Search Results (21,914)

Decarbonizing the construction sector requires high-volume replacement of Portland clinker with non-calcined supplementary cementitious materials (SCMs). This study investigates white cement pastes incorporating raw Algerian diatomite—a silica-rich biogenic mineral—at substitution levels from 40% to 95% (5% increments) and a fixed water-to-binder ratio of 0.5. The target application is ultra-lightweight, multifunctional composites for non-structural uses such as decorative panels and partition elements. Increasing diatomite content progressively reduced bulk density from 1.483 g/cm${}^3$ (D40) to 0.557 g/cm${}^3$ (D95) and increased porosity. 28-day compressive strength decreased monotonically from 16 MPa (D40) to 2.4 MPa (D95) as clinker dilution intensified. Ultrasonic pulse velocity dropped from 6205 m/s to 1495 m/s, reflecting progressive pore development and confirming the material’s lightweight potential. Statistically significant strength gains beyond 28 days were recorded ($+25.87\%$ for compression, p-value$<0.05$), evidencing delayed pozzolanic activity. These results confirm that raw, non-calcined diatomite is a viable SCM for eco-efficient, low-density construction systems. To overcome the extrapolation instability of purely data-driven approaches, a Meta-Avrami Hybrid Framework was developed. It anchors Gradient Boosting residual learning to a sigmoidal Avrami hydration kernel. The model achieved high predictive accuracy ($R^2\approx 0.999$, $\mathrm{RMSE}\approx 0.010$) under 10-fold cross-validation. Generalization was well-controlled, with a low overfitting gap ($\Delta R^2=0.0226$) and stable fold-to-fold performance ($\mathrm{Std}=0.0204$). These metrics confirm suitability for unseen mix designs. This is particularly relevant for service-life assessment of partition panels and lightweight façade elements, where long-term performance guarantees are required. The physics-informed architecture ensures asymptotic strength stabilization up to a 10-year horizon (amplification ratios 1.03–1.05). This prevents the non-physical divergence observed in polynomial and power-law hybrids (ratios 1.36–1.70). The framework provides a reliable and interpretable tool for service-life design of sustainable low-carbon cementitious systems. Full article

The global shift toward electric vehicles (EVs) has accelerated as governments pursue low-carbon transport systems and sustainable mobility transitions. In emerging economies such as Thailand, however, consumer adoption remains influenced by a complex interplay of policy incentives, perceived benefits, and charging-related uncertainties. This study investigates the determinants of EV adoption intention by integrating ecosystem and policy support with perceived value and perceived risk within a unified analytical framework. Grounded in customer perception theory and technology adoption perspectives, this research addresses the fragmented treatment of these factors in prior studies. Data were collected from 400 respondents with prior EV experience and analyzed using structural equation modeling to examine both direct and mediated relationships. The findings reveal that ecosystem and policy support significantly strengthen adoption intention, primarily by enhancing perceived value and reducing perceived risk. These results highlight the pivotal role of perception-based mechanisms in translating policy initiatives into consumer commitment. The study suggests that effective EV promotion in Thailand and similar emerging markets requires coordinated ecosystem development, clear policy communication, and reliable charging infrastructure to sustain long-term adoption momentum. Full article

Fused deposition modeling (FDM) of carbon fiber-reinforced polycarbonate (PC-CF) is increasingly used in medical applications due to its excellent strength-to-weight ratio and adaptability for custom geometries. However, sterilization is a critical step that may compromise the structural integrity of polymer composites. This study investigates the effects of two low-temperature sterilization methods—ethylene oxide (EO) and hydrogen peroxide vapor (HP)—on the mechanical, thermal, and viscoelastic properties of FDM-printed PC-CF parts. Characterization included tensile, impact, and hardness tests; thermomechanical analysis (TMA); and dynamic mechanical analysis (DMA). EO sterilization resulted in approximately 20% reduced elongation at break and lower glass transition temperature, indicating a loss of ductility and thermal stability. HP-treated samples showed reduced stiffness (16% in Young modulus) but increased Tg and reduced thermal expansion, suggesting improved dimensional stability. DMA results confirmed distinct viscoelastic behavior between treatment types. These findings provide evidence for selecting appropriate sterilization protocols for FDM-manufactured PC-CF components used in functional medical devices. Full article

