Search Results (678)

Alkali-activated materials (AAMs) offer a promising low-carbon alternative to Portland cement, but their development has been dominated by fly ash and slag, whose availability is increasingly limited. This research explores waste brick powder (WBP) and metakaolin residue (RN), two abundant yet underutilized by-products, as blended precursors for sustainable binder design. The novelty lies in demonstrating how complementary chemistry between crystalline-rich WBP and amorphous RN can overcome the drawbacks of single-precursor systems while valorizing construction and industrial residues. Pastes were prepared with varying WBP/RN ratios, activated with alkaline solutions, and characterized by Vicat setting tests, isothermal calorimetry, XRD with Rietveld refinement, MIP, SEM, and mechanical testing. Carbon footprint analysis was performed to evaluate environmental performance. Results show that WBP reacts very rapidly, causing flash setting and limited long-term strength, whereas the incorporation of 30–50% RN extends setting times, sustains dissolution, and increases amorphous gel formation. These changes refine the formed reaction products, leading to compressive strengths up to 39 MPa and flexural strengths of 8 MPa at 90 days. The carbon footprint of all blends remained 392–408 kg CO₂e/m³, thus providing about a 60% improvement compared to conventional Portland cement paste. The study establishes clear design rules for waste-derived blended precursors and highlights their potential as circular, low-carbon binders. Full article

In this study, cottonseed oil biodiesel and waste lard biodiesel were produced through a transesterification process and blended with conventional diesel at different ratios (B10 and B20). The performance and emission characteristics of these fuels were systematically evaluated in a single-cylinder, four-stroke, water-cooled diesel engine operating at speeds of 1000–1800 rpm under a constant 50% load. The physicochemical properties of the fuels were analyzed, and engine parameters including brake-specific fuel consumption (BSFC), brake thermal efficiency (BTE), exhaust gas temperature (EGT), and emissions of carbon monoxide (CO), hydrocarbon (HC), carbon dioxide (CO₂), and nitrogen oxides (NOx) were measured. The results demonstrated that, compared with diesel, biodiesel blends significantly reduced CO, HC, and CO₂ emissions. At 1800 rpm, the LB20 blend showed reductions of 31.03% in CO, 47.06% in HCs, and 19.14% in CO₂ relative to diesel. These reductions are mainly attributed to the higher oxygen content and lower hydrogen-to-carbon ratio of biodiesel, which promote more complete combustion. However, all biodiesel blends exhibited higher NOx emissions than diesel, with the increase being more pronounced at higher blend ratios. At 1800 rpm, the LB20 blend recorded the highest NOx emissions, which were 20.63% higher than those of diesel under the same condition. In terms of performance, biodiesel blends showed higher BSFC and lower BTE compared with diesel, mainly due to their lower calorific value and higher viscosity. The lowest BTE and the highest BSFC were both observed with the LB20 blend, at 22.64% and 358.11 g/kWh, respectively. Full article

Edible hydrogels are the central material class in 3D food printing because they reconcile two competing needs: (i) low resistance to flow under nozzle shear and (ii) fast recovery of elastic structure after deposition to preserve geometry. This review consolidates the recent years of progress on hydrogel formulations—gelatin, alginate, pectin, carrageenan, agar, starch-based gels, gellan, and cellulose derivatives, xanthan/konjac blends, protein–polysaccharide composites, and emulsion gels alongside a critical analysis of printing technologies relevant to food: extrusion, inkjet, binder jetting, and laser-based approaches. For each material, this review connects gelation triggers and compositional variables to rheology signatures that govern printability and then maps these to process windows and post-processing routes. This review consolidates a decision-oriented workflow for edible-hydrogel printability that links formulation variables, process parameters, and geometric fidelity through standardized test constructs (single line, bridge, thin wall) and rheology-anchored gates (e.g., yield stress and recovery). Building on these elements, a “printability map/window” is formalized to position inks within actionable operating regions, enabling recipe screening and process transfer. Compared with prior reviews, the emphasis is on decisions: what to measure, how to interpret it, and how to adjust inks and post-set enablers to meet target fidelity and texture. Reporting minima and a stability checklist are identified to close the loop from design to shelf. Full article

