Poly(ε-caprolactone) (PCL)-based materials have emerged as promising materials for water treatment due to their biodegradability, structural tunability, and compatibility with functional modifications. Beyond previous general PCL reviews, this work offers a focused assessment of PCL-based materials for water treatment, integrating fabrication routes, hierarchical structures, and treatment mechanisms into a coherent framework. A critical summary of recent progress in the design and application of PCL-based composites across four major treatment mechanisms (adsorption, membrane separation, photocatalytic degradation, and biodegradation) was provided, with an emphasis on underlying structure–property–performance relationships. The effects of fabrication strategies, including electrospinning, phase separation, freeze-drying, and 3D printing, on membrane morphology, surface functionality, and pollutant removal performance are systematically analysed. Strategies for performance enhancement are discussed in terms of polymer blending, nanofiller incorporation, and hierarchical structural design, highlighting how these approaches tune wettability, porosity, and interfacial interactions to enhance adsorption and separation efficiency. This review also examines multifunctional hybrid systems that couple photocatalysis with filtration or adsorption, along with the emerging use of PCL as a biodegradable carbon source and microbial carrier for denitrification. In addition, the review provides a comparative perspective that synthesises recent fabrication strategies and treatment pathways, clarifying their respective structural advantages and practical limitations. Despite notable advances, challenges remain in achieving long-term mechanical stability, recyclability, scalable fabrication, and consistent performance under real wastewater conditions. The review concludes with an outlook on integrating green fabrication, quantitative structure–performance correlations, and digital optimisation tools to accelerate the translation of PCL-based materials into practical, sustainable water treatment technologies.

Dry reforming of methane (DRM) simultaneously converts the greenhouse gases CH₄ and CO₂ into syngas with an H₂/CO ratio close to 1, offering a promising route for carbon emission reduction and sustainable feedstock production. Ni-based catalysts are attractive due to their low cost and strong CH₄ activation ability, but they suffer from sintering and carbon deposition at high temperatures, resulting in rapid deactivation. This study employed MgO-MgAl₂O₄ composites as supports to synthesize Ni-based catalysts with varying Ce/La molar ratios and doping contents via the sol-gel method. Optimized Ce-La ratios were further modified by Co co-doping to enhance activity and coke resistance. The catalysts were systematically characterized by SEM, BET, XRD, H₂-TPR, CO₂-TPD, TG, and XPS, and their DRM performance was evaluated in a fixed-bed reactor. Ce/La co-doping slightly decreased activity but greatly enhanced coke resistance. The catalyst with a Ce/La ratio of 75:25 and a total doping content of 7% exhibited the lowest coking level (8.19%) after 20 h of DRM, owing to the synergy between Ce-induced oxygen storage/release and La-enhanced CO₂ adsorption. Further incorporation of 3 wt% Co increased CH₄/CO₂ conversions and stabilized the H₂/CO ratio by improving Ni dispersion and reducibility, while also benefiting from Ce-La synergy in tuning oxygen vacancies and surface oxygen migration. This modification raised the fraction of surface reactive oxygen species (Oβ) to 75.9% and suppressed Ni sintering, thereby maintaining high activity and reducing coke formation (9.91%). The results demonstrate that rare-earth co-doping coupled with transition-metal adjustment provides an effective strategy for designing Ni-based DRM catalysts with high activity, stability, and coking resistance, offering valuable guidance for industrial catalyst development.

Mitigating global warming requires a rapid transition to carbon-neutral energy sources, with biomass-based heat production being a significant contributor. Wet scrubbers equipped with heat recovery enhance fuel efficiency by utilizing waste heat while removing particulate matter from flue gas. In this study, a Computational Fluid Dynamics (CFD) model was developed to investigate heat recovery and flow dynamics in a centrifugal wet scrubber installed at a 3MWth biomass-fired district heating facility, achieving an annual heat recovery of approximately 2 GWh. The model was validated against process data, showing a prediction error of 3.4 %, which is lower than other simulation models for similar purposes. This model, complemented by an Analysis of Variance (ANOVA), was used to explore different optimization strategies, including enlarging the contact zone opening, pre-scrubber moisture addition to the flue gas, and new compact geometries. Three scrubber designs were examined in-depth, focusing on gas flow, as well as heat and mass transfer. Increasing the contact zone opening from 100 to 150 mm yielded a 2 % boost in heat recovery. Coupling this design improvement with moisture addition can potentially elevate heat recovery by approximately 9 % over the conventional design. The new compact scrubber design can potentially increase heat recovery by 2.7 %, and further up to 9 % when combined with the moisture addition strategy. Notably, this compact geometry showed superior radial velocity and heat recovery, offering significant potential for material and space savings. This study provides valuable insights into the optimization of centrifugal wet scrubbers for improved heat recovery efficiency.

