Micrometric and Nanometric Characterization of Rock Aggregates Using AIMS, AFM, and SEM to Further Discussions on Geotechnical Roughness Classification Systems

The characterization of surface roughness in rock aggregates is essential for geotechnical engineering, directly influencing pavement performance and durability. This study compared three roughness analysis techniques: the Aggregate Imaging Measurement System (AIMS), Atomic Force Microscopy (AFM), and Scanning Electron Microscopy (SEM). Samples of volcanic rock (SUL) and plutonic rock (MIN) were analysed using all three techniques, revealing discrepancies in the results. AIMS presented limitations in representing materials with micrometric roughness and substantially coarse grain sizes, such as the MIN aggregate, where dominant minerals influenced the texture due to wavelet processing. AFM proved to be an efficient roughness characterization technique, quantifying parameters such as average roughness (Ra), root mean square roughness (Rq), surface skewness (Rsk), and surface kurtosis (Rku), but was limited to small scanning areas. The results reveal potential inconsistencies in traditional classification systems, particularly their inability to detect variations in rocks with different textures and granulometries. Data obtained from AFM and SEM demonstrated greater sensitivity, revealing features not identified by AIMS, especially in fine-grained materials like the SUL rock. Therefore, integrating micro- and nanoscale analyses is proposed as a complementary approach to overcome the limitations of conventional methods.