Bacterial cellulose (BC) is a biopolymer distinguished by its high purity, nanofibrillar structure, large specific surface area, and excellent mechanical and biocompatible properties, making it an attractive platform for biosensing applications. In this study, we report the in situ polymerization of p-phenylenediamine (PPD) on a bacterial cellulose matrix as a novel strategy for the fabrication of a functional composite material with potential biosensor applications. The polymerization process was carried out directly within the BC network, enabling uniform deposition and strong interfacial interactions between the polymer phase and the cellulose nanofibers. The resulting BC/PPD composite was characterized using spectroscopic, structural, and morphological analyses to confirm successful polymer formation and integration within the BC matrix. The modification led to noticeable changes in the physicochemical properties of bacterial cellulose, including enhanced electrical responsiveness and altered surface chemistry, which are critical parameters for sensor performance. Owing to the combination of BC’s porous architecture and the functional properties of poly(p-phenylenediamine), the developed composite demonstrates promising potential as a flexible, biocompatible sensing platform for future biosensor and bioelectronic applications.
Although photocurable compositions are widely used in 3D printing, protective coatings and biomedical materials, their polymerization in oxygen-containing environments is strongly hindered by oxygen inhibition, which prolongs the reaction time and reduces the conversion rate of monomers. This study investigated the effect of the reaction environment (argon atmosphere and liquid media: distilled water and CuSO4 solutions) on the kinetics of free-radical photopolymerization of four acrylic compositions (Bis GMA with TMPTA or EBECRYL 45, 130, 3300 oligomers). The kinetics were monitored using Fluorescence Probe Technology (FPT) with a coumarin 102 fluorescence probe and photorheology under 365 nm UV-LED irradiation. The results showed that in an argon atmosphere, oxygen inhibition is eliminated, resulting in the shortest induction times. In liquid environments, induction times are longer, but initial polymerization rates are higher than in the gas phase due to multiple reflections of UV radiation and a higher effective dose. The addition of Cu2+ ions partially suppresses this effect by absorbing light. The work provides new data on the design of photopolymerizable systems with increased oxygen resistance, which is important for applications in VPP photopolymerization 3D printing.
This paper proposes an artificial neural network model, MLP 17-37-5, to predict the share of five natural gas components (methane, ethane, propane, nitrogen, and carbon dioxide) in the natural gas mixture in a pipeline network, depending on selected calendar and weather factors. Natural gas composition variability in the pipeline network results from supplying it with gas of varying composition and from different suppliers. Using statistical analysis of 35,064 actual measurement data sets, factors (modelinput data) significantly affecting gas composition variability were selected. Models differing in structure (the MLP 17-37-5 model or five MLP 17-37-1 models) and the number of neurons in the hidden layer (from 20 to 230 neurons) were trained using sets ranging from 8,760 to 35,064 actual data points obtained using the chromatographic method. The quality of the models was assessed based on the correlation coefficient, while the quality of the forecasts was assessed based on the nRMSE error of the forecasts obtained for a new data set of 8,760 data points. The MLP 17-37-5 model was shown to predict natural gas composition with an average error of nRMSE = 0.321. The article proposes a ready-made tool, which has no equivalent in the literature, allowing for a significant reduction in the number of chromatographic tests performed to determine the composition of natural gas. This is a completely new approach to studying changes in the composition of natural gas over time, which in the proposed forecasting model depend on selected factors (not analyzed in chromatographic studies).
