Determination of specific surface area of irregular aggregate by random sectioning and its comparison with conventional methods

Qiang Ren, Luchuan Ding, Xiaodi Dai, Zhengwu Jiang, Guang Ye, Geert De Schutter

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Abstract

A two-dimensional (2D) image-based methodology was proposed to measure the specific surface area (SSA, specified as the surface area per unit volume) of irregular aggregate by random sectioning. Conventional methods including spherical assumption, Brunauer-Emmett-Teller (BET) and computed tomography (CT) tests were used and compared in this study. Results show that spherical assumption provides the lowest SSA among these methods since the feature of anisotropy in dimension is not considered. SSA by BET test has one order of magnitude higher value than others, which is attributed to the fact that BET method measures each position of particles that nitrogen molecule can be adsorbed on during the applied relative pressure, based on the ‘pixel’ of nitrogen molecule. The proposed random sectioning method presents very similar SSA result compared to CT method, indicating that it can be considered as a reliable method. To improve the estimation of SSA by random sectioning method, factors that may influence SSA result were analyzed. Results indicate that the number of samples should be high enough to reach a constant result and the thresholding algorithm should be adequate. Besides, a higher resolution of pixel provides a higher SSA value. The comparison among these methods demonstrate that it is necessary to determine the scale at which the features of the surface are supposed to be captured before selecting the optimal testing method.

Original languageEnglish
Article number122019
Pages (from-to)1-9
Number of pages9
JournalConstruction and Building Materials
Volume273
DOIs
Publication statusPublished - 2021

Keywords

  • Aggregates
  • BET
  • Computed tomography
  • Random sectioning
  • Specific surface area
  • Spherical assumption

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