## 1 Introduction  
As the world develops under the COVID-19 pandemic in recent years, all walks of life are accelerating their digital transformations, accompanied by a rapid development of information technologies such as the Internet of things, cloud computing and big data. Due to a work-from-home economy, cloud services are constantly soaring in the IT industry, especially in the hyper-scale enterprises. Statistically, the number of global Internet users is expected to increase from 3.7 billion in 2018 to 5 billion in 2025 [1], which means that modern society is entering the era of a digital economy. The global digitalization market size is expected to grow from USD 594.5 billion in 2022 to USD 1548.9 billion by 2027, at a compound annual growth rate (CAGR) of 21.1% according to MarketsandMarkets [2]. Moreover, an explosively developing technology, ChatGPT, may also greatly promote the digitalization in the future. The urgency and inevitability of digital transformation requires massive data to be processed, which creates many difficulties in the development of powerful chips, system design, thermal management, etc. Since it was launched a few months ago, ChatGPT has received more than billions of computing requests such that OpenAI has been forced to introduce queuing systems and other traffic-shaping measures [3], which means that its ability to process data is still limited, even though a high-performance network cluster with more than 10,000 GPUs has been adopted [4,5]. Thus, improving the capacity and efficiency of processing data is a key project for the development of data centers, which are the main supporters of massive data. However, a larger amount of data always means bigger data centers and power consumption is also greater. For most data centers, cooling systems account for the largest proportion of power consumption. Thus, good thermal management is an important means to maintain the safe and reliable operation of data centers. Under this background, the thermal management of data centers faces the dual challenges of \"quality\" and \"quantity\". From the perspective of \"quality\", with the massive growth in the scale of data generated through cloud computing, data centers need to use higher-performance processors to cope with greater computing power demands. Driven by innovative achievements such as 3D integration and heterogeneous integration [6], the miniaturization and structural complexity of chip components are the inevitable trends that will lead to a continuous increase in the heat flux of chips. How to effectively and stably control chip temperatures under extremely high heat fluxes is a huge challenge for the thermal management of the chips in data centers. From the perspective of \"quantity\", according to Forbes' report, the total power consumption of data centers reached 416 tWh in 2017, accounting for 3% of the world's total power consumption [7]. Some studies predict [8] that the total power demand of information and communication technology (ICT) will account for 20.9% of global power consumption in 2030, and that the power consumption of data centers will account for 1/3 of ICT, that is, 7-8% of global power consumption. Furthermore, nearly 40% of the total energy consumption of data centers is used by cooling systems [9]. How to reduce the energy consumption of cooling systems and improve their power usage effectiveness (PUE) is another major challenge for data centers. Hence, it can be implied that most IT enterprises are expected to have energy-efficient data center solutions, and liquid immersion cooling technology has been regarded as a promising solution for the thermal management of data centers, due to its relatively simple mechanisms, low risks of hotspots, high heat dissipation efficiency, well temperature uniformity, free noise and dust pollution, great integration and high reliability, etc. [10, 11, 12, 13, 14, 15, 16, 17, 18, 19].