The integration of artificial intelligence and machine learning into chemical engineering represents a paradigm transformation that fundamentally reconceptualizes practice across molecular, process, and industrial scales. This comprehensive narrative review synthesizes recent advances in AI/ML methodologies, including graph neural networks, physics-informed neural networks, deep reinforcement learning, and generative artificial intelligence – and critically evaluates their applications spanning molecular property prediction, catalyst design, pharmaceutical development, reactor optimization, process control, and sustainability initiatives. Contemporary AI/ML approaches demonstrate unprecedented capabilities in navigating complex multiscale phenomena while maintaining computational tractability and physical interpretability. Landmark achievements include 71% reduction in experimental iterations for reaction optimization through deep reinforcement learning, 98% accuracy in predictive maintenance using LSTM-based fault detection, sub-1% prediction errors in virtual metrology for semiconductor manufacturing, and substantial improvements incarbon capture efficiency through machine learning-guided materials discovery. Physics-informed neural networks address the critical challenge of plant-model mismatch by synergistically integrating mechanistic knowledge with data-driven learning, enabling extrapolation beyond training domains while respecting conservation laws. Explainable AI techniques, particularly SHAP analysis, enhance operational acceptance by 52% in safety-critical applications through transparent decision-making pathways. Despite remarkable progress, persistent challenges remain in data quality and standardization, model interpretability for regulatory compliance, computational scalability for real-time control, and integration with legacy industrial infrastructure. The review identifies transformative future directions including multi-modal learning frameworks, transfer learning for data-scarce applications, quantum machine learning for molecular design, and human-AI collaborative systems. Successful deployment demands interdisciplinary collaboration uniting chemical engineering domain expertise with computational intelligence, guided by principles of transparency, reproducibility, and responsible innovation to address sustainability imperatives while maintaining operational excellence and safety in chemical manufacturing.
Although composting is a mature and economically favorable waste treatment technology, the controlled aerobic biodegradation of organic waste generates physicochemical conditions that are highly aggressive toward metallic and cementitious materials. This paper examines the corrosive environment in municipal solid waste composting facilities and its implications for material degradation and structural durability. Appropriate corrosion protection strategies were proposed based on the obtained results. The corrosivity of composting atmospheres arises from both chemical and microbiological processes. Elevated temperatures (40–70°C), persistent high relative humidity (>90%), and the presence of condensates enriched with organic acids, ammonia, carbon dioxide, and reduced sulfur compounds create an environment conducive to accelerated corrosion. Operational factors, including condensation–evaporation cycles and acid-laden runoff, accelerate corrosion kinetics and compromise protective coatings. Given the limited empirical data on composting-specific atmospheric corrosivity, the corrosion rate of steel and zinc was determined under the conditions of a real operating composting plant according to the methodology described in the ISO 12944-2 standard and the appropriate corrosivity categories were defined. Based on this, optimized anti-corrosion systems were developed for new and renovated municipal solid waste composting facilities.
The production of soda by the Solvay process is based on complex phenomena of mass and heat transfer in multiphase systems, involving gas-liquid and liquid-solid reactions. The foundation of such analyses lies in understanding and optimizing the nonlinearity and dynamics of the processes involved. This paper presents a digital design, optimization, and comparison of process data obtained through simulation of the post-filtration liquor heating together with ammoniacal recirculating condensates cooling using plate heat exchangers, aimed at replicating realistic operational conditions of the process. The obtained results demonstrate the potential of modeling technologies in predicting process parameters, optimizing operations, and identifying operational deviations. As a result of the simulations conducted in the digital environment, 99.04% agreement was achieved between the process parameters obtained from the model and those measured in production. The simulation data served as the input basis for production tests, which resulted in an increase of 25 K in the temperature of the post-filtration liquor directed to the distillation unit, which enables further research towards the potential reduction of heat consumption in the form of steam within the ammonia recovery installation.
Biofiltration technology has emerged as the most widely applied and cost-effective method for mitigating odorous and harmful compounds in waste air streams, particularly in municipal waste treatment facilities. This study investigated the influence of different packing materials and the effect of additional microbial inoculation on the removal performance of benzene, toluene, ethylbenzene and xylenes (BTEX) from real post-composting exhaust air in conventional biofilters. The results showed that the highest removal efficiency of these aromatic hydrocarbons (removal efficiency between 0.80 and 0.99) was achieved in biofilters packed with ceramsite when the packing material was additionally inoculated with a commercial bacterial preparation. Under these conditions, the total BTEX elimination capacity reached approximately 11.2 g/(m3 & centerdot; h). The findings demonstrate promising strategies for the cost-effective enhancement of existing biofiltration systems by selecting appropriate packing materials and inoculation procedures to improve the removal of benzene, toluene, ethylbenzene and xylenes from waste gas streams.
