This study aims to address the environmental challenges posed by construction and demolition waste (CDW) through its upcycling into a green concrete solution that supports the principles of the circular economy. To this end, a new generation Eco-hybrid cement was developed for the binder phase, using a ternary combination of CDW, calcium sulfoaluminate (CSA) cement, and Portland cement (PC). For the aggregate phase, 100% CDW-based recycled concrete aggregate was utilized. The green concrete was analyzed for its mechanical and environmental performance using comprehensive testing parameters, including compressive strength, drying shrinkage, water absorption, freeze-thaw resistance, chloride permeability, and life cycle assessment. The green concrete achieved a compressive strength of 43.8 MPa at 28 days, with acceptable early-age strength owing to CSA cement and increased strength over time due to the pozzolanic activity of CDW. Its durability was comparable to PC concrete, making it suitable for structural applications. Microstructural analyses validated that CDW components contributed to mechanical performance by forming C-S-H gel at later ages. Environmentally, Eco-hybrid cement resulted in a global warming potential of 575.34 kg CO-eq per ton, compared to 845 kg CO-eq for PC. Green concrete exhibited reductions in various environmental impact categories, ranging from 29% to 42% compared to PC concrete. Unlike conventional approaches that primarily use CDW in aggregate production, this study demonstrates the feasibility of reducing the PC phase in concrete through a well-designed ternary system, ultimately using approximately 87.8% waste material by mass in the final concrete mixture.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.jenvman.2025.124564 | DOI Listing |
Sci Rep
March 2025
Departamento de Ciencias de la Construcción, Facultad de Ciencias de la Construcción Ordenamiento Territorial, Universidad Tecnológica Metropolitana, Santiago, Chile.
The traditional evaluation of compressive strength through repeated experimental works can be resource-intensive, time-consuming, and environmentally taxing. Leveraging advanced machine learning (ML) offers a faster, cheaper, and more sustainable alternative for evaluating and optimizing concrete properties, particularly for materials incorporating industrial wastes and steel fibers. In this research work, a total of 166 records were collected and partitioned into training set (130 records = 80%) and validation set (36 records = 20%) in line with the requirements of data partitioning and sorting for optimal model performance.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
March 2025
Dr. Vishwanath Karad MIT World Peace University, Pune, India.
Concrete is the most used material globally, with cement production causing 8% of emissions. Waste-based supplementary cementitious materials (SCMs) offer a partial cement replacement to address climate goals. The present study explores using Ground Granulated Blast Furnace Slag (GGBS) and biochar as SCMs to elevate concrete's sustainability while maintaining structural performance.
View Article and Find Full Text PDFSci Rep
March 2025
College of Materials and Metallurgy, Guizhou University, Guiyang, 550003, China.
Red mud (RM), a solid waste byproduct of the alumina industry, has accumulated in significant global stockpiles. Currently, the primary application of RM involves magnetic separation to recover iron oxides, while the residual RM is predominantly landfilled. Due to its strong alkalinity, RM can serve as a substitute for strong alkalis or sodium salts in the alkali activation of concrete, thereby accelerating setting time and improving early-age strength.
View Article and Find Full Text PDFSci Rep
February 2025
Departamento de Ciencias de la Construcción, Facultad de Ciencias de la Construcción Ordenamiento Territorial, Universidad Tecnológica Metropolitana, Santiago, Chile.
Physics-informed modeling (PIM) using advanced machine learning (ML) represents a paradigm shift in the field of concrete technology, offering a potent blend of scientific rigor and computational efficiency. By harnessing the synergies between physics-based principles and data-driven algorithms, PIM-ML not only streamlines the design process but also enhances the reliability and sustainability of concrete structures. As research continues to refine these models and validate their performance, their adoption promises to revolutionize how concrete materials are engineered, tested, and utilized in construction projects worldwide.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
February 2025
Department of Civil Engineering, SRM Institute of Science and Technology, Kattankulathur, 603203, Tamil Nadu, India.
The concept of sustainability in agricultural residue management has gained significant attention worldwide in recent years. After harvesting, large volumes of waste are generated, often dumped into the environment, contributing to pollution. However, these wastes can be used in the concrete industry to reduce the depletion of mineral resources, thus preventing environmental degradation.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!