Search Results (8,497)

This study characterised the hot-press forming process of long carbon fibre PA6 materials using laminates prepared from UD-CA708A prepregs manufactured by Nanjing Special Plastic Composites Materials Co., Ltd. In order to investigate the resin flow behaviour during the hot compression moulding process, a unified model integrating the material forming and resin flow sequences was established by Lagrangian and Eulerian discretization methods. Simultaneous measurements by rotational and torsional rheometers revealed that in-plane fibre flow dominated, and the long carbon fibre PA6 material showed anisotropic behaviour. The anisotropic viscosity tensor principal model was used to characterise this anisotropy, the parameters of which were determined experimentally by the rheometer. Based on these findings, a unified modelling approach for material forming and resin flow was developed and applied to simulation analysis. The validity of the anisotropic viscosity intrinsic model and the unified simulation framework is verified by integrating the rheological analysis, in-mold analysis, and evaluation of the microstructure and mechanical properties of the moulded specimens, which provides a technical framework and a strategy for the application of the model in complex geometries. Full article

Additive manufacturing offers rapid and customizable production, yet conventional plastic-based methods remain energy-intensive and environmentally harmful, often resulting in higher impacts per part than traditional manufacturing. The goal of this study was to evaluate whether upcycled biomaterials, specifically oyster shells, pistachio shells, and clay, could be used as lower-impact alternatives to PLA in 3D printing. The scope included detailed measurement of print parameters for each material and a full life cycle assessment (LCA) of the printed elements, covering printer manufacturing, raw material extraction, transport, operation, and end of life. The results show that ambient-temperature extrusion of these upcycled biomaterials can reduce energy consumption by up to 89% and overall environmental impact by up to 94% (as measured by ReCiPe Endpoint H points) compared to PLA printing. These reductions were observed for the Netherlands and EU contexts, where electricity mixes are relatively clean and recycling rates are high; even greater improvements were observed for the US. Although the printed biomaterial objects exhibit lower mechanical strength, limited waterproofness, and reduced print resolution, they are already suitable for low-load applications such as prototypes and architectural models. Overall, the findings demonstrate that upcycled biomaterial extrusion has strong sustainability potential, outperforming both conventional plastics and bioplastics such as PLA in terms of material impacts and energy use. Continued development of material formulations as well as pre- and post-processing techniques could further expand functionality and support the broader adoption of low-impact 3D printing across a wide range of applications. Full article

Plastic pollution, particularly in marine environments, has become a major global concern; therefore, monitoring and controlling these contaminants is essential to safeguard ecosystem integrity and human health. This study evaluates the ability of Posidonia oceanica spheroids to incorporate and retain plastic debris, with a particular focus on microplastics (MPs). A total of 1300 spheroids were collected along the Latium coast (Central Italy); among these, 454 (34.9%) contained plastic debris, with an average of 3.1 items per spheroid. Overall, 1415 plastic items were extracted and identified. Based on size classification, 48.7% were microplastics, 29.6% mesoplastics, and 21.9% macroplastics. Plastic items mainly consisted of filaments (40.9 ± 12.6%) and fibers (21.5 ± 5.2%). Eleven different colors were recorded, with white (28.8 ± 9.1%), transparent (13.4 ± 6.0%), and black (11.1 ± 6.8%) being the most frequent. A strong correlation was observed between the number of plastic items contained in the spheroids and proximity to wastewater treatment plants, which are known sources of synthetic fibers. Fourier transform infrared spectroscopy (FTIR) identified a total of 15 polymer materials, with nylon (18.2 ± 11.0%) and polyethylene terephthalate (PET; 17.3 ± 7.2%) being the most abundant. Structural alterations observed in FTIR spectra, together with carbonyl index values, indicate that most MPs are of secondary origin, resulting from prolonged environmental degradation. These results demonstrate that P. oceanica spheroids effectively promote plastic trapping and highlight their potential as a simple and cost-effective monitoring tool for marine plastic pollution. Full article