The results of the catalytic oxidation of isopropanol and hexane on Fe2O3/cenosphere (Fe2O3/C) and Ag/Fe2O3/cenosphere (Ag/Fe2O3/C) catalysts in a fluidized bed reactor are presented. The Fe2O3/C catalyst was developed by depositing an Fe2O3 layer on cenospheres by chemical vapor deposition of Fe, followed by oxidation of the Fe layer. The Ag/Fe2O3/C catalyst was obtained by Ag/Fe ion exchange. The catalysts were analyzed by AAS, XRD, and SEM-EDS methods, and the composition of the gaseous products formed during the process was determined using an FTIR analyzer. Catalytic oxidation of isopropanol and hexane was carried out at temperatures ranging from 200 to 450 degrees C. Enrichment of the cenosphere coating with Ag significantly improves the catalytic decomposition of isopropanol. The temperature of allmost full conversion of this pollutant to CO2 in the Ag/Fe2O3/C process is approximately 370 degrees C, while the same decomposition using an Fe2O3/C catalyst requires temperatures higher than 450 degrees C. Analysis of the toxicity of exhaust gases generated during the catalytic conversion of hexane showed that up to 450 degrees C, the gaseous products produced are more toxic than hexane. However, a decrease in the toxicity of the gaseous products during isopropanol conversion was achieved, both for the Fe2O3/C and Ag/Fe2O3/C processes.
Water contamination with heavy metals, including chromium ions, poses a significant environmental and health threat because of their toxic, carcinogenic, and mutagenic properties. Although Cr(III) is an essential trace element, its potential oxidation to Cr(VI) necessitates effective removal strategies. Among various techniques, adsorption is considered the most cost-effective and efficient method for chromium removal. Activated carbons (ACs), owing to their high surface area and porosity, are widely used adsorbents. However, their recovery from aqueous systems is challenging. To address this, magnetic activated carbons were synthesized by impregnating ACs with iron oxide (Fe3O4) nanoparticles via co-precipitation, enabling easy separation using an external magnetic field. The modified activated carbons obtained were characterised by XRD, N2 sorption at-196 degrees C, FT-IR, SEM-EDS, iodine adsorption number analysis, and magnetisation measurements. Their adsorption performance for the removal of Cr(III) ions was evaluated at an adsorbent dose of 1 g & centerdot; L-1 and a solution pH of 5.00, using initial Cr(III) concentrations ranging from 30 to 400 mg & centerdot; L-1 , which fall within the moderate concentration range typical of industrial wastewater. The data were fitted to Langmuir and Freundlich isotherm models to elucidate the adsorption mechanisms. From the obtained results it was proved, that the introduction of iron nanoparticles onto the surface of the AC, did not cause a significant decrease in the adsorption properties. The adsorption capacity varied in the range from 22.37 to 25.84 mg Cr(III) g-1. In addition, the effects of solution pH, adsorbent dose, adsorption temperature, and three successive adsorption cycles were investigated using single-point adsorption experiments.
In the present study, a new method involving ultrasound-assisted direct exfoliation with supercritical carbon dioxide is reported for graphene flake production. The influence of the starting material type-graphite (natural and expanded graphite) and duration of ultrasound treatment on the quality of the produced graphene-based material was assessed. By conducting scanning electron microscopy and Raman spectroscopy, it was found that the use of expanded graphite combined with 5 h of sonication in supercritical carbon dioxide yielded graphene nanoplatelets.
The paper presents a model of drug penetration into infected gingival mucosa via hydrogel overlays, which can be fully or partially covered with a polymer with limited permeability. The general geometry of the single drug carrier (single hydrogel overlay) was proposed as a flat cuboid with a triangular base. The number of overlays depends on the size of the infected area. The model assumptions were formulated to account for the unsteady diffusion of the component within the carrier, the tissue, and the biofilm formed by pathogens, as well as for diffusion and convective transport in the liquid phase. The system of corresponding differential equations was solved using CFD methods. Based on the modelling, the influence of key parameters such as polymer coverage of the carrier and hydrogel layer thickness was determined. It was demonstrated that external carrier coverage is crucial for effective, long-term therapy. Simulations showed that impermeable surfaces facing saliva slowed release by over 9-fold. Rendering those surfaces impermeable is especially desirable as the flow velocity increases. The distribution of the ingredient mass between system domains depends substantially on geometry, with hydrogel thickness influencing release dynamics.
