# Two-phase thermosiphon cooling in data centers: a comprehensive review of refrigerants for practical selection

Ahmed G Rahma, Frédy Abadassi, Jiyan Akyol, Abderahmane Marouf, Pierre François, Fabrice Lawniczak, Abdellah Ghenaim, Yannick Hoarau, Constanze Bongs, Michael Kauffeld, et al.

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Ahmed G Rahma, Frédy Abadassi, Jiyan Akyol, Abderahmane Marouf, Pierre François, et al. Two-phase thermosiphon cooling in data centers: a comprehensive review of refrigerants for practical selection. Journal of Engineering and Applied Science, 2025, 72, 10.1186/s44147-025-00833-3. hal-05423167

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# Two-phase thermosiphon cooling in data centers: a comprehensive review of refrigerants for practical selection

Ahmed G. Rahma<fnref n="1" />* , Frédy Abadassi<fnref n="2" />, Jiyan Akyol<fnref n="3" />, Abderahmane Marouf<fnref n="1" />, Pierre François<fnref n="1" />, Fabrice Lawniczak<fnref n="1" />, Abdellah Ghenaim<fnref n="2" />, Yannick Hoarau<fnref n="1" />, Constanze Bongs<fnref n="3" />*, Michael Kauffeld<fnref n="3" />* and Denis Funfschilling<fnref n="1" />*

**Abstract**

Data centers (DCs) play a crucial role in supporting artificial intelligence (AI), online platforms and cloud services. Currently, there are approximately 5 billion users worldwide, and this number is expected to grow by 5% annually. This surge will result in a substantial increase in energy consumption and will push us to reconsider appropriate energy management strategies. Two-Phase Thermosiphon (TPT) systems provide effective cooling for DCs through the natural circulation driven by gravity and the phase change of refrigerants. This process facilitates efficient heat transfer without the need for moving components, resulting in improved reliability and energy efficiency, which makes them well-suited for medium to high-density power applications. This paper presents a theoretical and practical in-depth review of common refrigerants used in TPT systems and evaluated them in terms of thermal capacity, operating conditions, geometrical design limitations, environmental impact, health and safety considerations, and international regulations. To synthesize the evaluation of the theoretical comparison findings, a decision matrix was developed to assess the overall suitability of selected refrigerants across all criteria. Water ranked highest, achieving an outstanding score of 89 out of 90, followed by methanol, ammonia, and ethanol with 58.5, 56.5, and 56, respectively. Other natural refrigerants such as pentane and 2-methylbutane demonstrated moderate suitability. In contrast, several alternatives received significantly lower scores due to safety concerns or unfavorable environmental characteristics. Based on in-practice comparisons, water exhibits higher thermal conductance, greater heat capacity, and enhanced thermal stability than many refrigerants commonly employed in TPT systems across a range of operating conditions.

**Keywords** Data centers (DCs), Two-phase thermosiphon (TPT), Refrigerants selection, Decision matrix, Thermal performance

<figure><img src="image_3.png" /></figure>

<footnote>*Correspondence:</footnote>

<footnote>Ahmed G. Rahma</footnote>

<footnote>arahma@unistra.fr</footnote>

<footnote>Constanze Bongs</footnote>

<footnote>Constanze.Bongs@h-ka.de</footnote>

<footnote>Michael Kauffeld</footnote>

<footnote>michael.kauffeld@h-ka.de</footnote>

<footnote>Denis Funfschilling</footnote>

<footnote>dfunfschilling@unistra.fr</footnote>

<footnote n="1">¹Université de Strasbourg, CNRS,
ICUBE UMR 7357, Strasbourg
67000, France</footnote>

<footnote n="2">²INSA Strasbourg, CNRS, ICUBE UMR
7357, Strasbourg 67000, France</footnote>

<footnote n="3">³HKA, Hochschule Karlsruhe –
University of Applied Sciences,
Karlsruhe 76133, Germany</footnote>
Introduction

Data centers (DCs) are specialized facilities for storing and managing vast amounts of data using servers, storage devices, and networking hardware [1]. They need a significant amount of electrical power and cooling capacity to ensure continuous performance [2]. They play a crucial role in powering artificial intelligence (AI), online platforms, cloud services, and various other digital applications, especially with the rapid growth in global internet usage. The number of users is projected to grow by approximately 5% per year, with a global estimation indicating an increase from 3.7 billion in 2018 to around 5 billion by 2025 [3]. The projected growth in internet users, along with the corresponding increase in the number of data centers and their energy consumption, has been anticipated for several years, particularly with the rapid expansion of AI in daily life. The International Energy Agency (IEA) estimated in 2025 that energy consumption by data centers could reach 945 terawatt-hours (TWh) by 2030. This prediction is in line with the corresponding growing demands, driven by the expansive use of AI and other emerging technologies [4, 5]. In 2019, data centers (DCs) consumed approximately 200 TWh of electricity, accounting for 1% of the world's total electricity usage and 10% of the overall energy consumption within the information and communications technology sector [6, 7]. By 2024, the energy consumption of DCs worldwide had significantly increased compared to 2019, reaching approximately 415 TWh, or about 1.5% of global electricity consumption [5]. Recent advancements in data processing have significantly increased the rated power of servers, growing from 1 kW to about 20 kW per rack [8, 9]. Correspondingly, the heat flux produced by these servers has escalated roughly 20-fold compared to two decades ago [10]. Data indicates that the energy intensity of DCs is at least 100 times higher than that of conventional office buildings [7, 11, 12]. This increasing reliance on DCs underscores the urgent need for efficient energy management to ensure sustainable growth in the digital era.

The operation of Central Processing Units (CPUs) requires significant electrical power, a significant part of which is dissipated as heat. In data centers, a considerable amount of the total electrical power is additionally consumed by cooling systems such as fans, air conditioners, pumps, and ventilation units [13, 14]. This generated heat must be promptly and effectively dissipated; otherwise, it can lead to heat accumulation, risking server overheating and compromising safe operation [15]. Therefore, beside the IT equipment's energy usage, the cooling accounts for approximately 40% of the overall power consumption, as shown in Fig. 1 [16]. The majority of the heat generated in DCs originates from the CPUs and GPUs. The amount of power it dissipates varies based on factors such as its size, architecture, workload intensity, and operational efficiency. Higher computational demands lead to increased power consumption, directly influencing the thermal output within the system. The power consumption of processors varies significantly depending on the categories, reflecting their intended use cases [17]. High-performance processors, built for AI, cloud, and high-performance computing, demand the highest power, ranging from 225 W to 500 W, with the highest-end models exceeding 500 W due to increased core counts and workload intensity [17]. As computing power increases, so does energy consumption, making efficient thermal management essential for DCs. Traditional cooling methods in DCs primarily rely on Computer Room Air Conditioning (CRAC) units, which employ vapor compression refrigeration systems along with a cold/hot aisle layout. In this arrangement, cold air is delivered by
<figure><img src="image_4.png" /><figcaption>**Fig. 1** Identification of energy usage in different sections of data centers [16]</figcaption></figure>

the CRAC units through perforated tiles in a raised floor, allowing it to absorb heat produced by the server racks [18]. The warmed air is then expelled from the back of each rack and returned to the CRAC units, where it is cooled and recirculated. This configuration effectively minimizes the mixing of hot and cold air, improving cooling efficiency and extending the lifespan of the equipment. Despite their effectiveness, CRAC systems present some challenges, such as elevated noise levels and higher energy consumption by fans and pumps [19, 20]. These factors can compromise system reliability and lead to a big carbon footprint [21]. In response to these concerns, new energy-efficient cooling technologies have emerged, attracting considerable interest as more sustainable solutions [22–24].

Energy-efficient cooling technologies are essential for decreasing overall energy consumption in DCs, with three prominent methods: free cooling, liquid cooling, and two-phase cooling, as shown in Fig. 2. Free cooling takes advantage of ambient air, oil bath or water to reduce dependence on mechanical cooling systems; however, its effectiveness is influenced by external environmental conditions, making it less efficient in hotter climates. The free cooling methods and their performance criteria have been comprehensively discussed by Zhang et al. (2014) [23]. Liquid cooling, which utilizes cold plates or immersion methods, is particularly beneficial for high density configurations due to its excellent heat transfer properties, but it necessitates a more complex infrastructure [25]. Liquid cooling and liquid free cooling primarily differ in their liquid circulation mechanisms. In liquid cooling systems, circulation is actively driven by an external pump, whereas in liquid free cooling, the flow is induced passively by the system's inherent hydraulic inertia, eliminating the requirement for any external driving force. Two-phase cooling employs phase-change processes, such as heat pipes, thermosiphons, two-phase cold plates, and two-phase immersed liquid cooling, to manage heat efficiently by
<figure><img src="image_5.png" /><figcaption>**Fig. 2** Various energy-saving cooling technologies for DCs</figcaption></figure>
exploiting the latent heat of vaporization, thereby minimizing energy consumption [26]. These systems can maintain uniform temperatures across high-power devices; however, in extremely high-temperature conditions, additional cooling mechanisms may be required to ensure thermal stability [9]. Two-phase cooling is a way to move heat from the CPU to a secondary circuit. It is very efficient for removing intense heat because it uses the latent heat of the fluid, which is considerably higher than the sensible heat used in liquid cooling. Also, the secondary heat exchanger can be much larger, because the steric hindrance on this secondary heat exchanger is much lower than on the CPU, where the steric hindrance is very high. Each of these technologies plays a vital role in enhancing energy efficiency in DCs, improving key metrics like Power Usage Effectiveness (PUE) [23] and Energy Savings Rate (ESR) [27].

Studies have shown that heat pipes and two-phase thermosiphons can substantially reduce energy consumption, achieving an ESR of up to 38.7% [26]. Among energy-efficient cooling solutions for data centers, passive two-phase cooling systems are particularly favored because they eliminate the need for mechanical components, thereby optimizing energy use [23]. Heat pipes and two-phase thermosiphons (illustrated in Fig. 2) are representative examples, as they rely on natural forces such as gravity or capillary action to circulate the coolant. By eliminating mechanical circulation, these systems reduce both energy consumption and operational costs, positioning them as highly effective and promising cooling technologies for modern data centers [28, 29].

Two-phase thermosiphon (TPT) systems serve as intermediate heat exchangers capable of transferring medium to high power densities directly to a free cooling source (such as ambient air) or to another loop for heat recovery [30–32]. Other high-density cooling methods, such as single-phase and two-phase cold plates and immersion cooling systems, rely on closed loops with specific working fluids. Single-phase cold plates typically use treated water or water-glycol mixtures to absorb heat through sensible heat capacity, whereas two-phase cold plates and two-phase immersion systems exploit the latent heat of low-boiling dielectric fluids. These systems transfer the absorbed heat to an external loop, most often operating on a vapor compression cycle, which increases the overall electrical consumption. In contrast, TPT systems act as intermediate heat exchangers that can reject heat directly to an free cooling source (such as ambient air) or to another loop for heat recovery, providing a more energy-efficient pathway for thermal management.

