Search Results (1,186)

This study addresses a critical challenge in surface engineering: developing robust nanocomposite layers on high-performance thermoplastics without inducing macroscopic thermal degradation. While cold gas dynamic spraying (CGDS) of polymers is often described in the literature as a deposition process based on purely mechanical anchoring of particles into polymer surface, our work establishes a multi-scale, hybrid physical–chemical adhesion framework. Using a coupled 3D thermoplasticity finite element model with a Mie–Grüneisen equation of state and Johnson–Cook criteria, we evaluate the supersonic impact dynamics ($V_0=1000 \mathrm{m}/\mathrm{s}$) of single-walled (5,0) CNTs impacting a PEEK substrate at oblique angles (0–20°). The core scientific lies in bridging continuum mechanics with quantum-chemical statistics. By applying Weibull weakest-link theory to a 37-bond monomer model, we demonstrate that compliant $C_{arom}-O$ ether bonds selectively absorb impact energy, covering 8.37% of their dissociation barrier. This non-uniform energy sharing yields a 0.23% monomer activation probability, generating a high free-radical density of ~1100 ${\mathrm{\mu }\mathrm{m}}^{-2}$ beneath the particle plume. This localized “chemical nano-welding” network provides exceptional chemical adhesion, while the remaining 99.77% of intact chains ensure structural rigidity, reinforced by a mechanical “self-locking” field (residual compressive stresses up to 0.9 GPa). This study provides a scientific foundation for designing functional coatings tailored for engineering, aerospace, and biomedical applications. Full article

Under the dual-carbon strategy, green hydrogen as a zero-carbon fuel is rapidly expanding in engineering applications. However, the absence of gas radiation models specifically validated under high H₂O mole fraction, pure H₂ combustion conditions compromises the accuracy of radiation calculations in hydrogen-fueled thermal systems. To bridge this gap, 43,680 line-by-line calculations spanning the full operating space were performed using the HITEMP2010 database. These calculations systematically quantify the effects of temperature, total pressure, radiation path length, and H₂O mole fraction on the emissivity of pure hydrogen combustion gases. Based on this high-fidelity benchmark dataset, a novel four-gray-gas weighted-sum-of-gray-gases model (WSGGM) applicable at 1 atm was developed using the Levenberg–Marquardt algorithm, covering 500–3000 K, 0.01–60 m, and 1–100% H₂O mole fraction. The results establish the following influence hierarchy: radiation path length > temperature > H₂O mole fraction > total pressure. Radiation path length dominates across all temperatures. Emissivity exhibits three-stage saturation growth with increasing radiation path length, with 56.1% of the total increment occurring within the first 5 m at 500 K. At a radiation path length of 10 m and 30% H₂O mole fraction, emissivity decreases monotonically with temperature, dropping by 80.7% from 500 to 3000 K (1 atm). Emissivity is most sensitive to H₂O mole fractions below 0.1, whereas pressure exerts the weakest influence, with its effect saturating above 10 atm. The WSGGM fits total emissivity with excellent accuracy (R² = 0.999820, MAE = 0.002153) and is directly implementable in mainstream CFD software, providing a ready-to-use radiation model for high-fidelity simulation and design of hydrogen-fueled thermal systems. Full article

This study assesses the capabilities of UAV-based Earth observation for analyzing marginalized communities, using Roma settlements in southeastern Slovakia as a case study. Marginalized populations are often underrepresented in official spatial datasets, resulting in a limited understanding of their living conditions, infrastructure needs, and environmental risks. To address this gap, we propose a multi-scalar, UAV-based observational approach that bridges the limitations of coarse satellite imagery and logistically constrained ground surveys. High-resolution RGB and thermal imagery were acquired across three settlements with varying spatial characteristics and processed using photogrammetric workflows to generate detailed orthophotos and spatial products. The results demonstrate that UAV data with centimeter-level spatial resolution enable precise mapping of settlement morphology, infrastructure, waste distribution, and thermal inequalities. Furthermore, UAV observations enable change detection and environmental risk assessment at scales that are not achievable with conventional remote sensing. However, the study also highlights critical operational and ethical challenges, including regulatory constraints, privacy concerns, and the need for community engagement. By integrating technical evaluation with socially sensitive research practices, this work proposes a methodological framework for responsible UAV deployment in marginalized contexts. The findings underscore the potential of UAV-based observation to improve spatial visibility and support evidence-based planning while emphasizing the importance of ethical implementation. Full article