The inorganic proton acid-doped polyaniline (H-PANI-X) is synthesized directly on a graphite carbon paper electrode. The polyaniline doped with hydrochloric acid (yielding H-PANI-Cl), sulfuric acid (yielding H-PANI-HSO₄), and nitric acid (yielding H-PANI-NO₃) is employed to construct both finite molecule and periodic molecule computational models. Theoretical calculation and experimental measurement of a polyaniline/graphite carbon paper electrode are adopted to reveal the doping effect of inorganic acid radical ions (Cl⁻, HSO₄⁻, NO₃⁻) on electrical and electrochemical properties of H-PANI-X. H-PANI-X shows a lower electronic band gap structure, indicating more feasible electron transfer than PANI. H-PANI-X shows a lower HOMO-LUMO orbital energy gap, indicating lower excitation energy than PANI. H-PANI-X also shows a higher electronic density of states level, indicating higher electrical conductivity than PANI. The charge density difference of H-PANI-X reveals a more delocalized electrostatic potential distribution, indicating an enhanced electrostatic interaction between protonated PANI and charge-balancing anions. Furthermore, H-PANI-HSO₄ and H-PANI-NO₃ exhibit hydrogen bonding between the protonated PANI and charge-balancing anions, resulting in reduced electronic band gaps and enhanced electronic density of states compared with H-PANI-Cl. H-PANI-NO₃ with higher electronic states at the Fermi level and higher anionic electronegativity exhibits higher electrical conductivity than H-PANI-Cl and H-PANI-HSO₄. The experimental measurement is conducted to investigate the electrochemical properties of H-PANI-X. The electrochemical impedance spectroscopy measurement indicates H-PANI-NO₃ maintains lower charge transfer resistance (0.357 Ω) than H-PANI-HSO₄ (3.003 Ω) and H-PANI-Cl (10.571 Ω). The cyclic voltammetry measurement indicates that H-PANI-NO₃ has much higher redox current and mean current density responses, accordingly exhibiting superior capacitance (208.0 mF cm⁻²) performance in comparison with H-PANI-Cl (129.5 mF cm⁻²) and H-PANI-HSO₄ (157.9 mF cm⁻²). Theoretical calculation and experimental investigation confirm H-PANI-NO₃ presents superior electroactivity to H-PANI-Cl and H-PANI-HSO₄ for promoting its electrochemical capacitance performance. Full article

For shipboard CCUS facilities, the integration of chemical absorption columns is constrained by a limited vertical envelope, which motivates packings with axially stretched or compressed Kelvin cells to support compact layout and flow control. This study employs computational fluid dynamics to investigate microscale flow and mass transfer characteristics in Kelvin cells. A comparison among the regular Kelvin cell (RKC), the vertically elongated Kelvin cell (VEKC), and the vertically compressed Kelvin cell (VCKC) indicates that axial stretching and compression modify internal flow distributions and gas–liquid mass transfer during CO₂ absorption. The liquid distribution transitions from a film along the struts with localized accumulation at the nodes in RKC to a continuous columnar stream in VEKC, and then to a stable hollow cylindrical liquid film promoted by lateral redistribution in VCKC. VCKC promotes a stable and expanded liquid film, whereas VEKC tends to induce columnar flow. Reducing the cell size and porosity improves mass transfer efficiency, and the liquid load governs mass transfer flux. These findings provide theoretical guidance for the design and optimization of compact packings for process intensification in shipboard carbon-capture applications. Full article

Blast furnace cement-dolomite mortars prepared from commercial cement (CEM-III/B) containing ~75% of slag and natural dolomite were aged under accelerated conditions at 60 °C in 1 M NaOH for 0–24 months. The hydration products and microstructure features of the mortars were studied using XRD, TGA and SEM-EDS methods, with blast furnace cement paste for comparison. The results showed that the presence of dolomite enhanced slag hydration, as the carbonates released during dedolomitisation promoted Ca and Si dissolution from the slag grains. After prolonged ageing, a multi-rim structure was observed around the slag particles: the inner rim primarily consisted of a hydrotalcite-like phase mixed with C-S(A)-H gel, while the outer rims were richer in C-S(A)-H gel, with varying calcium content. Monocarbonate phase was additionally detected at the slag–paste interface in the presence of dolomite. The observed increase in mechanical strength during ageing had to do with two reasons: (i) the increase in hydration product content and (ii) the densification of microstructure due to the formation of calcium carbonate, which filled pores and microcracks and the possible carbonation of C-S (A)-H gel in the binding paste. Under the investigated alkaline ageing conditions, dolomite acts as a chemically active component rather than an inert filler, influencing both slag hydration kinetics and the composition of the resulting hydration products. Full article