Bioplastics are gaining attention as eco-friendly alternatives to conventional plastics, with Polybutylene Adipate Terephthalate (PBAT) emerging as a promising biodegradable substitute for polyethylene (PE) in food packaging. Commercial PBAT is often blended with other plastics or bio-based fillers to improve mechanical properties and reduce costs, though these additives can influence its environmental footprint. Therefore, this study quantifies the environmental impacts of producing PBAT resin blends reinforced with common inorganic fillers and compares end-of-life (EoL) performance against PE. While prior studies have largely assessed virgin PBAT or PBAT/Polylactic Acid (PLA) systems, systematic LCA of commercial-style PBAT blends with inorganic fillers and screening LCA level for comparisons of composting vs. landfill remain limited. The contributions of this study are to: (i) map gate-to-gate environmental hotspots for PBAT-blend conversion, (ii) provide a screening gate-to-grave comparison of PBAT composting vs. PE landfill using ReCiPe 2016 and IPCC GWP100 methods, and (iii) discuss theoretical implications for material substitution in the context of EoL strategies. The results indicated that producing 1 kg of PBAT blend generated a single score impact of 921 mPt with Human Health and Resource categories contributing similarly, and a GWP of 8.64 kg CO₂-eq, dominated by mixing and drying processes. EoL screening showed PBAT composting offered clear advantages over landfilling PE, yielding −53.9 mPt and 11.35 kg CO₂-eq savings, effectively offsetting production emissions. In contrast, landfilling PE resulted in 288.8 mPt and 2.2 kg CO₂-eq emissions. Sensitivity analysis further demonstrated that a 30% reduction in electricity use could decrease impacts by up to 10%, underscoring the importance of energy efficiency improvements and renewable energy adoption for sustainable PBAT development. Full article

This work provides a systematic evaluation of the performance and regulated emissions of binary n-pentanol–diesel blends under steady-state conditions, thereby clarifying condition-dependent efficiency–emission trade-offs across multiple loads and speeds. A single-cylinder, air-cooled diesel engine was operated at two speeds (1700 and 2700 rpm) and four brake mean effective pressure (BMEP) levels (0.25–0.49 MPa) using commercial diesel (D100) and three n-pentanol–diesel blends at volume ratios of 10%, 30%, and 50% (designated D90P10, D70P30, and D50P50, respectively). Brake thermal efficiency (BTE), brake specific energy consumption (BSEC), and brake specific fuel consumption (BSFC) were measured alongside exhaust emissions of nitrogen oxides (NO_x), carbon monoxide (CO), hydrocarbon (HC), carbon dioxide (CO₂), and smoke opacity. The results show that due to a lower cetane number, high latent heat of vaporization, and reduced heating value, n-pentanol blends incur efficiency and fuel consumption penalties at light to moderate loads. However, these disadvantages diminish or reverse at high loads and speeds: D50P50 surpasses D100 in BTE and matches or improves BSEC and BSFC at 2700 rpm and 0.49 MPa. Emission data reveal that the blend’s fuel-bound oxygen and enhanced mixing provide up to 16% NO_x reduction; 35% and 45% reductions in CO and HC, respectively; and a 74% reduction in smoke opacity under demanding conditions, while CO₂ per unit work output aligns with or falls below D100 at high load. These findings demonstrate that optimized n-pentanol–diesel blends can simultaneously improve efficiency and mitigate emissions, offering a practical pathway for low-carbon diesel engines. Full article

To encourage the use of alternative fuels while limiting the use of fossil fuels, researchers have focused on using more environmentally friendly fuels. Furthermore, the goal is to improve engine performance to increase energy efficiency. A four-stroke, single-cylinder, diesel engine with a common rail fuel injection system runs with diesel, biodiesel, and biodiesel–alcohol fuel blends. The tests were performed using a constant engine speed of 2000 rpm and three different gas pedal positions (20%, 50% and 80%). It was found that maximum cylinder gas pressure increased in all test fuels with increased gas pedal position (GPP) and advanced injection start time. In general, the maximum heat release rate increased in blended fuels compared to diesel fuel. In addition, it was seen that advanced injection timings caused an increase in ignition delay in all fuel types. In the same test conditions, it was observed that biodiesel–alcohol fuel blends caused an increase in ignition delay by more than 10% compared to diesel fuel (D100), while shortening combustion duration (CD) by more than 10%. A decreasing trend in CO and HC emissions was observed in the use of biodiesel fuel compared to diesel fuel. With the use of biodiesel–alcohol fuel blends, CO₂ emissions tend to decrease. Advanced injection timings caused high NO emissions. Full article