To accurately characterize the warm deformation behavior and workability of the 5A06 aluminum alloy, this study presents an innovative workflow that develops and systematically validates machine learning-assisted Johnson–Cook (ML-JC) frameworks based on artificial neural network (ANN) surrogate models. Two predictive frameworks—the parallel-decoupled PD-ANN-JC and the multi-objective integrated MOI-ANN-JC—were constructed. Quantitatively, both developed ML-JC frameworks achieve significantly higher stress prediction accuracy and superior generalization capability compared with the conventional JC model. Specifically, on the testing set, the MOI-ANN-JC framework yields an average absolute relative error (AARE) of 1.424% and an R² of 0.997, outperforming the PD-ANN-JC framework (AARE of 3.246%, R² of 0.988). On the validation set, the MOI-ANN-JC framework also demonstrates exceptional generalization, with an AARE of 3.302% and an R² of 0.987. Scientifically, the superior performance of the MOI-ANN-JC framework stems from its ANN-mnδ surrogate model, which simultaneously predicts the strain hardening exponent n, thermal softening exponent m, and relative error δ directly from deformation parameters. This mutual coupling establishes an intrinsic correlation between m and n, successfully aligning with the physical reality wherein strain hardening and thermal softening are inherently linked during deformation. Qualitatively and practically, by integrating the MOI-ANN-JC framework into finite element (FE) simulation software, dynamic tracking and visualization of the thermal softening exponent m during warm deformation were achieved. Combined with FE simulations, Vickers hardness testing and EBSD observations, this study successfully establishes a direct qualitative spatial correspondence between low-m regions and macroscopic defects, which was further verified through the warm forging of a thin-walled dual-cavity component. Crucially, this approach for evaluating deformation stability bridges the gap caused by the inapplicability of conventional processing maps within this temperature regime, offering a robust and broadly applicable workflow for complex forming optimization. Full article

We present cystamine-modified polydopamine (PDA) coatings as tunable gatekeepers for mesoporous silica nanoparticles (MSNs) in drug delivery. Unlike conventional post-functionalization strategies, cystamine moieties were incorporated directly into the PDA network, enabling tunable shell composition and redox responsiveness by simply adjusting the dopamine-to-cystamine ratio. By varying the cystamine:dopamine ratio, pH- and redox-responsive release of doxorubicin (DOX) and sorafenib (SO) was achieved, with release kinetics following the Higuchi model. Cystamine-modified PDA nanoparticles with varying disulfide bridge content were synthesized and comprehensively characterized using SEM, TGA, FTIR, and zeta potential measurements. The cystamine content was found to influence thermal stability, coating performance, and protective properties. Importantly, increasing disulfide content did not necessarily improve release performance, suggesting that excessive crosslinking may partially restrict shell permeabilization and drug diffusion. These findings reveal important structure–property relationships in catechol-based coatings and underline the significance of disulfide linkages in the design of bioinspired stimuli-responsive drug delivery systems. Full article

In the context of the tangible consequences of climate change, this paper develops strategies for the energy-efficient transformation of high-rise post-war buildings of the 1950s and 1960s, taking the Asemwald housing estate in Stuttgart as a case study. The objectives are full decarbonization while under occupation, while preserving the architecture of the buildings. The main aim is the significant reduction in heating energy consumption, which can in turn enable the estate to be supplied with renewable energy. Revitalizing the estate completed in 1968 preserves important architectural designs and ideas and can serve as a model for sustainable refurbishment. Thermal bridge calculations and energy simulations are carried out to identify and evaluate energy inefficiencies. Based on this, two façade renovation concepts are developed. These concepts differ in the degree of invasiveness and combine architectural sensitivity with energy optimization. In addition, an analysis is carried out to determine which alternative environmentally friendly heating systems can be used. The results show an energy saving potential of up to 60% and that a conversion to a CO₂-neutral heating system is possible. It can be shown that a significant reduction in energy requirements is an important step towards converting to geothermal energy. The study emphasizes the relevance of integral and architecturally sensitive retrofitting to serve as a model for similar post-war high-rise housing estates. Full article