This study reports the fabrication of sandwich-structured PCL/PMMA@PCL/PCL electrospun membranes with PCL outer layers and a PMMA@PCL middle layer, designed to enhance mechanical strength and separation efficiency for oil-in-water emulsion treatment. To improve surface wettability, the membranes were treated with ethanol, introducing physically adsorbed hydroxyl groups without altering the chemical structure. A cold-pressing process was employed to increase membrane compactness resulting in enhanced mechanical performance. Morphological and structural characterisation confirmed the successful formation of the layered architecture, with reduced fibre diameter attributed to axial stretching under compressive force. Compared with single-layer PCL membranes, the multilayer structure exhibited a more balanced combination of mechanical robustness and separation performance. The Sandwich-1 membrane exhibited high oil rejection rates (∼95 %) and satisfactory mechanical properties in short-term filtration tests, indicating its suitability for water treatment applications. Although the flux recovery ratio (FRR) remained above 90 %, it was somewhat limited due to the basic deionized water rinsing, which was insufficient to fully remove trapped oil droplets. Long-term filtration further revealed a gradual flux decline attributed to membrane compaction and partial pore blockage. These findings highlight the potential of structural and physical surface modifications for developing high-performance membranes and suggest that future optimisation should focus on durable hydrophilic treatments and more effective antifouling and cleaning strategies to improve long-term operational stability.

A novel Cu₂LaO₄/ZSM-5 sorbent was synthesized using the sol–gel method, and the role of H₂S in enhancing Hg⁰ removal was investigated through experimental and theoretical approaches. Mercury removal performance was evaluated in a fixed-bed reactor under simulated syngas conditions, revealing that H₂S significantly promoted removal efficiency, achieving 95.6 % at 200 °C. In contrast, H₂ and CO inhibited Hg0 removal by depleting surface oxygen species. The addition of H₂S mitigated these effects, facilitating Hg0 adsorption and oxidation via a Langmuir–Hinshelwood mechanism. Density functional theory (DFT) calculations confirmed strong chemisorption of Hg0 and H₂S on the Cu₂LaO₄ surface, with adsorption energies of −123.71 kJ/mol and −168.98 kJ/mol, respectively. The reaction to form HgS had a manageable energy barrier of 25.80 kJ/mol and an exothermic enthalpy of −196.82 kJ/mol, with HgS formation as the rate-limiting step. This study highlights the effectiveness of Cu₂LaO₄/ZSM-5 for mercury capture and its potential application in industrial syngas purification.

Poly(ε-caprolactone) (PCL) is a widely used biodegradable polymer in tissue engineering due to its excellent biocompatibility, processability, and mechanical tunability. However, its clinical translation is limited by inherent drawbacks such as hydrophobicity, low bioactivity, and slow degradation. This review aims to provide a comprehensive and critical evaluation of PCL-based scaffolds, focusing on fabrication strategies, composite modifications, and their performance across diverse tissue engineering applications. Four primary fabrication techniques-electrospinning, 3D printing, freeze-drying, and phase separation-are systematically compared in terms of structural characteristics, mechanical performance, scalability, and biological functionality. Various material modifications involving natural polymers (e.g., gelatin, chitosan, collagen), synthetic polymers (e.g., Polylactic acid, Poly(lactic-co-glycolic acid), Polyethylene glycol) and inorganic or conductive additives (e.g., hydroxyapatite, metal oxides, carbon nanomaterials) are discussed for their roles in enhancing scaffold bioactivity, degradation rate, and tissue-specific functionality. Application-specific insights are provided for PCL-based scaffolds in regenerating bone, skin, nerve, ligament, cartilage, dental and periodontal tissues, as well as emerging roles in cardiac, pulmonary, and hepatic repair. The review also highlights recent advances in intelligent scaffold design using computational modelling and artificial intelligence, and assesses sustainability, sterilisation, and regulatory challenges for clinical translation. Despite current limitations, PCL-based scaffolds show great promise for personalised and functional tissue regeneration. Future research should focus on integrating multiscale fabrication, responsive materials, green manufacturing processes, and standardised evaluation protocols. Interdisciplinary collaboration will be essential to overcome translational barriers and realise the clinical potential of PCL-based biomaterials in regenerative medicine.

