities for improvement in operational flows, relationships between critical areas, and space proportions, allowing for precise adjustments without altering the original design logic. Likewise, AI verification and immersive validation using AR confirmed the spatial compatibility of the layout with the selected site, facilitating the early assessment of circulation, access, and volumetric behavior. Thus, the sequential integration of SLP + AI + AR demonstrated its potential to reduce uncertainty in the early stages and move toward modernizing plant design in line with Industry 4.0 principles.

Abstract: Additive manufacturing is one of the most efficient approaches for fabricating components with complex geometries. Among the wide variety of additive manufacturing technologies, extrusion-based processes using gel materials are attracting increasing attention from researchers. In this work, we consider the extrusion of gel materials for 3D printing and propose a method for calibrating additive manufacturing equipment based on optimization of the pre-extrusion and retraction parameters. Experimental studies were carried out on the extrusion of materials with different rheological properties. The capabilities of the proposed calibration method to improve printing quality are demonstrated using gel materials based on partially crosslinked sodium alginate with a viscosity of 1053 Pa·s. A multi-material 3D printing process was also implemented, enabling the combination of different materials within a single fabrication process. To realize the proposed 3D printing approach, we present a custom-built setup that allows the use of two extrusion modules for materials with different physicochemical properties. The capabilities of the developed system are demonstrated by fabricating a structure with an internal hollow channel and a structure based on a sodium alginate–chitosan polyelectrolyte complex.

Abstract: In this study, the dyeing kinetics of polyamide fabrics with acid dyes, Telon Blue M2R, under both conventional and microwave-assisted heating conditions were comprehensively investigated. While the conventional dyeing reaction was completed in 30 minutes, microwave-assisted dyeing was performed in the microwave device for 10 minutes. Dyeing kinetics were investigated as a function of reaction time, reaction concentration and dyeing temperatures. The K/S values (color depth) of the dyed fabrics were correlated with the concentration. A significant reduction in the dyeing process time for polyamide fabric was observed with microwave heating compared to the conventional method. Kinetic analysis revealed that the PSO kinetic model provides a better fit to the experimental data on the diffusion process of acid dye in polyamide fabrics, as evidenced by higher correlation coefficients (R²) compared to the PFO model. The activation energy of the reaction in dyeing was found to be 63.27 kJ/mol, and the Arrhenius constant was determined as 7,20 x 10¹⁰ L/g.min in conventional media and 18,70 x 10¹⁰ L/g.min in microwave media. The Arrhenius factor in the microwave medium was more than two times higher than in the conventional one.

Abstract: Trichloroethylene (TCE) and tetrachloroethylene (PCE) are chlorinated organic liquids widely employed in various industrial processes. However, due to their high toxicity and cancerogenic proprieties, these compounds are recognized as environmental pollutants. Therefore, the removal of TCE and PCE from wastewater is a crucial objective for environmental protection. This work investigated the adsorption capacity of syndiotactic polystyrene (sPS) fibers, activated in the nanoporous crystalline δ form, to remove volatile organic compounds from aqueous solutions. TCE can be adsorbed in the nanoporous crystalline δ form of sPS, leading to the formation of a clathrate structure, in which it acts as the guest molecule. This adsorption mechanism allows for high process selectivity, as well as the capture of even trace amounts (in the ppb range) of the pollutants under consideration, in relatively short times (e.g., 67 hours). Also, a process with two successive adsorption tests was performed replacing the solid used for the first contact with the contaminated solution with fresh δ-sPS fibers. This approach allowed the reduction of TCE concentration down to 8 ppb. In conclusion, δ-sPS nanoporous fibers demonstrated a great potential for the efficient removal of chlorinated organic compounds from wastewater, providing a promising alternative to conventional adsorption processes.

