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April 30, 2026Journal of the Korea Concrete Institute

Data-Driven Classification of Water-to-Cement Ratio Based on Electrochemical Impedance Features

Joohye Park Junyoung Lee Jinyoung Hong Hajin Choi

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Key Points

To develop a simple and accurate method for assessing the water-to-cement ratio (w/c) using electrochemical impedance data.
Utilized raw impedance spectrum data from initial cement pastes for w/c classification.
Applies random forest algorithm for model optimization.
Statistical examination of classification possibilities through impedance analysis.
Achieved classification accuracy of 0.925 for the 36% w/c threshold.
Macro-average F1 score of 0.917 and ROC AUC of 0.982.
Proposes the potential for expanding into multi-class classification with complex conditions.

Implication

Demonstrates a high accuracy classification of water-to-cement ratio, suggesting practical evaluation methods for concrete quality.

Abstract

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Cite This Study

Park et al. (2026) studied this question.

synapsesocial.com/papers/6a002147c8f74e3340f9c1e1 https://doi.org/10.4334/jkci.2026.38.2.139

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Keep reading

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1In Situ Monitoring of Water-to-Cement Ratio of 3D-Printed ConcreteOriginal Research · 2026
2Comparative Assessment of Pore Structure and Water Retention in Concrete Using MIP, CT, SEM, and Dewpoint Techniques2025 · 2 citations
3Analysis of Damage Mechanisms and Evolution in Recycled Aggregate Concrete Considering the Effects of Water–Cement Ratio and Pore WaterOriginal Research · 2026
4Combined water fraction (cwf): Theoretical insights, literature data mining, methodological implications and practical useMeta-Analysis · 2026
5Influence of water-cement ratio on electrical properties of smart cement composites2025 · 1 citations

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