[Objective] The self-inducing impeller reactor is a high-efficiency device for gas-liquid and gas-liquid-solid three-phase mixing. This innovative reactor offers several advantages over traditional stirred reactors, such as higher gas utilization, a simpler structure, easier operation, and superior heat and mass transfer performance. Its potential applications span a range of chemical processes, from foam flotation and bio-fermentation to hydrogenation, oxidation, alkylation, and halogenation reactions. Despite its promising capabilities, the development and scale-up of the self-inducing impeller reactor largely rely on empirical knowledge and experimental work. Therefore, there is a clear need for more fundamental research to gain a better understanding of the reactor mechanics and provide essential foundational data for its future application. [Methods] In this study, we designed and constructed a double-disk self-inducing impeller using 3D-printing. The effects of different speeds and immersion depth of the impeller on the critical impeller speed, gas holdup, and gas-liquid mass transfer performance were studied. The critical impeller speed, a key indicator of the reactor's gas dispersal capability, is defined by the minimum speed at which the first bubble appears. It is influenced by several factors, such as the impeller's shape, size, immersion depth, as well as liquid properties. [Results] The experimental results indicate that the critical impeller speed increases as the immersion depth of the impeller increases. Moreover, deviations were observed between the predicted critical speeds and those achieved during operation, which could be likely attributed to axial drifts in the critical speed. Increasing the speed of the self-inducing impeller was found to significantly improve both the gas holdup and the gas-liquid interfacial area within the system. Under the experimental conditions described in this work, the gas holdup varied from 0% to 10%, with bubble sizes ranging from 1 to 5 mm. An automated platform based on LabVIEW was established to measure the mass transfer coefficient of hydrogen in tetrahydrofuran, achieving optimal gas-liquid mass transfer coefficients between 0.08 to 0.17 s^-1 for a liquid volume of 1.2 L. Furthermore, a dimensionless correlation was fitted to predict the k_La for the self-inducing impeller reactor, offering valuable guidance for reactor scaling-up. The results show that fitting data closely aligns with the experimental data. Finally, we explored the kinetics of the progesterone hydrogenation reaction within a self-inducing impeller reactor and conducted simulations using the Dynochem software based on the experimental data. These simulations indicated that variations in the mass transfer coefficients, specifically at 0.08/s and 0.8/s, do not significantly affect the reaction outcomes. This observation suggests that the mass transfer rate greatly exceeds the reaction rate (R_rxn/R_mt<10%). [Conclusions] In summary, this study successfully established an online automated research platform for a self-inducing impeller reactor. This innovative platform facilitated the evaluation of the reactor performance, focusing on crucial parameters such as critical speed, power consumption, gas holdup, bubble size, and mass transfer coefficient. Additionally, experiments and simulations were conducted on a small scale, specifically focusing on a progesterone hydrogenation reaction. These investigations provided preliminary insights into the effective scale-up of the reactor, laying a solid foundation for further analysis and development.