Dataset of Microstructural and Dynamic Mechanical Properties of Compacted Loess Modified by Calcium Oxalate Crystals: Implications for Geotechnical Engineering in Loess Regions

Abstract

Loess is a widely distributed and collapsible soil on China's Loess Plateau, and due to its poor dynamic performance under cyclic loads, it poses significant challenges to the stability of infrastructure. However, systematic datasets linking calcium oxalate crystal-induced modification, microstructural characteristics, and dynamic mechanical responses remain limited. The dataset includes compacted loess specimens prepared at oxalic acid concentrations of 0, 0.5, 1.5 and 2.0 mol/L and target moisture contents of 14%, 17% and 20%. Dynamic damping-ratio curves were obtained using a hollow cylindrical torsional shear apparatus, while SEM observations and PCAS analysis were used to quantify pore-size distribution, pore morphology, pore orientation and related microstructural descriptors. Microstructural characterisation was performed using JSM-6700F scanning electron microscopy combined with the Pore and Crack Analysis System. The image-based analysis provided quantitative information on pore-size distribution, pore orientation, pore morphology and the bonding characteristics between crystals and soil particles. This dataset includes the basic physical properties of loess, the dynamic damping ratio curves versus shear strain for calcium oxalate crystal-modified loess and untreated loess, scanning electron microscopy images of microstructures before and after dynamic shear, quantitative pore structure parameters derived from Pore and Crack Analysis System analysis, and Pearson correlation matrices linking oxalic acid concentration, microstructural parameters and dynamic damping ratios. This dataset provides reusable data for Earth system science and civil engineering research. It can be used to validate numerical models of soil modification, compare eco-friendly stabilisation methods for collapsible loess and support further assessment of infrastructure performance in loess regions.