# Quantification of Total Porosity from CT Images by Segmenting Unhydrated Cement: A Model-Informed Framework Integrating POWERS’ Volume Model

**Authors:** Haoran Liu, Eryu Zhu, Min Ji, Zhengwei Bai, Teng Li

PMC · DOI: 10.3390/ma19040686 · 2026-02-11

## TL;DR

This paper introduces a new method to measure total porosity in cement using CT scans by combining a hydration model with image analysis.

## Contribution

A novel model-informed framework that integrates Powers’ hydration model with micro-CT analysis to quantify total porosity in cement.

## Key findings

- Total porosity of cement pastes ranged from 36.5% to 60.3% as w/c ratio increased from 0.4 to 0.7.
- CT-derived porosity showed strong correlation (R2 > 0.98) with established porosity–strength models.
- The method enables micro-CT to be used for quantitative microstructural analysis of cementitious materials.

## Abstract

Quantification of total porosity, including the nano-scale fraction, is critical for predicting the performance of cement-based materials but remains a significant challenge. While X-ray computed tomography (CT) is a powerful non-destructive tool, a fundamental trade-off between resolution and representative sample volume prevents the direct segmentation of nano-scale pores in macroscopically relevant specimens. Herein, we propose and validate a novel model-informed framework that overcomes this limitation by integrating the classical Powers’ hydration model with micro-CT analysis. The method circumvents the need for nano-scale resolution by deriving the total porosity from the volume fraction of the easily segmentable, micron-scale unhydrated cement phase. The framework’s validity was demonstrated by showing a strong correlation between the CT-derived total porosity and established porosity–strength relationships. Quantitative analysis indicated that the total porosity of the cement pastes ranged from 36.5% to 60.3% as the w/c ratio increased from 0.4 to 0.7. Laboratory strength data show good correlation (R2 > 0.98) with four porosity–strength prediction models, demonstrating the feasibility of applying the Powers’ volume model in CT-based analyses of cement pastes. This work transforms micro-CT from a qualitative imaging tool into a comprehensive technique for the quantitative microstructural characterization of cementitious materials.

## Full-text entities

- **Diseases:** fracture (MESH:D050723), injury to (MESH:D014947)
- **Chemicals:** Water (MESH:D014867), chloride (MESH:D002712), Nitrogen (MESH:D009584), OPC (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

14 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12941572/full.md

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Source: https://tomesphere.com/paper/PMC12941572