金属有机骨架衍生双金属氧化物的锂离性能

通过一步微波法设计合成了含有 Co 和 Zn 的双金属有机骨架结构, 并在氧气氛围下 500 ${^\circ}$C 煅烧衍生获得由纳米粒子组装的 Co-Zn-O 双金属氧化物微米棒材料. 衍生材料延承了双金属有机骨架前驱体的微米棒形貌和多孔特性, 具有两种不同的金属组分之间的协同储锂作用. Co-Zn-O 双金属氧化物作为锂离子电池负极材料时展现了较高的比容量与循环稳定性, 经过 100 圈的充放电循环后, 比容量保持在 1 137 mA$\cdot$h$\cdot$g-1.     

矿山机车用中等功率型锂离子电池制备技术

分别以LiFePO4、人造石墨为正、负极活性物质,成功研制出可替代铅酸电池用于矿山机车、额定容量为23 Ah的中等功率4866135型方型钢壳锂离子电池．针对矿山机车使用工况,提出了锂离子动力电池的设计依据和各项工艺参数,重点研究了电池的荷电特性、功率特性和安全性能．测试结果表明,4866135型锂离子电池5 C倍率的持续放电质量比功率高达354.6 W/kg,1 C循环450周,容量保持率在86%以上．安全性能测试表明,电池可靠性高,各项技术指标均达到了设计要求．     

锂离子电池失效的快速判定

通过锂离子单体电池的循环寿命实验,分析了该电池的充放电电流,电压以及内阻随循环次数的老化特性.研究发现,随着充放电次数的增加,电池在恒流阶段充入的容量占总容量的百分比的变化趋势和电池内阻变化相一致,因此可以根据恒流充电的时间来快速判定电池的衰减程度.     

溶胶-凝胶法合成LiAl0.1Mn1．9O4及其电化学性能

通过溶胶-凝胶法合成LiAl0.1Mn1.9O4，XRD的结果表明掺杂少量的铝后并没有改变晶体的结构。利用恒流充放电测试手段比较研究了尖晶石型的LiAl0.1Mn1.9O4，XRD铝的掺杂后的LiAl0.1Mn1.9O4，XRD比没有掺杂的LiMn2O4更好的可逆性能，更好的循环性能。     

碳点修饰硅在锂离子电池中的应用研究

Silicon (Si) particles were functionalized using carbon dots (CDs) to enhance the interaction between the Si particles and the binders. First, CDs rich in polar groups were synthesized using a simple hydrothermal method. Then, CDs were loaded on the Si surface by impregnation to obtain the functionalized Si particles (Si/CDs). The phases and microstructures of the Si/CDs were observed using Fourier-transform infrared reflection, X-ray diffraction, scanning electron microscopy, and high-resolution transmission electron microscopy. Si/CDs were used as the active material of the anode for electrochemical performance experiments. The electrochemical performance of the Si/CD electrode was assessed using cyclic voltammetry, electrochemical impedance spectroscopy, and constant current charge and discharge experiment. The electrodes prepared with Si/CDs showed good mechanical structure stability and electrochemical performance. After 150 cycles at 0.2 C, the capacity retention rate of the Si/CD electrode was 64.0%, which is twice as much as that of pure Si electrode under the same test conditions.     

氯化亚锡作为还原剂在废旧锂离子电池有价金属浸出回收中的应用研究

The reductant is a critical factor in the hydrometallurgical recycling of valuable metals from spent lithium-ion batteries (LIBs). There is limited information regarding the use of SnCl₂ as a reductant with organic acid (maleic acid) for recovering valuable metals from spent LiCoO₂ material. In this study, the leaching efficiencies of Li and Co with 1 mol·L?1 of maleic acid and 0.3 mol·L?1 of SnCl₂ were found to be 98.67% and 97.5%, respectively, at 60°C and a reaction time of 40 min. We investigated the kinetics and thermodynamics of the leaching process in this study to better understand the mechanism of the leaching process. Based on a comparison with H₂O₂ with respect to leaching efficiency, the optimal leaching parameters, and the activation energy, we determined that it is feasible to replace H₂O₂ with SnCl₂ as a leaching reductant in the leaching process. In addition, when SnCl₂ is used in the acid-leaching process, Sn residue in the leachate may have a positive effect on the re-synthesis of nickel-rich cathode materials. Therefore, the results of this study provide a potential direction for the selection of reductants in the hydrometallurgical recovery of valuable metals from spent LIBs.     

锂离子电池LiNiO_2正极材料的高温固相合成①及其影响因素研究

采用高温固相法合成了LiNiO2,XRD确定了合成物的结构,用SEM表征LiNiO2粉体的形貌.探讨了反应条件:包括原材料、Li/Ni摩尔比、烧结气氛和温度对产物结构和性能的影响,从而优化了LiNiO2的合成工艺.在空气中合成只能得到Li2Ni8O10相,在O2中才能得到LiNiO2相,所得LiNiO2的电化学性能明显优于所得Li2Ni8O10.合成电化学性能良好的LiNiO2需要稍过量的锂和在氧气中600℃恒温3h,720℃恒温6h,合成过程中得预热处理,解决了低温下反应速度慢,高温下易于烧结而难于控制产物粒径的问题.分析了采用固相配位法合成LiNiO2失败的原因.     

纳米级锂离子电池正极材料LiCoO2的制备及表征

LiCoO2是锂离子电池中最有前途的正极材料之一，近年来人们对它进行了广泛的研究．这里我们通过两种不同的湿化学方法首次合成了纳米级的LiCoO2：溶胶—凝胶法(方法B)和一种改进了的溶胶—凝胶法(方法C)。为了便于比较，我们也采用了固相反应法(方法A)。用DTA，IR，XRD，TEM等技术对前驱体和LiCoO2纳米颗粒进行了表征．结果表明在600℃煅烧时可以得到晶化程度较好的LiCoO2纳米颗粒，方法A和方法B得到了直径大约为100和40nm的球状颗粒，而方法C主要得到球形颗粒，同时伴有少量小棒形颗粒生成，直径约为50nm。电化学测试表明方法C得到的产物具有最好的性能。     

基于开路电压特性的动力电池健康状态诊断与估计

电池系统复杂的配置和严苛、不确定性的工作环境造成的电池衰退过程极为复杂.为了准确地实施电池系统的管理与控制以保证其高效、可靠和安全运行,有效的电池健康状态诊断与估计必不可少.利用容量增量分析和差分电压分析等原位电化学分析方法对电池开路电压特性变化进行分析,建立电池容量衰退与其衰退机理的量化关系,追溯到电池衰退的源头,从衰退机理角度对电池健康状态进行更真实和更准确的诊断.同时,建立基于电池开路电压曲线的容量估计模型用于电池健康状态估计,该模型不仅能捕捉电池内部不同阶段电化学反应特性,而且具有较高的精度和鲁棒性.在电池全生命周期内,该模型估计误差均小于4%.