5-methyl-2-hexanone is used as a versatile polymerization solvent for industrial preparation processes of bulk and fine chemicals. An efficient catalyst, Pd/γ-AlO, is reported for the preparation of 5-methyl-2-hexanone by selective hydrogenation of 5-methyl-3-hexen-2-one. The catalyst exhibits remarkable activity and selectivity even at atmospheric pressure and low temperature (1 atm, 80 °C). The influence weight of reaction conditions on the reaction process was obtained through the Artificial Neural Network model, which were reaction pressure, reaction temperature and liquid hourly space velocity in order. The reaction kinetics and mechanism of 5-methyl-2-hexanone preparation by hydrogenation over Pd/γ-AlO catalyst were investigated. The hydrogenation reaction pathway of 5-methyl-3-hexen-2-one was obtained by using Density functional theory calculations, and the mechanism of selective hydrogenation of CC double bonds and CO double bonds was revealed. A kinetic model based on the LHHW model assumption was also proposed and compared with experimental results demonstrating good predictability.

中文翻译：

---

Pd/Al2O3催化剂下5-甲基-3-己烯-2-酮加氢制备5-甲基-2-己酮的机理研究


5-甲基-2-己酮用作散装和精细化学品的工业制备过程中的通用聚合溶剂。据报道，一种有效的催化剂 Pd/γ-Al2O3 可用于通过 5-甲基-3-己烯-2-酮选择性加氢制备 5-甲基-2-己酮。即使在大气压和低温（1 atm，80 °C）下，该催化剂也表现出显着的活性和选择性。通过人工神经网络模型得到反应条件对反应过程的影响权重，依次为反应压力、反应温度和液时空速。研究了Pd/γ-Al2O催化剂加氢制备5-甲基-2-己酮的反应动力学和机理。利用密度泛函理论计算得出5-甲基-3-己烯-2-酮的加氢反应路径，揭示了CC双键和CO双键的选择性加氢机理。还提出了基于 LHHW 模型假设的动力学模型，并与实验结果进行了比较，证明了良好的可预测性。