Blast Furnace Slag, Post-Industrial Waste or Valuable Building Materials with Remediation Potential?

Performance Research of Cement Concrete Pavements with a Lower Carbon Footprint

The growing interest in the use of building materials with a reduced carbon footprint was the aim of this research assessing the impact of four different types of low-emission cements on the properties of cement concretes used for the construction of local roads. This research work attempted to verify the strength characteristics and assess the durability of such solutions, which used the commonly used CEM I 42.5 R pure clinker cement and three multi-component cements: CEM II/A-V 42.5 R, CEM III/A 42.5 N-LH/HSR/NA, and CEM V/A S-V 42.5 N-LH/HSR/NA. Cement was used in a constant amount of 360 kg/m3, sand of 0/2 mm, and granite aggregate fractions of 2/8 and 8/16 mm. This research was carried out in two areas: the first concerned strength tests and the second focused on the area of assessing the durability of concrete in terms of frost resistance F150, resistance to de-icing agents, water penetration under pressure, and an analysis of the air entrainment structure in concrete according to the PN EN 480-11 standard. Analyzing the obtained test results, it can be concluded that the highest compressive strength of more than 70 MPa was obtained for CEM III concrete, 68 MPa for CEM V concrete, and the lowest for CEM I cement after 90 days. After the durability tests, it was found that the smallest decrease in compressive strength after 150 freezing and thawing cycles was obtained for CEM III (-0.9%) and CEM V (-1.4%) concretes. The high durability of concrete is confirmed by water penetration tests under pressure, because for newly designed recipes using CEM II, CEM III, and CEM V, water penetration from 17 mm to 18 mm was achieved, which proves the very high tightness of the concrete. The assessment of the durability of low-emission cements was confirmed by tests of resistance to de-icing agents and the aeration structure performed under a microscope in accordance with the requirements of the PN-EN 480-11 standard. The obtained analysis results indicate the correct structure and minimal spacing of air bubbles in the concrete, which confirms and guarantees the durability of concrete intended for road construction. Concretes designed using CEM V cement are characterized by a carbon footprint reduction of 36%, and for the mixture based on CEM III, we even observed a decrease of 39% compared to traditional concrete. Concrete using CEM II, CEM III, and CEM V cements can be successfully used for the construction of local roads. Therefore, it is necessary to consider changing the requirements of the technical specifications recommended for roads in Poland.

Review on the modifications of natural and industrial waste CaO based sorbent of calcium looping with enhanced CO2 capture capacity

The calcium looping cycle (CaL) possesses outstanding CO2 capture capacity for future carbon-capturing technologies that utilise CaO sorbents to capture the CO2 in a looping cycle. However, sorbent degradation and the presence of inert materials stabilise the sorbent, thereby reducing the CO2 capture capacity. Consequently, the CaO sorbent that has degraded must be replenished, increasing the operational cost for industrial use. CaO sorbents have been modified to enhance their CO2 capture capacity and stability. However, various CaO sorbents, including limestone, dolomite, biogenesis calcium waste and industrial waste, exhibit distinct behaviour in response to these modifications. Thus, this work comprehensively reviews the CO2 capture capacity of sorbent improvement based on various CaO sorbents. Furthermore, this study provides an understanding of the effects of CO2 capture capacity based on the properties of the CaO sorbent. The properties of various CaO sorbents, such as surface area, pore volume, particle size and morphology, are influential in exhibiting high CO2 capture capacity. This review provides insights into the future development of CaL technology, particularly for carbon-capturing technologies that focus on the modifications of CaO sorbents and the properties that affect the CO2 capture capacity.

Synthesis and application of waste-based layered double hydroxide: A review

The synthesis of layered double hydroxide (LDH) from industrial wastes is a sustainable approach to aid circular economy and hazardous material disposal. In this review, the researches on the synthesis and application of waste-based LDH from 2010 to 2023 are summarized and discussed. At present, there are mainly four types of waste-based LDH produced from red mud, slag, fly ash and wastewater, with co-precipitation being the most typical synthesis method. Red mud is used as the trivalent metal source supplemented by chemical reagents or other types of waste as divalent metal source to produce red mud-based LDH. Slag can act as the sole metal source providing both divalent and trivalent metal sources for slag-based LDH. Fly ash was used either as the trivalent metal source or both divalent and trivalent metal sources to produce fly ash-based LDH. Wastewater-based LDH was typically synthesized by in-situ co-precipitation method to achieve the self-purification of wastewater. The impurities in waste-based LDH can act as a two-edged weapon. It may either hinder or promote the performance of waste-based LDH. The challenge in the synthesis of waste-based LDH lies in the efficient extraction of available metals. The future research prospects for waste-based LDH are suggested.

