Self-Healing Bio-Concrete Using Bacillus subtilis Encapsulated in Iron Oxide Nanoparticles.

For the creation of healable cement concrete matrix, microbial self-healing solutions are significantly more creative and potentially successful. The current study investigates whether gram-positive "Bacillus subtilis" (B. subtilis) microorganisms can effectively repair structural and non-structural cracks caused at the nano- and microscale. By creating an effective immobilization strategy in a coherent manner, the primary challenge regarding the viability of such microbes in a concrete mixture atmosphere has been successfully fulfilled. The iron oxide nanoparticles were synthesized. The examined immobilizing medium was the iron oxide nanoparticles, confirmed using different techniques (XRD, SEM, EDX, TGA, and FTIR). By measuring the average compressive strength of the samples (ASTM C109) and evaluating healing, the impact of triggered B. subtilis bacteria immobilized on iron oxide nanoparticles was examined. The compressive strength recovery of cracked samples following a therapeutic interval of 28 days served as a mechanical indicator of the healing process. In order to accurately correlate the recovery performance as a measure of crack healing duration, the pre-cracking load was set at 80% of the ultimate compressive stress, or "f c," and the period of crack healing was maintained at 28 days. According to the findings, B. subtilis bacteria greatly enhanced the compressive strength and speed up the healing process in cracked cement concrete mixture. The iron oxide nanoparticles were proven to be the best immobilizer for keeping B. subtilis germs alive until the formation of fractures. The bacterial activity-driven calcite deposition in the generated nano-/micro-cracks was supported by micrographic and chemical investigations (XRD, FTIR, SEM, and EDX).

Scientometric Analysis and Research Mapping Knowledge of Coconut Fibers in Concrete.

Biodegradable materials are appropriate for the environment and are gaining immense attention worldwide. The mechanical properties (such as elongation at break, density, and failure strain) of some natural fibers (such as Coir, Hemp, Jute, Ramie, and Sisal) are comparable with those of some synthetic fibers (such as E glass, aramid, or Kevlar). However, the toughness of coconut fibers is comparatively more than other natural fibers. Numerous studies suggest coconut fibers perform better to improve the concrete mechanical properties. However, the knowledge is dispersed, making it difficult for anyone to evaluate the compatibility of coconut fibers in concrete. This study aims to perform a scientometric review of coconut fiber applications in cementitious concrete to discover the various aspects of the literature. The typical conventional review studies are somehow limited in terms of their capacity for linking different literature elements entirely and precisely. Science mapping, co-occurrence, and co-citation are among a few primary challenging points in research at advanced levels. The highly innovative authors/researchers famous for citations, the sources having the highest number of articles, domains that are actively involved, and co-occurrences of keywords in the research on coconut-fiber-reinforced cementitious concrete are explored during the analysis. The bibliometric database with 235 published research studies, which are taken from the Scopus dataset, are analyzed using the VOSviewer application. This research will assist researchers in the development of joint ventures in addition to sharing novel approaches and ideas with the help of a statistical and graphical description of researchers and countries/regions that are contributing. In addition, the applicability of coconut fiber in concrete is explored for mechanical properties considering the literature, and this will benefit new researchers for its use in concrete.

Application of Machine Learning Techniques for Predicting Compressive, Splitting Tensile, and Flexural Strengths of Concrete with Metakaolin.

The mechanical properties of concrete are the important parameters in a design code. The amount of laboratory trial batches and experiments required to produce useful design data can be decreased by using robust prediction models for the mechanical properties of concrete, which can save time and money. Portland cement is frequently substituted with metakaolin (MK) because of its technical and environmental advantages. In this study, three mechanical properties of concrete with MK, i.e., compressive strength (f'c), splitting tensile strength (fst), and flexural strength (FS) were modelled by using four machine learning (ML) techniques: gene expression programming (GEP), artificial neural network (ANN), M5P model tree algorithm, and random forest (RF). For this purpose, a comprehensive database containing detail of concrete mixture proportions and values of f'c, fst, and FS at different ages was gathered from peer-reviewed published documents. Various statistical metrics were used to compare the predictive and generalization capability of the ML techniques. The comparative study of ML techniques revealed that RF has better predictive and generalization capability as compared with GEP, ANN, and M5P model tree algorithm. Moreover, the sensitivity and parametric analysis (PA) was carried out. The PA showed that the most suitable proportions of MK as partial cement replacement were 10% for FS and 15% for both f'c and fst.

Evaluation of Moisture Damage Potential in Hot Mix Asphalt Using Polymeric Aggregate Treatment.

