Search Results (341)

The successful application of extrusion-based 3D-printed geopolymer mortars largely depends on precursor chemistry, activator composition, mixture proportions, and fresh-state behavior, which is highly sensitive to time-dependent structural build-up. This review examines the relationships among mix design, geopolymerization chemistry, rheological properties, and printability requirements for 3D-printed geopolymer mortars. Particular emphasis is placed on the effects of precursor type, alkaline activator characteristics, liquid-to-solid ratio, additives, and fibers on flowability, yield stress, viscosity, extrudability, buildability, shape retention, and interlayer bonding. The review further discusses how geopolymerization kinetics influence the evolution of fresh-state properties, the printable time window, and the transition from extrusion to structural stability. In addition, early-age performance is evaluated in terms of setting behavior, green strength development, and layer-interface integrity. Current challenges, including the lack of standardized test methods, limited comparability among published studies, and the complex coupling between material design and process parameters, are also highlighted. Finally, the review identifies key research gaps and proposes future directions for developing robust, printable, and sustainable geopolymer mortar systems for additive manufacturing in construction. Full article

Gold-mine tailings have attracted increasing interest as alternative constituents in cement-based materials, yet their use in structural concrete remains limited by the lack of multivariable approaches capable of capturing the interaction between tailing fractions with different functional roles. In this study, a tailing-derived fine aggregate and a fine tailing sludge from the Cisneros Project (Santo Domingo, Antioquia, Colombia) were jointly incorporated into structural concrete and evaluated through a response surface methodology based on a central composite design. The tailings were characterized by physical, chemical, mineralogical, and morphological analyses, while concrete mixtures proportioned according to ACI 211 were assessed in terms of 28-day compressive strength. The statistical model revealed a significant quadratic response and a strong interaction between both incorporation variables. The most favorable strength region, based solely on 28-day compressive strength, was identified at sludge contents below 20% and tailing aggregate replacement below 90%, with the latter interpreted as a preliminary mechanical threshold rather than as a practical recommendation for field application. Higher incorporation levels led to strength losses associated with the increasing fineness of the system and greater water demand. This study demonstrates that the performance of tailing-modified structural concrete depends on the coordinated dosage of fractions with distinct roles and provides preliminary mechanical incorporation limits based solely on 28-day compressive strength. Since durability and environmental safety tests, including heavy metal/cyanide leaching, permeability, shrinkage, and chemical resistance, were not conducted, these limits should not be interpreted as definitive recommendations for long-term structural application. Full article

The transition towards a circular economy in architecture requires new methods for reusing construction and demolition waste as a material resource. Recycled aggregates are a promising alternative to natural aggregates, although their variable porosity and particle grading often limit practical application. This study evaluates the suitability of recycled concrete aggregate (RCA) and recycled ceramic aggregate for small-scale architectural elements such as street furniture. Three comparative mixtures were analysed using particle size distribution data, the Modified Andreasen model, and the EMMA (Elkem Materials Mix Analyzer) tool. Two mixtures contained recycled aggregates, while one reference mixture was based on natural aggregates. The assessment focused on particle packing, water demand, and binder content. The recycled concrete aggregate mixture showed results closest to the reference mix, with water content of 180 kg/m³ and a water-to-cement ratio of 0.50, compared with 170 kg/m³ and 0.50 for the natural aggregate mixture. The ceramic aggregate mixture required the highest water content (200 kg/m³) and cement dosage (380 kg/m³) due to its higher porosity (15–18%) and finer particle fraction. By adjusting aggregate proportions within the packing model, satisfactory particle structuring was still achieved in all mixtures (q = 0.31–0.35). The study shows that particle packing methods, commonly used in concrete technology, can also support early-stage architectural material selection. Recycled aggregates, particularly RCA, may therefore be considered a viable substitute for natural materials in benches, seating panels, and other small-scale circular design applications. Full article