The aim of this study was to evaluate the efficiency of soluble compound extraction from coffee using three cold brew process variants, addressing both technological and environmental aspects of this production method. Experiments were conducted with a custom-designed extraction basket and a forced-flow liquid system to ensure uniform raw material extraction. The process was carried out at temperatures not exceeding 30 degrees C, and the concentrations of total dissolved solids (TDS) and extraction yield (EY) were analyzed. Results showed that secondary extraction recovered up to 31.8% of the initial TDS, while replacing water with an enriched extract improved efficiency by 36.2%. The highest EY values (above 26%) were obtained in multistage variants, with a maximum TDS concentration of 2.65%. A short, 3-4-minute secondary extraction ensured effective performance, reducing the total process time to approximately 60 minutes-much shorter than the traditional 24-hour cold brew method-without loss of efficiency. The shorter process duration and its operation under low-temperature conditions can potentially improve efficiency and help reduce energy and water consumption, which in turn may also contribute to enhanced sustainability and resource efficiency in cold brew coffee production.
Pressure-driven membrane processes such as microfiltration, ultrafiltration, nanofiltration, and reverse osmosis are essential in water treatment, food, pharmaceutical, and wastewater applications. Poly(ethylene terephthalate) (PET) offers high mechanical strength, chemical resistance, and thermal stability, making it a promising alternative to conventional polymers used in membrane preparation. However, its poor solubility in environmentally benign solvents limits its application in wet phase inversion technology. This study proposes a reactive modification of PET via glycolysis with 1,5-pentanediol to enhance solubility in less toxic solvents. The two-step process - PET depolymerisation and subsequent polycondensation - yields poly(pentamethylene terephthalate), characterised by 1H NMR, gel permeation chromatography (GPC) and contact angle measurements. The modification reduces crystallinity, improves chain flexibility, and significantly increases solubility in solvents such as THF, Cyrener, and DMF at 40 degrees C. Membranes prepared from Cyrener solutions via wet phase inversion exhibit a porous, finger-like morphology confirmed by SEM. The hydrophilicity of the modified PET surface increased markedly (contact angle reduction from 110 degrees to 65 degrees). Combining chemical modification with a bio-based solvent provides a practical, sustainable pathway for producing PET-based membranes. The results demonstrate strong potential for developing environmentally friendly, durable membrane materials for advanced separation processes.
This paper presents the results of an electrovibrational investigation of the expansion unit in a micro-CHP ORC power plant. The study demonstrates that a maximum electrical output of approximately 0.64 kW was achieved in the ORC system at an HFE-7100 flow rate of 0.06 kg/s and a heat source power of 16 kW. It has been determined that, for any given working fluid flow rate, there is an optimal heat source thermal power at which the electrical output of the ORC system reaches its maximum. In contrast, for any preset heat source power and working fluid flow rate, there is an optimal generator load at which the electrical power output of the ORC system is maximised. It has been observed that, irrespective of the working fluid flow rate, changes in thermal power cause the electrical power output of the ORC system to vary along the generator's load line. The research also included vibration measurements, which showed that the operating conditions of the expander unit, including the electrical load on the generator, influenced the vibroacoustic behaviour of the machine.
The development of the contact surface between mixed liquids and the reduction of striation thickness and filament diameters of the dispersed phase enable effective diffusive transport of components under stable laminar flow conditions. Hydrodynamic focusing accomplishes this at the initial mixing stage by generating viscous stresses tangential to the liquid-liquid interface and normal stresses associated with pressure. As a result, the additive stream forms either an elongated filament (3D focusing) or a thin striation (2D focusing). This work examines the influence of the physical properties of liquids and the focusing method on the intermaterial surface area concentration in vertical flow systems, where gravitational segregation is avoided. The Navier-Stokes equations were solved for the axisymmetric core-ring flow in a pipe and the stratified symmetric flow in rectangular channels of different aspect ratios. The effects of differences in liquid density and viscosity, as well as the axial pressure gradient, on the transverse size of the focused stream and the contact surface concentration were determined for both upward and downward flow. In addition, the influence of the rectangular channel geometry on the residence-time distribution of the additive liquid was analysed.
