Islam Md Hamidul, Prova Zannatun Noor, Sobuz Md Habibur Rahman, Nijum Nusrat Jahan, Aditto Fahim Shahriyar
Department of Building Engineering and Construction Management, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh.
Heliyon. 2025 Jan 13;11(2):e41924. doi: 10.1016/j.heliyon.2025.e41924. eCollection 2025 Jan 30.
The rapid global expansion of e-waste poses significant environmental and health risks, making it crucial to find sustainable uses and mitigate its harmful effects. The significance of this research is to look into the impact of e-waste as a possible substitute for natural coarse aggregates (NCA) on the fresh, hardened and durability characteristics of concrete, alongside machine learning (ML) predictive analysis. Four kinds of concrete mixes were made with produced coarse aggregates as a substitute material for NCA, and substitution levels were calculated as 0 %, 10 %, 15 % and 20 % (by mass of NCA). Compressive and splitting tensile tests evaluated the mechanical properties of e-waste concrete, whereas water permeability and electrical resistivity tests assessed durability to determine the optimal e-waste proportion for construction. The compressive and tensile strengths of e-waste concrete were reduced by 13.41%-25.50 % and 11%-19.26 %, respectively, for replacement levels ranging from 10 % to 20 % at 28 days. The specimens, evaluated at 300 °C, exhibited reductions in compressive strength by 15.26%-30.87 % and tensile strength by 10.52%-19.74 % for e-waste replacement levels of 10%-20 %, respectively. With high coefficient correlation (R) values, the linear regression (LR) model predicted mechanical property outcomes more accurately than the random forest (RF) model. The electrical resistivity test showed better results increased range of 239.06 %-478.82 %. The findings of the water permeability test improved when the quantity of e-waste plastic was increased by 15 %. In terms of all the percentage results, the 15 % replacement produced the best results and produced a sustainable construction material.
电子垃圾在全球范围内的迅速扩张带来了重大的环境和健康风险，因此寻找可持续利用方式并减轻其有害影响至关重要。本研究的意义在于探讨将电子垃圾作为天然粗骨料（NCA）的一种可能替代品，对混凝土的新拌性能、硬化性能和耐久性特征的影响，并进行机器学习（ML）预测分析。用生产的粗骨料作为NCA的替代材料制作了四种混凝土混合料，替代水平计算为0%、10%、15%和20%（按NCA质量计）。抗压和劈裂抗拉试验评估了电子垃圾混凝土的力学性能，而水渗透性和电阻率试验评估了耐久性，以确定用于建筑的最佳电子垃圾比例。在28天时，对于10%至20%的替代水平，电子垃圾混凝土的抗压强度和抗拉强度分别降低了13.41%-25.50%和11%-19.26%。在300°C下评估的试件，对于10%-20%的电子垃圾替代水平，抗压强度降低了15.26%-30.87%，抗拉强度降低了10.52%-19.74%。线性回归（LR）模型的系数相关性（R）值较高，比随机森林（RF）模型更准确地预测了力学性能结果。电阻率试验显示出更好的结果，增加范围为239.06%-478.82%。当电子垃圾塑料的用量增加15%时，水渗透性试验的结果有所改善。就所有百分比结果而言，15%的替代率产生了最佳效果，并产生了一种可持续的建筑材料。