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The Bayer process, the dominant method of alumina production for over a century, faces several challenges, including low iron content in bauxite residue, increased caustic alkali consumption and low alumina recovery rates. This article focuses on studying electrolytic reduction processes of bauxite iron minerals in alkaline solutions as a potential improvement to the traditional Bayer process for producing alumina. The research employs a metal mesh cathode at the bottom of an electrochemical cell to simultaneously reduce iron minerals and leach aluminium and silica from coarse boehmite bauxite before milling and high-pressure leaching. Preliminary thermodynamic research indicates that the presence of both hematite (α-Fe₂O₃) and chamosite ((Fe²⁺,Mg,Al,Fe³⁺)₆(Si,Al)₄O₁₀(OH,O)₈) in this type of bauxite helps to achieve a higher iron concentration in the solution. Cyclic voltammetry revealed that, in the initial stage of electrolysis, overvoltage at the cathode decreases as metallic iron deposited and conductive magnetite form on the surface of the particles. After 60 min, the reduction efficiency begins to decrease. The proportion of the current used for magnetization and iron deposition on the cathode decreased from 89.5% after 30 min to 67.5% after 120 min. Studying the electrolysis product using SEM-EDS revealed the formation of a dense, iron-containing reaction product on the particles' surface, preventing diffusion of the reaction products. Mössbauer spectroscopy of the high-pressure leaching product revealed that the primary iron-containing phases of bauxite residue are maghemite (Fe₃O₄), formed during the hydrolysis of sodium ferrite (Na₂FeO₄).

Abstract: Effective management of discharged wastewater quality is crucial for maintaining public health, preserving aquatic ecosystems, and ensuring compliance with environmental regulations. However, spatial and temporal data sparsity remains a fundamental constraint. This review critically examines the role of Geographic Information Systems (GIS) and statistical interpolation techniques in bridging these data gaps to create continuous maps of wastewater quality parameters (e.g., BOD₅, COD, TSS, nutrients). Moving beyond a simple compilation of methods, this paper presents a comprehensive framework that categorizes and evaluates interpolation techniques, ranging from deterministic and geostatistical approaches to emerging machine learning (ML) and hybrid models, based on their ability to address specific challenges in wastewater systems. A key contribution is a meta-analysis of 28 comparative studies, which quantitatively synthesizes evidence on the prediction accuracy (RMSE) of different methods. The results indicate that machine learning and hybrid models significantly outperform deterministic and basic geostatistical methods, with a pooled reduction in RMSE of 18.4% (95% CI: 12.1-24.3%) compared to Ordinary Kriging. We explore applications in pollutant tracking, impact assessment, and infrastructure planning, highlighting how the integration of real-time sensor data (IoT) and remote sensing is transforming static maps into dynamic monitoring tools. Finally, we present a forward-looking roadmap for research, informed by our quantitative findings, emphasizing the need for hybrid modeling frameworks that leverage AI, the development of digital twins for wastewater networks, and the integration of uncertainty quantification into decision-support systems. By quantitatively synthesizing the current state-of-the-art and identifying critical knowledge gaps, this review aims to guide future research towards more intelligent, adaptive, and reliable spatial assessments of wastewater quality.

Abstract: The commitment to the Sustainable Development Goals and the need for increasing circularity of industrial processes call for the exploitation of byproducts to generate value-added chemicals in cost- and energy-advantageous processes. In this process simulation-based research, two technologies were evaluated for the synthesis of isoamyl acetate from fusel oil: A) an indirect process, and B) a direct process using reactive distillation. Aspen Hysys v14.0 was used for the simulation. A sensitivity analysis was performed to identify the influence of operating parameters on product purity, isoamyl acetate recovery and productivity, and energy consumption. Technology B was found to be the most favorable, obtaining 22.27 kg/h of isoamyl acetate with a purity of 98%. The total consumption of cooling water and heating was 87.6 MJ/h and 88.22 MJ/h, respectively. Based on the best conditions, a technical-economic analysis was performed that demonstrated the viability of the process, obtaining a net present value (NPV) of US$3,587,110/year, an internal rate of return (IRR) of 38.95% and a payback period (PP) of 5.05 years. If acid recirculation is considered in the process, an NPV of US$7,232,950, an IRR of 56.34%, and a PP of 3.56 years are obtained.

Abstract: This research optimized the parameters of Ohmic Heating Pasteurization (OHP) for passion fruit juice utilizing a Box–Behnken design. Researchers assessed how temperature (75–95°C), holding time (15–45 s), and voltage gradient (10–30 V/cm) influence the system performance coefficient (SPC), total color difference (ΔE), and vitamin C retention. The op-timal conditions were 82.5°C, 25 s, and 18.5 V/cm, achieving a microbial reduction exceeding 5 log CFU/mL, 45% retention of vitamin C, minimal color alteration (ΔE = 7.56), and an SPC of 0.85. Traditional pasteurization (85°C, 25 s) preserved merely 10% of vitamin C, induced a more significant color alteration (ΔE = 14.87), and resulted in a reduced SPC (0.54). The OHP-treated juice demonstrated superior antioxidant activity and prolonged shelf life (70 days at 8°C) in comparison to conventionally processed juice (28 days). The research as-sessed enzymatic activity (POD, PPO), demonstrating that OHP achieved superior inactiva-tion, thereby enhancing color stability and long-term product quality. These results indicate that OHP is a promising and sustainable thermal technology for high-acid fruit juice pas-teurization, combining energy efficiency with superior quality retention and enzyme inac-tivation.