This review provides a comprehensive overview of current fabrication techniques for inorganic sulfide structures, with particular emphasis on their synthesis, structural control, and application potential. Inorganic sulfides, especially transition metal sulfides, exhibit unique electronic, optical, and catalytic properties, rendering them highly attractive for applications in semiconductors, optoelectronics, and energy conversion. Various synthesis methods are discussed, including chemical vapor deposition, atomic layer deposition, hydrothermal processing, spray pyrolysis, electrodeposition, and physical vapor deposition. Their operational principles, advantages, limitations, and impacts on material properties are systematically analyzed. A comparative discussion highlights how synthesis conditions influence morphology, crystallinity, and functional performance. Furthermore, the review surveys the application landscape of sulfide nanostructures, focusing on photovoltaics, sensors, catalysis, and energy storage systems. It is concluded that although several fabrication methods have reached industrial relevance, challenges related to scalability, environmental sustainability, and process reproducibility remain. Emerging strategies, such as the integration of machine learning and green chemistry principles, offer promising avenues for optimizing sulfide material synthesis. This work thus serves as a valuable resource for materials scientists and engineers seeking to advance the design and production of next-generation sulfide-based technologies.
Olefin metathesis represents a key process in selective olefin production. Despite being relatively new compared to light paraffin dehydrogenation, its history spans from accidental discovery through Nobel Prize-winning catalyst development that significantly advanced catalysis science. A longstanding challenge in heterogeneous catalysis has been the limited number of carbene centers (active sites), in many cases, only a small fraction of the surface metal forms active sites. While photoreduction methods using CO with molybdenum catalysts emerged in the 1970s–90s to generate more active centers, the past decade has witnessed the development of simpler activation approaches. This review examines contemporary methods for activating heterogeneous metathesis catalysts, particularly focusing on activation in methane and olefin atmospheres. The potential use of paraffins introduces promising catalytic synergies. Furthermore, if paraffins prove effective in activating olefin metathesis catalysts, this could enable the integration of dehydrogenation reactions and facilitate scaling from laboratory to industrial applications.
The work aimed to investigate the possibility of selective separation of Co(II), Ni(II), Zn(II) and Cd(II) ions from chloride solution with variable chloride ion concentration (0.25, 0.5 and 1.0 M) using polymer inclusion membranes. In the studies, polymer inclusion membranes were used, with cellulose triacetate as the matrix, o-nitrophenyl octyl ether as the plasticizer, and 1-decylimidazole as a metal ion carrier. The receiving phase was demineralized water. The results of the studies on the transport of metal ions through polymer inclusion membranes with 1-decylimidazole as an ion carrier indicate a strong influence of the chloride ion concentration in source phase on the transport rate and their separation properties. The kinetic parameters such as the transport flux, the recovery factor, as well as the separation coefficients were determined for the experimental data. It was found that zinc(II) ions were the easiest to separate from the aqueous chloride solution. The recovery rates (%) of zinc ions, for chloride ion concentrations of 0.25 M, 0.5 M, and 1.0 M, were 71%, 88%, and 65%, respectively. The lowest recovery observed was for nickel(II) ions, which did not exceed 2%. In contrast, cadmium ions had removal recovery rates ranging from 5.5% to 6.5%, and for cobalt ions-from 2.5% to 14.5%, depending on chloride anion concentration in the source phase. The separation coefficient for zinc ions was the highest compared to the other ions. The results from studies on the transport of nickel(II), cobalt(II), cadmium(II), and zinc(II) ions through polymer inclusion membranes with 1-decylimidazole suggest that this process can be effectively used for the selective separation of Zn(II) ions from a multi-metal aqueous solution.
Laboratory testing plays a key role in ensuring the quality of the rubber production process. Quality has a direct impact on the efficiency and innovation of industrial enterprises. Control of the chemical structure of rubber at individual stages of production, carried out using advanced analytical methods such (Gel Permeation Chromatography), enables the detection of any non-compliance. FTIR enables an early assessment of structural changes in the material, which is the foundation for further research. DSC is used to study the stability of polymers. Its main purpose is to analyse changes in the mechanical, physical and physicochemical properties of polymers with a controlled increase or decrease in temperature. The technological process of rubber production also depends on the molecular weight of the sample at a given stage of the process. The analysis was performed using the GPC method. By using the selected testing techniques, the rubber production process can be corrected promptly, minimising waste and improving the quality of the final product. Regular testing, including the identification of moisture content, eliminates problems that can prevent precise measurements and the ultimate functionality of the rubber. Based on the results of the tests, changes were made to the rubber production technology, introducing an additional drying stage which enabled not only the elimination of the observed problems but also the optimisation of the process and improvement of the quality of the final product. Such measures make it possible not only to enhance productivity but also to meet the growing demands of customers and remain competitive in a dynamic market.
