Research Highlights

Engineered cementitious composites (ECC) are the unique material with a high ductility in nature for different applications. However, the high cement dosage in ECC contributes to an elevated carbon footprint, higher costs, and an increased risk of restrained shrinkage cracking, indicating a need for improvements. In recent years, researchers have consistently worked towards developing a more environmentally friendly ECC. These initiatives largely involve the use of more economical and eco-friendly binders, fibers, and other raw materials. This study reviews sustainable ECC incorporating various percentages of limestone calcined clay cement (LC3). It discusses the mechanical properties, durability, shrinkage, self-healing ability, hydration, and microstructural performance of LC3-ECC with different LC3 percentages, fibers, water-to-binder ratios, and mix proportions. Based on previous studies, it is evident that LC3-ECC exhibits a higher tensile strain capacity, durability properties, and lower compressive strength than conventional ECC (C-ECC). Notably, ECC with 25% to 80% LC3 exhibited a maximum tensile strain of 4% to 9%, making it appropriate for various structural resilience applications. Additionally, it reduces production costs, CO2 emissions, and energy consumption compared to C-ECC. Moreover, the early-age hydration is considerably enhanced owing to the higher pozzolanic reaction of LC3. Overall, this review provides a comprehensive analysis of influence of LC3 in ECC for various applications, thereby advancing the research in this area. 

This article investigates the influence of sintered lightweight concrete (SLWC) surface quality, carbonation, and acid resistance cast using controlled permeable formwork (CPF) liner. Carbonation and acid resistance of SLWC tend to be lower than those of normal weight aggregate concrete (NWC) owing to the higher porosity and lower density of sintered fly ash aggregate (SFA). The lower density SFA reaches towards the surface and causes non-uniform w/c ratio near the surfaces during compaction. CPF liner is an active technique that helps to enhance the properties of concrete in the cover region. In this study, image processing technique was used for studying the surface imperfections like bug holes, various tests including accelerated carbonation, acid resistance, dynamic acid resistance, sorptivity, water penetration were used for assessing surface quality and transport properties. The results showed that the SLWC surfaces cast against CPF liner revealed around a 90% reduction in bug holes, and improved performance in terms of carbonation, acid resistance, dynamic acid resistance, and water penetration by 97%, 48%, 8%, and 93%, respectively. Overall, CPF liner enhances the quality of SLWC surfaces by decreasing the bug hole ratio and improving the resistance to penetration of deteriorating agents.

This study investigates the development of engineered geopolymer composites (EGCs) reinforced with basalt fbers (BF) as a sustainable alternative to conventional cement concrete (CCC). By replacing ordinary Portland cement (OPC) with industrial by-products such as fy ash and ground granulated basalt furnace slag (GGBS), these composites signifcantly reduce carbon emissions. However, to overcome inherent brittleness and fexural strength limitation of EGCs, in this study, diferent percentage of BF, such as 0.5%, 1%, 1.5%, 2% and 2.5%, are reinforced in mix to enhance the performance of EGCs. The research explores the ideal mix of materials through various testing under ambient curing. The experimental results revealed that EGCs reinforced with BF signifcantly enhance the performance under ambient curing. The mix with 2% of BF exhibited a notable increase in compressive and fexural strength of 68.36 Mpa and 21.23 Mpa, respectively, at 28 days. This is due to improved fber-matrix bonding. The optimum mix, EGC-F2 (2% basalt fber), exhibited a notable increase in strength compared to other mixes, this is primarily due to improved fber-matrix bonding. Similarly, the mix with 2% of BF absorbed lower water and showed superior resistance to chloride ion penetration, ensuring improved long-term performance of EGCs. Additionally, reduced porosity, better fber dispersion, and strong matrix integrity were observed in the mix using SEM analysis. 

