Zeng Defu, Li Yalin, Xia Tao, Cui Fuyi, Zhang Jing
School of Environment, Harbin Institute of Technology, Harbin 150090, P. R. China.
College of Environment and Ecology, Chongqing University, Chongqing 400045, P. R. China.
ACS Omega. 2022 Sep 9;7(37):33482-33490. doi: 10.1021/acsomega.2c04382. eCollection 2022 Sep 20.
Designing economical and nonprecious catalysts with a catalytic performance as good as that of noble metals is of great importance in future renewable bioenergy production. In this study, the metal-organic framework (MOF) was applied as a precursor template to synthesize CoO nanoparticles with a carbon matrix shell (denoted as M-CoO). To select the synthesized optimal catalyst, stearic acid was chosen as the model reactant. The effects of catalyst dosage, methanol dosage, water dosage, temperature, and reaction time on catalytic efficiency were examined. Under the designed condition, M-CoO exhibited high catalytic performance and the catalyst showed higher conversion of stearic acid (98.7%) and selectivity toward C8-C18 alkanes (92.2%) in comparison with Pt/C (95.8% conversion and 93.2% selectivity toward C8-C18). Furthermore, a series of characterization techniques such as scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), nitrogen adsorption isotherms (Brunauer-Emmett-Teller (BET) method), and thermogravimetric analysis (TGA) was applied to investigate the physicochemical properties of the catalysts. Finally, we proposed that decarbonization (deCO) could be the presumably mechanistic pathway for the production of C8-C18 alkanes from the decomposition of stearic acid.
设计出具有与贵金属相当催化性能的经济且非贵金属催化剂,对于未来可再生生物能源生产至关重要。在本研究中,金属有机框架(MOF)被用作前驱体模板,以合成具有碳基质壳层的CoO纳米颗粒(记为M-CoO)。为了筛选出合成的最佳催化剂,选择硬脂酸作为模型反应物。考察了催化剂用量、甲醇用量、水用量、温度和反应时间对催化效率的影响。在设计条件下,M-CoO表现出高催化性能,与Pt/C(转化率95.8%,对C8-C18的选择性93.2%)相比,该催化剂对硬脂酸的转化率更高(98.7%),对C8-C18烷烃的选择性更高(92.2%)。此外,还应用了一系列表征技术,如扫描电子显微镜(SEM)、高分辨率透射电子显微镜(HRTEM)、X射线粉末衍射(XRD)、X射线光电子能谱(XPS)、氮吸附等温线(布鲁诺尔-埃米特-泰勒(BET)法)和热重分析(TGA)来研究催化剂的物理化学性质。最后,我们提出脱碳(deCO)可能是硬脂酸分解生成C8-C18烷烃的推测反应机理途径。