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：

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Pd/Al2O3催化剂加氢5-甲基-3-己烯-2-酮制备5-甲基-2-己酮的机理见解


5-甲基-2-己酮用作多功能聚合溶剂，用于散装和精细化学品的工业制备过程。据报道，一种高效的催化剂 Pd/γ-AlO 用于通过 5-甲基-3-己烯-2-酮的选择性加氢制备 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著的活性和选择性。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、反应温度和液体小时空速。研究了 Pd/γ-AlO 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到 5-甲基-3-己烯-2-酮的加氢反应途径，揭示了 CC 双键和 CO 双键的选择性加氢机理。还提出了一个基于 LHHW 模型假设的动力学模型，并与实验结果进行了比较，显示出良好的可预测性。