This study evaluates the potential use of Graphene Nanoplatelets (GNP) and copper slag (CS) to enhance the performance of concrete exposed to harmful environmental conditions. Graphene is an effective filler material, significantly reducing porosity and improving structural integrity. The investigation aims on evaluating compressive strength, mass loss, and dimensional changes in GNP-CS-blended concrete subjected to conventional curing, as well as sulfate, acid, and chloride exposures. A composite with 0.25 % of GNP and 60 % of CS demonstrates optimum resistance, showing an 7.60 % reduction in strength loss owing to acid attack and 9.06 % reduction under sulfate attack. Microstructural investigations in concrete were conducted to examine the deterioration mechanisms attributed to sulfate and acid environments. The filler effect of GNP and the pozzolanic activity of CS enable concrete to the densification of hydration products and reduction in pore volume, thereby enhancing resistance to chemical attacks. Additionally, significant correlations were observed between water absorption and bulk density (R2 = 0.9947), and between Rapid Chloride Penetration Test (RCPT) results and electrical resistivity (R2 = 0.9911). Although graphene is inherently conductive, the synthesis of GNP alters its structure, eliminating conductivity and making it suitable as a filler. To facilitating experimental actions, predictive equations were developed using regression models, and their accuracy was validated through analysis of variance (ANOVA) and statistical method. 

Engineered cementitious composites (ECC) represent a significant advancement in construction materials, especially for overlay applications on bridge decks and pavements. Unlike traditional concrete, ECC exhibits exceptional ductility and tensile strength, effectively mitigating its brittleness. This distinctive characteristic enables ECC to endure increased levels of loading, cracking, and deformation without experiencing catastrophic failure. This study examined the behavior of existing substrate concrete slab (SCS) with different percentages of mineral admixtures (MA's) blended ECC overlays for bridge deck and pavement applications. A total of twenty-one types of ECC mixtures were developed with three different MA's: ground granulated blast furnace slag (GGBS), bagasse ash (BA), and rice husk ash (RHA). Additionally, the abrasion resistance, bonding, and mechanical properties of each mixture, as well as the behavior of SCS without overlay, were investigated to further understand the suitability of ECC for overlay applications. The results showed that ECC with MA's enhanced the structural behavior of SCS, improving bonding and mechanical properties. The ultimate load carrying capacity of ECC with 40% GGBS, 10% BA, and 10% RHA achieved 228 kN, 212 kN, and 176 kN, respectively, which are almost 125 times higher than that of SCS without overlay. This study holds promise for improving the understanding of the behaviors of SCS with different ECC overlays for bridge deck and pavement applications.

The adoption of engineered cementitious composites (ECC) has witnessed a notable surge in recent years, primarily because of their remarkable strain-hardening behavior and other hardened properties. On the other hand, machine learning (ML) approaches have been widely employed to predict various properties in engineering applications by incorporating an ‘n’ number of inputs and target data. An ML aids in understanding the selection, properties, and blending ability of materials, thereby reducing the cost and duration of research. In this study, an ML technique based on an artificial neural network (ANN) is utilized to predict the mechanical properties of ECC with different binders. For this purpose, several parameters are collected from the present investigation and various literature sources, and the collected data are trained using three algorithms, namely, scaled conjugate gradient (SCG), Bayesian regularization (BR), and Levenberg–Marquardt (LM). The correlations and variations between the experimental and predicted outputs are analyzed. In addition, a comparison between the experimental results obtained by each investigator and the corresponding outputs predicted by the individual algorithms is highlighted. The LM algorithm achieved a mean regression value of 0.910 for the prediction of compressive strength, whereas the BR showed values of 0.908 and 0.852 for predicting the direct tensile and flexural properties of ECC, respectively. Furthermore, considering the standard benchmark, the proposed model exhibited a high correlation with the coefficient of determination (R2). 

This research examined the development of modified engineered cementitious composites (MECC) using manufactured sand (M-sand) and a high content of raw agricultural by-products, such as bagasse ash (BA) and rice husk ash (RHA), instead of conventional silica sand and fly ash. Fourteen different types of MECC mixtures were developed using raw BA and RHA blended with M-sand to reduce the cost of MECC. The fresh and hardened properties of all mixtures were examined using various types of testing methods. In addition, microstructure analysis were conducted for both the control and optimal mixtures to identify the bonding of fibres in cementitious composites. The correlation between conventional and MECC was also evaluated based on the hardened properties and cost analysis. The results revealed that workability steadily dwindled with increasing percentages of BA and RHA, from 10 to 55. Optimal mechanical properties were attained with the incorporation of BA and RHA at 10% cement replacement. In contrast, 30% BA and 40% RHA exhibited maximum impact strength compared to the respective control mixes. Similarly, ECC with 20% BA and RHA exhibited optimal durability properties. Moreover, compared to conventional ECC, the cost of the newly developed MECC was slightly lesser due to the incorporation of agricultural by-products and M-sand.