This study investigates the as-cast Mg-8Gd-1Y-2Sm-1.2Zn-0.5Mn (wt.%) alloy with high rare-earth content. Solution treatments were conducted at 480 °C, 520 °C, and 560 °C for 6–10 h. Microstructure and mechanical properties were characterized using OM, XRD, SEM-EDS, and compression testing. The as-cast alloy shows a dendritic structure with continuous grain-boundary phases (Mg₅RE, W, and LPSO), exhibiting a compressive yield strength of 145 MPa, ultimate strength of 238 MPa, and fracture strain of 12.66%. Solution temperature has a critical influence on phase dissolution and grain refinement. Notably, the overall plasticity of the material did not show a significant dependence on the specific solution temperature or holding time within the studied range. Treatment at 520 °C produces the most balanced microstructure: clear grain boundaries, extensive phase dissolution, refined grains, and enhanced solid-solution strengthening. Specifically, 520 °C for 10 h results in the finest and most uniformly distributed residual phases, a homogeneous matrix, the highest compressive strength, and suitable conditions for subsequent aging, thus being identified as optimal. Fractography reveals a transition from quasi-cleavage in the as-cast state toward enhanced ductility after solution treatment. However, small cleavage facets after 10 h are attributed to stress concentrations from rare-earth-rich regions and reduced deformation compatibility due to retained LPSO phases. Full article

Rheology plays an important role in the 3D concrete printing technology, because it directly governs the flowability and shape retention of the material, impacting both the printing process and the final quality of the obtained structure. Local raw materials such as Portland cement, washed sand, and tap water were used for the preparation of 3D-printed concrete mixtures. The solid-state polycarboxylate ether with an anti-foaming agent was used as superplasticizer. The Portland cement was partially replaced (by volume) with a natural zeolite additive in amounts ranging from 0% to 9% in 3D-printed concrete mixtures. A rotational rheometer with coaxial cylinders was used in this research for the determination of rheological characteristics of prepared 3D-printed concrete mixtures. The Herschel–Buckley model was used to approximate experimental flow curves and assess rheological parameters such as yield stress, plastic viscosity, and shear-thinning/thickening index. The additional experiments and calculations, such as water bleeding test and evaluation of the carbon footprint of 3D-printed concrete mixtures, were performed in this work. The replacement of Portland cement with natural zeolite additive positively influenced rheological and stability-related properties of 3D-printed concrete mixtures. Natural zeolite additive consistently reduced water bleeding, enhanced yield stress under increasing shear rates, and lowered plastic viscosity, thereby improving flowability and mixture transportation during the 3D printing process. As the shear-thinning/thickening index remained stable (indicating non-thixotropic behavior in most cases), higher amounts of natural zeolite additive introduced slight thixotropy (especially under decreased shear rates). These changes contributed to better shape retention, layer stability, and the ability to print taller and narrower structures without collapse, making natural zeolite additive suitable for use in the optimized processes of 3D concrete printing. A significant decrease in total carbon footprint (from 3% to 19%) was observed in 3D-printed concrete mixtures with an increase in the mentioned amounts of natural zeolite additive, compared to the mixture without this additive. Full article

Disposable absorbent hygiene products (AHPs) contain plastics that are challenging to recycle and not biodegradable, making a significant contribution to landfill. Decreasing the nonbiodegradable mass of products could reduce this burden. Despite this, public data on how AHP design and material selection relate to performance is limited. In this work, fifteen commercial AHPs were characterised using dimensional measurement, infrared spectroscopy, and imaging. Simulated urination, air permeability, and moisture management testing were used to assess expected leakage and user comfort. Sustainable materials currently in use were identified, and their performance compared to typical plastics, informing opportunities to replace or reduce nonbiodegradable materials. Polybutylene adipate terephthalate-based leakproof layers replaced polyolefins. Commercial alternatives to polyacrylate superabsorbent polymers (SAPs), with comparable absorption, were not seen. Although absorbency correlated with the mass of absorbants, SAPs reduced surface moisture after absorption and are known for high absorption capacity under pressure, preventing rewetting. Channels and side guards were observed to prevent side leakage and guide fluid distribution, potentially reducing the need for nonbiodegradable nonwoven and absorbant content by promoting efficient use of the full product mass. While synthetic nonwovens typically outperformed cellulosics, apertured and layered nonwovens were associated with improved moisture transport; polylactic acid rivalled typical thermoplastics as a bio-derived, compostable alternative. Although the need for biopolymer-based SAPs and foams remains, it is hoped that these findings will guide AHP design and promote research in sustainable materials. Full article

