4.2 Article

Prediction of cation exchange capacity from soil index properties

Journal

CLAY MINERALS
Volume 41, Issue 4, Pages 827-837

Publisher

MINERALOGICAL SOC
DOI: 10.1180/0009855064140222

Keywords

cation exchange capacity; specific surface area; clay fraction; organic matter; Atterberg limits; swell index

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In many areas of geotechnical engineering it is necessary to have an estimate of the cation exchange capacity (CEC) of a soil in order to allow preliminary design estimates. Standard methods of CEC determination are time-consuming and involve several steps (e.g. displacement of the saturating cation requires several washings with alcohol). Therefore, a rapid method of CEC estimation would be very useful. During preliminary site investigations, the soil engineering parameters can be estimated from the considerable number of correlations available in the literature. In this study, relationships between CEC and various other soil engineering properties have been investigated, resulting in a quick method for estimating CEC. Simple correlations were developed between CEC and specific surface area (SSA), soil organic matter (OM), clay fraction (CF), activity (A), Atterberg limits (liquid (LL), plastic (PL), and shrinkage (SL)), and modified free swell index (MFSI) of the soils. Strong correlations are observed between the CEC values and those for ethylene glycol monoethyl ether (EGME) uptake and methylene blue (MB) titration. However, no significant correlation was found between CEC and N-2_SSA. No unique relationship was seen between CEC and CF (r(2) <0.5). No relationship was observed between CEC and OM in this study. The best correlation coefficient between the CEC and Atterberg limits exists between CEC and LL (r(2) = 0.61). No significant relationship was seen between CEC and PL or SL. The correlation coefficient between CEC and MFSI was 0.65. Multiple linear regression analyses were developed to investigate the contributions of different soil parameters to CEC. These analyses show that EGME SSA, in combination with LL, accounted for 91% of the variation in CEC. Correlations between CEC and EGME _ SSA, MB _ SSA and LL appear to be sufficiently good to enable an indication of CEC to be estimated from these parameters.

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