This article examines the pozzolanic performance of Portland cement blended with ground granulated blast furnace slag (GGBS), and bagasse Ash (BA). The effect of different water to binder ratios in cementitious composites is analyzed through the hydration process of the proposed mixes using thermodynamic modeling and experimental technique. The hydration of the composites involves the formation of Portlandite, calcium-silicate hydrate (C-S-H), ettringite and monosulfoaluminate (AFm) at 28 days. The results of thermodynamic modeling are compared with compressive strength, dry density, Frattini, lime saturation and strength activity index tests. Portland cement blended with GGBS attained better pozzolanic activity with 0.4 and 0.5 water to binder ratios than admixed BA under all types of testing. The compressive strength of GGBS blended mixes with water to binder ratios of 0.4 and 0.5 attained 51.5 MPa and 44.458 MPa, respectively, at 28 days, which are 20.778% and 12.128% higher compared to BA blended mixes.

Engineering cementitious composites (ECC) is a new type of fibre-reinforced bendable cementitious composite,which is used in various civil engineering applications instead of conventional and fibre reinforced concrete dueto its high mechanical and durable properties. In the macro and micro mechanic systems of ECC, the incorporation of different materials plays a vital role in enhancing the properties of ECC. The improper selection of materials with different physical and chemical properties, curing conditions and mixing ratios adversely affects the fresh and mechanical properties. To enrich the fresh and mechanical properties of ECC, the behavior of incorporation of materials are need to be studied in detail. Furthermore, the effect of curing conditions, details of conducting experiments such as methods, types and specimen details with standard codal provisions are very important for achieving better properties of ECC. In these connections, this paper reviews the influences of incorporation of SCM, fibres and fine aggregates on fresh and mechanical properties of ECC, namely compressive strength, direct tensile, splitting tensile and flexural properties. The correlations on mechanical properties of ECC with fibres ratios and water to binder ratios are also highlighted. Moreover, the incorporation of different materials with their microstructure and physical properties, and mix-design, details of experiments used by many investigators are also discussed and listed. In the conclusion, the selection of different materials water to cement ratio and curing conditions for attaining better compressive strength, direct tensile, splitting tensile and flexural properties of ECC are commended.

In recent times, Machine Learning Techniques are emerging continuously as an affordable and efficient in predicting how the property of the materials influences the properties, cost and time of the proposed mixes. In Civil engineering domain, the utilization of ML techniques are need to be strengthened with respect to the incorporation of Supplementary Cementitious Materials (SCM) to the conventional proportioning of mix. Hence to increase the sustainability and thereby reduce the environmental pollution that occurs due to disposal of the Industrial wastes which also holds the pozzolanic property. In this study one of the ML techniques namely Artificial Neural Network (ANN) are used to determine the 28 days compressive strength of the Engineered Cementitious Composite (ECC) incorporated with industrial pozzolans like Fly ash and Ground Granulated Blast Slag (GGBS) with respect to mix proportions and physical properties of polyvinyl alcohol fibres (PVA). The physical properties of fibre and mix proportions such as the ratio of cement, fly ash or GGBS, fine aggregate, water to binder (W/B) ratio, high range water reducer to binder (HRWR/B) ratio, length of fibres, diameter, tensile strength, density, modulus of elasticity and elongation were used to predict the compressive strength of ECC. Furthermore, the experimental investigations were conducted on the compressive strength of ECC with fly ash and GGBS separately and also verified with the ANN outputs. Hence, the present model (Levenberg-Marquardt algorithm) is validated by considering the standard benchmark with respect to the coefficient of determination (R2) which is highly correlated.