Inaccurate prediction of shrinkage in self-compacting concrete (SCC) may result in underestimated cracking risk, increased permeability, serviceability deterioration, and reduced long-term durability of concrete structures. Although conventional empirical shrinkage models are widely used in engineering practice, their accuracy is often limited when applied to SCC mixtures with high paste volume, mineral admixtures, manufactured sand, and high-range water-reducing admixtures. Recent machine-learning-based models provide an alternative approach, but single learning algorithms may show limited robustness for small and heterogeneous datasets. In addition, random sample-level data splitting may introduce information leakage when shrinkage measurements obtained at different curing ages from the same mixture are assigned to both training and testing sets. To address these issues, this study develops a stacking-based ensemble learning framework for SCC shrinkage prediction using mixture proportions and curing age as input variables. A multi-source database containing 61 mixture designs and 448 data samples was established from published experimental studies. To obtain a more realistic assessment of model generalization, a mixture-level validation strategy was adopted, in which all age-dependent samples from the same mixture were assigned exclusively to either the training set or the testing set. Under this strategy, 358 data samples were used for model training and 90 data samples were used for independent testing. Four base learners, including multilayer perceptron (MLP), support vector regression (SVR), decision tree (DT), and gradient boosting decision tree (GBDT), were constructed and integrated through different ensemble configurations. The Stacking-SVR model achieved the best overall performance on the independent testing set, with a mean absolute error (MAE) of 13.6 με and a mean absolute percentage error (MAPE) of 7.5%. Compared with GBDT, Stacking-GBDT, and DT models, the proposed Stacking-SVR model reduced the MAPE by approximately 10.7%, 11.8%, and 35.3%, respectively. Stability and applicability analyses further indicate that the proposed framework can provide reliable shrinkage predictions within the investigated mixture and curing-age ranges. However, because the model was developed from a compiled database and does not explicitly include environmental variables such as relative humidity and temperature, its use should be limited to parameter ranges represented in the database. Overall, the results demonstrate that stacking ensemble learning combined with mixture-level validation offers a leakage-controlled and engineering-oriented approach for SCC shrinkage prediction. Full article

The use of iron tailing powder (ITP) and granulated blast-furnace slag (GBFS) offers a feasible route for preparing low-cement mortar while recycling industrial by-products. In this study, seven cement mortar mixtures were designed to investigate the influence of the ITP–GBFS ratio on mechanical properties, microstructure, hydration products, and chloride ion penetration resistance. The mixtures included plain cement mortar (A0), mortar with 50% ITP (A1), mortar with 50% GBFS (A2), and four composite mixtures (A3–A6) in which ITP and GBFS jointly replaced 50% of cement at different ratios. The results showed that the mixture containing 20% ITP and 30% GBFS (A4) exhibited the best overall performance among the composite mixtures. At 28 d, A4 reached a compressive strength of 51.3 MPa and a flexural strength of 11.0 MPa, exceeding those of the plain cement control. SEM and XRD analyses suggested that the optimized ITP–GBFS combination promoted the formation of poorly crystalline hydration products, such as C–S–H/C–A–S–H gels, and refined the pore structure, resulting in a denser hardened matrix. The rapid chloride migration test showed that the chloride migration coefficient of A4 was 15.47 × 10⁻¹² m²/s, only slightly higher than that of A0, indicating that the optimized composite binder maintained chloride penetration resistance close to that of plain cement mortar while replacing 50% of cement. The results indicate that a properly proportioned ITP–GBFS binder can maintain acceptable strength and chloride resistance while reducing cement consumption. Full article

In southern Brazil, a large proportion of farmers maintain their fields under fallow conditions during the transition period between summer and winter crops. During this interval, mechanical practices such as chiseling or the introduction of cover crop species may contribute to improving soil management and conservation in no-tillage systems. Therefore, this study aimed to investigate the effects of mechanical soil chiseling and production system intensification on soil physical–hydric properties and soybean performance. The experiment was conducted in São José do Ouro, Rio Grande do Sul, Brazil, from September 2023 to April 2025. The experimental design consisted of three factors: soil management (spring 2023 chiseling, autumn 2024 chiseling, and a no-till control), post-maize cover (millet and fallow conditions), and winter cover crops (black oat, white oat, vetch, and radish) grown either as monocultures or in mixtures. A randomized block design with split plots and three replicates was used. The evaluated variables included dry biomass of winter cover crops, soil bulk density, total porosity, microporosity, macroporosity, soil water content at field capacity, soil penetration resistance, plant gas exchange, leaf area index, thousand-grain weight, and soybean grain yield. The results indicated that soil chiseling altered soil physical properties by reducing soil bulk density, penetration resistance, microporosity, and field capacity, while increasing total porosity and macroporosity. Soil chiseling promoted short-term increases in thousand-grain weight and soybean grain yield, with no persistent effects after 20 months. Production system intensification, through the use of cover crops and millet, did not affect grain yield but increased stomatal conductance and soybean leaf area index. Therefore, occasional tillage in high-clay subtropical Oxisols should be strategically applied and associated with long-term conservation agriculture practices to sustain improvements in soil physical quality. Full article