Polylactic acid (PLA) is a promising biodegradable polymer whose widespread application is hindered by inherent brittleness. Polyethylene glycol (PEG) is a common plasticizer, but the effects of intermediate molecular weights, such as 4000 g/mol, on the coupled thermal, mechanical, and rheological properties of PLA remain insufficiently understood. This study presents a comprehensive analysis of PLA plasticized with 0–20 wt% PEG 4000, employing differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), and rheology. DSC confirmed excellent miscibility and a significant glass transition temperature (T_g) depression exceeding 19 °C for the highest concentration. A complex, non-monotonic evolution of crystallinity was observed, associated with the formation of different crystalline forms (α′ and α). Critically, DMA revealed that the material’s thermo-mechanical response is dominated by its thermal history: while the plasticizing effect is masked in highly crystalline, as-cast films, it is unequivocally demonstrated in quenched amorphous samples. The core finding emerges from a targeted rheological investigation. An anomalous increase in melt viscosity and elasticity at intermediate PEG concentrations (5–15 wt%), observed at 180 °C, was systematically shown to vanish at 190 °C and in amorphous samples. This proves that the anomaly stems from residual crystalline domains (α′ precursors) persisting near the melting point, not from a transient molecular network. These results establish that PEG 4000 is a highly effective PLA plasticizer whose impact is profoundly mediated by processing-induced crystallinity. This work provides essential guidelines for tailoring PLA properties by controlling thermal history to optimize flexibility and processability for advanced applications, specifically in melt-processing for flexible packaging. Full article

The microstructure of the Ti-Al binary system is an area of great interest, as it affects material properties and plasticity. Phase transformations induce microstructural changes; therefore, accurately modeling the phase transformations of the Ti-Al system is necessary to describe plasticity. Interatomic potentials can be a powerful tool to model how materials behave; however, existing potentials lack accuracy in certain aspects. While classical potentials like the Modified Embedded Atom Method (MEAM) perform adequately for modeling a dilute Al solute within Ti’s $\alpha$ phase, they struggle with accurately predicting plasticity. In particular, they struggle with stacking fault energies in intermetallics and to some extent elastic properties. This hinders their effectiveness in investigating the plastic behavior of formed intermetallics in Ti-Al alloys. Classical potentials also fail to predict the $\alpha$-to-$\beta$ phase boundary. Existing machine learning (ML) potentials reproduce the properties of formed intermetallics with density functional theory (DFT) but do not accurately capture the $\alpha$-to-$\beta$ or $\alpha$-to-D0₁₉ phase boundaries. This work uses a rapid artificial neural network (RANN) framework to produce a neural network potential for the Ti-Al binary system. This potential is capable of reproducing the Ti-Al binary phase diagram up to 30% Al concentration. The present interatomic potential ensures stability and allows results near the accuracy of DFT. Using Monte Carlo simulations, the RANN potential accurately predicts the $\alpha$-to-$\beta$ and $\alpha$-to-D0₁₉ phase transitions. The current potential also exhibits accurate elastic constants and stacking fault energies for the L1₀ and D0₁₉ phases. Full article

Acrylonitrile Styrene Acrylate (ASA) is widely used in outdoor structural applications due to its favorable mechanical stability and weather resistance; however, its temperature-dependent plastic behavior remains insufficiently characterized for accurate numerical simulation. This study presents a non-standard method of calibrating the temperature-dependent Johnson–Cook (J-C) plasticity model for ASA in the practical operating temperature range below the glass transition temperature. Uniaxial tensile tests at constant strain rate 0.01 s⁻¹ were performed at −10 °C, +23 °C, and +65 °C to characterize the effect of temperature on the material’s plastic response. The J-C parameters $A$, $B$, and $n$ were identified for each temperature separately and globally using least-squares optimization implemented in MATLAB R2024b, showing good agreement with the experimental stress–strain curves. The calibrated parameters were subsequently implemented in Abaqus 2024 and validated through finite element simulations of the tensile tests. Numerical predictions demonstrated a very high correlation with the experimental data across all temperatures, confirming that the J-C model accurately captures the hardening behavior of ASA. The presented parameter set and calibration methodology provide a reliable basis for future simulation-driven design, forming analysis, and structural assessment of ASA components subjected to variable thermal conditions. Full article

Ceramsite foam concrete (CFC), recognized for its lightweight, thermal insulation, and eco-friendly properties, is a promising material for composite structures. The interfacial shear bond behavior between CFC and normal concrete (NC) critically governs the structural integrity of CFC-NC systems. This study investigates the interfacial shear bond strength through direct double shear tests on twelve cubic specimens with controlled interface roughness and casting intervals. Quantitative analysis reveals that increased roughness enhances shear strength by up to 28.6~59.5%, while prolonged casting intervals reduce strength by 22.3~34.6%. Notably, excessive roughness shifts failure modes from interfacial debonding to material failure within CFC, where shear bond strength becomes governed by CFC’s compressive strength. A rigid–plastic model is developed to characterize the shear bond behavior of CFC-NC interface and demonstrates 96% accuracy in predicting experimental results. The findings provide useful insights for improving CFC-NC composite design in engineering applications. Full article