Abstract: In this study, the effect of hot air drying (HAD, 55 °C), infrared drying (IRD, 62 W), and combined infrared and hot air drying (CD) with different IR pretreatment times (30, 60, 90 min) on the drying kinetics, color, and rehydration of orange and black carrots was evaluated. IRD was characterized by the shortest drying time (140–160 min) and the highest effective moisture diffusion coefficient (1.40–1.42 × 10⁻⁹ m²/s), shortening the total drying time by 65–70% compared to HAD. The combined drying method (CD-90) with a 90-min IR pretreatment showed the best performance in terms of color retention (ΔE = 3.60–4.80) and rehydration rate (5.07–5.19), while achieving diffusion rates comparable to IRD. The Midilli-Küçük model described the drying kinetics of carrots with high accuracy for all drying methods (R² ≥ 0.9998). The results also indicated carrot variety-specific differences, with black carrots exhibiting faster moisture diffusion and higher structural strength. Results obtained in this study have shown that infrared-hot air combined drying, especially with extended infrared pretreatment of 90 minutes, is an energy-efficient and industrially applicable way to produce high-quality dried carrots capable of maintaining rehydration capacity and color retention capability.

Abstract: We present a theoretical and numerical framework for computing asymmetric two-dimensional droplet shapes on surfaces with a sharp wetting boundary separating regions of distinct contact angles. Through Lagrange multiplier analysis of the constrained Gibbs free energy functional, we derive a spreading condition that relates the contact line position ratio to the ratio of spreading functions, which encode the unbalanced Young stress at each contact line. Under geometric self-similarity assumptions valid for moderate gravitational effects, this condition reduces to an explicit algebraic relation. Hydrophilic surfaces exhibit intuitive spreading toward regions with better wettability, producing flattened asymmetric profiles. Conversely, hydrophobic surfaces display counterintuitive behavior where droplets preferentially occupy regions with poorer wettability, maintaining tall compact geometries. Bond number variations from capillary-dominated to gravity-influenced regimes demonstrate systematic gravitational flattening, yet the contact line position ratio remains invariant across gravitational conditions, confirming that horizontal partitioning depends exclusively on interfacial energy ratios rather than body forces. Mixed hydrophilic-hydrophobic boundaries violate equilibrium conditions and drive spontaneous droplet migration. These findings provide quantitative design criteria for applications requiring controlled droplet positioning on patterned substrates.

Abstract: Spray-drying production of litchi powder is frequently constrained by low yield and unstable quality, largely attributable to variations in fruit sugar–acid profiles. To elucidate the compositional factors affecting powder performance, ten litchi cultivars with distinct sugar–acid ratios were processed under identical conditions. Baitangying produced superior powder with the highest yield (89.23±1.25%), solubility (98.17±0.49%), and glass transition temperature (52.17±2.00 ℃). Jizuili also performed well. Both high-sucrose, low-acidity cultivars demonstrated excellent drying efficiency and storage stability. Conversely, high-acid and reducing-sugar cultivars (Feizixiao, Guanxiangli) retained more moisture (> 7%) and showed lower glass transition temperature, suggesting inferior stability. Correlation analysis revealed that fructose (ρ = −0.794, p < 0.001) and titratable acidity (ρ = −0.770, p < 0.001) were negatively correlated with yield, while sucrose was positively associated with yield and color lightness (ρ = 0.630, p < 0.05). Antioxidant capacity varied among cultivars and was mainly governed by total phenolics and litchi thaumatin-like protein, with Feizixiao and Jingganghongnuo showing the highest FRAP values (19.36 ± 0.12 and 17.38 ± 0.33 μg TE/mg DW). Overall, intrinsic sugar–acid profiles fundamentally determine the drying efficiency, powder stability, and bioactive retention of litchi powder.