This study examines the integration of biochar and bio-oil co-production within an existing biomass-fired district heating system.Through scenario-based modeling, three operational strategies were assessed: (i) biochar production aligned with actual heat demand, (ii) full-capacity operation to maximize biochar output, and (iii) combined production of biochar, heat, and bio-oil via pyrolysis gas condensation. The analysis, based on real operational data, included energy and mass balances, financial performance metrics (payback period and return on investment), and carbon sequestration potential. Results demonstrate short payback times (<4 years) across scenarios. Annual CO2 sequestration ranged from 3,650 to 8,400 tonnes, highlighting the system’s climate mitigation potential. Sensitivity analysis identified investment cost and heat price as key economic drivers. The findings support retrofitting existing biomass DH systems with pyrolysis technology as a viable strategy for carbon-negative energy production and resource valorization.

Abstract: Establishing the quantitative relationships between heavy metals and mineral phases in coal gangue is essential for its comprehensive landfill and refined utilization. In this study, the Guandi coal gangue was subjected to a stepwise dissociation method using seven concentration gradients (0.1, 1.0, 4.0, 6.0, 8.0, 10.0, 12.0 mol/L) of aqua regia and hydrofluoric acid. Combined with the Rietveld refinement method, inverse matrix calculations of residual fractions of mineral phases and dissociation degrees of heavy metals after dissociation, the quantitative relationships between Pb, As, Zn, Cr and the mineral phases were determined. The results show that kaolinite, quartz, pyrite, and the amorphous phase are the primary host phases for Pb, As, Zn, and Cr, with their contents in crystalline phases ranging from 71.36% to 87.68%. Validation via the standard addition method demonstrates that the relative standard deviation of the stepwise dissociation for Pb, As, Zn, and Cr is​ ≤7.23%, with spike recovery rates ranging from 85.43% to 112.85%, indicating favorable test results. Sequential chemical leaching demonstrates that heavy metals are mainly distributed in stable aluminosilicate-bound state and carbonate or oxide-bound state. The toxicity characteristic leaching procedure test indicated that Cr exhibited high toxicity and thus required long-term monitoring. The results of this study provide important theoretical guidance for the comprehensive landfilling and resource utilization of Guandi coal gangue, and the established analytical method can be extended to studies on quantitative relationships between heavy metals and mineral phases in other tailings.

Electrospun nanofibrous membranes are widely used in biomedical, filtration, and energy applications, where fibre diameter plays a key role in determining membrane morphology and performance. Conventional manual measurement of fibre diameters from scanning electron microscope (SEM) images is inefficient and subject to human error. This study compared two image-processing tools, DiameterJ and SIMPoly, to improve measurement efficiency and accuracy of fibre diameter. DiameterJ was selected for its higher reliability and batch-processing capability. Using DiameterJ, 144 datasets were collected and used to train an artificial neural network (ANN) model with four electrospinning parameters (molecular weight, solution concentration, flow rate, and tip-to-collector distance) as inputs. The ANN model showed high predictive accuracy, with correlation coefficients exceeding 0.97 and prediction errors below 4%. A response surface methodology (RSM) model was also developed for comparison, but showed limited predictive capability for unseen conditions, with errors up to 28.57%. The ANN exhibited superior reliability and generalizability. Index of relative importance (IRI) and contour analyses revealed molecular weight and concentration as dominant factors. The proposed integration of automated image analysis with ANN provides a data-driven and scalable framework for intelligent design and optimisation of electrospun materials, with potential applicability across diverse fibrous manufacturing systems.

This study explores the potential and impact of electricity cogeneration using Organic Rankine Cycle (ORC) integrated with small-scale biomass boilers within district heating systems. An analysis is conducted on a 3 MW_th biomass-fired district heating plant in southern Sweden. Process monitoring data, collected over a one-year period from the plant, serves as the basis for simulation and analysis. The study examines operational changes and fuel usage at a local level, together with an extension to a regional scale considering both short-term and long-term energy system implications. The results show that integrating a 200 kW_e ORC unit with the existing boiler having a flue gas condenser is cos-optimal and could cogenerate approximately 1.1 GWh electricity annually, with a levelized electricity cost of €64.4 per MWh. This is equivalent to a system power-to-heat ratio of 7.5%. From a broader energy system perspective, this efficient integration could potentially reduce CO₂ emissions by 234-454 tons per year when the saved energy locally is used to replace fossil fuels in the energy system, depending on how biomass is utilized and what type of fossil fuels are replaced. Increasing installed capacity of ORC unit to maximize electricity co-generation could result in a carbon abatement cost ranging from €204 to €79 per ton CO₂. This cost fluctuates depending on the installed capacity, operation of the ORC units, and prevailing electricity prices. The study highlights the trade-off between financial gains and CO₂ emission reductions, underscoring the complex decision-making involved in energy system optimization.