The purpose of this study was to obtain a holistic view of mechanically recycled cotton from denim fabrics and the repurposing and recycling methods for similar fibres. A pre-consumer denim and three types of post-consumer denims were shredded into new fibres, which were characterised with single-fibre tensile testing, SEM imaging and DSC analysis. The opened cotton fibres were then blended with primary cotton with varying ratios and spun into yarns of 40 tex with a ring spinning machine. A ratio of 75/25 of recycled fibres to virgin fibres was obtained, with promising tensile strength results. Further, the yarns were knitted into single jersey fabrics, and abrasion testing was performed to evaluate their wearing out. Best abrasion resistance was obtained for knits consisting of 100% virgin cotton fibres and the knits consisting of a blend of pre-consumer and virgin fibres. The results suggest the yarns made with mechanically opened fibres are suitable for single jersey knits. SEM and DSC confirm the input of mechanical recycling defines the output. Moreover, the SEM pictures indicate there is little to no damage to single fibres caused by mechanical shredding, causing no further barriers for secondary use as raw materials. Full article

Over the last decades, Computational Fluid Dynamics (CFD) has become a fundamental tool for the design of gas turbine combustors, partly making up for the costs and duration issues related to the experimental tests involving high-pressure reactive processes. Nevertheless, high-fidelity simulations of reactive flows remain computationally expensive, particularly for conjugate heat transfer (CHT) analyses aimed at predicting liner metal temperatures and characterising wall heat losses. This work investigates the robustness of a cost-effective numerical setup for CHT simulations, focusing on the prediction of cold-side thermal loads in industrial combustor liners under realistic operating conditions. The proposed approach is tested using both Reynolds-Averaged Navier–Stokes (RANS) and unsteady Stress-Blended Eddy Simulation (SBES) turbulence models for the combustor flame tube, coupled via a time desynchronisation strategy with transient heat conduction in the solid domain. Cold-side heat transfer is modelled using a 1D correlation-based tool, runtime coupled with the CHT simulation to account for cooling-induced thermal loads without explicitly resolving complex cooling passages. The methodology is applied to a single periodic sector of the NovaLT^TM16 annular combustor, developed by Baker Hughes and operating under high-pressure conditions with natural gas. Validation against experimental data demonstrates the methodology’s ability to predict liner metal temperatures accurately, account for modifications in cooling geometries, and support design-phase evaluations efficiently. Overall, the proposed approach offers a robust trade-off between computational cost and predictive accuracy, making it suitable for practical engineering applications. Full article

To tackle the challenges of complex construction environment interference (e.g., lighting variations, occlusion, and marker contamination) and the demand for high-precision alignment during the hoisting process of bridge-erecting machines, this paper presents a two-stage marker detection–localization network tailored to hoisting alignment. The proposed network adopts a “coarse detection–fine estimation” phased framework; the first stage employs a lightweight detection module, which integrates a dynamic hybrid backbone (DHB) and dynamic switching mechanism to efficiently filter background noise and generate coarse localization boxes of marker regions. Specifically, the DHB dynamically switches between convolutional and Transformer branches to handle features of varying complexity (using depthwise separable convolutions from MobileNetV3 for low-level geometric features and lightweight Transformer blocks for high-level semantic features). The second stage constructs a Transformer-based homography estimation module, which leverages multi-head self-attention to capture long-range dependencies between marker keypoints and the scene context. By integrating enhanced multi-scale feature interaction and position encoding (combining the absolute position and marker geometric priors), this module achieves the end-to-end learning of precise homography matrices between markers and hoisting equipment from the coarse localization boxes. To address data scarcity in construction scenes, a multi-dimensional data augmentation strategy is developed, including random homography transformation (simulating viewpoint changes), photometric augmentation (adjusting brightness, saturation, and contrast), and background blending with bounding box extraction. Experiments on a real bridge-erecting machine dataset demonstrate that the network achieves detection accuracy (mAP) of 97.8%, a homography estimation reprojection error of less than 1.2 mm, and a processing frame rate of 32 FPS. Compared with traditional single-stage CNN-based methods, it significantly improves the alignment precision and robustness in complex environments, offering reliable technical support for the precise control of automated hoisting in bridge-erecting machines. Full article