Abstract: Battery health monitoring is essential for ensuring the safety, longevity, and efficiency of energy storage systems, particularly in critical applications where reliability is important. Traditional methods for assessing battery degradation, such as Electrochemical Impedance Spectroscopy (EIS), are effective but impractical for large-scale deployment due to their time-intensive nature. This study introduces a novel model-based approach for estimating a critical indicator of battery aging, the internal resistance. Using the NASA battery dataset, specifically focusing on batteries number 5 and 7 with NCA chemistry, a comprehensive framework that integrates advanced predictive models, i.e. the Random Forest Regressor (RF), the XGBoost Regressor (XGBR), the Gated Recurrent Unit (GRU), and the Long Short-Term Memory (LSTM) networks, was developed. The models were evaluated using common regression metrics, while hyperparameter tuning was performed accomplished to optimize performance. The results demonstrated that recurrent neural networks, particularly GRU and LSTM, effectively capture the temporal dependencies inherent in battery aging, offering more accurate State of Health (SOH) predictions. This approach significantly improves computational efficiency and prediction accuracy, paving the way for practical applications in Battery Management Systems (BMS).

Abstract: In the described studies, raw material from chemically recycled petrochemical foam and biobased polyurethane foams (100% of rapeseed oil polyol were used in polyol premix) were utilised in order to obtain viscoelastic foams. The recycled foams exhibited differ-ences in chemical structure, resulting in the formation of four different repolyols. The ob-tained repolyols were employed as replacements for 10 to 30% wt. of the petrochemical polyol in the mixture utilised to produce viscoelastic polyurethane foams. It was deter-mined that the chemical structure of the polyol utilised for the foam's initial production influences the properties of the repolyols obtained, and thus also the properties of the vis-coelastic foams obtained using them. It was found that foams obtained with the addition of 10%wt. repolyols were character-ized by the best properties among the obtained modified foams, comparable or even better than in the case of petrochemical reference foam. The apparent density of such foams was about 70 kg/m3. Depending on the type of repolyol used, the hardness of the foams ranged from 2 to 8 kPa, and the comfort factor was between 2.5 and 5.0. The foams obtained were characterised by their ability to absorb energy, as evidenced by a resilience of not more than 10% in most cases. However, increasing the percentage of repolyol in the reaction mixture caused too much changes in the structure of the polymer chains, disrupting the arrangement of rigid and elastic segments, which caused the hardness to increase signifi-cantly, and the foams were more susceptible to permanent deformation.

Abstract: This study produces high-purity nano-silica from corn straw ash (biomass power plants) using an alkaline fusion derived sodium silicate solution. CO₂ replaces traditional acids in the carbonation reaction, enabling high extraction yield (93.11%). The process addresses the gap in directly utilizing combustion ash for such high-purity silica. Key optimal conditions identified were: 5 M HCl concentration, NaOH fusion reagent, 1:1.2 mixing ratio, 3 M NaOH solvent, and 12 h ripening. The resulting nano-silica achieved 92.73% purity, 10-50 nm particle size, 270 × 10⁻⁵ m³/kg DBP absorption, 55.9916 m²/g specific surface area, 6.38% LOD, and 6.69% LOI. These properties meet national standards for premium, loosely structured nano-silica. This method provides an economical and effective silicon source, reducing costs and offering economic-environmental benefits.

Abstract:

Bioethanol continues to gain popularity as a viable alternative to fossil fuels considering that it is a renewable fuel obtained from biomass. This study explores the optimization of bioethanol production from three potentially useful feedstocks that is marine algae, vegetable waste and lignin-based cellulosic biomass which includes sugarcane, switchgrass, Wood Chips and Corn Stover. Vegetable waste is widely available, but to reduce contamination and maintain sustainability, it must be collected and handled carefully. Although lignocellulosic biomass is a specific energy crop choice, pre-treatment is required to transform its complex structures efficiently. While marine algae grow quickly and do not compete with land resources, large-scale cultivation and harvesting systems still require improvement. Each feedstock's advantages and disadvantages are examined, taking into account issues with conversion, sustainability, and availability. Kinetic modeling will be employed to analyze reaction rates, identify key parameters, optimize process conditions, and guide the development of cost-effective, sustainable bioethanol production. Individual MATLAB simulation models of Saccharomyces cerevisiae were developed for potato peels, sugarcane bagasse, and brown marine algae, revealing their unique bioresource potential. Simulation model analysis for potato peels concentrated mainly on fermentation based on the Monod equation and Michaelis-Menten kinetic models of starch hydrolysis having carbohydrate content of 21.05g by difference. While for marine algae, Saccharina latissima was considered which had an Alginate content of around 34.5% dry weight and it addressed how the polysaccharide is extracted and transformed from it. Sugarcane bagasse models included its complex lignocellulosic structure and pre-treatment simulations containing carbohydrate content of 10.9g.

