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• Traditional methods for soil specific surface area (SSA) are costly and laborious. • We propose models to estimate SSA from a single hygroscopic water content (w h) • Separate SSA models are developed for soil samples grouped by clay mineralogy. • Considering soil clay mineralogy in SSA models significantly improved performance. • Models based on w h were superior to models based on texture, carbon or CEC. The soil specific surface area (SSA) is an important variable for soil science and geoenvironmental engineering applications, but traditional measurement methods are difficult and time-consuming. Regression models or pedotransfer functions are often used to estimate SSA from other soil properties (e.g., clay content and cation exchange capacity), but these models do not consider the impact of clay mineralogy. Hygroscopic water content (w h) is intimately linked to these soil properties, which suggests that w h may be a better parameter for SSA estimation. This study (i) proposes regression models that estimate SSA from w h at different relative humidity values (5 to 90%) for kaolinite-rich samples (KA), illite-rich or mixed clay samples (IL/MC), montmorillonite-rich samples (ML), and a combination of all samples (ALL) and (ii) compares the performance of the w h models to other published models that comprise clay, silt and soil organic carbon contents and cation exchange capacity. We found that the sample-specific w h regression models accurately estimated SSA for KA, IL/MC and ML samples. For KA and IL/MC samples, the performance of the KA model (e.g., for adsorption, average RMSE = 10.5 m2/g) and IL/MC model (average RMSE = 21.3 m2/g) were better than the ALL-calibration model (KA: average RMSE = 18.7 m2/g; ML: average RMSE = 22.4 m2/g). For ML samples, similar model performance between the ML-calibration model (average RMSE = 41.4 m2/g) and the ALL-calibration model (average RMSE = 41.1 m2/g) was observed. In addition, the model performance of regression models based on w h was superior to models published in the literature that are based on clay, silt and soil organic carbon contents and cation exchange capacity. Overall, this study confirms that a single measure of w h can provide reliable estimates of the SSA while revealing a significant impact of clay mineralogy on model performance. [ABSTRACT FROM AUTHOR]

A comprehensive study of expansive soil behavior includes understanding the surface phenomena of clay particles within the soil matrix. This research studies four micro-scale properties of four remolded expansive soils--matric suction, pH, surface conductance and percentage of montmorillonite--in order to predict soil swelling. An approach to approximate surface conductance is presented. Linear regression analyses were undertaken in an attempt to predict percent swell and swell pressure based on each of these micro-scale properties. Matric suction was found to be the most accurate predictor of the swelling behavior of the studied soils, which were initially compacted at optimum moisture content. Surface conductance, which is a combination of specific surface area, cation exchange capacity and cation mobility, also gave good predictions, except for one soil with high acidity. [ABSTRACT FROM AUTHOR]

X-ray micro-computed tomography (μ CT) scanning is a proven technique with applications in geoscience, soil science, and geotechnical engineering. Here we apply the technique to investigate the effects of cation treatments on clayey soil micro-fabric in a frozen state. We imaged six suites of frozen cation-treated soils (montmorillonite, kaolinite, illite, illite-smectite, chlorite, and Copper River heterogeneous soil) at a resolution of 8.17 μm. Although this resolution was insufficient to observe differences in microaggregate formation as a result of cation treatment, we did observe micro-lenticular ice structures in the smectite-bearing soils that were invisible to the unaided eye. Quantitative analysis of the morphometric parameters from the illite-smectite and Copper River sample suites provided results that supported the visual observations, with the Copper River heterogeneous soil being more frost susceptible than illite-smectite, regardless of cation treatment. The μ CT results of these small soil cores also indicate that within the Copper River suite, the Ca2+-treated and Na+-treated samples are the most and least frost susceptible, respectively, which is in agreement with previous frost heave testing. Results from this study indicate that μ CT morphometric parameters can be used to quantify micro-lenticular ice lens formation in small samples and to serve as a quality control on sample preparation. • Uses μ CT scanning to visualize micro-fabric changes as a result of cation treatment on clayey soils • Provides images with high resolution (8.17 µ m), which is not typical for µ CT scanning of frozen soils • Discusses how μ CT scanning revealed the presence of ice lensing in certain types of soils and cation treatments [ABSTRACT FROM AUTHOR]