The TPT systems are mainly divided into two types: the Two-Phase Closed-Pipe Thermosiphon (TPCT) and the Two-Phase Loop Thermosiphon (TPLT), as shown in Fig. 3. The TPCT consists of a sealed hollow tube closed at both ends and divided into three sections: the evaporator at the bottom, the adiabatic section in the middle, and the condenser at the top. In contrast, the TPLT features a looped configuration in which the evaporator and condenser are separated into distinct sections, known as the riser and the downcomer, as shown in Fig. 3. Both systems can be implemented as standalone solutions for data center cooling. To minimize thermal losses, the evaporators of the TPCT and TPLT can be directly attached to the CPU, a configuration referred to as on-chip level cooling in data centers. In this setup, the condenser section is connected to a heat exchanger to transfer the extracted heat outside the data center room, as shown in Fig. 3. This heat exchanger attached to the TPCT or TPLT may be significantly larger than the evaporator directly attached to the CPU, which must extract heat efficiently
<figure><img src="image_6.png" /><figcaption>**Fig. 3** Schematic illustration of the complete data center rack cooling configuration and the detailed layout of a single unit for (a) TPCT and (b) TPLT</figcaption></figure>

while being sterically hindered. For heat recovery applications and energy reduction, the 2PhaseEx project aims to utilize heat recovery loop to cool the system while reusing the heated refrigerant for domestic purposes, such as underfloor heating, radiator systems and similar applications (Fig. 3) [33]. The refrigerants selection in this approach are extensive, and will be the primary focus of this review paper.

The implementation of TPT as an energy-efficient cooling technology presents multiple challenges beyond its operational optimization. A key aspect is the selection of environmentally friendly refrigerants that adhere to international regulations, including the Montreal Protocol [34], the Kigali Amendment [35], EU-F-gas Regulation [36], and PFAS Regulations [37]. In addition to reducing environmental impact and ensuring compliance with health and safety standards, the chosen refrigerants must possess adequate thermal capacity and operational efficiency while accommodating the geometric constraints of TPT systems. For TPT cooling applications, various refrigerants have been used in research applications, including n-Pentane [38, 39], HFC-365mfc, SES-36, HFE-7000, and FC-3284 [40]. Additionally, R134a has been widely referenced in studies [41–43]. Other refrigerants such as helium [44] and hydrocarbons like R600a and R290 have also been investigated for their cooling efficiency in TPT [45]. However, due to the operating temperature requirements of CPUs and the introduction of new regulations, many of these refrigerants are either not suitable or no longer suitable for on-chip cooling applications in DCs.
This paper presents a comprehensive review of the general criteria for refrigerant selection for TPT systems designed for on-chip (CPU and GPU) level cooling in data centers [46–48]. The remainder of this paper is structured as follows: Refrigerants in TPT cooling systems: theoretical considerations section presents the theoretical considerations of refrigerants used in TPT cooling systems, including a comparison of thermal capacity, global warming potential (GWP), health impacts, and optimal operating conditions. A theoretical comparison is also illustrated in the form of a decision matrix. Refrigerants in TPT cooling systems: practical consideration section discusses the practical considerations of refrigerants in TPT cooling systems, highlighting the thermal performance comparisons reported in the literature. Conclusion section summarizes the findings and offers concluding insights. This review links theory with a comparative study of different refrigerants under DC operating conditions, providing guidance for future selection.

## Refrigerants in TPT cooling systems: theoretical considerations

Various refrigerants, including water, R134a, CO₂ (R744), and others, have been explored for their effectiveness in TPT systems, as detailed in Table 1. Water consistently shows strong performance across different geometries and conditions, with optimal results at mid-inclination angles and varying filling ratios [49–53]. R134a frequently outperforms water under unstable flow conditions, showing little to no performance loss, whereas water exhibits a 5–20% reduction in performance [41–43]. CO₂ exhibits significant variability in the results, as its boiling heat transfer performance is challenging to predict accurately [54], while refrigerants like R600a, R290, and helium improve thermal resistance but face challenges such as geyser boiling at higher fill levels [44, 45]. Where geyser boiling in a two-phase thermosiphon is an unstable phenomenon, the superheated liquid rapidly produces and expands vapor, leading to sudden pressure surges that induce flow oscillations, vibrations, and possible structural stress on the pipes [55]. Overall, refrigerant selection plays a critical role in optimizing cooling system performance, and the selection involves various criteria such as thermal capacity, operational conditions, GWP, health impacts, safety (flammability and toxicity), and regulatory compliance.

In the current TPT applications, some refrigerants reported in the literature are unsuitable due to their specific limitations. Helium (R704) requires extremely low temperatures (5.2 K) to reach its supercritical state, making it impractical for data center cooling. Nitrogen (R728) demands very low temperatures (–147 °C) and high pressures (3.39 MPa), which are challenging to maintain under operational conditions. Carbon dioxide (CO₂, R744) is not recommended because its critical temperature is 31 °C, which is below typical CPU operating temperatures, making it unsuitable for this application. For these refrigerants, the critical point lies far below the desired operating range of the CPU, as CPU temperatures could be remain above 40 °C [74]. Collectively, these factors limit the suitability of these refrigerants for TPT applications [75, 76].

Therefore, this section will introduce several potential refrigerants suitable for use in TPT systems for on-chip DC cooling applications. The key reason for employing on-chip level cooling is that it enables a minimal temperature difference between the operating temperature of the TPT and that of the CPU [46]. This is achieved through increased direct contact, particularly in comparison to rack-level and room-level cooling systems. According to the CPU manufacturer's recommendations, the CPU temperature should
<table><caption>**Table 1** Overview of refrigerants and main findings in TPT studies</caption><thead><tr><td>Author (Year)</td><td>Approach</td><td>Refrigerant(s)</td><td>Main results/effects</td></tr></thead><tbody><tr><td>Abreu & Colle [56]</td><td>Experimental</td><td>Water</td><td>Evaporator temperature increased with a higher Filling Ratio (FR) (60% to 80%).</td></tr><tr><td>Hussein et al. [57]</td><td>Experimental</td><td>Water</td><td>Water showed optimal performance across different working fluids and geometries, good mass flow rates.</td></tr><tr><td>Abou-Ziyan et al. [42]</td><td>Experimental</td><td>R134a, Water</td><td>R134a outperformed water in reducing vibration-induced performance loss, with optimal performance at 50% fill.</td></tr><tr><td>Noie et al. [58]</td><td>Experimental</td><td>Water</td><td>Water performed best at mid-inclination angles (15–60°), with geyser boiling occurring at lower fill ratios.</td></tr><tr><td>Samanci & Berber [41]</td><td>Experimental</td><td>R134a</td><td>Two-phase R134a increased the efficiency of the TPT solar water heater by 43% compared to single-phase water.</td></tr><tr><td>Long & Zhang [44]</td><td>Experimental</td><td>Helium</td><td>Helium demonstrated decreasing thermal resistance up to an 80% fill ratio; over 100%, resistance increased due to geyser boiling.</td></tr><tr><td>Solomon et al. [45]</td><td>Experimental</td><td>R600a, R290</td><td>R600a and R290 performed better in anodized TPTs than the non-anodized TPT, reducing thermal resistance by 23% in vertical configurations.</td></tr><tr><td>Ong et al. [59]</td><td>Experimental</td><td>R410A, Water</td><td>R410A outperformed water in vertical thermosiphons; water showed better performance at lower filling ratios.</td></tr><tr><td>MacGregor et al. [60]</td><td>Experimental and theoretical</td><td>Water, Methanol, Ethylene Glycol, R134a</td><td>Water 5% ethylene glycol mixture did not perform as well as R134a in heat transfer applications.</td></tr><tr><td>Jouhara et al. [61]</td><td>Experimental</td><td>Water, Ethanol-Water</td><td>Water-Ethanol mixtures used in TPT for solar collectors showed no significant performance change at different angles.</td></tr><tr><td>Wu et al. [43]</td><td>Experimental and theoretical</td><td>R134a</td><td>R134a successfully cooled DCs with thermosiphons of up to 5 meters in length.</td></tr><tr><td>Bolozdynya et al. [62]</td><td>Experimental</td><td>Nitrogen</td><td>Nitrogen-operated TPT worked in low-temperature conditions (80-120K) with a heat transfer limit of 100W.</td></tr><tr><td>Ding et al. [54]</td><td>Theoretical</td><td>CO<sub>2</sub> (R744), R134a, R22, R410A</td><td>R744 had the highest uncertainty in performance; R134a performed best with the lowest uncertainty.</td></tr><tr><td>Ding et al. [63]</td><td>Experimental and theoretical</td><td>CO<sub>2</sub> (R744)</td><td>R744 coolant demonstrated high variability in heat transfer coefficient across different conditions.</td></tr><tr><td>Barua et al. [49]</td><td>Experimental</td><td>Water, Ethanol</td><td>Water excelled at lower heat inputs, while Ethanol performed comparably at higher inputs. Water had a higher evaporation temperature, and Ethanol showed lower thermal resistance at higher FRs.</td></tr><tr><td>Jouhara & Robinson [64]</td><td>Experimental</td><td>Water, FC-84, FC-77, FC-3283</td><td>Water had superior thermal performance over fluorinated liquids. FC-84 excelled at low power (<30 W), but water outperformed at higher power levels. FC-77 and FC-3283 faced significant declines in performance at higher power due to liquid entrainment.</td></tr><tr><td>Kyung & Lee [65]</td><td>Experimental and theoretical</td><td>R113</td><td>For R113, maximum flow rates are influenced by subcooling, pressure drops, and unstable boiling at high heat flux levels.</td></tr><tr><td>Chu et al. [66]</td><td>Experimental</td><td>Water</td><td>Water performs best at low fill levels, though unstable pulsing behavior is noted with insufficient liquid fill.</td></tr><tr><td>Na et al. [67]</td><td>Experimental</td><td>R11</td><td>For R11 the mass flow rate is determined by the size of the condenser, and achieving optimal performance requires an ideal liquid charge.</td></tr><tr><td>Pal et al. [68]</td><td>Experimental</td><td>Water, PF5060</td><td>Water demonstrated superior cooling capabilities for processors compared to PF5060, showing that its performance remained largely unaffected by orientation.</td></tr><tr><td>Mukherjee & Mudawar [69]</td><td>Experimental and theoretical</td><td>Water, FC-72</td><td>Under saturated conditions, both water and FC-72 exhibited comparable performance, although some fluctuations were observed.</td></tr></tbody></table>
<table><caption>**Table 1 (continued)**</caption><thead><tr><td>Author (Year)</td><td>Approach</td><td>Refrigerant(s)</td><td>Main results/effects</td></tr></thead><tbody><tr><td>Honda et al. [70]</td><td>Experimental</td><td>FC-72</td><td>FC-72 experienced notable variations in mass flow rates at varying loop heights, specifically between 250 mm and 450mm.</td></tr><tr><td>Khodaban-deh & Palm [71]</td><td>Experimental and theoretical</td><td>R600a</td><td>For R600a, the heat transfer coefficients were found to rise as the diameter of the evaporator channels decreased.</td></tr><tr><td>Huo et al. and Chen et al. [72, 73]</td><td>Experimental</td><td>R134a</td><td>In the case of R134a, nucleate boiling was predominant at low vapor quality, with the heat transfer rate showing a strong dependence on the quality of the vapor.</td></tr></tbody></table>

remain below 85 °C. Therefore, Marcinichen et al. [74] suggested that the upper critical threshold for the TPT internal average operation temperature should not exceed 55 ° C, as this represents the saturation or operating temperature in “worst-case” scenarios. They further advised that the maximum power limit for an individual CPU (5 cm × 5 cm) should be capped at 600 W (24 W/cm²) to prevent exceeding the critical heat flux and to avoid dry-out. These reference values will guide the selection of refrigerants that not only comply with safety and environmental regulations but also ensure optimal cooling capacity.

