碳酸锂
降水
碳酸盐
粒度分布
粒径
锂(药物)
材料科学
超声波
粒子(生态学)
化学工程
化学
物理
地质学
冶金
离子
医学
气象学
海洋学
声学
有机化学
内科学
工程类
离子键合
作者
Doni Riski Aprilianto,Indra Perdana,Irwan Endrayanto,Fajar Adi-Kusumo,Rochmadi Rochmadi,Himawan Tri Bayu Murti Petrus
出处
期刊:ACS omega
[American Chemical Society]
日期:2025-07-14
卷期号:10 (29): 32226-32245
标识
DOI:10.1021/acsomega.5c04035
摘要
This study investigates ultrasound-assisted precipitation (sonocrystallization) as a method to precisely control lithium carbonate (Li2CO3) particle formation from a lithium-rich solution of spent lithium-ion batteries. In addition to its high purity, to meet battery-grade standards, the Li2CO3 precipitates must exhibit well-defined particle size distribution. By controlling the nucleation and growth rates through the simultaneous adjustment of ultrasound power and temperature, both the particle size and morphology of the precipitates can be accurately defined. A detailed kinetic analysis was performed to evaluate the effects of ultrasound power and temperature on the precipitation process. The proposed kinetic model combining population balance and a compartment-based discretization approach accurately simulated the particle size distribution. The model provided general kinetic parameters for nucleation and particle growth as functions of the process variables. Experimental validation showed that increased ultrasound power reduced the particle size and improved uniformity, while lower temperatures promoted smaller particles due to the distinct crystallization behavior of the endothermic process. Compared to conventional stirring precipitation, which results in larger agglomerated morphologies, the ultrasound-assisted precipitation yielded non-agglomerated particles. Under the optimal condition (320 W, 90 °C), the process achieved particle sizes of d 10 = 2.85 μm, d 50 = 5.5 μm, and d 90 = 14.55 μm, meeting industrial specifications. These experimental and kinetic simulation findings provide general insight into controlling the particle size through sonocrystallization, particularly to support scalable battery-grade Li2CO3 recovery from secondary sources.
科研通智能强力驱动
Strongly Powered by AbleSci AI