Research on Flocculant Selection for Classified Fine Tailings Based on Micro-Characterization of Floc Structure Characteristics

Materials (Basel). 2022 Mar 27;15(7):2460. doi: 10.3390/ma15072460.

Abstract

The rapid settlement of tailings is an important technical guarantee for the continuous production of downhole filling. The selection of a reasonable flocculant is essential for accelerating the settlement speed of classified fine tailings. The present paper conducts indoor static sedimentation experiments, NMR observation, electron microscope scanning, and other methods to analyze the porosity and pore-size distribution characteristics of floc solution for classified fine tailing under four flocculants, namely, ZYZ, ZYD, JYC-1, and JYC-2. The dimension, spatial distribution characteristics, particle size characteristics, and morphological characteristics of the scanning electron microscope images of floc were studied. Results show that the unit consumption of flocculant at 30 g/t is the critical value for increasing the flocculation and sedimentation effect of the classified fine tailings solution. The highest distribution percentage of small-sized classified fine tailings and the lowest average pore size was observed under the ZYZ-type flocculant. This flocculant also obtained the lowest porosity, largest average floc size, largest area occupied by the floc, lowest pore percentage, and the densest floc structure. Thus, this flocculant showed the best flocculation effect. A negative correlation was observed between the equivalent diameter of floc with varying settlement heights. The dimension of floc increased with the decrease in bed settlement height, and the overall structure of the floc gradually transitioned from loose to dense from top to bottom. The present paper characterizes the microscopic morphology and spatial structure characteristics of floc under different flocculants from a microscopic point of view. The present paper also provides a scientific basis for the selection of the optimal flocculant.

Keywords: SEM image; classified fine tailings; flocculation and sedimentation; gray value; nuclear magnetic resonance.