This study examined the effects of particle size blending and hybrid binder content on the structural properties and methane adsorption behavior of coconut shell-based activated carbon monoliths. Monoliths were prepared using activated carbon particles with two size ranges (212–250 µm and 26–53 µm), blending ratios of 1:9, 3:7, 5:5, and 7:3, and a hybrid binder containing styrene–butyl acrylate (SBA) and carboxymethylcellulose (CMC). Morphology and elemental composition were analyzed by SEM-EDS, specific surface area and pore structure were evaluated by BET analysis, and surface properties were examined by XPS. Structural density and compressive strength were also measured. Among the tested samples, M50ML showed the highest structural density (0.544 g/cm³), compressive strength (27.5 MPa), and methane uptake (3.06 mg/g). This result was related to improved packing by particle size blending while maintaining microporosity. These results indicate that particle size blending and binder content significantly affected the structural properties and methane adsorption behavior of the prepared monoliths. Full article

Water, energy, and food (WEF) are essential resources for sustaining urban development, yet their production and consumption generate substantial carbon dioxide (CO₂) emissions. Carbon-reduction policies designed to curb these emissions have profound impacts on WEF systems by reshaping both the resource production and consumption patterns. This study employs system dynamics (SD) modeling to examine the mutual interactions between the WEF system and carbon emissions through scenario analysis for the period of 2016–2030. A WEF–carbon SD model comprising 76 variables is developed and calibrated using data from 2016 to 2023. The results show that under the business-as-usual (BAU) scenario, energy consumption continues to increase, while CO₂ emissions rise slightly from 87.2 million tonnes in 2023 to 88.7 million tonnes in 2030. In contrast, under the economic optimization scenario (e.g., through industrial structure adjustments), water consumption will be reduced by approximately 100 million cubic meters by 2030 compared with the BAU scenario. Energy consumption declines by about 7%, food production decreases slightly by 4%, and CO₂ emissions are reduced by 7.9%. Furthermore, land-use changes will enhance the carbon sequestration capacity by 12.67% in 2030, while exerting only marginal effects on CO₂ emissions (less than 1%) and water consumption. Overall, this study enriches the existing WEF–carbon nexus modeling and provides policy-relevant insights for Beijing to reduce carbon emissions from an integrated WEF perspective. Full article

During a tunnel fire, the foremost priority is the safe evacuation of passengers. Extreme temperatures and toxic combustion products can quickly lead to mass casualties, so evacuation support systems require fast forecasts of how hazardous conditions will evolve in space and time. This study investigates whether sparse sensor measurements can be used to reconstruct future tunnel-wide fire conditions on two-dimensional sections that are directly relevant to structural assessment and human exposure. To this end, we develop 2D ST-FAM, a data-driven forecasting model that maps time-resolved measurements from 75 tunnel sensors to future temperature, soot, and carbon monoxide (CO) fields derived from 108 computational fluid dynamics (CFD) fire simulations. The study is organized around three questions: whether the model can accurately reconstruct future tunnel fields from sparse measurements, whether this performance is maintained on both the vertical center plane and the horizontal breathing plane, and which physical quantities remain most challenging to predict. Results show high structural agreement with the CFD reference fields over the full 1800 s prediction horizon, with average structural similarity index (SSIM) values of 0.964 for temperature, 0.984 for CO, and 0.937 for soot. These findings indicate that sparse-sensor forecasting is feasible for tunnel-scale temperature and toxic-gas field prediction, while soot prediction remains comparatively more difficult because of its sharper spatial structures. Full article

