ASSESSMENT OF COAL CLEANABILITY FOR VARIOUS BENEFICIATION PROCESSES BY SEM-BASED AUTOMATED IMAGE-ANALYSIS

Techniques employing scanning electron microscopy-based automated image analysis (SEM-AIA) are emerging as useful tools for the characterization of coal and its associated mineral matter to be used in conjunction with advanced coal conversion and coal cleaning processes. New methodology and applications have been developed at the Ames Laboratory and Iowa State University to study the nature and amount of mineral phases, their particle size distributions, and their degree of association with the organic coal matrix. Since the mineral content and composition can vary widely from coal to coal, the detailed characterization provided by these SEM-AIA techniques is quite helpful for the planning, design, testing, and evaluation of coal beneficiation and conversion processes. The methodology of SEM-AIA is described along with several illustrative applications related to coal beneficiation. © 1990.