## Thermal capacity

When selecting an appropriate refrigerant based on thermal capacity, several methodologies are commonly referenced in the literature. The most commonly employed methods in the literature include the Merit number (M) [77, 78], and the heat of vaporization ($h_{fg}$) [79].

The Merit number, often referred to as the Liquid Transport Factor or Figure of Merit, is a key parameter for evaluating the performance of working fluids in TPTs and heat pipes. While it is widely used as a standard metric for fluid selection in vapor chambers, such as heat pipes [80, 81], many researchers have also applied it to study TPTs [82, 83]. This parameter offers a qualitative approach to rank the suitability of different fluids for TPTs. A higher Merit number signifies a fluid with superior thermal performance [84, 85]. The Merit number is a function of several properties, including the liquid density $ρ_L$ (kg/m³), the surface tension $σ_{LV}$ (N/m), the latent heat of vaporization $h_{fg}$ (J/kg), and the liquid dynamic viscosity $μ_L$ (Pa s), as shown below:

$$M = \frac{\rho_L \sigma_{LV} h_{fg}}{\mu_L} \qquad (1)$$

The latent heat of vaporization ($h_{fg}$) is the energy required to transform a liquid into vapor at a constant temperature. It is essential in cooling systems like TPTs, as it determines how much heat a fluid can absorb during the phase change.

In this section, a brief overview of the thermal capacity potential of the refrigerants discussed in the literature, along with some of the recommended refrigerants for TPT applications, focusing on their latent heat of vaporization ($h_{fg}$) will be provided. Additionally, their performance will be evaluated using the Merit number, with particular attention to TPT systems, for which this value will be assessed at an operating
temperature corresponding to the upper critical threshold of 55°C, as recommended by
Marcinichen et al. [74].

In this analysis (as shown in Fig. 4a), Water exhibits the highest Merit num-
ber at 55 °C, reaching 3.11 × 10¹¹ W/m², making it the most effective among
the compared refrigerants. Ammonia (R-717) ranked second with a value of
7.91 × 10¹⁰ W/m², demonstrating strong performance. Methanol follows with a Merit
number of 4.42 × 10¹⁰ W/m², while Ethanol has a value of 2.06 × 10¹⁰ W/m². Pen-
tane, Propyne, and Cyclopropane show slightly lower performance, with Merit num-
bers of 1.85 × 10¹⁰ W/m², 1.65 × 10¹⁰ W/m², and 1.32 × 10¹⁰ W/m², respectively.
Hydrocarbons like 2-Methylbutane, n-Butane (R600), and Isobutane (R600a) have simi-
lar values, ranging from 1.41 × 10¹⁰ W/m² to 9.09 × 10⁹ W/m². Propane (R290) and
Propene fall slightly below this range, with Merit numbers of 6.08 × 10⁹ W/m² and
5.77 × 10⁹ W/m². R22 and R134a are at the lower end, with values of 7.15 × 10⁹ W/m²
and 5.11 × 10⁹ W/m², respectively, while R-410A exhibits the lowest Merit number of
1.94 × 10⁹ W/m².

In this analysis (as shown in Fig. 4b) at 55 °C, Water has the highest latent heat at 2371 kJ/kg, making it highly effective for heat transfer in thermosiphon systems. Methanol (1115 kJ/kg) and Ammonia (R717) (1024.95 kJ/kg) also demonstrate strong performance. In contrast, refrigerants such as Propyne (416.66 kJ/kg) and Cyclopropane (352.52 kJ/kg) show significantly lower values, indicating reduced efficiency. Other hydrocarbons, including Pentane (341.79 kJ/kg) and n-Butane (327.66 kJ/kg), further emphasize the trend of decreasing latent heat.

In conclusion, considering both the Merit number and the latent heat of vaporization,
water is the most effective refrigerant for thermosiphon cooling applications, excelling
in both aspects of thermal property. Methanol, Ethanol, and Ammonia (R-717) serve
as viable alternatives, offering good thermal performance when water is not a suitable
option. By analyzing the behavior of the Merit number and the latent heat of vaporiza-
tion within the CPU operating temperature range of 25 °C to 85 °C [86, 87] (Fig. 5) it
was observed that the Merit number of Water increases with temperature up to 90 °C,
showing the highest values among the compared fluids. Ammonia exhibits a sharp
decrease as the temperature increases, and at 80 °C, methanol surpasses its value. Meth-
anol exhibits a slower increase, stabilizing around 65 °C with lower values than water.
Ethanol also displays lower Merit numbers, with only a slight increase over the same
temperature range, placing it fourth in this category. Regarding latent heat of vaporiza-
tion, values slightly decrease with temperature for all fluids; however, water consistently
exhibits higher values compared to Ammonia, Ethanol, and Methanol.

Operating conditions

The operating conditions, such as the saturation pressure *p*<sub>sat</sub> (at the recommended operating temperature) and volume flow rate *V̇*, are critical for selecting refrigerants. Refrigerants are more suitable when the *p*<sub>sat</sub> is close to ambient pressure, as this helps to avoid the need for tight sealing and working away from extreme pressures what simplified the need of reinforced structure to avoid deformation which may lead to leaks. Additionally, a lower *V̇* can help reduce vibrations in the system.

The saturation or operating pressure *p*<sub>sat</sub> values for the selected working fluids are
presented in Fig. 6a at an operation temperature of 55°C. Methanol and Ethanol, with
<figure><img src="image_7.png" /><figcaption>**Fig. 4 a** The Merit number ($M$) and **b** the latent heat of vaporization ($h_{fg}$) value for the selected working fluids at 55°C</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>Fig. 5 a The Merit number ($M$) and b the latent heat of vaporization ($h_{f,g}$) value for the selected working fluids at CPU operating temperature range</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>**Fig. 6 a** The saturation pressure ($p_{sat}$) and **b** the volume flow rate ($V'$) value for the selected working fluids at 55°C and P=600 W</figcaption></figure>
saturation pressures of about 68.93 kPa (31.97% deviation to the ambient pressure) and 36.24 kPa (64.22% deviation), respectively. Pentane, while slightly higher at 185 kPa, still demonstrates a significant deviation of 82.94%. Water is also considered, though its specific saturation pressure was approximately 15.76 kPa with pressure deviation than the atmospheric pressure of 84.45%. In contrast, refrigerants such as R410A and Ammonia (R717) exhibit saturation pressures of 3439.84 kPa and 2311.1 kPa, respectively, leading to pressures respectively of 33 and 22 times the atmospheric pressure, indicating the need for robust sealing in data center cooling applications

By examining the required volume flow rate in the evaporator $\dot{V}$ to absorb the maximum power ($P$) limit for an individual CPU (5 cm × 5 cm), which should be capped at $P=600$ W (24 W/cm²) as suggested by [74], the calculation can be performed as follows:

$$ \dot{V} = \frac{P}{\rho_L \cdot h_{fg}} \qquad (2) $$

The $\dot{V}$ values for the selected working fluids are presented in Fig. 6b. Water shows the lowest $\dot{V}$ at approximately 0.015 L/min, signifying its excellent efficiency in heat transfer applications. Methanol, Ethanol, and Ammonia (R-717) exhibit slightly higher $\dot{V}$ values of 0.042 L/min, 0.053 L/min, and 0.063 L/min, respectively. Meanwhile, the other refrigerants exhibit values higher than 0.15 L/min. This trend indicates that as the working fluid shifts from more efficient refrigerants, such as water and methanol, to less efficient ones, such as R-410A, the required volume flow rates become considerably larger. The low vapor density of water and methanol made them suitable only for systems of limited height such as those used in local cooling units, as the one presented in Fig. 3.

In conclusion, in terms of operating conditions, specifically saturation pressure $p_{sat}$ and Volume flow rate $\dot{V}$, Water, Methanol, and Ethanol are the most suitable refrigerants for thermosiphon cooling applications, excelling in both areas. By analyzing the behavior of the saturation pressure within the CPU operating temperature range of 25 °C to 85 °C [86, 87] (Fig. 7), it was observed that water has the lowest saturation pressure compared to Ethanol and Methanol. For the same temperature range and the recommended CPU power input (25 W to 600 W) [17, 74], the required volume flow rate for water is significantly lower compared to ethanol and methanol, as illustrated in Fig. 8.

## Geometry limitation

The critical diameter determines the range in which two-phase flow boiling or slug flow can exist in thermosiphon systems. These limits depend on the properties of the fluid and gravity, and are expressed through the Bond number and the capillary length $L_B$. The minimum critical diameter $d_{crit, min}$ represents the smallest tube diameter that allows for two-phase flow boiling or slug flow, and is mainly influenced by surface tension ($\sigma$) [88]:

$$ d_{\text{crit, min}} \approx 2\sqrt{\frac{\sigma}{g(\rho_L - \rho_V)}} = 2L_B \qquad (3) $$

The maximum critical diameter $d_{crit, max}$ defines the upper limit of the tube diameter, beyond which two-phase flow does not occur and we will have only pool boiling [88]. As in two-phase flow boiling, liquid circulation enhances convective heat transfer and facilitates continuous vapor removal along the flow path. However, when the
<figure><img src="image_10.png" /><figcaption>**Fig. 7** The saturation pressure ($p_{sat}$) value for the selected working fluids at CPU operating temperature range</figcaption></figure>
<figure><img src="image_11.png" /><figcaption>**Fig. 8** The volume flow rate (V') values for a Water, b Ethanol, and c Methanol at CPU operating temperature and powers ranges</figcaption></figure>
buoyancy-driven circulation becomes insufficient, the system transitions to pool boiling, where heat transfer depends only on natural convection and surface nucleation, leading to reduced performance. The critical diameter is given by:

$$d_{\text{crit, max}} \approx 19 \sqrt{\frac{\sigma}{g(\rho_L - \rho_V)}} = 19L_B \quad (4)$$

These expressions help in defining one of the geometrical limitations and selecting suitable tube dimensions to ensure efficient thermosiphon operation. Therefore, this section provides a comprehensive investigation of the diameter interval for the design, as it primarily depends on the working fluid, highlighting which fluid will offer a wider range of suitable diameters for current applications.