Agricultural and agro-industrial waste can be valorized through biodrying, a process that uses microbial activity to accelerate water loss to obtain a biodried material (BM) with high calorific value and potential use as a biofuel. This material has the advantage of being easily transported, stored, and preserved until later use. However, its high organic matter content allows it to be used for other purposes. In this study, the use of BM (made from orange peel, grass, mulch, pruning waste, and compost), either alone or mixed with fresh organic waste (FOW) as feed for Eisenia foetida in a vermicomposting system, was evaluated over a period of 49 days. The proportions of BM used were 100%, 75%, 50%, 25%, and 0%, with the remainder completed with FOW. During the bioprocess, temperature, moisture, and pH were monitored, and at the end of the experiment, the survival and reproduction of E. foetida as well as the quality of the humus obtained were analyzed. In the treatments containing 100% and 75% BM, worm survival was reduced by 28.5% and 7.7%, respectively, although the highest number of cocoons (28 and 24 cocoons kg_humus⁻¹) was observed in these treatments compared with all others. The humus obtained from all treatments complied with the NMX-FF-109-SCFI-2008 standard, which designates quality grades as extra, first, and second. The treatment with 100% BM produced first-quality humus, but the treatments with mixtures of BM and FOW produced extra-quality humus. The results support the diversification of BM uses and its incorporation into sustainable bioprocesses such as vermicomposting and the production of new value-added products. Full article

This study develops a ternary Fe-based geopolymer system composed of metakaolin (MK), red mud (RM), and fly ash (FA) for the preparation of sustainable water-retaining subgrade materials for sponge-city roadbed applications. Unlike conventional formulations primarily designed for structural strength or rapid permeability, the proposed MK–FA–RM system was designed to improve water-storage capacity while maintaining adequate mechanical support and environmental compatibility. In this ternary system, MK provides highly reactive aluminosilicate species for geopolymer network formation, RM introduces Fe-bearing phases and enhances industrial solid-waste utilization, and FA contributes to particle packing, workability, and resource efficiency. A constrained ternary mixture design implemented using Design-Expert software was adopted to optimize precursor proportions. Within the investigated compositional range, the fitted first-order mixture model showed acceptable statistical adequacy for preliminary composition screening (R² = 0.86). The optimal blend (60% MK, 30% RM, and 10% FA) achieved a 7-day compressive strength of 8.37 MPa and a water retention rate of 35.3% under ambient curing conditions, satisfying the strength requirement considered for the target subgrade/base-layer application. Microstructural and phase analyses suggest that the synergistic interaction of the three precursors promoted Fe-modified aluminosilicate gel formation together with conventional geopolymer gel products, while improving matrix continuity and preserving interconnected pore space for water storage. This multiscale structural effect helps explain how the material achieved a balance between water retention capacity and mechanical support. Under the tested conditions, the material maintained acceptable residual strength after short-term exposure to water, acid, and sulfate-containing solutions. Life-cycle assessment indicated a 70% reduction in CO₂ emissions compared with ordinary Portland cement, while pilot-scale cost analysis showed a 39% lower production cost than MetaMax-based geopolymer materials. Pilot-scale application further demonstrated the constructability and water-regulation potential of the material in practical environments. Overall, the proposed ternary Fe-based geopolymer demonstrates that Fe-rich industrial wastes can be engineered into low-carbon and economically viable water-retaining subgrade materials that balance hydraulic regulation, structural adequacy, and sustainability. Nevertheless, long-term durability, cyclic loading performance, and direct nanoscale characterization of Fe-bearing gel evolution still require further investigation. Full article

Chirality has emerged as a critical determinant in the design, efficacy, and environmental behavior of modern insecticides. While a significant proportion of agrochemicals are inherently chiral, most are still commercialized as racemic mixtures, despite well-documented differences in biological activity, toxicity, and degradation pathways between enantiomers. In this review, we provide a comprehensive and critical analysis of advances in the stereoselective synthesis and resolution of chiral insecticides, with particular emphasis on neonicotinoids, pyrethroids, and oxadiazines, including indoxacarb. A systematic survey of the literature (1985–2025), including peer-reviewed articles and patents, reveals that multiple strategies have been developed to access enantiomerically enriched compounds, including asymmetric organocatalysis, transition-metal catalysis, chiral-pool approaches, biocatalytic transformations, and chromatographic resolution techniques. Among these, recent developments in photoredox catalysis, recyclable metal complexes, and enzyme-mediated processes have significantly improved enantioselectivity and scalability, bridging the gap between academic methodologies and industrial applications. Despite these advances, challenges remain in achieving cost-effective, sustainable, and universally applicable asymmetric processes. Importantly, the relationship between stereochemistry and biological performance underscores the need for integrating synthetic chemistry with toxicological and environmental studies. Future directions point toward the incorporation of green chemistry principles, continuous-flow processes, and computational tools, including machine learning and molecular modeling, to accelerate the rational design of enantiopure agrochemicals. This review highlights both the progress achieved and the critical gaps that must be addressed to realize the potential of stereoselective insecticide development fully. Full article

