Waste Glass Utilization in Cement-Based Materials for Sustainable Construction: A Review

Qin, Di; Hu, Yidan; Li, Xuemei

doi:10.3390/cryst11060710

Cited by 34 publications

(29 citation statements)

References 121 publications

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“…Comparable findings were also noticed in other mixes (2 and 3), and the highest FS was accomplished at 10% WGP proportion as cement substitute, which was nearly 32% and 26% higher than the reference specimen in Mixes-2 and 3 specimens, respectively. The probable causes are the filling effect and the pozzolanic nature of WGP [ 30 ]. The filling effect lowers the void ratio, causing a dense and compact structure.…”

Section: Results and Analysismentioning

confidence: 99%

“…The higher content of SiO 2 in the glass’s composition [ 73 ] interacts with Ca(OH) 2 in the mix to form improved calcium-silicate-hydrate (C-S-H) gel, improving the characteristics of CCs [ 74 , 75 ]. At greater proportions of WGP (12.5 and 15%), the FS declined due to the excess quantity of WGP incorporated into mixes than needed for the pozzolanic activity [ 30 ] and cement dilution. Therefore, the application of WGP up to 10% cement substitute is advantageous for attaining the highest strength.…”

Section: Results and Analysismentioning

confidence: 99%

“…The mechanical performance of CCs has been shown to improve with the addition of some waste materials [ 28 , 29 ]. As a result of its abundance, waste glass (WG) is commonly found in landfills across the world [ 30 – 32 ]. Particularly, large urban areas are facing a dramatic decline in landfill space despite their populations producing ever-greater quantities of municipal solid waste [ 33 ].…”

Section: Introductionmentioning

confidence: 99%

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Experimental and machine learning approaches to investigate the effect of waste glass powder on the flexural strength of cement mortar

et al. 2023

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Using solid waste in building materials is an efficient approach to achieving sustainability goals. Also, the application of modern methods like artificial intelligence is gaining attention. In this regard, the flexural strength (FS) of cementitious composites (CCs) incorporating waste glass powder (WGP) was evaluated via both experimental and machine learning (ML) methods. WGP was utilized to partially substitute cement and fine aggregate separately at replacement levels of 0%, 2.5%, 5%, 7.5%, 10%, 12.5%, and 15%. At first, the FS of WGP-based CCs was determined experimentally. The generated data, which included six inputs, was then used to run ML techniques to forecast the FS. For FS estimation, two ML approaches were used, including a support vector machine and a bagging regressor. The effectiveness of ML models was assessed by the coefficient of determination (R2), k-fold techniques, statistical tests, and examining the variation amongst experimental and forecasted FS. The use of WGP improved the FS of CCs, as determined by the experimental results. The highest FS was obtained when 10% and 15% WGP was utilized as a cement and fine aggregate replacement, respectively. The modeling approaches’ results revealed that the support vector machine method had a fair level of accuracy, but the bagging regressor method had a greater level of accuracy in estimating the FS. Using ML strategies will benefit the building industry by expediting cost-effective and rapid solutions for analyzing material characteristics.

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Section: Results and Analysismentioning

confidence: 99%

Section: Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Experimental and machine learning approaches to investigate the effect of waste glass powder on the flexural strength of cement mortar

et al. 2023

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“…Globally, a substantial quantity of GW is produced, most of which is discarded in landfills, posing health and environmental risks [ 23 ]. Furthermore, CM is the most common construction material, but its overuse depletes natural resources and generates CO 2 .…”

Section: Discussionmentioning

confidence: 99%

“…It has also been noticed that using some waste materials enhances the performance of CM [ 21 , 22 ]. Globally, a substantial amount of glass waste (GW) is generated, with a substantial volume of GW discarded in landfills [ 23 ]. Although a growing number of towns are producing more municipal solid waste, landfill space is becoming gradually insufficient, especially in large cities [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Strength and Impact of Raw Ingredients of Cement Mortar Incorporating Waste Glass Powder Using Machine Learning and SHapley Additive ExPlanations (SHAP) Methods

et al. 2022

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This research employed machine learning (ML) and SHapley Additive ExPlanations (SHAP) methods to assess the strength and impact of raw ingredients of cement mortar (CM) incorporated with waste glass powder (WGP). The data required for this study were generated using an experimental approach. Two ML methods were employed, i.e., gradient boosting and random forest, for compressive strength (CS) and flexural strength (FS) estimation. The performance of ML approaches was evaluated by comparing the coefficient of determination (R2), statistical checks, k-fold assessment, and analyzing the variation between experimental and estimated strength. The results of the ML-based modeling approaches revealed that the gradient boosting model had a good degree of precision, but the random forest model predicted the strength of the WGP-based CM with a greater degree of precision for CS and FS prediction. The SHAP analysis revealed that fine aggregate was a critical raw material, with a stronger negative link to the strength of the material, whereas WGP and cement had a greater positive effect on the strength of CM. Utilizing such approaches will benefit the building sector by supporting the progress of rapid and inexpensive approaches for identifying material attributes and the impact of raw ingredients.

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Achieving sustainable development with sustainable packaging: A natural‐resource‐based view perspective

Lau,

Wong

2024

Bus Strat Env

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Sustainable packaging is a pivotal aspect of sustainable development, involving multi‐faceted issues such as stakeholder management and environmental policy compliance. Despite the efforts to find packaging solutions, the extant literature is largely fragmented, featuring a high level of heterogeneity among studies that spread across different disciplines, with the majority examining important packaging issues in isolation. A study that systematically consolidates findings of different important areas of sustainable packaging implementation is lacking. This challenges companies' adoption of research findings in business strategy development. Thus, this paper conducts a systematic literature review combining keyword co‐occurrence analysis, thematic analysis and qualitative content analysis to uncover major research domains, consolidate important findings and reveal unsolved research gaps, which are crucial to advancing sustainable packaging management. The findings reveal four major research domains: (1) sustainable packaging materials and properties, (2) management practices of sustainable packaging, (3) consumer behaviours towards sustainable packaging and (4) packaging waste management. Drawing on the natural‐resource‐based view (NRBV) theory and the review findings, this study proposes four future research directions: (1) identifying ways to enhance the commercialisation of sustainable packaging technological innovations, (2) uncovering reasons for insufficient social aspect investigation in sustainable packaging research, (3) exploring strategies to enhance stakeholder integration in sustainable packaging management and (4) examining contingency factors of packaging waste management effectiveness. The research agenda is important to provide practical and managerial insights for business strategy development in sustainable packaging to achieve pollution prevention, product stewardship and sustainable development capabilities to gain future growth and competitive advantage.

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Waste Glass Utilization in Cement-Based Materials for Sustainable Construction: A Review

Cited by 34 publications

References 121 publications

Experimental and machine learning approaches to investigate the effect of waste glass powder on the flexural strength of cement mortar

Experimental and machine learning approaches to investigate the effect of waste glass powder on the flexural strength of cement mortar

Evaluating the Strength and Impact of Raw Ingredients of Cement Mortar Incorporating Waste Glass Powder Using Machine Learning and SHapley Additive ExPlanations (SHAP) Methods

Achieving sustainable development with sustainable packaging: A natural‐resource‐based view perspective

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