Akademik Veri Yönetim Sistemi
Journal of Energy Storage, cilt.97, 2024 (SCI-Expanded)
Natural graphite, the most preferred battery anode material driving the EV revolution, is purified by flotation after being micronized. Therefore, grinding, an energy-intensive process that affects the size and shape of particles, is of very central importance not only for graphite ore flotation but also for the anode material preparation. Since controlling particle shape through the selection of an appropriate grinding system can enhance these processes, obtaining optimum grinding conditions by modeling the change of particle shape with grinding time can bring remarkable benefits in terms of time, energy, and cost. However, grinding modeling has mostly focused on particle size and the effect of particle shape has generally been lacking. Therefore, this study delves into the relationship between the shape of graphite particles obtained at the same size fraction by grinding them in “tumbling” and “non-tumbling” mills and the grinding time. Linear and nonlinear models were trained on shape data determined by DIA, which is the most accurate technique and used to estimate the required grinding time for spherical-shaped particles. The results showed that the time-dependent linear shape model (BRARav. = − a.t + b) was the best as it had the highest R2 (0.96), and the lowest errors compared to other tested models. It was also found that the predicted values were in good agreement with the actual values.