Engineered cementitious composite (ECC) is a high-graded advanced construction material that can be used to strengthen and repair structural composites owing to its high mechanical and durability properties. Nevertheless, the ability of ECC to strengthen and repair concrete surfaces depends on the interfacial bond between the conventional concrete (CC) substrate texture and ECC overlay. It ensures sufficient adhesive or bonding ability over a lifetime under various loading and environmental conditions. The present study investigates the bond strength between CC substrate and modified ECC with agro-industrial by-products, such as ground granulated blast furnace slag (GGBS), bagasse ash (BA), and rice husk ash (RHA). The bond strength is determined using three types of tests, namely the slant shear, split cylinder, and split prism tests. A mathematical model has also been developed to predict the bond strength of the different ECC mixtures. The results indicate that incorporating 40% GGBS, 10% BA, and 10% RHA in ECC helps in attaining the maximum interfacial bond strength with crosshatched textures under all types of testing. According to the ACI standard, ECC with agro-industrial by-products ranging from 10% to 55% achieved the required bond strength in all three tests. Correspondingly, the outcomes of the present research are compared with those obtained from previous studies to gain further insights into various applications, which are highly relatable. Furthermore, the experimental outcomes were strongly correlated with the mathematical modeling with great accuracy.

This research extensively used different progressive machine learning (ML) techniques to predict the compressive strength (CS) and tensile strain (TSt) of engineered cementitious composites (ECC) with 14 input variables and six algorithms. Specifically, random forest (RF), support vector machine, extreme gradient boosting (XGBoost), light gradient boosting machine, categorical gradient boosting (Cat- Boost), and natural gradient boosting techniques were used in the present study, to understand mechanical properties of ECC meanwhile these properties are crucial for design codes and developing new reliable models for mixtures. The discrepancy between the ML technique and specific ECC expected outputs is novel in this study and will aid researchers in better understanding of ECC features. To estimate the CS and TSt of the ECC, 2535 and 1469 input data points, respectively, were incorporated based on the material ratio, W/B, and different properties of the fibers. In addition, hyperparameter optimization techniques have also been used in ML to improve over fitting and make the model more accurate and robust. Moreover, an error analysis was highlighted between the actual and predicted CS and TSt of the ECC with each ML technique. Also, the significance and influence of the variable inputs that affect the CS and TSt were explained using the Shapley additive explanation (SHAP) approach. Among all approaches, CatBoost and XGBoost predicted the CS and TSt of ECC with greater accuracy than other techniques in terms of the coefficient of determination (R2), mean square error, mean absolute error, root mean square error, and symmetric mean absolute percentage error. The training and testing R2 values of CatBoost and XGBoost for predicting the CS and TSt of ECC were 0.96, 0.89, 0.89, and 0.76, respectively. SHAP analysis revealed that W/B and fiber elongation were the most significant input variables for the CS and TSt of the ECC.

The composite stub column composed of fiber-reinforced polymer (FRP), Eco engineered cementitious composite (ECC), and high-strength concrete (HSC) core is experimentally investigated in this study. The ductile performance of HSC-FRP is enhanced by proving an ECC ring of 30 mm thickness as sandwich layer between HSC and FRP. During experimentation the premature failure of the FRP-HSC column is observed at the initial phase, which exhibits brittle nature of the column. The material properties of FRP, ECC, and HSC were characterized. The performance of composite columns was observed with four FEH (FRP-ECC-HSC) columns, four HE (HSC-ECC) columns, and two FH (FRP-HSC) columns. The parameters such as uniform hoop strain distribution, ultimate load-carrying capacity, axial and hoop strain, and confining efficiency of the FRP were investigated to understand the behaviour of composite columns. From results, the ultimate load-carrying capacity of FH columns was 15.56 % higher than the FEH columns. The FEH columns showed the enhanced confining efficiency of FRP and 21% increase in uniform hoop strain distribution than the FH columns. The hoop strain capacity of FEH columns were increased twice the times of FH columns, which indicates the increased ductile behaviour of the FEH columns. In addition, experimental results of composite columns were highly correlated with the existing theoretical equation from literatures.