Abstract: Ammonia, widely regarded as the "hydrogen carrier of the future," offers high hydrogen content, ease of production, and a well-established infrastructure for handling and transportation on a global scale. Meanwhile, ammonia cracking requires heat supply at high temperatures and induction heating provides efficient, precise, and rapid heating to conductive materials of different shapes and sizes. Therefore, this work presents a proof of concept for ammonia cracking using induction heating with 3 different reactor configurations: (1) a 3D metal workpiece; (2) a 3D metal workpiece and Ni/Al2O3 catalyst; and (3) only Ni/Al2O3 catalyst. The performance of the inductively heated reactor is also compared to the one using an electric furnace. The results showed that the reactor configuration containing both the workpiece and the catalyst was the most efficient in terms of electric power usage to achieve high temperatures quickly; the least efficient configuration is the one with just the catalyst. While the workpiece surface showed minor structural changes after time on stream, the system’s performance was not affected. Overall, the introduction of the 3D workpiece allowed for fast and uniform conversion and heating within the reactor enabling efficient and dynamic process control when applying induction heating to chemical reactors.

Abstract: The pristine (p-SiO₂) and sulfonated silica (s-SiO₂) particles were created using the sol-gel and Stober methods. Furthermore, this study sought to show the impact of calcination time and surface changes on the morphology, and hence functionality, of the silica nanoparticles synthesised as potential fuel cell membrane additives. Tetraethyl orthosilicate (TEOS) was used as a silica precursor dissolved in water, with sulphuric acid serving as the sulphonation agent. Parametric data on particle morphology, such as particle size, porosity, total surface area, and agglomeration, were measured and evaluated using BET, Fourier transform infrared (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM). The amorphous nature of silica nanoparticles was confirmed by XRD analysis. The BET outcome data acquired for the synthesised silica particles were surface area ranges from 271 to 487 m²/g, pore diameter 12.10 nm - 21.02 nm, and total pore volume 0.76 - 1.58 cm³/g. This data gives crucial characteristics for designing appropriate silica nanofillers for hybrid fuel cell membranes. As a result, the gathered data can be used to make future decisions about silica synthesis methods for fuel cell applications.

Abstract: Rotating packed beds (RPBs) have recently gained significant attention from researchers as a promising approach to intensify the performance of traditional packed columns. Although numerous lab-scale experimental and numerical studies on RPBs are available in the literature, there is a scarcity of operational data for large-scale RPBs. In this research, high gas flow rates in large-scale RPBs are investigated using CFD simulation to predict the dry pressure drop in a rotating bed. A 2D geometry with periodic boundary condition was applied to simulate the turbulent gas flow in a rotating packed bed. The simulation results offer valuable insights into the gas flow dynamics within rotating beds, highlight-ing the pressure and velocity variations that occur at high rotational speeds. A semiem-pirical correlation successfully replicated the results obtained in this study and can be uti-lized to predict the pressure drop in large-scale RPBs under operating conditions similar to those studied in this research.

Abstract: In vitro cultured biomass of Rindera graeca , a rare endemic plant, is an efficient renewable source of bioactive naphthoquinones, e.g., rinderol, a potential bioactive inducer of apoptosis in cancer cells. Bioengineering strategies, as biomass immobilization on functionalized biomaterial-based scaffolds, elicitation by chitosan, and in situ extraction of metabolites, are tested for intensifying naphthoquinones production in R. graeca hairy roots. The aim of the study was to investigate the effects of hybrid poly(lactic)–chitosan scaffolds on biomass proliferation and rinderol production in R. graeca hairy roots. Effects of chitosan origin (fungal or squid), viscosity (10-3500 cps), and concentration (up to 45%) in the developed hybrid scaffolds have been quantitatively identified, and the results were compared to the reference culture system containing an unmodified PLA-based construct. Applying PLA–chitosan scaffold containing 33% of fungal chitosan resulted in 635 times higher rinderol production (3660 µg gDW-1) than the application of reference scaffolds. Among the tested parameters, the chitosan concentration in the hybrid scaffolds revealed significant importance in rinderol production. To sum up, the developed hybrid PLA-chitosan scaffold may be recognized as a functional key element supporting the production of naphthoquinones in cultures of R. graeca biomass.