This study investigates the thermo-mechanical and microstructural performance of concrete incorporating waste tire rubber (WR) and recycled steel fibers (WS) under elevated temperatures. Four mixtures were prepared: plain concrete (PL), rubber-modified concrete (WR5), and hybrid mixtures containing 0.4% and 0.8% steel fibers (WS0.4WR5 and WS0.8WR5). Specimens were exposed to temperatures of 400 °C, 600 °C, and 800 °C to simulate fire conditions. The results indicate that the incorporation of rubber reduces compressive strength at ambient temperature due to its lower stiffness and weak interfacial bonding. However, the addition of recycled steel fibers significantly improves crack resistance and enhances thermal stability. At 400 °C, the WS0.8WR5 mixture showed a retention rate of 92.9% (absolute strength: 44.32 MPa), compared to 72.2% for plain concrete (absolute strength: 44.11 MPa). Although the hybrid mixture has a lower ambient strength (47.68 MPa vs. 61.07 MPa), its superior retention makes it competitive in fire scenarios. Ultrasonic pulse velocity (UPV) measurements revealed a strong correlation with compressive strength degradation, confirming its effectiveness as a non-destructive indicator of internal damage. Microstructural analyses (SEM, XRD, and TGA-DTA) demonstrated that elevated temperatures lead to dehydration, phase transformation, and increased porosity, while steel fibers help maintain matrix integrity through crack-bridging mechanisms. The findings highlight a synergistic interaction between waste rubber and steel fibers, offering a sustainable and effective approach for improving the fire resistance of concrete. Full article

Quantitative assessment of historical urban waterlogging on the Qinghai–Tibet Plateau (QTP) is severely hindered by the lack of early instrumental records. To bridge this data gap during the initial rapid urbanization period (1985–2003), this study proposes an integrated retrospective framework combining Large Language Models (LLMs)-based semantic mining, spatial reconstruction, and Extreme Gradient Boosting (XGBoost)- SHapley Additive exPlanations (SHAP) modeling under a Spatial Block Cross-Validation (SBCV) strategy. Historical disaster archives were transformed into spatially explicit training samples, enabling the reconstruction of a high-resolution urban waterlogging susceptibility atlas across the QTP. The results indicate that high-susceptibility areas are predominantly concentrated within urbanized river valleys and account for approximately 45% of the total urban built-up area across the QTP. The proposed framework achieved an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.9793 under the SBCV strategy, indicating good spatial transferability within the study area. SHAP analysis revealed that geomorphic variables contributed more strongly than most climatic variables, highlighting the important role of a geomorphic confinement effect in shaping susceptibility patterns. Comparative analyses further suggest a spatial transition from basin-dominated accumulation patterns to increasingly valley-confined susceptibility distributions under stronger topographic constraints. In addition, surface albedo and land surface temperature were identified as influential predictors, likely reflecting integrated thermal-hydrological conditions associated with antecedent soil moisture and local urban thermal dynamics. This study establishes a historical risk baseline for the QTP and provides a reproducible and cost-effective framework for historical hazard assessment in other data-scarce mountainous and high-altitude regions. Full article

