Artificial intelligence in the design, optimization, and performance prediction of concrete materials: a comprehensive review Article Swipe

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Dayou Luo , Kejin Wang , Dongming Wang , Anuj Sharma , Wengui Li , In Ho Choi ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1038/s44296-025-00058-8

Artificial Intelligence (AI) is transforming concrete research. This review explores various AI techniques that drive cutting-edge solutions across all stages of concrete lifecycle, from material, mixture, and process optimization to quality control and performance prediction. Meta-analysis shows that XGBoost model excels in predicting workability (R 2 = 0.98), while ensemble models provide the best strength predictions (R 2 = 0.93). The study highlights trends, gaps, and future AI opportunities in concrete technology.

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Type: review
Language: en
Landing Page: https://doi.org/10.1038/s44296-025-00058-8
PDF: https://www.nature.com/articles/s44296-025-00058-8.pdf
OA Status: diamond
Cited By: 9
References: 314
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DOI: https://doi.org/10.1038/s44296-025-00058-8

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Title: Artificial intelligence in the design, optimization, and performance prediction of concrete materials: a comprehensive review

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Type: review

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Language: en

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Publication year: 2025

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Publication date: 2025-05-17

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Authors: Dayou Luo, Kejin Wang, Dongming Wang, Anuj Sharma, Wengui Li, In Ho Choi

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Landing page: https://doi.org/10.1038/s44296-025-00058-8

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PDF URL: https://www.nature.com/articles/s44296-025-00058-8.pdf

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OA URL: https://www.nature.com/articles/s44296-025-00058-8.pdf

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Concepts: Computer science, Engineering, Artificial intelligence

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Cited by: 9

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Citations by year (recent): 2025: 9

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References (count): 314

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Related works (count): 10

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