Concrete is a material that is widely used in the construction market due to its availability and cost, although it is prone to fracture formation. Therefore, there has been a surge in interest in self-healing materials, particularly self-healing capabilities in green and sustainable concrete materials, with a focus on different techniques offered by dozens of researchers worldwide in the last two decades. However, it is difficult to choose the most effective approach because each research institute employs its own test techniques to assess healing efficiency. Self-healing concrete (SHC) has the capacity to heal and lowers the requirement to locate and repair internal damage (e.g., cracks) without the need for external intervention. This limits reinforcement corrosion and concrete deterioration, as well as lowering costs and increasing durability. Given the merits of SHCs, this article presents a thorough review on the subject, considering the strategies, influential factors, mechanisms, and efficiency of self-healing. This literature review also provides critical synopses on the properties, performance, and evaluation of the self-healing efficiency of SHC composites. In addition, we review trends of development in research toward a broad understanding of the potential application of SHC as a superior concrete candidate and a turning point for developing sustainable and durable concrete composites for modern construction today. Further, it can be imagined that SHC will enable builders to construct buildings without fear of damage or extensive maintenance. Based on this comprehensive review, it is evident that SHC is a truly interdisciplinary hotspot research topic integrating chemistry, microbiology, civil engineering, material science, etc. Furthermore, limitations and future prospects of SHC, as well as the hotspot research topics for future investigations, are also successfully highlighted.

The huge demand for concrete is predicted to upsurge due to rapid construction developments. Environmental worries regarding the large amounts of carbon dioxide emanations from cement production have resulted in new ideas to develop supplemental cementing materials, aiming to decrease the cement volume required for making concrete. Palm-oil-fuel-ash (POFA) is an industrial byproduct derived from palm oil waste’s incineration in power plants’ electricity generation. POFA has high pozzolanic characteristics. It is highly reactive and exhibits satisfactory micro-filling ability and unique properties. POFA is commonly used as a partially-alternated binder to Portland cement materials to make POFA-based eco-efficient concrete to build building using a green material. This paper presents a review of the material source, chemical composition, clean production and short-term properties of POFA. A review of related literature provides comprehensive insights into the potential application of POFA-based eco-efficient concrete in the construction industry today.

Nowadays, using advanced structural materials such as preplaced aggregate concrete (PAC) and fiber-reinforced preplaced aggregate concrete (FR-PAC) are widely investigated due to their benefits in designing infrastructures. Therefore, finding the mechanical characteristics of PAC and FR-PAC can be help structural engineers. This study explores the material characteristics, performance, and potential challenges associated with using PAC and FR-PAC, aiming to provide insights into their practical implementation and long-term benefits in construction. In addition, a superior estimation tool based on multi-target stacked machine-learning (ML) model was introduced to reduce the cost of experimental tests and increase the accuracy and speed of finding the best mixture for PAC and FR-PAC. Experimental tests were conducted to prepare unseen dataset to validate the general ability of the ML models. Results show that the proposed multi-target stacked ML models can estimate the compressive and tensile strengths of PAC specimens with an accuracy of 97.4% and 94.7%, respectively; however, for compressive, flexural, and tensile strengths FR-PAC specimens, the accuracy of 97.7%, 98.0% and 98.3%, were determined, respectively. The proposed predictive model was turned into a graphical user interface (GUI) with ability on predicting the mechanical properties of PAC and FR-PAC in different curing day, and updating the database in future.