计算机科学
新颖性
数据挖掘
水准点(测量)
冗余(工程)
足迹
碳足迹
领域(数学)
数据科学
机器学习
地质学
操作系统
哲学
古生物学
海洋学
温室气体
纯数学
数学
神学
大地测量学
作者
Benjamín Moreno Torres,Christoph Völker,Rafia Firdous
出处
期刊:Data in Brief
[Elsevier]
日期:2023-08-28
卷期号:50: 109525-109525
被引量:19
标识
DOI:10.1016/j.dib.2023.109525
摘要
This data article introduces a dataset comprising 1630 alkali-activated concrete (AAC) mixes, compiled from 106 literature sources. The dataset underwent extensive curation to address feature redundancy, transcription errors, and duplicate data, yielding refined data ready for further data-driven science in the field of AAC, where this effort constitutes a novelty. The carbon footprint associated with each material used in the AAC mixes, as well as the corresponding CO2 footprint of every mix, were approximated using two published articles. Serving as a foundation for future expansions and rigorous data applications, this dataset enables the characterization of AAC properties through machine learning algorithms or as a benchmark for performance comparison among different formulations. In summary, the dataset provides a resource for researchers focusing on AAC and related materials and offers insights into the environmental benefits of substituting traditional Portland concrete with AAC.
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