A systematic review on the bioremediation of metal contaminated soils using biochar and slag: current status and future outlook

Heavy metals contaminated soils are posing severe threats to food safety worldwide. Heavy metals absorbed by plant roots from contaminated soils lead to severe plant development issues and a reduction in crop yield and growth. The global population is growing, and the demand for food is increasing. Therefore, it is critical to identify soil remediation strategies that are efficient, economical, and environment friendly. The use of biochar and slag as passivators represents a promising approach among various physicochemical and biological strategies due to their efficiency, cost-effectiveness, and low environmental impact. These passivators employ diverse mechanisms to reduce the bioavailability of metals in contaminated soils, thereby improving crop growth and productivity. Although studies have shown the effectiveness of different passivators, further research is needed globally as this field is still in its early stages. This review sheds light on the innovative utilization of biochar and slag as sustainable strategies for heavy metal remediation, emphasizing their novelty and potential for practical applications. Based on the findings, research gaps have been identified and future research directions proposed to enable the full potential of passivators to be utilized effectively and efficiently under controlled and field conditions.

Perspective on the Application of Machine Learning Algorithms for Flow Parameter Estimation in Recycled Concrete Aggregate

The constantly expanding civilization and construction industry pose new challenges for a sustainable development economy. Aiming to protect the environment is often associated with waste management, thereby reducing the number of landfills. The management of recycled concrete aggregate (RCA) from building demolition and its reuse in construction perfectly fits into this trend. The characteristics of post-industrial and recycled materials are not homogeneous as is usually the case with natural materials. This leads to a search for solutions to determine the parameters in the simplest possible manner and with as few resources as possible, while eliminating estimation risks. This task can be solved using machine learning, whose algorithms are increasingly used and developed in many areas of life and industry. The research in this study is aimed at comparing the effectiveness of k-Nearest Neighbors (k-NN) and Artificial Neural Network (ANN) algorithms in determining the permeability coefficient to a linear regression model. This parameter has an important role from the perspective of the application of RCA in civil engineering, particularly in earth construction. Two different RCA materials with different origins and properties were used in the study. The filtration test for each sample was pre-prepared using different compaction energies of 0.17 and 0.59 J/cm³ and for loosely packed samples. Differences in the structures of the test results are presented for both materials. The lowest prediction errors were obtained for the k-NN model. This algorithm obtained for the training sample a coefficient of determination (R²) equal to 0.947 and for the test sample an R² equal to 0.980. In the case of ANN, the coefficient of determination was in the range of 0.877-0.936. An important part of the study was the interpretation with SHAP of the obtained models, allowing insight into which parameters influenced the predictions. That is significant and novel, considering the heterogeneity of the materials studied, and provides a rationale for further research in this area.

Mechanical Characterization of Industrial Waste Materials as Mineral Fillers in Asphalt Mixes: Integrated Experimental and Machine Learning Analysis

In this study, the effect of seven industrial waste materials as mineral fillers in asphalt mixtures was investigated. Silica fume (SF), limestone dust (LSD), stone dust (SD), rice husk ash (RHA), fly ash (FA), brick dust (BD), and marble dust (MD) were used to prepare the asphalt mixtures. The obtained experimental results were compared with ordinary Portland cement (OPC), which is used as a conventional mineral filler. The physical, chemical, and morphological assessment of the fillers was performed to evaluate the suitability of industrial waste to replace the OPC. The volumetric, strength, and durability of the modified asphalt mixes were examined to evaluate their performance. The experimental data have been processed through artificial neural networks (ANNs), using k-fold cross-validation as a resampling method and two different activation functions to develop predictive models of the main mechanical and volumetric parameters. In the current research, the two most relevant parameters investigated are the filler type and the filler content, given that they both greatly affect the asphalt concrete mechanical performance. The asphalt mixes have been optimized by means of the Marshall stability analysis, and after that, for each different filler, the optimum asphalt mixtures were investigated by carrying out Indirect tensile strength, moisture susceptibility, and abrasion loss tests. The moisture sensitivity of the modified asphalt mixtures is within the acceptable limit according to the Indian standard. Asphalt mixes modified with the finest mineral fillers exhibited superior stiffness and cracking resistance. Experimental results show higher moisture resistance in calcium-dominant mineral filler-modified asphalt mixtures. Except for mixes prepared with RHA and MD (4% filler content), all the asphalt mixtures considered in this study show MS values higher than 10 kN, as prescribed by Indian regulations. All the values of the void ratio for each asphalt mix have been observed to range between 3–5%, and MQ results were observed between 2 kN/mm–6 kN/mm, which falls within the acceptable range of the Indian specification. Partly due to implementing a data-augmentation strategy based on interpolation, the ANN modeling was very successful, showing a coefficient of correlation averaged over all output variables equal to 0.9967.