Evolution of Multiscale Mechanical Properties of Shales

This dataset is a multi-scale, multi-modal correlated dataset that directly links microscopic information with mechanical properties.

1 Microstructural Data (FE-SEM Analysis)

Data Content: High-resolution secondary electron and backscattered electron images revealing nano- to micro-scale features. This includes the distribution and morphology of organic matter (OM), mineral grains (quartz, clay platelets, etc.), pore types (OM pores, interparticle pores, intraparticle pores), micro-fractures, and their interrelationships.

2 Mineralogical Data (XRD Analysis)

Data Content: Quantitative data on the whole-rock mineral composition (weight %). This is the key dataset for differentiating siliceous (quartz-rich) from argillaceous (clay-rich) shales. It includes the content of quartz, various clay minerals (illite, smectite, etc.), carbonate minerals, feldspar, pyrite, etc.

3 Crystallographic Orientation Data (EBSD Analysis)

Data Content: Crystallographic orientation and micro-textural information of mineral grains. This data generates orientation imaging maps (OIM), pole figures, and inverse pole figures, used to quantify crystallographic preferred orientation (anisotropy), grain boundary types, and intragranular strain distribution.

4 Nanomechanical Data (Nanoindentation Test)

Data Content:

Raw Data: 1,400 load-displacement curves (100 indents/sample × 14 samples).

Derived Data: A matrix of Elastic Modulus (E) and Hardness (H) values calculated from each curve using the Oliver-Pharr method. This data can be plotted as frequency histograms or spatial property maps.

5 Macro-Mechanical Data (Triaxial Compression Test)

Data Content: Axial stress-strain, radial stress-strain, and volumetric strain-axial strain curves. From these, macro-mechanical parameters are derived: peak strength (σₚ), Young's Modulus (E), Poisson's Ratio (ν), cohesion (c), and angle of internal friction (φ).