This study aims to address the poor extensibility, brittleness, and limited hydration stability of pure sodium alginate (SA) hydrogels, which hinder their use in flexible, skin-adherent applications such as facial masks, by developing bio-based composites incorporating five representative functional additives: xanthan gum, guar gum, hydroxyethyl cellulose (HEC), poly(ethylene glycol)-240/hexamethylene diisocyanate copolymer bis-decyl tetradeceth-20 ether (GT-700), and Laponite^® XLG. Composite hydrogels were prepared by blending 1.5 wt% SA with 0.3 wt% of each additive in aqueous humectant solution, followed by ionic crosslinking using 3% (w/w) CaCl₂ solution. Physicochemical characterization included rotational viscometry, uniaxial tensile testing, ATR-FTIR spectroscopy, swelling ratio analysis, and pH measurement. Among them, the SA/XLG composite exhibited the most favorable performance, showing the highest viscosity, shear-thickening behavior, and markedly enhanced extensibility with an elongation at break of 14.8% (compared to 2.5% for neat SA). It also demonstrated a mean swelling ratio of 0.24 g/g and complete dissolution in water within one year. ATR-FTIR confirmed distinct non-covalent interactions between SA and XLG without covalent modification. The hydrogel also demonstrated excellent conformability to complex 3D surfaces, consistent hydration retention under centrifugal stress (+23.6% mass gain), and complete biodegradability in aqueous environments. Although its moderately alkaline pH (8.96) may require buffering for dermatological compatibility, its mechanical resilience and environmental responsiveness support its application as a sustainable, single-use skin-contact material. Notably, the SA/XLG composite hydrogel demonstrated compatibility with personalized fabrication strategies integrating 3D scanning and additive manufacturing, wherein facial topography is digitized and transformed into anatomically matched molds—highlighting its potential for customized cosmetic and biomedical applications. Full article

Background: Although electrohydrodynamic atomization (EHDA) consistently provides drug-encapsulation efficiencies (DEE) far above those of conventional bottom-up nanotechnologies, the question of how to systematically push that efficiency even higher remains largely unexplored. Methods: This study introduces a modified triaxial electrospinning protocol tailored to the application and benchmarks it against two conventional techniques: single-fluid blending and coaxial electrospinning. Ethylcellulose (EC) served as the polymeric matrix, while curcumin (Cur) was chosen as the model drug. In the triaxial setup, an electrospinnable, drug-free EC solution was introduced as an intermediate sheath to act as a molecular barrier, preventing Cur diffusion from the core fluid. Ethanol alone was used as the outermost fluid to guarantee a stable and continuous jet. Results: This strategy provided a DEE value of 98.74 ± 6.45%, significantly higher than the 93.74 ± 5.39% achieved by coaxial electrospinning and the 88.63 ± 7.36% obtained with simple blending. Sustained-release testing revealed the same rank order: triaxial fibers released Cur the most slowly and exhibited the smallest initial burst release effect, followed by coaxial and then blended fibers. Mechanistic models for both fiber production and drug release are proposed to clarify how the tri-layer core–shell structure translates into superior performance. Conclusions: The modified triaxial electrospinning was able to open a new practical route to produce core-sheath nanofibers. These nanofibers could provide a higher DEE and a better sustained drug release profile than those from the coaxial and blending processes. Full article

Material extrusion (MEX) is an additive manufacturing process used for 3D printing thermoplastic-based polymers, including single polymers, blends, and reinforced polymer composites (RPCs). RPCs are highly valued in various industries for their exceptional properties. The surface finish of RPC MEX-printed parts is high due to the process-related layering nature and the materials’ properties. This study explores RPC development for MEX printing and the potential of dry milling post-processing to enhance the MEX-printed part’s surface quality. RPC MEX filaments were developed by incorporating graphene nanoplatelets (GNPs) and/or recycled-carbon fibers (rCFs) into a polylactic acid (PLA) matrix. The filaments, including pure PLA and various GNPs-PLA composites, rCF-PLA, and rCF-GNPs-PLA, were developed through ball mill mixing and melt extrusion. Tensile tests were performed to assess the mechanical properties of the developed materials. Dry milling post-processing was carried out to assess the machinability, with the aim of enhancing the MEX-printed part’s surface quality. The results revealed that adding GNPs into PLA showed no considerable enhancements in the tensile properties of the fabricated RPCs, which is contrary to several existing studies. Dry milling showed an enhanced surface quality of MEX-printed parts in terms of surface roughness (Sa and Sz) and the absence of defects such as delamination and layer lines. Adding GNPs into PLA facilitated the dry machining of PLA, resulting in reduced surface asperities compared to pure PLA. Also, there was no observation of pulled-out, realigned, or naked rCFs, which indicates good machinability. Adding GNPs also suppressed the formation of voids around the rCFs during the dry milling. This study provides insights into machining 3D-printed polymer composites to enhance their surface quality. Full article