Figure 9 presents the critical diameter intervals for various refrigerants at 55 °C, detailing the minimum critical diameter ($d_{\text{crit, min}}$), maximum critical diameter ($d_{\text{crit, max}}$), and the corresponding diameter interval for each selected working fluid. A larger diameter interval indicates better design availability limits, which is crucial for optimizing system performance and ensuring reliability. Among the refrigerants, water exhibits the widest diameter interval of approximately 44.80 mm, with a minimum critical diameter of 5.27 mm and a maximum of 50.07 mm, making it particularly suitable for thermosiphon applications. Following closely are Methanol and Ethanol, with diameter intervals of 27.66 mm and 27.64 mm, with a minimum critical diameter of 3.25 mm for both and a maximum of 30.91 mm and 30.89 mm, respectively, serving as effective alternatives, providing wide design diameter intervals when water is not suitable. Ammonia (R717) presents a similar interval of approximately 27.56 mm. In contrast, refrigerants like R410A show a significantly narrower diameter interval of only about 7.80 mm, with a minimum critical diameter of 0.92 mm and a maximum of 8.72 mm.

In conclusion, in terms of critical diameter intervals, Water, Methanol, and Ethanol demonstrate the widest ranges, making them the most suitable refrigerants for thermosiphon cooling applications, as they provide greater design tolerance and operational flexibility. By analyzing the behavior of the critical diameter intervals within the CPU operating temperature range of 25 °C to 85 °C [86, 87] (Fig. 10), it was observed that water exhibits the largest range between the critical maximum and minimum values across the entire temperature span. Ethanol and Methanol also show approximately the same range of intervals.

## Environmental impact

The environmental effects of refrigerants are mainly assessed through two metrics: Global Warming Potential (GWP) and Ozone Depletion Potential (ODP). GWP quantifies the total heat-trapping effect of a substance released into the atmosphere relative to an equivalent mass of carbon dioxide ($CO_2$) over a specified time horizon, typically 100 years. $CO_2$ serves as the reference gas and is assigned a GWP of 1. ODP represents the relative ability of a chemical to destroy stratospheric ozone compared to CFC-11 (R11), which is set to have an ODP 1. Most regulated compounds, including CFCs and HCFCs, have ODP values between 0 and 1, while some highly destructive bromine-containing compounds, such as Halons, can exceed 1 due to bromine's greater effect on ozone depletion.
<figure><img src="image_12.png" /><figcaption>**Fig. 9** The design diameter interval including the maximum $d_{crit}$, max and minimum $d_{crit}$, min critical diameter values for the selected working fluids at 55°C</figcaption></figure>
<figure><img src="image_13.png" /><figcaption>**Fig. 10** The design diameter interval including the maximum *d*<sub>crit, max</sub> and minimum *d*<sub>crit, min</sub> critical diameter values for the selected working fluids at CPU operating temperature range</figcaption></figure>
In addition to GWP and ODP, environmental concerns related to PFAS (Per- and Poly-fluoroalkyl Substances) and their degradation products, particularly trifluoroacetic acid (TFA, $CF_3COOH$), should also be considered. Many modern fluorinated refrigerants, including HFOs and HFCs, are classified as PFAS or degrade into PFAS compounds. Atmospheric degradation of these refrigerants, designed to reduce GWP, can lead to TFA formation, with some compounds such as HFO-1234yf converting 100% into TFA. TFA is highly water-soluble and accumulates in surface water, groundwater, and drinking water, as conventional treatment methods are largely ineffective. Due to its extreme persistence, TFA concentrations are increasing globally, posing regulatory and ecotoxicological concerns. While its toxicity is generally lower than that of other PFAS, the persistence and bioaccumulation potential of TFA highlight the importance of considering environmental impact beyond just GWP and ODP when selecting refrigerants.

In Table 2, the ODP and GWP values are presented based on data reported by the Intergovernmental Panel on Climate Change (IPCC) in its Sixth Assessment Report (AR6) [89] and the Regulation (EU) 2024/573 of the European Parliament and of the Council [90]. Certain other refrigerants, including ethanol, methanol, propyne, cyclopropane, 2,2-dimethylpropane, and 2-methylbutane, are classified as volatile organic compounds (VOCs) with very short atmospheric lifetimes, typically ranging from a few hours to several days [91]. Due to their rapid degradation in the atmosphere, their contribution to direct radiative forcing is negligible, and their GWP is conventionally considered to be approximately zero (~0) over the standard 100-year assessment period [92]. Ammonia (R717), water, ethanol, isobutane (R600a), methanol, n-butane (R600), pentane, propane, propene (R1270), propyne, cyclopropane, 2,2-dimethylpropane, and 2-methylbutane exhibit the most favorable environmental profiles, characterized by ODP and GWP values, typically close to zero, making them among the most environmentally benign refrigerant options. In contrast, synthetic refrigerants such as R11, R113, and R134a have significantly higher GWP values and are either fully phased out or are currently being phased down globally due to their environmental impacts, indicating that their use should be avoided. R11 and R113 also have high ODP values of 1 and 0.8, respectively, which contribute to ozone layer depletion. For instance, R113 has a GWP of 6520 and an ODP of 0.8, making it particularly harmful to both global warming and ozone depletion. R134a, while having an ODP of 0, still has a GWP of 1530, significantly contributing to greenhouse gas emissions. R410A and R22, despite their widespread use in the past, also pose environmental challenges. R410A has a high GWP of 2255.5, though it has an ODP of 0. R22 has an ODP of 0.05 and a GWP of 1960, making it harmful to both the ozone layer and the climate, leading to its phase-out in many regions.

## Health and safety impact

The health and safety impact of refrigerants is influenced by their toxicity, flammability, and the associated risks in handling and storage. The classification of refrigerants into groups such as A1 (Low toxicity, not flammable), A2L (Low toxicity, mildly flammable), A3 (Low toxicity, highly flammable), and B2L (Higher toxicity, mildly flammable) helps in understanding their safety profile and the precautions needed for their use [93–95].

In Table 2, Water, R11, R113, R134a, R22, and R410A fall under the A1 category, indicating low toxicity and non-flammable properties, making them relatively safe to handle. However, R11, R113, R22, and R410A have significant environmental impacts
<table><caption>**Table 2** Environmental, health, and safety impact for selected working fluids</caption><thead><tr><th>Refrigerant</th><th>ODP</th><th>GWP<sub>100yr</sub></th><th>Toxicity</th><th>Flammability</th><th>Flammability class</th><th>Health & safety considerations</th></tr></thead><tbody><tr><td>Ammonia (R717)</td><td>0</td><td>0</td><td>Toxic</td><td>Yes</td><td>B2L</td><td>High toxicity; corrosive; requires strict handling protocols.</td></tr><tr><td>Water</td><td>0</td><td>0</td><td>Non-toxic</td><td>No</td><td>A1</td><td>Safe to handle, but must be managed to avoid mold or contamination.</td></tr><tr><td>Ethanol</td><td>0</td><td>~ 0</td><td>Toxic</td><td>Yes</td><td>A3</td><td>Flammable; ingestion or inhalation can cause adverse health effects.</td></tr><tr><td>Isobutane (R600a)</td><td>0</td><td>0</td><td>Low toxicity</td><td>Yes</td><td>A3</td><td>Highly flammable; requires careful handling to avoid ignition risks.</td></tr><tr><td>Methanol</td><td>0</td><td>~ 0</td><td>Toxic</td><td>Yes</td><td>A3</td><td>Poisonous if ingested, inhaled, or absorbed through skin; flammable.</td></tr><tr><td>n-Butane (R600)</td><td>0</td><td>0.006</td><td>Low toxicity</td><td>Yes</td><td>A3</td><td>Highly flammable; can cause asphyxiation in confined spaces.</td></tr><tr><td>Pentane</td><td>0</td><td>0</td><td>Low toxicity</td><td>Yes</td><td>A3</td><td>Very flammable; risk of explosion; should be handled with care.</td></tr><tr><td>Propane</td><td>0</td><td>0.02</td><td>Low toxicity</td><td>Yes</td><td>A3</td><td>Highly flammable; explosion risk in confined areas; non-toxic.</td></tr><tr><td>Propene (R1270)</td><td>0</td><td>0</td><td>Low toxicity</td><td>Yes</td><td>A3</td><td>Flammable; can cause dizziness or asphyxiation if inhaled in large amounts.</td></tr><tr><td>Propyne</td><td>0</td><td>~ 0</td><td>Low toxicity</td><td>Yes</td><td>A3</td><td>Highly flammable; requires careful storage and handling.</td></tr><tr><td>Cyclopropane</td><td>0</td><td>~ 0</td><td>Low toxicity</td><td>Yes</td><td>A3</td><td>Flammable; used as an anesthetic but with significant handling risks.</td></tr><tr><td>2,2-Dimethylpropane</td><td>0</td><td>~ 0</td><td>Low toxicity</td><td>Yes</td><td>A3</td><td>Flammable and can cause respiratory irritation upon inhalation.</td></tr><tr><td>2-Methylbutane</td><td>0</td><td>~ 0</td><td>Low toxicity</td><td>Yes</td><td>A3</td><td>Highly flammable; can be an asphyxiant in confined spaces.</td></tr><tr><td>R11</td><td>1</td><td>6230</td><td>Low toxicity</td><td>No</td><td>A1</td><td>Not flammable, but high GWP and ODP make it environmentally harmful.</td></tr><tr><td>R113</td><td>0.8</td><td>6520</td><td>Low toxicity</td><td>No</td><td>A1</td><td>Non-flammable, but has high GWP and contributes to ozone depletion.</td></tr><tr><td>R134a</td><td>0</td><td>1530</td><td>Low toxicity</td><td>No</td><td>A1</td><td>Non-flammable but contributes significantly to global warming.</td></tr><tr><td>R22</td><td>0.05</td><td>1960</td><td>Low toxicity</td><td>No</td><td>A1</td><td>Moderately high GWP; phased out due to ozone depletion potential.</td></tr><tr><td>R410A</td><td>0</td><td>2255.5</td><td>Low toxicity</td><td>No</td><td>A1</td><td>Non-flammable but has a high GWP; used in residential A/C systems.</td></tr></tbody></table>
despite their safety in handling. Refrigerants such as Ammonia (R717) are categorized as B2L, meaning they have higher toxicity and are mildly flammable. Ammonia can pose some health risks due to its toxicity and corrosiveness, but it is also easy to detect due to its strong smell. Careful management and restricting its use to industrial-scale facilities make ammonia an interesting refrigerant fluid. Ethanol, Methanol, and most hydrocarbon refrigerants like Isobutane (R600a), n-Butane (R600), Pentane, Propane (R290), Propyne, and others fall into the A3 category, characterized by low toxicity but high flammability. While they pose a lower risk in terms of toxicity, their flammability requires careful storage, handling, and ventilation to prevent fire or explosion hazards. Methanol and Ethanol, for example, are toxic if ingested or inhaled, while the vapors of the aforementioned hydrocarbon refrigerants can be asphyxiants in confined spaces.