This study concentrated on the influence of manufactured sand on the compressive strength of polyvinyl alcohol fibred-based ECC (PVA-ECC) with different types of mineral admixtures namely ground granulated blast-furnace slag (GGBS), fly ash, bagasse ash, rice husk ash (RHA), metakaolin and silica fume. The proportion of water/cementitious ratio and PVA fiber were kept constant of 0.3 and 2% of volume respectively for all mixes. To develop this mixture, mineral admixtures were added in PVA-ECC at different ratios such as 10, 20 and 30%. The experimental result exhibited that PVA-ECC with GGBS, fly ash, bagasse ash and metakaolin were produced satisfied compressive strength at 7 and 28 days compared to silica fume and rice husk ash. Also, the incorporation of different percentagesof GGBS in the ECC Mix was produced higher strength at 7 and 28 days compared to control mix.

In current scenario, Engineered Cementitious Composites (ECC) plays vital role in construction industries because of its high strain hardening property, tensile ductility, and high performance in strength and durability properties due to bonding with different fibres. In this study an extensive review is carried out about the mechanical behaviour of ECC and its applications. Compressive, Tensile and flexural strength along with physical and chemical properties of different materials, fibres and mix proportions used in ECC were observed and recapitulated. Cracking strength, strain and average cracking width of ECC at different proportions of fibres and mineral admixtures were discussed. In addition, porosity, pore size distribution, pore volume and surface topography of the ECC materials are comprehensively studied. This paper reviews the mechanical properties of ECC and its applications are widely used in different construction industries.

This study examines the influence of manufactured sand (Msand) gradation with different w/c ratios on ECC’s compressive strength at 3, 7 and 28 days. The flowability of ECC with different gradations of sand and w/c ratio is also discussed. The interaction between the compressive strength of the ECC with the w/c ratio and gradation of sand is also highlighted. The experimental results showed that the ECC flowability increased with increasing sand gradation and w/c ratio. Similarly, ECC with fine and medium sand exhibited a lower compressive strength than coarse sand. The maximum compressive strength of ECC with fine, medium and coarse sand were attained of about 46.3 MPa, 48.2 MPa and 58.1 MPa at 0.33, 0.34 and 0.37 w/c ratios, respectively.

Concrete is among the most widely used building materials on the planet. Bacteria-based concrete has the potential to be a future automated self-healing solution for environment-friendly buildings. Consequently, more data are needed to emulate real-world settings before concrete technologies can be deployed on a larger scale. Although much technology reduces crack formation, present concrete treatment procedures like chemicals and polymers pose human health and environmental dangers. Introducing bacteria-based concrete is gaining increasing attention as a priority research topic in the durability performance of concrete due to the short time used for alleviating the problem. However, it has some limitations on crack width and large-scale application. The primary goal of this article is to provide an overview of existing research, focusing on improving durability performance using different nutrients and bacteria for self-healing concrete and showing the consequences for further research improvement. The review was conducted to make an extensive database of bacteria influencing self-healing concrete from 2008 to the present. Many articles (over 90%) led to the bacterial development of the self-healing process in concrete. In this study, the highlighted compressive strength enhanced about 25–30% utilizing Bacillus subtilis, which fill the cracks by nearly 3 mm. The urea and calcium supplies in Bacillus pasteurii, Sporosarcina pasteurii, and B. subtilis heal the cracks upto 0.1–2.0 mm, 0.22–0.86 mm, and 0.4 mm, respectively. 

Engineering cementitious composites (ECC) were discovered as a better alternative to conventional concrete due to their ability to achieve higher tensile strength. In subsequent years, additional studies were conducted to modify the materials in ECC to achieve a more sustainable and environmentally friendly composition. Incorporating nano-carbons such as fullerenes, carbon nanotubes, carbon nanoparticles, and graphene into ECC makes the advanced material highly advantageous. This chapter investigates the behavior of ECC reinforced with nano-carbons. The performance of ECC blended with nano-carbon is analyzed by comparing the fresh, mechanical and durability properties. In addition, the self-sensing and self-healing functionalities of ECC blended with nano-carbon are observed. The crack behaviour and healing performance of ECC are monitored due to the conductive ability of nano-carbon. Adding graphene in the range of 0.01 to 0.08% in ECC improves the young’s modulus compared to conventional ECC.