目的 在奥氏体不锈钢锅炉管内壁制备抗高温蒸汽氧化涂层。方法 采用料浆法在锅炉过/再热器用小口径Super304H不锈钢锅炉管内壁制备铝化物涂层，研究了钢管热处理制度范围内制备工艺（时间、温度）对涂层结构、成分和相组成的影响规律，同时基于扩散定律建立了涂层结构的预测模型。结果 铝化物涂层厚度约为30~150 μm，与基体冶金结合良好。涂层为双层结构，外层由(Fe,Ni)Al(Cr)相、CrxSiy相以及少量Fe3Al相组成，互扩散层（IDZ）由(Fe,Ni)Al相、CrxSiy相、点状M6C碳化物相和针状TCP相组成。涂层的制备温度和保温时间对互扩散层厚度变化影响显著，其随时间和温度的变化曲线近似满足抛物线规律。管材热处理制度范围内的温度过高，易减小涂层外层厚度。结论 在匹配Super304H锅炉管热处理工艺的基础上，采用料浆法在小口径Super304H锅炉管内壁获得了双层结构的铝化物涂层。基于Fick第二扩散定律建立了涂层结构控制的预测模型，拟合结果与实验实测数据吻合较好，可为获得不同结构的涂层提供参考。

The work aims to prepare the high-temperature resistant steam oxidation coating on the inner surface of austenitic stainless steel boiler tube. Al-Si slurry deposition process was employed to prepare aluminide coatings on the inner surface of Super304H boiler tubes used on overheater and reheater. The effects of process parameters (time and temperature) on the structure, composition, phase composition and atomic diffusion of the coatings were studied within the scope of the heat- treatment on steel tube. Meanwhile, a prediction model of coating microstructure was established based on the Fick’s diffusion law. The aluminide coating had a thickness of about 30~150 μm and showed good metallurgical bonding properties with the substrate. The coating had a two-layer structure, with an outer layer of (Fe,Ni)Al(Cr) phase, CrxSiy phases and a little Fe3Al and IDZ of (Fe,Ni)Al phase, CrxSiy phase, spotted M6C phase and needle-like TCP phase. The thickness of IDZ was significantly affected by the temperature and holding time. The thickness variation of this layer followed parabolic law with the holding time and the temperature. Besides, an excessive temperature within the heat treatment regime of tubes could easily reduce the thickness of outer layer. Aluminized coatings are successfully prepared on the inner surface of Super304H austenitic stainless steel boiler tube depending Al-Si slurry deposition process on the basis of matching Super304H boiler tube heat treatment process. A prediction model of coating microstructure control is established based on the Fick‘s second diffusion law. The prediction results are in good accordance with the experimentation results and can provide a reference for preparing the coatings with different microstructures.