Driven by the growing global energy demand and the pursuit of carbon utilization goals, dry reforming of methane (DRM) has attracted considerable attention for its ability to convert CO₂ and CH₄ into syngas. Biogas, an eco-friendly product of processes such as anaerobic digestion, is primarily composed of CO₂ and CH₄ and ideally meets the feedstock requirements for DRM. In practice, biogas is generated via anaerobic digestion of livestock manure and other organic waste, providing a stable and sustainable source for the DRM reaction and thus enabling waste valorization. Supported Ni⁰ catalysts have become a research focus in this field due to their high catalytic activity and moderate cost. Conventional particulate Ni⁰ catalysts, however, are prone to carbon coking in fixed-bed applications and are difficult to effectively recover and regenerate after the reaction; thus, they are often being discarded, leading to resource waste and environmental burden. To address these issues, this study has designed a novel metal-sintered fleece catalyst support and developed a corresponding reactor. The effects of the catalyst preparation method, activation conditions, and the support structure on DRM performance have been systematically investigated. The spent Ni-based catalyst could be regenerated via calcination to restore catalytic activity and enable multiple cycles of use, significantly extending the catalyst’s lifespan and offering both economic and environmental benefits. Experimental results have demonstrated that the reactor achieved a conversion rate exceeding 80% with near-complete product selectivity. Full article

This study quantitatively evaluates the effect of solid-phase pre-reduction of chromite concentrate on the energy efficiency and techno-economic performance of high-carbon ferrochrome (HC FeCr) smelting. Laboratory pre-reduction experiments were conducted at 1200–1400 °C using Shubarkol coal, metallurgical coke, and special coke as carbonaceous reducing agents. Structural and phase transformations were characterized by X-ray diffraction (XRD) and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS). At 1200 °C, the degree of metallization remained low (<5%), whereas at 1400 °C it increased to 41.3% under laboratory conditions and up to 65% in pilot-scale tests due to the decomposition of the spinel matrix and the formation of metallic and carbide phases. The application of pre-reduced feedstock in a submerged arc furnace reduced specific electricity consumption by up to 33.5% compared with conventional smelting and increased chromium recovery to 89.71%. Industrial-scale extrapolation indicates the potential to decrease power consumption to approximately 3190 kWh/t of alloy. Techno-economic analysis demonstrates that the use of pre-reduced feedstock reduces the production cost by approximately 10–23%, depending on the type of carbonaceous reducing agent (Shubarkol coal, metallurgical coke, or special coke). Special coke provided the highest energy efficiency, whereas Shubarkol coal ensured the greatest direct economic benefit. The integrated microstructural, energetic, and economic assessment confirms the industrial applicability of the proposed pre-reduction approach. Full article

This paper proposes a physics-informed hybrid digital CO₂ emission-control technology for maritime transport, designed for adaptive ship speed optimization along a predefined geographical route between two ports, discretized into quasi-stationary segments and evaluated under forecasted metocean conditions, subject to economic and regulatory constraints associated with maritime decarbonization. The framework integrates two exact optimization methods, Backtracking (BT) and Dynamic Programming (DP), with a reinforcement learning approach based on Proximal Policy Optimization (PPO), operating on a unified physical, economic, and regulatory modeling core. By reducing propulsion fuel demand, the system acts as an upstream CO₂ emission-control mechanism for ship propulsion. This operational stabilization of the engine load creates favourable boundary conditions for advanced combustion processes and reduces the volumetric flow of exhaust gas, thereby lowering the technical burden on potential post-combustion carbon capture systems. Segment-wise speed profiles are optimized subject to propulsion limits, Estimated Time of Arrival (ETA) feasibility, and regulatory constraints, including the Carbon Intensity Indicator (CII), the European Union Emissions Trading System (EU ETS) and FuelEU Maritime. The physics-based propulsion and energy model is validated using full-scale operational data from four real voyages of an oil/chemical tanker. A detailed case study on the Milazzo–Motril route demonstrates that adaptive speed optimization consistently outperforms conventional cruise operation. Exact optimization methods achieve voyage time reductions of approximately 10% and fuel and CO₂ emission reductions of about 9–10%. The reinforcement learning approach provides the best overall performance, reducing voyage time by approximately 15% and achieving fuel savings and CO₂ emission reductions of about 13%. At the route level, the Carbon Intensity Indicator is reduced by approximately 10% for the exact methods and by about 13% for PPO. Backtracking and Dynamic Programming converge to nearly identical globally optimal solutions within the discretized decision space, while PPO identifies solutions located on the most favourable region of the cost–time Pareto front. By benchmarking reinforcement learning against exact discrete solvers within a shared physics-informed structure, the proposed digital platform provides transparent validation of learning-based optimization and offers a scalable decision-support technology for pre-fixture evaluation of fixed-route voyages. The system enables quantitative assessment of CO₂ emissions, ETA feasibility, and regulatory exposure (CII, EU ETS, FuelEU Maritime penalties) prior to transport contracting, thereby supporting economically and environmentally informed operational decisions. Full article

