Chemo-mechanical controls on clay fabric: Generalized maps for predicting soil behavior in variable chemical environments

Understanding the link between clay microstructure and macro-scale geotechnical behavior is critical for predicting soil performance in engineering applications. This study develops and validates generalized fabric maps for clay suspensions, capturing transitions between dispersed, mixed, and flocculated regimes as a function of pore-fluid chemistry (ionic concentration and pH) and clay mineralogy (kaolinite, illite, and bentonite). Controlled laboratory suspensions of pure clay minerals were used to isolate fundamental physicochemical mechanisms, including interparticle forces governed by diffuse double-layer repulsion, van der Waals attraction, and edge–face interactions, as described by DLVO theory. Sedimentation behavior, including induction-stage settling rates, post induction-stage settling rates, sediment height, and porosity, was quantified to construct the fabric maps, which provide mechanistic insights into clay particle association under varying chemical conditions. Results demonstrate that the critical ionic concentration for regime transitions is strongly influenced by specific surface area rather than mineralogy alone, highlighting the scalability of physicochemical interactions across different clay types. The mixed sedimentation regime exhibits unique characteristics, including heterogeneity in fabric, structural anisotropy, and sensitivity to minor chemical fluctuations, posing challenges for modeling and geotechnical engineering design. These findings have direct implications for soil stabilization, sediment management, and the design of geotechnical structures in chemically variable environments. The manuscript explicitly outlines the limitations of extrapolating from simplified systems to natural soils with mixed mineralogy and organic content and identifies future directions, including integration with direct measurements of permeability, shear strength, and compressibility, as well as validation in complex natural systems. Overall, this work advances fabric mapping as a predictive framework for understanding chemo-mechanical behavior in clay-rich soils.