Environmental benefits of nano-modified cement incorporating high slag content: A machine learning approach

Cleaner Waste Systems Pub Date : 2025-01-27 DOI:10.1016/j.clwas.2025.100216

Serhat Demirhan , Necim Kaya , Yılmaz Kaya , Mem Çiftçi

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Abstract

This research makes a significant contribution to the field of environmental management by elucidating the environmental advantages of producing nanomaterial-modified cement, specifically by incorporating ground granulated blast furnace slag (GGBFS) replaced by cement up to 81 %. To achieve this, a total of 58 distinct mixtures were meticulously formulated, with the inclusion of nanomaterials such as nano-calcite, nano-alumina, and nano-silica in small quantities to produce standard cement mortars. The compressive strength of the resulting specimens was tested at curing intervals of 2, 7, and 28 days. The data obtained from these tests were analyzed using the Group Method of Data Handling (GMDH) machine learning model. Additionally, the experimental results were further evaluated through other machine learning estimation models. This study provides eco-friendly strategies to enhance cost-effectiveness and time efficiency in the production of CEM III cement with a high slag content, offering significant benefits for both cement manufacturers and environmental sustainability.

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高矿渣含量纳米改性水泥的环境效益：一种机器学习方法

这项研究通过阐明生产纳米材料改性水泥的环境优势，特别是用水泥代替81% %的磨碎高炉矿渣（GGBFS），对环境管理领域做出了重大贡献。为了实现这一目标，共精心配制了58种不同的混合物，其中包含少量纳米材料，如纳米方解石、纳米氧化铝和纳米二氧化硅，以生产标准的水泥砂浆。试件的抗压强度分别在2、7和28天的养护间隔内进行测试。从这些测试中获得的数据使用数据处理组方法（GMDH）机器学习模型进行分析。此外，通过其他机器学习估计模型进一步评估实验结果。本研究提供了环保策略，以提高高矿渣含量CEM III水泥生产的成本效益和时间效率，为水泥制造商和环境可持续性提供了显著的好处。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cleaner Waste Systems

CiteScore

2.60

自引率

0.00%

发文量