As climate change intensifies heat extremes, the Urban Heat Island (UHI) effect amplifies local thermal stress. Assessing the UHI using robust observational data, whether ground- and/or satellite-based, is essential for climate risk assessment and evidence-based urban adaptation. Therefore, this study aims to provide a comprehensive climatological assessment of air temperature patterns and UHI intensity across the Lisbon Metropolitan Area (LMA) over a 26-year period (2000–2025). The methodology employs a dense, high-quality integrated network of in-situ weather stations from the Portuguese Institute for Sea and Atmosphere (IPMA) and the National Water Resources Information System (SNIRH). To bridge critical gaps in traditional climate assessments, this research implements a dual-perspective approach that combines the high temporal resolution of MSG-SEVIRI and the spatial precision of MODIS Land Surface Temperature (LST). This framework accurately captures the lag effects between surface heating and atmospheric response. Validation results demonstrate that satellite-derived LST is a robust proxy for monitoring the nocturnal UHI, with differences generally below 1 °C compared with near-surface air temperature observations (T2m). However, daytime LST significantly overestimates atmospheric temperatures, with deviations of 2–8 °C due to solar radiation and urban geometry. The selection of rural reference stations constitutes a critical methodological factor, as a baseline shift can alter perceived UHI intensities by more than 3 °C. Despite these sensitivities, the results unequivocally confirm a persistent and spatially heterogeneous UHI effect in Lisbon, which intensifies during extreme heat events by up to an additional 4 °C. Analysis of the 2003 and 2018 heatwaves reveals surface LST anomalies exceeding 10 °C and urban–rural thermal differentials reaching up to 7 °C under conditions of suppressed maritime breezes. These nocturnal anomalies are particularly pronounced in densely built-up areas, limiting thermal dissipation and preventing physiological recovery. Integrating multi-sensor satellite data with in-situ validation provides a new benchmark for climate risk assessments, delivering the reliable, reproducible data required to strengthen long-term urban resilience under increasingly frequent extreme heat events. Full article

Graphite-filled polymer composites exhibit high in-plane thermal conductivity but suffer from severe thermal anisotropy, which limits their practical heat dissipation performance in the thickness direction. In this study, hierarchically structured Al/GO@AgNPs hybrid fillers were developed to enhance the through-plane thermal conductivity of polypropylene (PP)/graphite composites. The hybrid fillers were fabricated through GO-assisted surface modification of Al particles followed by electroless deposition of Ag nanoparticles. The GO layer improved the interfacial characteristics of Al and served as a platform for Ag nucleation, resulting in the formation of Ag nanoparticles on the Al/GO surface. When incorporated at a low loading of 1.0 wt%, the Al/GO@AgNPs hybrid filler increased the through-plane thermal conductivity from 11.24 to 48.33 W·m⁻¹·K⁻¹, corresponding to more than a fourfold enhancement compared with the graphite-only composite, while maintaining an in-plane thermal conductivity of 106.87 W·m⁻¹·K⁻¹. This improvement is attributed to the bridging effect of spherical hybrid fillers between adjacent graphite platelets and the resulting reduction in interfacial thermal resistance in the through-plane direction. The proposed hybrid filler system effectively mitigates thermal anisotropy and provides a promising strategy for designing highly filled polymer composites for advanced thermal management applications. Full article

Radiofrequency ablation (RFA) is commonly modeled using classical heat diffusion equations; however, growing evidence suggests that heat transport in biological tissues exhibits nonlocal and scale-dependent behavior driven by capillary perfusion. In this work, we develop a fractional diffusion framework for the computational modeling of hepatic tumor ablation based on the fractional Laplacian operator. A characteristic length scale is introduced to bridge microscale capillary effects and macroscale heat propagation, enabling the model to capture the superdiffusive thermal transport associated with hepatic vascular networks. Owing to its nonlocal nature, the fractional formulation entails significantly higher computational costs than classical diffusion models. To address this challenge, we investigate the complexity of two temporal discretization strategies: the backward Euler method with uniform time stepping and an adaptive backward–forward Euler scheme. Numerical experiments involving single- and double-probe ablation configurations demonstrate the robustness of the proposed framework and illustrate its applicability to realistic ablation scenarios. Overall, the results indicate that fractional diffusion provides a flexible and physiologically meaningful framework for modeling heat transfer during RFA. Full article

Single crystals of the one-dimensional coordination polymer Co(dca)₂(py)₂ (dca = dicyanamide, py = pyridine) were synthesized from methanolic solution and characterized by single-crystal X-ray diffraction, infrared spectroscopy, UV/Vis spectroscopy, thermal analysis, and magnetic susceptibility measurements. It crystallizes in the monoclinic space group I2/m with lattice parameters a = 7.3829(5) Å, b = 13.2221(7) Å, c = 8.4934(6) Å, and β = 114.766(9)°, and consists of octahedrally coordinated Co²⁺ ions linked by μ_1,5-bridging dca ligands, resulting in linear chains. Magnetic data reveal behavior as a one-dimensional system and a transition into a magnetically ordered state at T_C = 8.1 K, associated with weak ferromagnetic hysteresis behavior and slow magnetic relaxation. The results demonstrate the important role of magnetic anisotropy in stabilizing long-range order in this low-dimensional Co(II) coordination polymer. Full article

