Low-Carbon Technology and Chemical Reaction Engineering Lab, School of Chemical Engineering, Sichuan University, Chengdu 610065, China.
Chemistry and Chemical Engineering Data Center, Institute of Process Engineering, Chinese Academy of Sciences (CAS), Beijing 100190, China.
Int J Mol Sci. 2023 Mar 7;24(6):5066. doi: 10.3390/ijms24065066.
A large amount of cyanide-containing wastewater is discharged during electrode material synthesis. Among them, cyanides will form metal-cyanide complex ions which possess high stability, making it challenging to separate them from these wastewaters. Therefore, it is imperative to understand the complexation mechanism of cyanide ions and heavy metal ions from wastewater in order to obtain a deep insight into the process of cyanide removal. This study employs Density Functional Theory (DFT) calculations to reveal the complexation mechanism of metal-cyanide complex ions formed by the interaction of Cu and CN in copper cyanide systems and its transformation patterns. Quantum chemical calculations show that the precipitation properties of Cu(CN) can assist in the removal of CN. Therefore, transferring other metal-cyanide complex ions to Cu(CN) can achieve deep removal. OLI studio 11.0 analyzed the optimal process parameters of Cu(CN) under different conditions and determined the optimal process parameters of the removal depth of CN. This work has the potential to contribute to the future preparation of related materials such as CN removal adsorbents and catalysts and provide theoretical foundations for the development of more efficient, stable, and environmentally friendly next-generation energy storage electrode materials.
在电极材料合成过程中会排放出大量含氰废水。其中，氰化物会形成金属氰化物络合离子，具有很高的稳定性，难以从废水中分离出来。因此，了解废水中氰化物离子和重金属离子的络合机制对于深入了解氰化物去除过程至关重要。本研究采用密度泛函理论（DFT）计算揭示了铜氰化物体系中 Cu 和 CN 相互作用形成的金属氰化物络合离子的络合机制及其转化模式。量子化学计算表明，Cu(CN)的沉淀性能有助于去除 CN。因此，将其他金属氰化物络合离子转化为 Cu(CN)可以实现深度去除。OLI studio 11.0 分析了不同条件下 Cu(CN)的最佳工艺参数，并确定了 CN 去除深度的最佳工艺参数。这项工作有望为未来制备相关材料（如 CN 去除吸附剂和催化剂）提供理论基础，并为开发更高效、稳定和环保的下一代储能电极材料提供理论基础。