Overall, refrigerant such as Water offers safer handling in terms of toxicity and flammability, but hydrocarbon-based refrigerants for example Propane and Isobutane, while less toxic, necessitate stringent safety measures due to their flammability especially in large-scale applications. Hydrocarbon-based refrigerants may be appropriate for use in an Oxygen Reduction System (ORS) by decreasing the oxygen levels in the air. Typically, around 25% to 50% of the oxygen content (which translates to about 5% to 10% of the total air volume) is substituted with an equivalent volume of nitrogen. This leads to the formation of a hypoxic atmosphere with approximately 15% vol of oxygen and 85% vol of nitrogen. In such a normobaric hypoxic setting, typical materials are unable to ignite or burn when subjected to localized ignition sources of limited scale [96, 97].

## International regulations

Regulating refrigerants plays a crucial role in addressing environmental challenges related to ozone layer depletion and climate change. As outlined in Table 3, various refrigerants are subject to different regulatory statuses under international agreements, including the Montreal Protocol and the Kigali Amendment [34, 35]

Ammonia (R717), Water, Ethanol, Isobutane (R600a), Methanol, Pentane, Propene, Propyne, Cyclopropane, 2,2-dimethylpropane, and 2-Methylbutane are all classified as non-regulated, allowing for their continued usage without phase-out requirements. Conversely, Isobutane (R600a) and Propane (R290) are recognized as long-term, low-GWP (Natural Refrigerant) alternatives to HFCs, and their adoption is promoted through the Kigali Amendment's policy and funding mechanisms. In contrast, refrigerants such as R11 and R113 have been phased out due to their significant ozone depletion potential as CFCs under the Montreal Protocol. Additionally, R134a and R410A have recently been undergoing regulatory phase-out processes due to their high Global Warming Potentials. Under the EU F-Gas Regulation, R410A has already been banned in new air-conditioning and heat pump equipment from January 1, 2025, while R134a has already been banned in new vehicles since 2017 and in new commercial refrigeration systems since January 1, 2022.

## Decision matrix

The pursuit of sustainable energy solutions remains a key challenge in addressing global climate change. One promising approach involves the use of TPT for efficient cooling and thermal energy recovery. To develop feasible options for the future, these should be operated with environmentally working fluids as focused here.
<table><caption>**Table 3** Overview of international regulations on selected working fluids, including phase-out status, montreal protocol compliance, and Kigali Amendment status for refrigerants</caption><thead><tr><td>Refrigerant</td><td>Phase out</td><td>Montreal protocol status</td><td>Kigali Amendment status</td><td>Regulatory notes</td></tr></thead><tbody><tr><td>Ammonia (R717)</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Commonly used in industrial applications; has high toxicity but is not classified as an ODS or HFC.</td></tr><tr><td>Water</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Environmentally benign; not subject to any phase-out regulations.</td></tr><tr><td>Ethanol</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Generally recognized as safe, but flammable; not subject to phase-out regulations.</td></tr><tr><td>Isobutane (R600a)</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Considered a natural refrigerant with low GWP; promoted as an alternative under the Kigali Amendment.</td></tr><tr><td>Methanol</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Flammable and toxic but not subject to phase-out under environmental agreements.</td></tr><tr><td>n-Butane (R600)</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Low GWP hydrocarbon, used as a natural refrigerant alternative.</td></tr><tr><td>Pentane</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Used in insulation foams; low GWP and not subject to international phase-out agreements.</td></tr><tr><td>Propane (R290)</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Low GWP refrigerant; encouraged as an alternative under the Kigali Amendment.</td></tr><tr><td>Propene</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Used as a refrigerant in some applications; low GWP and not subject to specific phase-out timelines.</td></tr><tr><td>Propyne</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Not commonly used as a refrigerant; flammable but not regulated under phase-out agreements.</td></tr><tr><td>Cyclopropane</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Primarily used as an anesthetic; not regulated as a refrigerant.</td></tr><tr><td>2,2-Dimethylpropane</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Low GWP and not commonly regulated under environmental treaties.</td></tr><tr><td>2-Methylbutane</td><td>Not regulated</td><td>Not regulated</td><td>Not regulated</td><td>Low GWP and used in specific refrigerant blends; not subject to phase-out.</td></tr><tr><td>R11</td><td>Phased out</td><td>Phased out (1996 for developed countries)</td><td>Not applicable</td><td>CFC; phased out under the Montreal Protocol due to high ODP.</td></tr><tr><td>R113</td><td>Phased out</td><td>Phased out (1996 for developed countries)</td><td>Not applicable</td><td>CFC; phased out under the Montreal Protocol due to high ODP.</td></tr><tr><td>R134a</td><td>Ongoing</td><td>Not applicable</td><td>Phased down</td><td>High GWP HFC; targeted for gradual phase-down under the Kigali Amendment, with phase-out timelines varying by country.</td></tr><tr><td>R22</td><td>Phased out</td><td>Phased out (2020 for developing countries)</td><td>Not applicable</td><td>HCFC; phased out under the Montreal Protocol due to its ozone depletion potential.</td></tr><tr><td>R410A</td><td>Ongoing</td><td>Not applicable</td><td>Phased down</td><td>HFC blend; subject to gradual phase-down under the Kigali Amendment due to high GWP.</td></tr></tbody></table>
<figure><img src="image_14.png" /><figcaption>**Fig. 11** Decision matrix for the most commonly used refrigerants in TPT systems</figcaption></figure>
As the global future trend moves toward achieving zero carbon emissions, there is an increasing focus on energy efficiency, environmental sustainability, health, safety, and cost-effectiveness. These different aspects should be considered in the refrigerant selection for the TPT systems. Based on the in-depth classification of refrigerants in the previous section, a decision matrix is presented to outline future options for the TPT framework, excluding refrigerants that have been phased out or are currently being phased out, as shown in Fig. 11 and in Appendix.

The recommendation from the decision matrix indicates that water is achieving an outstanding total score of 89 out of 90. It received full marks across all criteria except for operational pressure. Methanol ranks second with a score of 58.5, followed by ammonia and ethanol with scores of 56.5 and 56, respectively. In the following ranking Pentane and 2-Methylbutane achieved scores of 53.5 and 52.5 out of 90, respectively. n-Butane, 2,2-Dimethylpropane, Propyne, Cyclopropane, and Isobutane obtained scores of 46.5, 45.5, 44.5, 43.5, and 40.5, respectively. Other compounds scored below 40, including Propane and Propene (both 37.5), indicating lower suitability based on the evaluation criteria.

In conclusion, water clearly stands out as the best refrigerant choice for TPT applications due to its near perfect performance across all assessed criteria.

## Refrigerants in TPT cooling systems: practical consideration

Beyond the theoretical classifications discussed in the previous section, numerous experimental and numerical studies have been conducted to evaluate the thermal behavior of refrigerants in TPT systems[61, 98]. In practical applications, Comparisons between refrigerants are performed at the same saturation temperature, ensuring that boiling initiates at this temperature. Under these conditions, Water demonstrates superior thermal conductance compared to other working fluids.

In the study by Smith et al. [99], the two-phase heat transfer characteristics of Water, Ethanol, and HFE-7000 were examined in a TPCT setup. The device was constructed from a sapphire tube measuring 500 mm in length, with an internal diameter of 8 mm and outer diameter of 10 mm. The layout included a 100 mm evaporator, a 200 mm condenser, and an adiabatic section of 180 mm between them. The applied heat flux ranged from 10–59 kW/m² for Water, 10–46.5 kW/m² for ethanol, and 12–19.5 kW/m² for HFE-7000. The system was charged with water (saturation temperature: 24.08 °C), ethanol (saturation temperature: 23.55 °C) [75], and HFE-7000 (saturation temperature: 23.66 °C) [100, 101]. These conditions ensured that the system was initialized with nearly identical saturation temperatures for all fluids. Figure 12 presents the interpolated thermal conductance of the working fluids as a function of the applied heat flux. The results indicate that across most of the power range, Water exhibits superior thermal conductance compared to ethanol and HFE-7000. However, at a low heat flux of 10 kW/m², HFE-7000 shows higher thermal conductance than Water. This behavior is attributed to the higher thermal resistance encountered by Water at low power input, which significantly decreases as the heat flux increases reported Y. cai et al. [102]. Ethanol demonstrates favorable thermal conductance performance, particularly over a wide range of heat flux values. However, when the heat flux exceeds approximately 39 kW/m², it approaches the onset of thermal failure, leading to a significant decrease in thermal conductance [102]. In contrast, Water can tolerate higher heat flux levels before entering this failure region, maintaining better thermal performance under high-power conditions.
<figure><img src="image_15.png" /><figcaption>**Fig. 12** Thermal conductance of the system using different refrigerants at various input heat flux levels, based on the experiments conducted by Smith et al. [99, 103]</figcaption></figure>

For data center cooling applications employing two-phase thermosiphon systems, n-Pentane has been widely adopted, as it operates under moderate pressures and does not require vacuum or high pressure conditions [38, 39]. Although Water theoretically provides superior thermal performance, its use in such applications remains limited due to the need for very low initial pressures, often requiring vacuum conditions [68].

Voirand et al. [104] experimentally compared n-Pentane and Water at different filling ratios and gap thicknesses (1 mm and 3 mm). The test device was a sealed rectangular container with a copper back panel holding a heat source powered up to 400 W and a transparent polycarbonate cover for visualization. The interpolated results indicate that Water exhibits significantly higher thermal conductance than n-Pentane across various filling ratios and gap thicknesses, except at low heat flux where Water remains in the high thermal resistance region [102], as illustrated in Fig. 13.

As theoretical analyses suggest that alcohols rank favorably for data center cooling applications after Water, several studies have conducted practical comparisons between alcohols, acetone, and Water under varying heat loads in TPT systems [99, 103, 105-107]. Birajdar and Sewatkar [108] conducted an experimental study on TPLT systems using Water, Methanol, Ethanol, and Acetone as low-saturation working fluids. The tests were performed at a FR of 60% with a medium adiabatic (vapor) section length. The results demonstrated that Water consistently exhibited higher thermal conductance across most heat input levels compared to the alcohol-based fluids, with the exception of the low-power region, where the alcohols performed slightly better, as shown in Fig. 14a. Interestingly, Acetone displayed thermal conductance values close to those of Water in this study, despite previous experimental findings typically reporting significantly lower conductance for Acetone when compared to Water [106, 107]. An experimental study by J. S. Kim et al. [107] investigated the performance of a TPCT using various fluids, including acetone and Water, under different FRs, angle of orientations, and heat
<figure><img src="image_16.png" /><figcaption>**Fig. 13** Thermal conductance of the system at different heat input levels for gap sizes of (a) 1 mm and (b) 3 mm, as reported in the experimental study by Voirand et al. [104]</figcaption></figure>

input levels. The results showed that Water exhibited higher thermal conductance than acetone across various orientation angles. An example of this behavior is illustrated in Fig. 14b at an inclination of 90° and FR of 25% and 75%.