While the demand for free-form architecture (FFA) has increased with advancements in computer-aided design (CAD) technology, the rationalization of complex surfaces into fabricable panels remains a significant challenge due to high production costs and technical complexity. Practical pain points, such as the prohibitive cost of unique molds and the inefficiency of manual data processing during design iterations, pose substantial economic risks. This study proposes an intelligent surface rationalization framework that integrates parametric design with machine learning algorithms in Autodesk^TM Dynamo Studio, a plug-in to Revit. A data-driven classification workflow was developed using four key geometric parameters—planarity, principal curvature (PC), Gaussian curvature (GC), and mean curvature (MC). Two unsupervised learning algorithms, a Gaussian mixture model and K-means clustering, were compared for their classification performance. As a result of two case studies, free-form surface classification by a Gaussian mixture model (CGMM) demonstrated flexibility in modeling complex surface data by probabilistically managing the uncertainty of the curvature distribution, and free-form surface classification by K-means clustering (CKC) was confirmed to be effective for the rapid classification of large-scale panel data. Optimizing the proportion of flat and single-curved panels through the proposed workflow contributes to deriving a reasonable balance between design intent and construction costs/constructability at the early design stage, and strengthening risk management capabilities for FFA. Full article

The durability and serviceability of steel-fiber-reinforced concrete (SFRC) tunnel linings in cold regions are significantly challenged by repeated freeze–thaw actions, making the accurate prediction of frost resistance a critical engineering problem. Although extensive research has been conducted on the freeze–thaw characteristics of concrete, the existing empirical and mechanism-based models remain limited in capturing the complex nonlinear interactions among mixture proportions, steel fiber characteristics, and environmental conditions. Therefore, a data-driven prediction framework based on machine learning was developed in this study. A database containing 277 groups of standardized SFRC freeze–thaw test results was established, incorporating key variables including mixture design parameters, fiber properties, and freeze–thaw cycle conditions. Four machine-learning models, namely, support vector regression, back-propagation neural network, gradient boosting, and extreme gradient boosting (XGB), were constructed and systematically compared. Model accuracy was assessed using MAE, MAPE, MSE, RMSE, and R². The results demonstrate that all models can reflect the nonlinear relationship between the input variables and mass loss rate, while the XGB model exhibits superior predictive performance with a testing R² of 0.91, representing an improvement of approximately 3–28% compared with other models. Meanwhile, the prediction errors are reduced significantly, with RMSE and MAE decreased by about 19–58% and 22–65%, respectively. The proposed approach provides an improved and reliable tool for predicting frost resistance and supports the durability design and optimization of SFRC tunnel linings in severe cold-region environments. Full article

Achieving low hydration heat without sacrificing strength is essential for early-age temperature-crack control in concrete. This study designed a low-heat Portland cement (LHPC)–fly ash (FA)–ground-granulated blast-furnace slag (GGBS)–silica fume (SF) binder system with LHPC fixed at 80 wt.% and total supplementary cementitious materials (SCMs) fixed at 20 wt.%. Compressive strength at 3, 7, and 28 d, 7 d isothermal calorimetry combined with Krstulović–Dabić (K–D) modeling, X-ray diffraction (XRD), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM) were used to identify a low-heat/high-strength pathway. The mixture containing 20 wt.% FA (F20) reduced the 7 d cumulative heat to 194.060 J·g⁻¹ but lowered the 28 d compressive strength to 44.2 MPa. Replacing FA with GGBS under the same replacement level restored the strength baseline, and the mixture containing 20 wt.% GGBS (G20) reached 56.7 MPa. Introducing SF created an optimum compositional window, and the mixture containing 10 wt.% FA, 3 wt.% GGBS, and 7 wt.% SF (F10G3S7) achieved the highest 28 d strength of 58.2 MPa. Notably, the mixture containing 10 wt.% FA, 9 wt.% GGBS, and 1 wt.% SF (F10G9S1) combined relatively low 7 d heat (203.545 J·g⁻¹) with high 28 d strength (54.2 MPa). K–D fitting showed that FA lowered the heat potential (Qmax = 217.98 J·g⁻¹) relative to LHPC (236.19 J·g⁻¹), whereas GGBS/SF blends increased Qmax to 268.77–271.55 J·g⁻¹, indicating composition-dependent hydration efficiency. TGA revealed higher bound water per unit LHPC at 28 d (21.46–22.97%) than in LHPC alone (17.17%), and bound water correlated more strongly with compressive strength (R² = 0.75–0.78) than calcium hydroxide (CH) content (R² = 0.66–0.67). SEM confirmed a more continuous gel-rich matrix in F10G9S1, suggesting that the low-heat/high-strength route is governed by efficient heat-to-hydrate conversion and microstructural densification rather than heat output alone. These findings provide both mechanistic insight and practical guidance for proportioning low-heat, high-strength binders for concrete applications requiring early-age temperature-crack control. Full article

