Comparison of Nature and Synthetic Zeolite for Waste Battery Electrolyte Treatment in Fixed-Bed Adsorption Column

To support a sustainable energy development, CO2 reduction for carbon neutralization and water-splitting for hydrogen economy are two feasible technical routes, both of which require a significant input of renewable energies. To efficiently store renewable energies, secondary batteries will be applied in great quantity, so that a considerable amount of energy needs to be invested to eliminate the waste battery electrolyte pollution caused by heavy metals including Cu2+, Zn2+ and Pb2+. To reduce this energy consumption, the removal behaviors of these ions by using clinoptilolite and zeolite A under 5, 7 and 10 BV h−1 in a fixed-bed reactor were investigated. The used zeolites were then regenerated by a novel NH4Cl solution soaking, coupled with the ultrasonication method. Further characterizations were carried out using scanning electron microscopy, N2 adsorption and desorption test, and wide-angle X-ray diffraction. The adsorption breakthrough curves revealed that the leaching preference of clinoptilolite was Pb2+ > Cu2+ > Zn2+, while the removal sequence for zeolite A was Zn2+ > Cu2+ > Pb2+. The maximum removal percentage of Zn2+ ions for clinoptilolite under 5 BV h−1 was 21.55%, while it was 83.45% for zeolite A. The leaching ability difference was also discussed combining with the characterization results. The fact that unit cell stayed the same before and after the regeneration treatment approved the efficacy of the regeneration method, which detached most of the ions while doing little change to both morphology and crystallinity of the zeolites. By evaluating the pH and conductivity changes, the leaching mechanisms by adsorption and ion exchange were further studied.

Quantum chemical calculations of lithium-ion battery electrolyte and interphase species

Lithium-ion batteries (LIBs) represent the state of the art in high-density energy storage. To further advance LIB technology, a fundamental understanding of the underlying chemical processes is required. In particular, the decomposition of electrolyte species and associated formation of the solid electrolyte interphase (SEI) is critical for LIB performance. However, SEI formation is poorly understood, in part due to insufficient exploration of the vast reactive space. The Lithium-Ion Battery Electrolyte (LIBE) dataset reported here aims to provide accurate first-principles data to improve the understanding of SEI species and associated reactions. The dataset was generated by fragmenting a set of principal molecules, including solvents, salts, and SEI products, and then selectively recombining a subset of the fragments. All candidate molecules were analyzed at the ωB97X-V/def2-TZVPPD/SMD level of theory at various charges and spin multiplicities. In total, LIBE contains structural, thermodynamic, and vibrational information on over 17,000 unique species. In addition to studies of reactivity in LIBs, this dataset may prove useful for machine learning of molecular and reaction properties.