The results presented in Figs. 12, 13, and 14 show that Water exhibits lower thermal conductance at low heat input but performs more effectively under high power conditions before reaching thermal failure. This behavior is linked to the transition between high and low thermal resistance regions, as well as the thermal failure region, as depicted in the heat map by Y. Cai et al. [102]. Their study was conducted using Water and R134a as working fluids in a TPLT system under different filling ratios (30% to 90%) and heat fluxes up to 390 W/cm². The system was filled with water and R-134a, with a saturation temperature set at 25 °C. The low thermal conductance observed in the previous results is primarily due to the high thermal resistance region (indicated by the dark brown in Fig. 15), which is significantly more obvious for Water compared to R134a. This region becomes bigger with increasing the FR, as higher fluid height raise the system's hydrostatic pressure. Consequently, the required saturation temperature also rises, leading to a larger temperature difference between the evaporator and condenser, which in turn reduces the thermal conductance. However, as the heat input increases, the system transitions into the low thermal resistance region, where the thermal conductance of Water
<figure><img src="image_17.png" /><figcaption>**Fig. 14** Evaluation of thermal conductance in (a) the TPLT system proposed by Birajdar and Sewatkar [108] and (b) the vertical TPCT system proposed by J.S. Kim et al. [107] using various heat input levels</figcaption></figure>
<figure><img src="image_18.png" /><figcaption>**Fig. 15** Thermal conductance and heat transfer characteristics illustration of the TPLT system developed by Y. Cai et al. [102], using Water and R134a under varying input heat flux levels and filling ratios</figcaption></figure>
surpasses that of the other fluids. Additionally, Water demonstrates the ability to sus-
tain higher power levels before reaching the thermal failure region (indicated by the light
brown area in Fig. 15). This suggests that Water is more suitable for high-power applica-
tions or systems with significant power fluctuations, such as data center cooling.

Although analytical or theoretical predictions can be insightful and valuable, certain phenomena, such as the thermal failure region, are difficult to predict without experimental investigations [39, 60, 109]. R. W. MacGregor et al. [60] performed a comparison between analytical predictions based on the ESDU (Engineering Sciences Data Unit) correlation [110] and experimental measurements on a 2200 mm TPCT with an inner diameter of 15.9 mm, using Water, R-134a, and methanol as working fluids. The ESDU correlation showed strong agreement with experimental data for Water, moderate deviation for methanol, and poor suitability for R-134a. Nevertheless, under high heat input, the thermal failure region was not easy to predict accurately for any of the three fluids, as shown in Fig. 16.

For both theoretical and experimental approaches involving pure fluids, Water demon-
strates superior thermal capacity, conductance, and overall stability. However, its ther-
mal performance can be further enhanced by using a Water–alcohol mixture, commonly
referred to as an aqueous solution [61, 98, 111]. Naresh et al. investigated the thermal
enhancement of Water–alcohol mixtures compared to pure Water by using aque-
ous solutions containing 0.1% heptanol, 2% pentanol, 0.6% hexanol, and 6% butanol as
working fluids. The results showed that these mixtures improved thermal conductance

<figure><img src="image_19.png" /><figcaption>**Fig. 16 a** Thermal conductance obtained from experimental measurements reported by R. W. MacGregor et al. [60]; **b** Thermal conductance predicted using the ESDU (Engineering Sciences Data Unit) correlation [60, 110]</figcaption></figure>
<figure><img src="image_20.png" /><figcaption>**Fig. 17** Comparison of thermal conductance between Water and other aqueous solutions at various heat input levels, based on the study by Naresh et al. [112]</figcaption></figure>

relative to pure Water under varying power inputs (Fig. 17). Among them, the heptanol–Water mixture exhibited the highest thermal conductance. Pentanol and hexanol mixtures followed, showing comparable performance. The butanol–Water mixture behaved similarly to pure Water at low power inputs but outperformed it as the power increased.

Overall, Water demonstrates superior thermal capacity and stability compared to various refrigerants used in TPT systems under different operating conditions. Furthermore, its thermal performance can be further enhanced by using Water–alcohol mixtures, which improve heat transfer characteristics. Therefore, Water remains a highly practical and effective choice as a working fluid for data center cooling applications, offering both reliability and potential for performance optimization.

## Conclusion

This paper has provided a comprehensive theoretical and practical review of refrigerant options for two-phase thermosiphon (TPT) systems in data center cooling, evaluating key factors such as thermal capacity, operating conditions, geometry limitations, environmental and health impacts, and international regulatory status. Among the refrigerants analyzed, Water consistently emerged as the most favorable choice, demonstrating superior thermal performance, broad operational flexibility, environmental safety, and regulatory compliance. Methanol and Ethanol also showed strong potential as alternatives when water is not viable, particularly in terms of operating pressure.

For the theoretical approach, Water was identified as the most effective refrigerant due to its high Merit number and latent heat of vaporization. Methanol, Ammonia, and Ethanol also performed well, especially when Water is not suitable. In terms of saturation pressure and volume flow rate, Water, Methanol, and Ethanol showed optimal performance, making them ideal candidates for the operating conditions typical in TPT systems, even water showed less in term of the operating pressure. These same three refrigerants also demonstrated the broadest critical diameter ranges, providing greater design flexibility and tolerance to geometric constraints.

From an environmental perspective, natural refrigerants like Water, Methanol, Ethanol, and Ammonia are recognized for their zero ODP and low GWP. In contrast,
synthetic refrigerants such as R-11, R-113, and R-134a have exhibited significantly higher environmental impacts and have been fully phased out or are currently being phased down globally due to these concerns. Regarding health and safety, water exhibits the safest characteristics with respect to toxicity and flammability. Hydrocarbon-based refrigerants like Propane and Isobutane, while non-toxic, require more stringent safety measures due to their flammable nature. In terms of regulation, Water, Methanol, Ammonia, Ethanol, and other natural refrigerants remain non-regulated and free from phase-out mandates, ensuring their continued availability and long-term viability.

For the in-practice approach, Water offers excellent thermal capacity and stability. Mixing it with alcohols can further improve heat transfer, making it a reliable and efficient fluid for data center cooling.

To consolidate these insights, a decision matrix was developed to score each refrigerant across all evaluation criteria. Water emerged as the top performer with a remarkable score of 89 out of 90. Methanol, Ammonia, and Ethanol followed with 58.5, 56.5, and 56, respectively. Other natural refrigerants like Pentane, 2-Methylbutane, and Ammonia also showed moderate suitability. In contrast, several refrigerants received significantly lower scores due to safety risks or poor environmental performance.

# Appendix

## Decision matrix scaling criteria

The design matrix scaling criteria for the refrigerants at 55°C and P = 600 W, as illustrated in Fig. 18, evaluate refrigerant performance using a multi-criteria scoring system based on thermal efficiency and environmental impact. A higher Merit number (≥ 1 × 10¹¹ W/m²) yields the highest score of 10, with progressively lower scores assigned as performance decreases. Similarly, latent heat of vaporization scores range from 10 (≥ 2000 kJ/kg) to 1 (< 500 kJ/kg).

<figure><img src="image_21.png" /><figcaption>**Fig. 18** Decision matrix scaling criteria</figcaption></figure>
For practical applications, refrigerants are considered more suitable when their saturation pressure is close to ambient pressure, as this reduces the need for complex sealing solutions and simplifies the selection of tubing. The operating pressure deviation is scored from 10 to 1, with refrigerants operating near ambient pressure (≤ 30% deviation) rated best.

For volume flow rate, lower values (≤ 0.016 L/min) are preferred and score highest, decreasing linearly to a score of 1 for values > 0.34 L/min. The diameter interval range is scored from 1 (for < 15 mm) to 10 (≥ 37.22 mm), supporting manufacturing flexibility.

Toxicity and flammability are rated qualitatively: non-toxic refrigerants score 10, while toxic ones score 1; flammability classes A1 to A3 score from 10 down to 2.5. For ODP, the lower the value, the better, with values below 0.1 earning a score of 10. Lastly, GWP is inversely scaled: refrigerants with a GWP ≤ 1 score 10, and those ≥ 30 receive a score of 1, emphasizing the importance of environmental sustainability in refrigerant selection.

**Abbreviations**

<table><tr><td>AI</td><td>Artificial Intelligence</td></tr><tr><td>CRAC</td><td>Computer Room Air Conditioning</td></tr><tr><td>CPU</td><td>Central Processing Unit</td></tr><tr><td>DC</td><td>Data Center</td></tr><tr><td>ESR</td><td>Energy Savings Rate</td></tr><tr><td>G</td><td>Thermal Conductance</td></tr><tr><td>GWP</td><td>Global Warming Potential</td></tr><tr><td>h<sub>fg</sub></td><td>Latent Heat of Vaporization</td></tr><tr><td>M</td><td>Merit Number</td></tr><tr><td>ODP</td><td>Ozone Depletion Potential</td></tr><tr><td>ORS</td><td>Oxygen Reduction System</td></tr><tr><td>PUE</td><td>Power Usage Effectiveness</td></tr><tr><td>p<sub>sat</sub></td><td>Saturation Pressure</td></tr><tr><td>TPT</td><td>Two-Phase Thermosiphon</td></tr><tr><td>TPCT</td><td>Two-Phase Closed-Pipe Thermosiphon</td></tr><tr><td>TPLT</td><td>Two-Phase Loop Thermosiphon</td></tr><tr><td>V̇</td><td>Volume Flow Rate in the Evaporator</td></tr><tr><td>d<sub>crit, min</sub></td><td>Minimum Critical Diameter</td></tr><tr><td>d<sub>crit, max</sub></td><td>Maximum Critical Diameter</td></tr></table>

**Acknowledgements**

The 2PhaseEx project (Ref: 20404/D1-5) is part of the Science Offensive of the trinational Upper Rhine Metropolitan Region, co-financed by the European Union via the Interreg Upper Rhine programme, the Grand Est Region, the Ministerium für Wissenschaft, Forschung und Kunst of the Land of Baden-Württemberg and the Ministerium für Wissenschaft und Gesundheit of the Land of Rhineland-Palatinate.