Biopolymer-based films have attracted increasing attention as sustainable and bioactive materials for wound management. Among them, chitosan (CTS) and starch (ST) blend represent promising candidate due to their natural origin, biodegradability, and intrinsic biological activity; however, their mechanical weakness and limited stability necessitate additional modification. This study reports the development and characterization of CTS-ST thin films crosslinked with dialdehyde alginate (ADA), synthesized via controlled oxidation. Two ADA variants differing in aldehyde group content were prepared to investigate the effect of crosslinking on the structural, physicochemical, and biological performance of the materials. The films were fabricated by blending 2% w/v CTS and ST in varying mass ratios (75/25, 50/50, and 25/75), followed by the addition of ADA (5% w/w) and glycerol (5% w/w) as a plasticizer. The mixtures were then cast onto plates and dried under ambient conditions. Comprehensive characterization included Fourier-transform infrared spectroscopy, moisture content analysis, contact angle measurements, antioxidant activity assay, hemolysis testing, and cytotoxicity evaluation using human keratinocyte cells. The results demonstrated that both the ADA variant and CTS/ST ratio significantly influenced crosslinking efficiency, hydrophilicity, and antioxidant behavior. All samples exhibited non-hemolytic behavior and no significant cytotoxic effects, indicating their favorable biocompatibility. The combination of biostability, antioxidant ability, and absence of cytotoxic effects highlights the potential of ADA-crosslinking CTS/ST films for further development as wound dressing materials and other biomedical applications. Full article

The growing global production of plastic, which reached 460 million tonnes in 2022 and has projections of 5.4 million tonnes of waste by 2050 without intervention, has created a severe environmental crisis that demands the development of sustainable alternatives. In this context, this study aims to characterise biodegradable films based on cassava starch and gellan gum, combining microstructural and mechanical properties with the evaluation of thermo-optical parameters. An important advance was the pioneering application of a self-normalised photoacoustic technique, used for the first time to measure thermal diffusivity (0.0013 ± 0.0002 cm²/s) and optical absorption coefficients (at 660 nm) as a function of different concentrations of aniline blue. The results validate the material, which showed high solubility (89.23 ± 1.03%) and crystallinity of 27.40 ± 1.68%. The film demonstrated remarkable biodegradability, losing almost all of its weight (98.30 ± 1.01%) in just 15 days. The measurement of the optical absorption coefficients (at 660 nm) confirmed a linear relationship with the concentration of aniline, validating Beer–Lambert’s law and providing the absorptivity of the dye within the solid matrix—something inaccessible with conventional methods. In conclusion, these films offer significant potential as a viable ecological substitute for single-use plastics, contributing significantly to mitigating the global impact of plastic waste. Full article

The development of high-performance wood-based materials has attracted increasing interest as a means of enhancing the mechanical properties of wood for structural applications. Mechanical densification combined with chemical pretreatment is an effective approach; however, many reported methods rely on complex multi-component chemical systems or severe chemical conditions designed to dissolve lignin or hemicelluloses. In this study, a simplified NaOH-only pretreatment followed by hot-press densification was investigated, targeting selective cell-wall plasticization rather than extensive polymer dissolution. Juniper (Juniperus communis), hawthorn (Crataegus monogyna), and birch (Betula pendula) were used as samples of softwood and hardwood species. Wood specimens were pretreated in 1 M NaOH at 145 °C for 10–30 min and subsequently densified by radial compression. Changes in chemical composition were evaluated by HPLC after acid hydrolysis and FTIR spectroscopy, while microstructural changes were examined using SEM. Physical and mechanical properties were assessed through density measurements and three-point bending tests. The results show that NaOH-only pretreatment induces hemicellulose deacetylation and modification of interpolymer linkages without substantial changes in the main wood polymer contents. Densification resulted in effective lumen collapse and a compact microstructure, leading to a significant increase in density and mechanical properties. Overall, the results demonstrate that efficient wood densification and mechanical enhancement can be achieved by promoting polymer mobility through selective cleavage of interpolymer bonds, using a simplified, single-alkali pretreatment that reduces chemical complexity and material loss while avoiding extensive lignin or hemicellulose dissolution. Full article