The durability of reinforced concrete structures is significantly affected by the carbonation process, which decreases the alkalinity of the pore solution and initiates corrosion of the steel reinforcement. However, the square roots of time equations, which are Fickian diffusion-based, are not able to accurately capture the nonlinear interactions of material properties with environmental factors. To overcome this limitation, this research introduces a novel hybrid model based on the integration of a physics-informed neural network (PINN) with residual regression via CatBoost, a categorical boosting algorithm. Using an expanded dataset of 6000 samples, the first stage of the model, which is based on the physics-informed neural network, is able to learn the underlying physics of the diffusion process by imposing monotonicity constraints. The second stage of the model, which is based on the CatBoost algorithm, is able to learn the residuals of the nonlinear interactions of factors such as the curing time, water–cement ratio, and supplementary cementitious material reactivity, which are not captured by the underlying physics of the diffusion law. Data augmentation via physics-based resampling increased the dataset from 3000 to 6000 samples. Validation of the model using 1200 samples resulted in R² = 0.871, MAE = 15.362, and RMSE = 24.37. SHAP confirmed that the model was physically consistent with the principles of concrete technology, reversing the counterintuitive linear correlations to accurately capture the protective effect of longer curing times. The suggested framework offers a practical method for enhancing durability evaluation and aiding the maintenance and service-life management of reinforced concrete structures. Full article

Developing sustainable electrode materials from renewable biomass is important for improving the environmental sustainability of lithium-ion batteries (LIBs). Sugarcane bagasse lignin, an abundant agricultural byproduct, is a promising precursor for lignin-derived carbon anode materials, yet systematic comparative studies on catalyst-dependent structure evolution and LIB performance remain limited. In this study, lignin extracted from sugarcane bagasse by an ethanosolv process was converted into Fe- and Ni-catalyzed lignin-derived carbon materials via catalytic pyrolysis at 900 °C. The effects of catalyst type, metal-to-lignin ratio, and pyrolysis holding time on textural properties, structural features, and electrochemical behavior were systematically investigated. Among the studied conditions, the Fe-catalyzed sample prepared at a metal-to-lignin ratio of 1:2.5 and a holding time of 3 h (GLKL-2.5Fe-3h) exhibited the highest BET surface area (332.71 m² g⁻¹) and the most developed porous morphology. SEM, TEM, Raman, and XRD analyses indicated catalyst-dependent differences in pore development, carbon domain morphology, and local graphitic ordering, with Fe- and Ni-catalyzed samples following distinct structural evolution pathways. Electrochemical testing showed that GLKL-2.5Fe-3h delivered the highest initial discharge capacity (759 mAh g⁻¹), retained 165 mAh g⁻¹ after 500 cycles, and exhibited more favorable rate performance and lower apparent interfacial resistance than the other tested samples under the same conditions. In contrast, the Ni-catalyzed and solvothermally treated samples showed lower capacity retention and/or less favorable electrochemical behavior. These results demonstrate the strong effect of catalyst type on the structure-performance relationship of bagasse lignin-derived carbon anodes and support Fe-catalyzed lignin-derived carbon as a promising sustainable anode candidate for LIB applications. Full article

Stimulating electronic transitions and promoting exciton dissociation are key to enhancing the photocatalytic performance of polymer carbon nitride (PCN). Herein, a controllable synthesis strategy based on supramolecular self-assembly and mild salt melting crystallization has been developed, successfully preparing carbon nitride-based photocatalytic materials with tunable crystal phase composition. The mixed crystal phases effectively induced significant n→π* electronic transition, expanding the material’s light response range to the near-infrared region (700 nm). Meanwhile, the homojunction promoted the efficient separation of photogenerated carriers through the built-in electric field. Under visible-light excitation, this material exhibits excellent selective catalytic performance, over 99% for the oxidation and removal of H₂S into elemental sulfur. This synergistic mechanism of crystal phase engineering in regulating electronic structure and interface charge dynamics provides a new material design strategy for efficient non-metallic photocatalysts. Full article