**Authors' contributions**

Ahmed G. Rahma: Conceptualization, Methodology, Software, Investigation, Formal analysis, Validation, Data Curation, Writing - Original Draft, Visualization, Writing - Review & Editing. Frédy Abadassi: Conceptualization, Methodology, Software, Investigation, Formal analysis, Validation, Data Curation, Writing - Original Draft, Visualization, Writing - Review & Editing. Jiyan Akyol: Conceptualization, Methodology, Software, Investigation, Formal analysis, Validation, Data Curation, Writing - Original Draft, Visualization, Writing - Review & Editing. Abderahmane Marouf: Resources, Methodology, Supervision, Writing - Review & Editing. Pierre François: Supervision, Methodology, Writing - Review & Editing. Fabrice Lawniczak: Writing - Review & Editing. Abdallah Ghenaim: Supervision, Writing - Review & Editing. Yannick Hoarau: Writing - Review & Editing. Constanze Bongs: Supervision, Methodology, Writing - Review & Editing. Michael Kauffeld: Resources, Conceptualization, Methodology, Writing - Original Draft, Writing - Review & Editing, Supervision, Funding acquisition. Denis Funfschilling: Resources, Methodology, Writing - Review & Editing, Supervision, Project administration, Funding acquisition.

**Funding**

INTERREG Upper-Rhine - 2PhaseEx (Ref: 20404/D1-5).

**Data availability**

The authors confirm that all data supporting the findings of this study are included within the article.

**Declarations**

**Competing interests**

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Received: 20 August 2025 / Accepted: 1 December 2025

Published online: 18 December 2025

## References

1. ASHRAE (2011) Thermal guidelines for data processing environments: Expanded data center classes and usage guidance. Tech. Rep., American Society of Heating, Refrigerating, and Air-Conditioning Engineers. Whitepaper prepared by ASHRAE Technical Committee (TC) 9

2. European Commission. Code of Conduct on Data Centres Energy Efficiency, Version 2.0: Participant Guidelines. Joint Research Centre (JRC), Institute for Energy, Renewable Energies Unit, European Commission, 2009. Available at: https://cdn.bcs.org/bcs-org-media/2887/participant_guidelines_v2_0_final.pdf

3. Srivastava A, Gupta MS, Kaur G (2020) Energy efficient transmission trends towards future green cognitive radio networks (5g): progress, taxonomy and open challenges. J Netw Comput Appl 168:102760. https://doi.org/10.1016/j.jnca.2020.102760

4. Goldman Sachs (2025) Ai to drive 165% increase in data center power demand by 2030. https://www.goldmansachs.com/insights/articles/ai-to-drive-165-increase-in-data-center-power-demand-by-2030?utm. Accessed 25 Oct 2025

5. International Energy Agency (2025) Energy demand from AI. https://www.iea.org/reports/energy-and-ai/energy-deman-d-from-ai. Accessed 25 Oct 2025

6. ABB (2022) Data center energy efficiency. https://new.abb.com/news/detail/93186/data-center-energy-efficiency. Accessed 25 Oct 2024

7. (IEA) IEA (2020) Tracking data centres and data transmission networks 2020. https://www.iea.org/reports/tracking-data-centres-and-data-transmission-networks-2020. Accessed 25 Oct 2024

8. Rasmussen N (2015) Guidelines for Specification of Data Center Power Density. Schneider Electric, White Paper, Document No. SPD_NRAN-69ANM9_EN, Version 2, Available at: https://www.se.com/us/en/download/document/SPD_NRAN-69ANM9_EN/

9. Yuan X, Zhou X, Pan Y, Kosonen R, Cai H, Gao Y, Wang Y (2021) Phase change cooling in data centers: a review. Energy Buildings 236:110764. https://doi.org/10.1016/j.enbuild.2021.110764

10. Rasmussen N (2017) Calculating Total Cooling Requirements for Data Centers, White Paper 25, Schneider Electric Data Center Science Center, Available online: https://www.se.com/us/en/download/document/SPD_NRAN-5TE6HE_EN/

11. Oró E, Depoorter V, Garcia A, Salom J (2015) Energy efficiency and renewable energy integration in data centres. Strategies and modelling review. Renew Sustain Energy Rev 42:429–445. https://doi.org/10.1016/j.rser.2014.10.035

12. Phan L, Lin CX (2014) A multi-zone building energy simulation of a data center model with hot and cold aisles. Energy Build 77:364–376. https://doi.org/10.1016/j.enbuild.2014.03.060

13. Haywood AM, Sherbeck J, Phelan P, Varsamopoulos G, Gupta SKS (2015) The relationship among CPU utilization, temperature, and thermal power for waste heat utilization. Energy Convers Manage 95:297–303. https://doi.org/10.1016/j.enconnan.2015.01.088

14. Siriwardana J, Halgamuge SK, Scherer T, Schott W (2012) Minimizing the thermal impact of computing equipment upgrades in data centers. Energy Build 50:81–92. https://doi.org/10.1016/j.enbuild.2012.03.026

15. Zhang Q, Meng Z, Hong X, Zhan Y, Liu J, Dong J, Bai T, Niu J, Deen MJ (2021) A survey on data center cooling systems: technology, power consumption modeling and control strategy optimization. J Syst Archit 119:102253. https://doi.org/10.1016/j.sysarc.2021.102253

16. Johnson P, Marker T (2009) Data center energy efficiency product profile. Pitt Sherry

17. Intel® Core™ Ultra 200V Series Processors Specification Update — intel.com. https://www.intel.com/content/www/us/en/content-details/827538/intel-core-ultra-200v-series-processors-specification-update.html. Accessed 10 Feb 2025

18. Nada SA, Said MA, Rady MA (2016) CFD investigations of data centers’ thermal performance for different configurations of CRACs units and aisles separation. Alex Eng J 55(2):959–971. https://doi.org/10.1016/j.aej.2016.02.025

19. Iyengar M, Schmidt R, Caricari J (2010) Reducing energy usage in data centers through control of Room Air Conditioning units. In: 2010 12th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems, pp 1–11. https://doi.org/10.1109/ITHERM.2010.5501418

20. Sultan H, Katiyar A, Sarangi SR (2016) Noise Aware Scheduling in Data Centers. In: Proceedings of the 2016 International Conference on Supercomputing, ICS '16. Association for Computing Machinery, New York. https://doi.org/10.1145/2925426.2926268

21. Bose R, Roy S, Mondal H, Chowdhury DR, Chakraborty S (2021) Energy-efficient approach to lower the carbon emissions of data centers. Computing 103(8):1703–1721. https://doi.org/10.1007/s00607-020-00889-4

22. Anderson SF (2010) Improving data center efficiency. Energy Eng 107(5):42–63. https://doi.org/10.1080/01998595.2010.10121753

23. Zhang H, Shao S, Xu H, Zou H, Tian C (2014) Free cooling of data centers: a review. Renew Sustain Energy Rev 35:171–182. https://doi.org/10.1016/j.rser.2014.04.017

24. Zhang Y, Zhao Y, Dai S, Nie B, Ma H, Li J (2022) Cooling technologies for data centres and telecommunication base stations – a comprehensive review. J Clean Prod 334(December 2021):130280. https://doi.org/10.1016/j.jclepro.2021.130280

25. Capozzoli A, Primiceri G (2015) Cooling systems in data centers: state of art and emerging technologies. Energy Procedia 83:484–493. https://doi.org/10.1016/j.egypro.2015.12.168

26. Daraghmeh HM, Sulaiman MW, Yang KS, Wang CC (2019) Investigation of separated two-phase thermosiphon loop for relieving the air-conditioning loading in datacenter. Energies 12(1). https://doi.org/10.3390/en12010105

27. Zhou F, Li C, Zhu W, Zhou J, Ma G, Liu Z (2018) Energy-saving analysis of a case data center with a pump-driven loop heat pipe system in different climate regions in China. Energy Build 169:295–304. https://doi.org/10.1016/j.enbuild.2018.03.081

28. Sundaram AS, Seeniraj RV, Velraj R (2010) An experimental investigation on passive cooling system comprising phase change material and two-phase closed thermosyphon for telecom shelters in tropical and desert regions. Energy Build 42(10):1726–1735. https://doi.org/10.1016/j.enbuild.2010.05.008

29. Zalba B, Marín JM, Cabeza LF, Mehling H (2004) Free-cooling of buildings with phase change materials. Int J Refrig 27(8):839–849. https://doi.org/10.1016/j.ijrefrig.2004.03.015
30. Montpetit J, Brend Y (2025) Ai-related data centres use vast amounts of water, but gauging how much is a murky business. CBC News. https://www.cbc.ca/news/ai-data-centre-canada-water-use-9.6939684. Accessed 5 Nov 2025

31. Yañez-Barnuevo M (2025) Data centers and water consumption. Environmental and Energy Study Institute (EESI). https://www.eesi.org/articles/view/data-centers-and-water-consumption. Accessed 5 Nov 2025

32. Ahmad R (2024) Engineers often need a lot of water to keep data centers cool. Civil Engineering Source. https://www.asce.org/publications-and-news/civil-engineering-source/civil-engineering-magazine/issues/magazine-issue/article/2024/03/engineers-often-need-a-lot-of-water-to-keep-data-centers-cool. Accessed 5 Nov 2025

33. Interreg Rhin Supérieur (2025) Transformer en ressource la chaleur inexploitée produite par les data centers - 2PhaseEx: Développement d'un échangeur de chaleur diphasique en circuit fermé basé sur le principe du thermosiphon utilisant des fluides respectueux de l'environnement pour la récupération de chaleur. 2phaseEx Project. Accessed 10 Feb 2025

34. United Nations Environment Programme (UNEP) (1987) The Montreal Protocol on Substances that Deplete the Ozone Layer. https://ozone.unep.org/treaties/montreal-protocol-substances-deplete-ozone-layer Accessed: 17 April 2025

35. United Nations Environment Programme (UNEP) (2016) The kigali amendment (2016): The amendment to the montreal protocol agreed by the twenty-eighth meeting of the parties. Kigali

36. Regulation - EU - 2024/573 - EN - EUR-Lex — data.europa.eu. http://data.europa.eu/eli/reg/2024/573/oj. Accessed 16 Feb 2025

37. (EPA) U (2025) Per- and Polyfluoroalkyl Substances (PFAS). https://www.epa.gov/pfas. Accessed 27 Oct 2025

38. Samba A, Louahlia-Gualous H, Le Masson S, Nörterhäuser D (2013) Two-phase thermosyphon loop for cooling outdoor telecommunication equipments. Appl Therm Eng 50(1):1351-1360. https://doi.org/10.1016/j.applthermaleng.2012.05.023

39. Nadjahi C, Louahlia-Gualous H, Le Masson S (2019) Experimental study and analytical modeling of thermosyphon loop for cooling data center racks. Heat Mass Transfer 56(1):121-142. https://doi.org/10.1007/s00231-019-02695-x

