Cleaner Materials最新文献

This study develops and presents an Artificial Neural Network (ANN) model employing the Levenberg-Marquardt Backpropagation (LMBP) training algorithm to predict the compressive strength of both normal and high strength concrete. The model's robustness was evaluated using an extensive dataset comprising 1637 samples. Eight input variables, including the cement content, blast furnace slag, fly ash, fine aggregate, coarse aggregate, water content, superplasticizer, and testing age, were considered. The optimal number of hidden layers and neurons in the layer were identified through analysis, and the effectiveness of the model was assessed through k-fold cross-validation and statistical measures, including correlation coefficient (R), coefficient of determination (R²), Root Mean Square Error (RMSE), and Mean Absolute Error (MEA). Comparison with other models was carried out, and the perturbation/super-position method was employed for parametric studies to investigate the effect of each input variable on the output variable. The k-fold cross-validation confirmed the generalizability of the model, and statistical measures showed good results, with unit cement content and superplasticizers having the highest impact on compressive strength. The findings demonstrate that the suggested ANN model is an extremely precise, economical, and practical predictive tool for concrete compressive strength.

Sustainable infrastructure is one of the fastest growing sectors and is concurrently producing huge amount of construction demolition waste (CDW). Correspondingly, industrial activities also result in generation of similar wastes, out of which slag from iron industries pose a serious threat to the environment. This study attempts to incorporate both of the above-mentioned wastes in concrete, thereby an attempt to encourage and contribute towards sustainability. The experimental program comprises the evaluation of strength and water absorption behaviour along with the prediction and validation of iron slag (IS) and recycled aggregate concrete (RAC). The replacement levels for IS range from 10 to 30% while those for recycled concrete aggregates (RCA) range from 0 to 50%. Based on the experimental outcomes, the predicted equations for strength and water absorption characteristics were established. Furthermore, the statistical analysis was performed, indicating the desired responses thereby validating the efficiency of the tested properties of IS–RAC concrete. The successful analysis indicates the optimum constituent mix of 24.8% IS and 26.9% RCA for maximum strength and water absorption behaviour. Finally, a comparative environmental estimation was performed by life cycle assessment, describing a reduction of nearly 12.28% and 22% in carbon dioxide emissions and eco-cost in optimized concrete respectively.

The metallurgical and cement industries contribute significantly to anthropogenic carbon dioxide emissions. Utilizing oxidic by-products from the metallurgical industry as supplementary cementitious materials (SCMs) can improve resource efficiency and reduce emissions from cement production. Iron silicate copper slags have been studied as SCMs, but mainly in systems where Portland cement is used as an activator. There is limited research on the inherent reactivity of the slag under changing processing conditions. The present study offers insight into the effect of granulation temperature and grinding on the inherent reactivity of an industrially produced iron silicate copper slag. The results showed that granulation temperature had an insignificant effect on reactivity, while grinding generated substantial improvements. The latter effect was concluded to stem from the increased specific surface area, increased number of sites for nucleation and growth of hydrates, and changes in the inherent reactivity owing to structural changes induced by the grinding.

Stabilization of pavement base material using asphalt emulsion has been widely used to improve pavement performance. This technology produces a high-quality base course material with decreased energy consumption, carbon footprint, and raw material usage. Cement has been used as a common additive to improve these mixes strength and moisture resistance. However, some drawbacks are also associated with cement, such as negative environmental impacts, high costs, and low-temperature deficiencies. Asphaltenes is a by-product of oil-sand bitumen with little commercial value in current practice. To investigate the impact of asphaltenes on improving the rheological properties of asphalt binder, a series of binder characteristics tests using a dynamic shear rheometer, breaking time and microscopic evaluation is conducted on modified asphalt emulsion with asphaltenes. Asphaltenes is then added to asphalt emulsion-stabilized granular material, to be compared with mixtures prepared with cement. Two asphaltenes and cement-modified mixes are prepared and compared to unmodified mixtures. All mixes are tested for permanent deformation and moisture sensitivity using a Hamburg wheel tracker and flow number test, while the low-temperature properties are evaluated using indirect tensile strength tests. Dynamic modulus is also evaluated to analyze the viscoelastic behavior of the mixes. The results of this study reveal a considerable increase in the rutting resistance of asphalt mixes by adding 1% of both additives (by total weight of mix), and asphaltenes-modification shows less adverse impacts at intermediate and low temperatures than cement-modification.

This paper systematically reviews published studies involving the recycling and reuse of alternative non-potable industrial and domestic wastewater, seawater, and oil-contaminated water sources in concrete, mortar, and cement paste applications. A summary of available industrial and domestic wastewater sources, their physical and chemical characteristics, optimum treatment methods is presented to provide additional context on potential future reuse of industrial and domestic water sources in concrete applications. Economic implications, gaps of knowledge, and future research needs are also discussed. There are several raw wastewater sources that are mostly aligned with standard water quality thresholds that may produce concrete on par with freshwater systems. In addition, developing specialized water treatments for concrete applications can improve performance, although the water remains non-potable (limited to only primary or secondary treatments).

Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments. This study presents a state-of-the-art review on the utilization of RCA for pavement construction, with a large scope originating from a comprehensive literature dissection. The study compares RCA and NA pavement's physical, chemical, mechanical, and durability properties. As reported, their properties highly depend on the methods, the extent of crushing, the amount of adhered paste and the residual mortar with which the RCA is produced. Pavement performance was conducted from three perspectives: the use of RCA for pavement sublayers, rigid layers, and flexible layers, as well as their separate evaluation test techniques. A comparative environmental evaluation revealed that the RCA inclusion contributes to sustainability gain in minimizing the health hazards effect, waste generation, and the pressure on landfill sites than conventional pavement construction.

There is a general, vernacular perception that polymers are not sustainable materials, and therefore could not be used in a product that is designed to be sustainable. Qualitative strategies, including the use of natural materials, have been long been defined to guide more environmentally friendly product development. Quantitative life cycle assessment tools indicate that there are cases in which polymers, which may not be considered natural, can be less ecologically impactful materials to use in a product. Whether qualitative or quantitative product development tools are used, if the choices made by new product creators are not consistent with the perceptions of a product’s customers, they may not influence the purchase of a more sustainable product over a less sustainable product. The objective of this study is to assess how people perceive the sustainabilities of polymer products. A set of ten, nearly identical, injection-molded drinking cups was given to research subjects for a Kansei engineering analysis regarding their perceptions of the products’ sustainabilities. Participants evaluated the cups on ten qualitative design strategies for sustainability, including durability, preciousness, recyclability and toxicity. Results show that perceptions of four of the ten attributes: durability, degradability, rawness and naturalness, most strongly influence the overall perception of the product’s sustainability. Four other attributes: expense, luxuriousness, preciousness and rareness influence the product’s overall perception of worth, which is conversely connected to a product’s perception of sustainability. The attributes of polymer products that people recognize as affecting sustainability can be used by product developers, as well as chemists and material engineers, to develop and specify more appropriate and accepted sustainable products and polymers.

In this research, an attempt is made to partially replace ground granulated blast furnace Slag (GGBS) with a binder rich in SiO₂ and CaO in alkali activated slag concrete (AASC) to increase workability and setting time. GGBS is replaced with bagasse ash powder (BAP) in 5%, 10%, and 15% of the binary mix, and subsequently with marble powder (MP) in 5% and 10% of the binary mix. After establishing the best mix for both binder replacements, a ternary mix with 5% BAP and 10% MP is created. The fine aggregates used in the comparison are 100 % river sand and slag sand. 10 M sodium hydroxide and the alkaline to binder ratio is 0.4, were used. Mechanical properties such as compressive strength, split tensile strength, and flexural strength are performed cured at 1, 3, 7, and 28 days samples. To further understand the intrinsic mechanism of strength development, microstructure, morphology and mineralogy on AASC are investigated. Based on the findings, it can be inferred that AASC mixes have a higher strength than OPC mixes. The mechanical strengths of the AASC binary mix with 10% MP and 5% BAP are higher. The microstructural analysis reveals the mixes developed with BAP and 100 % GGBS, had a denser microstructure than the normal mixes. The mechanical properties obtained for most of the AASC mixes are significantly higher than the IRC SP:62-2014 recommendations for rigid pavements for low volume roads.

3D printing process has gained significant attention because of its ability to manufacture complicated geometries. The process also has a lot of potential for reducing plastic waste. In recent years, the use of carbon fiber has become increasingly popular as a reinforcement material for 3D-printed objects. The combination of plastic waste and carbon fiber has the potential to create high-strength and lightweight structures for various applications. This presented paper reviews the advancements in 3D printing using plastic waste, focusing specifically on fused deposition modeling (FDM) and selective laser sintering (SLS) printing methods for carbon fiber composites. The study highlights the important role of materials in the 3D printing process, especially regarding the difficulties in producing non-recyclable plastics. The study highlights composite materials and processes and the industries that utilize these technologies. One of the key aspects of the article is the exploration of the impact of 3D printing on the environment through the recycling of plastic waste. This study shall be helpful for the demonstration of turning 3D printing plastic waste into durable, functional objects while minimizing its environmental impact.

Thermochemical conversion is the most economical approach to recovering energy and alternative fuels from biomass feedstock. This work first reviews the literature data on thermal-oxidative decomposition for common biomass types and forms a database of 18 parameters, including element, proximate, and thermogravimetric analysis (TGA). Then, an Artificial Neural Network (ANN) model is developed for the prediction of TGA data. Pearson correlation coefficient analysis reveals that the influence of environment heating rate on biomass thermal decomposition is larger than that of fuel properties. By inputting biomass elemental/proximate analysis and heating rate, the ANN model successfully predicts 8 key TGA parameters, namely, pyrolysis-onset temperature, peak pyrolysis temperature, oxidation-dominant temperature, peak oxidation temperature, oxidation-end temperature, peak pyrolysis rate, oxidation-dominant rate, and peak oxidation rate, with R² values greater than 0.98. A better performance can be achieved when all ten input features are considered. Final, an open-access online software, Intelligent Fuel Thermal Analysis (IFTA), is developed to predict thermal-oxidative decomposition across a wide range of heating rates and biomass types. This work provides a better understanding of biomass thermal-oxidative decomposition dynamics and a shortcut to obtain key parameters of biomass degradation without TGA tests.