Active packaging supports sustainable development by extending food shelf life and reducing spoilage, contributing to global food security. In this study, cellulose dialdehyde was synthesized and blended with polyvinyl alcohol in varying ratios to produce composite films. The incorporation of dialdehyde cellulose into films tended to increase puncture strength and Young’s modulus, decrease elongation, reduce water solubility, and enhance resistance to water vapor transmission because of crosslinking. Carbon quantum dots were subsequently incorporated into composite films to enhance their antibacterial property. This represents a novel combination of a natural bio-based crosslinker and fluorescent nanomaterials in a single packaging system. Carbon quantum dots were synthesized by an electrochemical method and incorporated as functional agents. The addition of carbon quantum dots influenced the mechanical properties of the films due to interactions between polymers and carbon quantum dots. This interaction also slightly reduced the antibacterial effectiveness of the films, consisting of dialdehyde cellulose and PVA in ratios of 3:1 and 4:0. Nevertheless, the composite films maintained sufficient antimicrobial activity against common foodborne bacteria, including Staphylococcus aureus, Escherichia coli, and Salmonella Typhimurium. Overall, the findings demonstrate that multifunctional material made from dialdehyde cellulose, polyvinyl alcohol, and carbon quantum dots are a promising alternative to conventional plastic packaging. Full article

Recent developments in natural language processing, particularly large language models (LLMs), create new opportunities for literary analysis in underexplored languages like Romanian. This study investigates stylistic heterogeneity and genre blending in 175 late 19th- and early 20th-century Romanian novels, each classified by literary historians into one of 17 genres. Our findings reveal that most novels do not adhere to a single genre label but instead combine elements of multiple (micro)genres, challenging traditional single-label classification approaches. We employed a dual computational methodology combining an analysis with Romanian-tailored linguistic features with general-purpose LLMs. ReaderBench, a Romanian-specific framework, was utilized to extract surface, syntactic, semantic, and discourse features, capturing fine-grained linguistic patterns. Alternatively, we prompted two LLMs (Llama3.3 70B and DeepSeek-R1 70B) to predict genres at the paragraph level, leveraging their ability to detect contextual and thematic coherence across multiple narrative scales. Statistical analyses using Kruskal–Wallis and Mann–Whitney tests identified genre-defining features at both novel and chapter levels. The integration of these complementary approaches enhances microgenre detection beyond traditional classification capabilities. ReaderBench provides quantifiable linguistic evidence, while LLMs capture broader contextual patterns; together, they provide a multi-layered perspective on literary genre that reflects the complex and heterogeneous character of fictional texts. Our results argue that both language-specific and general-purpose computational tools can effectively detect stylistic diversity in Romanian fiction, opening new avenues for computational literary analysis in limited-resourced languages. Full article

Wood–plastic composites (WPCs) are polymeric materials, usually thermoplastic, filled with wood flour or fibers. They are relatively durable and stiff and resistant to water. They are also, importantly, relatively cheap compared to materials with similar properties. The WPCs market has grown significantly in recent years, mainly thanks to the increasing construction and automotive markets. Currently, the global WPCs market is forecasted to reach about USD 15 billion by 2030, increasing at an impressive compound annual increase rate of about 12% until 2030. There are some review articles on WPCs written from many different points of view, e.g., the type of materials used (polymers, fillers, auxiliaries), the method of manufacturing and processing, processing properties (thermal and rheological) and functional properties, methods of designing composite products and designing (modeling) forming processes. In this article, we will summarize these different points of view and will present a thorough literature review of rheology and material processing, and more specifically, the modeling of WPCs processing. This work will be presented in relation to state-of-the-art research in the field of modeling the processing of other polymeric materials, i.e., standard (neat) polymers and polymer blends. The WPCs’ processing is significantly different from that of standard plastics due to the differences in thermo-rheological properties, diverse structures, etc. So far, the global WPCs processing models have only been developed for both gravity-fed and starve-fed single-screw extrusion. The models for twin-screw extrusion, both co-rotating and counter-rotating, as well as for injection molding, have still not been developed. WPCs show a yield stress and wall slip when extruding, which must be considered when modeling the process. As the slippage on the screw and barrel grows, the process throughput and pressure diminish, but as the slippage on the die grows, the throughput grows and the pressure diminish. As the yield stress in the screw grows, the process throughput and pressure grow, whereas as the yield stress in the die grows, the throughput diminishes and the pressure grows. Full article