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用饱和浸渍法把ＦｅＳＯ４ 直接担载于山东兖州和山西汾西两种烟煤上． 在实验的基础上，结合人工神经网络模型考察了ＦｅＳＯ４ 浸渍量、反应温度和反应时间对烟煤液化行为的影响，并通过ＸＲＤ和热力学计算探索了ＦｅＳＯ４ 在煤直接液化反应中可能发生的化学形态变化． 结果表明，训练完全的人工神经网络不仅可较好地拟合实验结果，而且可较好地预报反应条件对ＦｅＳＯ４ 催化活性的影响．ＦｅＳＯ４ 在煤液化反应时存在着临界浸渍量，当铁含量大于１－０ ％ 时，其值对液化结果影响不大； 煤直接液化反应存在着最佳反应温度，兖州煤为４１０ ℃左右，而汾西煤难以裂解，反应最佳温度为４３０ ℃； 在ＦｅＳＯ４ 催化条件下，兖州煤在４００ ℃反应４０ ｍｉｎ 以前即可达到较大程度的加氢液化，而汾西煤在４５０ ℃反应１ ｈ 以后才能达到较好的加氢效果．ＸＲＤ和热力学计算结果表明：ＦｅＳＯ４ 只有在煤中各种形态硫的作用下，才能转变为Ｆｅ１ － ｘＳ， 起到催化作用．
FeSO4 was loaded directly on two kinds of bituminous coal, Yanzhou, Shandong and Fenxi, Shanxi by saturated impregnation method. On the basis of experiments, the effects of FeSO4 impregnation, reaction temperature and reaction time on the liquefaction behavior of bituminous coal were investigated based on the ANN model. The possible chemical morphological changes of FeSO4 in direct coal liquefaction were investigated by XRD and thermodynamic calculations . The results show that the trained artificial neural network can not only fit the experimental results well, but also predict the effect of reaction conditions on the catalytic activity of FeSO4. When the iron content is more than 1-0%, the value of FeSO4 has little effect on the liquefaction results. There is the optimal reaction temperature for direct liquefaction of coal, and Yanzhou coal is about 410 ℃ Fenxi coal is difficult to be cracked, and the optimal reaction temperature is 430 ℃. Under FeSO4 catalytic conditions, Yanzhou coal can reach a large degree of liquefaction liquefaction before reaction at 400 ℃ for 40 min, while Fenxi coal reacts at 450 ℃ for 1 h After to achieve better hydrogenation effect. The results of XRD and thermodynamic calculations show that FeSO4 can be transformed into Fe1 - xS only under the action of various forms of sulfur in coal, which play a catalytic role.