To enhance the utilization of industrial coal gangue, response surface methodology was used to optimize the concrete mix proportions based on three key factors: the mass ratio of fly ash (FA) to metakaolin (MK) (A), the combined dosage of FA and MK (B), and the water-to-binder ratio (C). A quadratic regression model was established, and the optimal mixture was characterized using FT-IR, XRD, and SEM. The model exhibited high statistical significance (p < 0.001) and an excellent fit (R² > 0.95), confirming its predictive reliability. Single-factor analysis revealed that the order of influence on 28 d compressive strength was C > A > B, indicating that the water-to-binder ratio had the most significant effect on later-age strength. The optimal mix proportions were determined as follows: fly ash-to-MK ratio of 0.65, admixture dosage of 20% by mass of total binder, and C of 0.475. Under these conditions, the measured 28 d compressive strength reached 35.9 MPa, which was within 5% of the model-predicted value, thereby validating the model’s accuracy. Microstructural analysis demonstrated that the appropriate incorporation of FA and MK promoted the formation of C-S-H gel, refined the pore structure, and improved the quality of the interfacial transition zone, which collectively enhanced the mechanical performance. A systematic understanding of the strength and microstructural mechanisms of concrete incorporating coal gangue, fly ash, and metakaolin is currently lacking, which hinders the design of more robust and durable structures. This study addresses this gap by systematically clarifying the individual and combined effects of the key variables on the strength of coal gangue concrete. The findings reveal the underlying mechanisms, providing a scientific basis for the sustainable, large-scale application of coal gangue concrete in construction. Full article

We present a reproducible pipeline that converts color images into quantitative fluorescence maps by combining spectral measurement with a linear mixture model. The method is designed specifically for quantitative comparisons of Glo Germ™ on images of hands taken under different experimental conditions with controlled illumination. The emission spectrum of Glo Germ is measured using a spectral photometer and normalized to obtain its spectral power density function. This spectrum is projected into CIE XYZ coordinates and incorporated into a linear mixture model in which each pixel contains contributions from white light, UV-illuminated skin reflectance, and fluorophore emission. Component magnitudes are estimated with non-negative least squares, yielding a grayscale image whose intensity is a monotonic proxy for local fluorophore density. Spatial integration provides an image-level summary proportional to total detected material. Compared with single-channel proxies, the observer suppresses background structure, improves contrast, and remains radiometrically interpretable. Because the method depends only on measurable spectra and linear transforms, it can be reproduced across cameras and extended to other fluorophores. Full article

The nominal maximum aggregate size (NMAS) plays a critical role in determining the mechanical performance of cement-stabilized macadam (CSM), yet its meso-mechanical influence mechanism remains insufficiently understood. In this study, three skeleton-dense CSM mixtures with different NMAS values were designed, and a combined experimental–numerical approach was adopted to investigate the macro- and meso-scale mechanical behavior. Uniaxial compression tests and aggregate crushing value tests were conducted to evaluate strength development and load-transfer characteristics, while a three-dimensional discrete element method (DEM) model incorporating realistic aggregate morphology was established to analyze the evolution of contact forces and crack propagation. The results show that increasing NMAS significantly improves the mechanical performance of CSM. Compared with CSM-30, the 7-day compressive strength of CSM-40 and CSM-50 increased by approximately 10.3% and 37.3%, respectively. The stress–strain response indicates that mixtures with larger NMAS exhibit higher stiffness and a higher strain. At the meso-scale, a larger NMAS promotes the formation of a more efficient force-chain network dominated by coarse aggregates. Strong contacts were predominantly carried by aggregates larger than 9.5 mm, and in CSM-50, the proportion of strong contacts in the 37.5–53 mm fraction exceeded 90%, indicating that the largest particles likely form the primary load-bearing skeleton. In addition, increasing NMAS delayed crack initiation, reduced crack propagation rate, and decreased the total number of cracks at failure. These findings demonstrate that macroscopic strength improvement is closely associated with meso-scale optimization of the aggregate skeleton and enhanced load-transfer efficiency. This study provides a mechanistic basis for NMAS selection and gradation optimization in semi-rigid base materials. Full article