The increasing urgency to mitigate plastic pollution has accelerated the shift from linear manufacturing toward circular systems. This review synthesizes current advances in mechanical, chemical, biological, and upcycling pathways, emphasizing how artificial intelligence (AI) is reshaping decision-making, performance prediction, and system-level optimization. Intelligent sensing technologies—such as FTIR, Raman spectroscopy, hyperspectral imaging, and LIBS—combined with Machine Learning (ML) classifiers have improved material identification, reduced reject rates, and enhanced sorting precision. AI-assisted kinetic modeling, catalyst performance prediction, and enzyme design tools have improved process intensification for pyrolysis, solvolysis, depolymerization, and biocatalysis. Life Cycle Assessment (LCA)-integrated datasets reveal that environmental benefits depend strongly on functional-unit selection, energy decarbonization, and substitution factors rather than mass-based comparisons alone. Case studies across Europe, Latin America, and Asia show that digital traceability, Extended Producer Responsibility (EPR), and full-system costing are pivotal to robust circular outcomes. Upcycling strategies increasingly generate high-value materials and composites, supported by digital twins and surrogate models. Collectively, evidence indicates that AI moves from supportive instrumentation to a structural enabler of transparency, performance assurance, and predictive environmental planning. The convergence of AI-based design, standardized LCA frameworks, and inclusive governance emerges as a necessary foundation for scaling circular plastic systems sustainably. Full article

Introduction: Massage therapy delivers structured mechanosensory input that can influence brain function, yet the central mechanisms and potential for neuroplastic change have not been synthesized across neuroimaging modalities. This mechanistic review integrates evidence from electroencephalography (EEG), functional MRI (fMRI), and functional near-infrared spectroscopy (fNIRS) to map how massage alters human brain activity acutely and over time and to identify signals of longitudinal adaptation. Materials and Methods: We conducted a scoping, mechanistic review informed by PRISMA/PRISMA-ScR principles. PubMed/MEDLINE, Cochrane Library, Google Scholar, and ResearchGate were queried for English-language human trials (January 1990–July 2025) that (1) delivered a practitioner-applied manual massage (e.g., Swedish, Thai, shiatsu, tuina, reflexology, myofascial techniques) and (2) measured brain activity with EEG, fMRI, or fNIRS pre/post or between groups. Non-manual stimulation, structural-only imaging, protocols, and non-English reports were excluded. Two reviewers independently screened and extracted study, intervention, and neuroimaging details; heterogeneity precluded meta-analysis, so results were narratively synthesized by modality and linked to putative mechanisms and longitudinal effects. Results: Forty-seven studies met the criteria: 30 EEG, 12 fMRI, and 5 fNIRS. Results: Regarding EEG, massage commonly increased alpha across single sessions with reductions in beta/gamma, alongside pressure-dependent autonomic shifts; moderate pressure favored a parasympathetic/relaxation profile. Connectivity effects were state- and modality-specific (e.g., reduced inter-occipital alpha coherence after facial massage, preserved or reorganized coupling with hands-on vs. mechanical delivery). Frontal alpha asymmetry frequently shifted leftward (approach/positive affect). Pain cohorts showed decreased cortical entropy and a shift toward slower rhythms, which tracked analgesia. Somatotopy emerged during unilateral treatments (contralateral central beta suppression). Adjuncts (e.g., binaural beats) enhanced anti-fatigue indices. Longitudinally, repeated programs showed attenuation of acute EEG/cortisol responses yet improvements in stress and performance; in one program, BDNF increased across weeks. In preterm infants, twice-daily massage accelerated EEG maturation (higher alpha/beta, lower delta) in a dose-responsive fashion; the EEG background was more continuous. In fMRI studies, in-scanner touch and reflexology engaged the insula, anterior cingulate, striatum, and periaqueductal gray; somatotopic specificity was observed for mapped foot areas. Resting-state studies in chronic pain reported normalization of regional homogeneity and/or connectivity within default-mode and salience/interoceptive networks after multi-session tuina or osteopathic interventions, paralleling symptom improvement; some task-based effects persisted at delayed follow-up. fNIRS studies generally showed increased prefrontal oxygenation during/after massage; in motor-impaired cohorts, acupressure/massage enhanced lateralized sensorimotor activation, consistent with use-dependent plasticity. Some reports paired hemodynamic changes with oxytocin and autonomic markers. Conclusions: Across modalities, massage reliably modulates central activity acutely and shows convergent signals of neuroplastic adaptation with repeated dosing and in developmental windows. Evidence supports (i) rapid induction of relaxed/analgesic states (alpha increases, network rebalancing) and (ii) longer-horizon changes—network normalization in chronic pain, EEG maturation in preterm infants, and neurotrophic up-shifts—consistent with trait-level recalibration of stress, interoception, and pain circuits. These findings justify integrating massage into rehabilitation, pain management, mental health, and neonatal care and motivate larger, standardized, multimodal longitudinal trials to define dose–response relationships, durability, and mechanistic mediators (e.g., connectivity targets, neuropeptides). Full article