This review shows that lignocellulosic biomass is not merely an abundant feedstock for nanocellulose production but a strategic platform for building the next generation of sustainable, high-performance materials, integrating feedstock diversity, processing logic, characterization, market direction, and translational applications into a single narrative. Comparing woody and non-woody biomass through the lens of processability, recalcitrance, and value creation while showing why agricultural residues are increasingly central to low-cost, circular nanocellulose production beyond the usual acid-hydrolysis-centered discussion by emphasizing enzymatic hydrolysis as a lower-energy, lower-toxicity alternative while still acknowledging the persistent industrial advantages and environmental costs of chemical and mechanical routes. A further strength of this review is its effort to bridge structure and function: it links extraction strategy to morphology, crystallinity, thermal stability, and surface chemistry, then connects these properties to real applications in packaging, drug delivery, electronics, filtration, energy storage, and biomedical systems. Its distinctive contribution lies in showing that the future of nanocellulose depends not only on how it is extracted but also on how intelligently the biomass source, processing route, material performance, and market need are aligned. Full article

The increasing demand for materials with enhanced properties and high-performance devices has driven substantial research into nanomanufacturing, particularly using carbon nanotubes (CNTs), because of their exceptional properties and high sensitivity to chemical doping. In this way, this work summarizes nanomanufacturing methods for CNT-based devices developed in Brazil, covering the complete cycle from nanocomposite production to functional device assembly across cellulosic, polymeric, and metallic matrix systems. For cellulosic matrices, vacuum filtration enables the production of buckypaper, which is subsequently assembled into chemiresistive, thermoresistive, and thermoelectric devices. For polymeric matrices, 3D printing combined with surface functionalization techniques (spray coating, inverted immersion, and direct immersion) produces piezoresistive robotic sensors, metal-free thermal sensors, and biomedical scaffolds for tissue engineering. For metallic matrices, electrodeposition can produce Cu-CNT-coated aluminum comparable to traditional copper power transmission cables, while arc welding produces stainless steel composites with properties comparable to commercial high-grade steels. These devices have commercial and industrial applications, with low-cost and scalable production methods in comparison with conventional materials. Characterization results demonstrate that CNT integration into diverse matrices successfully bridges nanoscale properties to macroscopic functional devices. Current challenges include uniform CNT dispersion and structural defect control, laboratory to industry scale transition, and long-term device stability under environmental conditions. Future perspectives encompass lab-on-chip systems, wearable devices, 3D-printed smart structures, Internet of Things integration, and machine learning-enhanced analytics. Full article

This work investigates the potential of additive manufacturing (AM) technologies for prototyping and developing functional components in thermal systems, with particular emphasis on thermal and mechanical performance. The study focuses on two complementary prototyping strategies: (i) the use of metal-filled polymer filaments in Fused Deposition Modeling (FDM), also known as Material Extrusion (MEX) according to ISO/ASTM 52900:2022, and (ii) a hybrid approach combining polymer 3D printing with conductive coating and electrochemical copper deposition. While metal-filled filaments provide a rapid and low-cost solution for early-stage prototyping, their mechanical properties remain similar to those of the polymer matrix, limiting their applicability in load-bearing structures. In contrast, the hybrid method enables the fabrication of hollow metallic geometries with improved thermal and electrical conductivity. This approach is more time-consuming and process-intensive and is therefore considered a subsequent stage in the prototyping workflow following initial MEX-based design iterations. Compared with conventional polymer-based MEX, several AM approaches enable the development and fabrication of fully metallic or metal-functional structures, including Powder Bed Fusion (PBF), Directed Energy Deposition (DED), and hybrid polymer–metal methods based on electroplating. Furthermore, understanding mechanical properties such as tensile strength is essential for assessing the applicability of AM materials in energy system components. The results contribute to bridging the gap between rapid prototyping and the implementation of advanced AM technologies in thermal-related applications. Full article