To enhance the moisture damage performance of hot mix asphalt (HMA), treating the aggregate surface with a suitable additive was a more convenient approach. In this research, two types of aggregate modifiers were used to study the effect of moisture damage on HMA. Three different aggregate sources were selected based on their abundance of use in HMA. To study the impact of these aggregate modifiers on moisture susceptibility of HMA, the indirect tensile strength test and indirect tensile modulus test were used as the performance tests. Moisture conditioning of specimens was carried out to simulate the effect of moisture on HMA. The prepared samples' tensile strength ratio (TSR) and stiffness modulus (Sm) results indicated a decrease in the strength of the HMA after moisture conditioning. After treating the aggregate surface with additives, an improvement was seen in dry and wet strength and stiffness. Moreover, an increasing trend was observed for both additives. The correlation between TSR and strength loss reveals a strong correlation (R2 = 0.7219). Also, the two additives indicate increased wettability of asphalt binder over aggregate, thus improving the adhesion between aggregate and asphalt binder.

Recycled Untreated Rubber Waste for Controlling the Alkali-Silica Reaction in Concrete.

Recycled rubber waste (RW) is produced at an alarming rate due to the deposition of 1.5 billion scrap tires annually around the globe, which causes serious threats to the environment due to its open land filling issues. This study investigates the potential application of RW in concrete structures for mitigating the alkali-silica reaction (ASR). Various proportions of RW (5%, 10%, 15%, 20%, and 25%) partially replaced the used aggregates. RW was procured from a local rubber recycling unit. Cubes, prisms, and mortar bar specimens were prepared using a mixture design recommended by ASTM C1260 and tested for evaluating the compressive and flexural strengths and expansion in an ASR conducive environment for specimens incorporating RW. It was observed that the compressive and flexural strength decreased for specimens incorporating RW compared to that of the control specimens without RW. For example, an 18% and an 8% decrease in compressive and flexural strengths, respectively, were observed for specimens with 5% of RW by aggregates volume at 28 days. Mortar bar specimens without RW showed an expansion of 0.23% and 0.28% at 14 and 28 days, respectively, indicating the potential ASR reactivity in accordance with ASTM C1260. A decrease in expansion was observed for mixtures incorporating RW. Specimens incorporating 20% of RW by aggregate volume showed expansions of 0.17% at 28 days, within the limit specified by ASTM C1260. Moreover, specimens incorporating RW showed a lower reduction in compressive and flexural strengths under an ASR conducive environment compared to that of the control specimen without RW. Micro-structural analysis also showed significant micro-cracking for specimens without RW due to ASR. However, no surface cracks were observed for specimens incorporating RW. It can be argued that the use of RW in the construction industry assists in reducing the landfill depositing issues with the additional benefit of limiting the ASR expansion.

Robust strategies to eliminate endocrine disruptive estrogens in water resources.

The widespread occurrence and ubiquitous distribution of estrogens, i.e., estrone (E1), estradiol (E2), and estriol (E3) in our water matrices, is an issue of global concern. Public and regulatory authorities are concerned and placing joint efforts to eliminate estrogens and related environmentally hazardous compounds, due to their toxic influences on the environmental matrices, ecology, and human health, even at low concentrations. However, most of the available literature is focused on the occurrence of estrogens in different water environments with limited treatment options. Thus, a detailed review to fully cover the several treatment processes is needed. This review comprehensively and comparatively discusses many physical, chemical, and biological-based treatments to eliminate natural estrogens, i.e., estrone (E1), estradiol (E2), and estriol (E3) and related synthetic estrogens, e.g., 17α-ethinylestradiol (EE2) and other related hazardous compounds. The covered techniques include adsorption, nanofiltration, ultrafiltration, ultrasonication, photocatalysis of estrogenic compounds, Fenton, Fenton-like and photo-Fenton degradation of estrogenic compounds, electro-Fenton degradation of estrogenic compounds, ozonation, and biological methods for the removal of estrogenic compounds are thoroughly discussed with suitable examples. The studies revealed that treatment plants based on chemical and biological approaches are cost-friendly for removing estrogenic pollutants. Further, there is a need to properly monitor and disposal of the usage of estrogenic drugs in humans and animals. Additional studies are required to explore a robust and more advanced oxidation treatment strategy that can contribute effectively to industrial-scale applications. This review may assist future investigations, monitoring, and removing estrogenic compounds from various environmental matrices. In concluding remarks, a way forward and future perspectives focusing on bridging knowledge gaps in estrogenic compounds removal are also proposed.