40. Chehade A, Louahlia-Gualous H, Le Masson S, Lépinasse E (2015) Experimental investigations and modeling of a loop thermosyphon for cooling with zero electrical consumption. Appl Therm Eng 87:559-573. https://doi.org/10.1016/j.applthermaleng.2015.05.041

41. Samanci A, Berber A (2011) Experimental investigation of single-phase and two phase closed thermosyphon solar water heater systems. Sci Res Essays 6(4):688-693

42. Abou-Ziyan HZ, Helali A, Fatouh M, El-Nasr M (2001) Performance of stationary and vibrated thermosyphon working with water and R134a. Appl Therm Eng 21(8):813-830. https://doi.org/10.1016/S1359-4311(00)00089-2

43. Wu XP, Mochizuki M, Mashiko K, Nguyen T, Nguyen T, Wuttijumnong V, Cabusao G, Singh R, Akbarzadeh A (2011) Cold energy storage systems using heat pipe technology for cooling data centers. Front Heat Pipes 2(1) https://doi.org/10.5098/fhp.v2.1.3005

44. Long ZQ, Zhang P (2013) Experimental investigation of the heat transfer characteristics of a helium cryogenic thermosyphon. Cryogenics 57:95-103. https://doi.org/10.1016/j.cryogenics.2013.04.006

45. Solomon AB, Roshan R, Vincent W, Karthikeyan VK, Asirvatham LG (2015) Heat transfer performance of an anodized two-phase closed thermosyphon with refrigerant as working fluid. Int J Heat Mass Transf 82:521-529. https://doi.org/10.1016/j.ijheatmasstransfer.2014.11.034

46. Daraghmeh HM, Wang CC (2017) A review of current status of free cooling in datacenters. Appl Therm Eng 114:1224-1239. https://doi.org/10.1016/j.applthermaleng.2016.10.093

47. Chauhan A, Kandlikar SG (2019) Characterization of a dual taper thermosiphon loop for CPU cooling in data centers. Appl Therm Eng 146:450-458. https://doi.org/10.1016/j.applthermaleng.2018.10.010

48. Ding T, Chen X, Cao H, He Z, Wang J, Li Z (2021) Principles of loop thermosyphon and its application in data center cooling systems: a review. Renew Sustain Energy Rev 150:111389. https://doi.org/10.1016/j.rser.2021.111389

49. Barua H, Ali M, Nuruzzaman M, Quamrul Islam M, Feroz CM (2013) Effect of filling ratio on heat transfer characteristics and performance of a closed loop pulsating heat pipe. Procedia Eng 56:88-95. https://doi.org/10.1016/j.proeng.2013.03.093

50. Rahma AG, Abadassi F, Ghenaim A, François P, Hoarau Y, Funfschilling D, Marouf A (2025) Numerical assessment of condensation time relaxation coefficients for accurate prediction under atmospheric and subatmospheric conditions in two-phase thermosiphon systems. Int J Heat Mass Transf 252:127485. https://doi.org/10.1016/j.ijheatmasstransfer.2025.12.7485

51. Rahma AG, Abadassi F, Ghenaim A, François P, Hoarau Y, Funfschilling D, Marouf A (2025) Numerical Investigation of Condensation Time Relaxation Coefficients in Two-Phase Thermosiphon Systems for Low-Pressure Applications. In: 26ème Congrès Français de Mécanique, l'Association Française de Mécanique, Metz. https://hal.science/hal-05219419 Accessed 30 August 2025

52. Abadassi F, Rahma AG, François P, Lawniczak F, Ghenaim A, Marouf A, Funfschilling D (2025) Thermal Characterization of a Two-Phase Closed Thermosyphon with Optimal Filling Ratio under Varying Condenser Temperatures. In: Congrès Français de la Mécanique (CFM) 2025, Metz. https://hal.science/hal-05219487 Accessed 30 August 2025

53. Rahma AG, Abadassi F, Ghenaim A, François P, Hoarau Y, Funfschilling D, Marouf A (2025) Influence of filling ratio on flow pattern in a two-phase closed thermosiphon at fixed confinement number. In: 2025 4th International Conference on Electronic Engineering (ICEEM), IEEE, pp 1-6. https://doi.org/10.1109/iceem66692.2025.11225207

54. Ding T, Wang J, Yang CO, Cao H, He Z, Li Z (2019) Comparison work about different empirical formulas for the boiling heat transfer coefficient in separated heat pipe system. Int J Low-Carbon Technol 14(2):103-107. https://doi.org/10.1093/ijlct/ctz007

55. Khazaei I, Hosseini R, Noie S (2010) Experimental investigation of effective parameters and correlation of geyser boiling in a two-phase closed thermosyphon. Appl Therm Eng 30(5):406-412. https://doi.org/10.1016/j.applthermaleng.2009.09.012

56. Abreu SL, Colle S (2004) An experimental study of two-phase closed thermosyphons for compact solar domestic hot-water systems. Sol Energy 76(1):141-145. https://doi.org/10.1016/j.solener.2003.02.001

57. Hussein HMS, El-Ghetany HH, Nada SA (2006) Performance of wickless heat pipe flat plate solar collectors having different pipes cross sections geometries and filling ratios. Energy Convers Manage 47(11):1539-1549. https://doi.org/10.1016/j.encman.2005.08.009

58. Noie SH, Sarmasti Emami MR, Khoshnoodi M (2007) Effect of inclination angle and filling ratio on thermal performance of a two-phase closed thermosyphon under normal operating conditions. Heat Transf Eng 28(4):365-371. https://doi.org/10.1080/01457630601122997
59. Ong KS, Tong WL, Gan JS, Hisham N (2014) Axial temperature distribution and performance of R410a and water filled thermosyphon at various fill ratios and inclinations. Front Heat Pipes 5(1) https://doi.org/10.5098/fhp.5.2

60. MacGregor RW, Kew PA, Reay DA (2013) Investigation of low Global Warming Potential working fluids for a closed two-phase thermosyphon. Appl Therm Eng 51(1):917-925. https://doi.org/10.1016/j.applthermaleng.2012.10.049

61. Jouhara H, Ajji Z, Koudsi Y, Ezzuddin H, Mousa N (2013) Experimental investigation of an inclined-condenser wickless heat pipe charged with water and an ethanol-water azeotropic mixture. Energy 61:139-147. https://doi.org/10.1016/j.energy.2012.09.033

62. Bolozdynya AI, Dmitrenko VV, Efremenko Y, Khromov AV, Shafigullin RR, Shakirov AV, Sosnovtsev VV, Tolstukhin IA, Uteshev ZM, Vlasik KF (2015) The two-phase closed tubular cryogenic thermosyphon. Int J Heat Mass Transf 80:159-162. https://doi.org/10.1016/j.ij heatmasstransfer.2014.09.001

63. Ding T, Wen Cao H, Guang He Z, Li Z (2017) Boiling heat transfer characteristics of the R744 coolant in the evaporator of the separated heat pipe system. Int J Heat Mass Transf 113:1254-1264. https://doi.org/10.1016/j.ij heatmasstransfer.2017.05.122

64. Jouhara H, Robinson AJ (2010) Experimental investigation of small diameter two-phase closed thermosyphons charged with water, FC-84, FC-77 and FC-3283. Appl Therm Eng 30(2-3):201-211. https://doi.org/10.1016/j.applthermaleng.2009.08.007

65. Kyung IS, Lee SY (1996) Periodic flow excursion in an open two-phase natural circulation loop. Nucl Eng Des 162(2):233-244. https://doi.org/10.1016/0029-5493(95)01126-9

66. Chu RC, Simons RE, Chrysler GM (1999) Experimental investigation of an enhanced thermosyphon heat loop for cooling of a high performance electronics module. In: Fifteenth Annual IEEE Semiconductor Thermal Measurement and Management Symposium (Cat. No.99CH36306), pp 1-9. https://doi.org/10.1109/STHERM.1999.762421

67. Na MK, Jeon JS, Kwak HY, Nam SS (2001) Experimental study on closed-loop two-phase thermosyphon devices for cooling MCMs. Heat Transf Eng 22(2):29-39. https://doi.org/10.1080/01457630116920

68. Pal A, Joshi YK, Beitelmal MH, Patel CD, Wenger TM (2002) Design and performance evaluation of a compact thermosyphon. IEEE Trans Compon Packag Technol 25(4):601-607. https://doi.org/10.1109/TCAPT.2002.807997

69. Mukherjee S, Mudawar I (2003) Pumpless loop for narrow channel and micro-channel boiling. J Electron Packag 125(3):431-441. https://doi.org/10.1115/1.1602708

70. Honda H, Zhang Z, Takata N (2004) Flow and heat transfer characteristics of a natural circulation evaporative cooling system for electronic components. J Electron Packag 126(3):317-324. https://doi.org/10.1115/1.1772412

71. Khodabandeh R, Palm B (2002) Influence of system pressure on the boiling heat transfer coefficient in a closed two-phase thermosyphon loop. Int J Therm Sci 41(7):619-624. https://doi.org/10.1016/S1290-0729(02)01355-8

72. Chen L, Tian YS, Karayiannis TG (2006) The effect of tube diameter on vertical two-phase flow regimes in small tubes. Int J Heat Mass Transf 49(21):4220-4230. https://doi.org/10.1016/j.ij heatmasstransfer.2006.03.025

73. Huo X, Chen L, Tian YS, Karayiannis TG (2004) Flow boiling and flow regimes in small diameter tubes. Appl Therm Eng 24(8):1225-1239. https://doi.org/10.1016/j.applthermaleng.2003.11.027

74. Marcinichen JB, Armas GS, Rouaze G, Thome JR, Zhang LW (2021) Air-cooled loop thermosyphon cooling system for high heat load CPUs-Part I: design and performance simulation. IEEE Trans Components Packag Manuf Technol 11(10):1679-1686. https://doi.org/10.1109/TCPMT.2021.3112080

75. ASHRAE (2013) 2013 ASHRAE Handbook: Fundamentals. American Society of Heating, Refrigerating, and Air-Conditioning Engineers

76. Lemmon EW, Bell IH, Huber ML, McLinden MO (2023) Thermophysical Properties of Fluid Systems. https://doi.org/10.18434/T4D303

77. ChiSW (1976) Heat pipe theory and practice: a sourcebook. Hemisphere Publishing Corporation, Washington. https://www.osti.gov/biblio/5467269 Accessed 17 April 2025

78. Reay DA, Kew PA, McGlen RJ (2014) Heat pipe: Theory, design and applications, 6th edn. Buterworth

79. Palm B, Khodabandeh R (2003) Choosing working fluid for two-phase thermosyphon systems for cooling of electronics. J Electron Packag 125(2 SPEC.):276-281. https://doi.org/10.1115/1.1571570

80. Ömür C, Horuz I (2019) Investigation of the saturation pressure effect of the working fluid on the thermal performance of grooved heat pipes. In: 22nd Congress of Thermal Sciences and Technology (ULIBTK 2019)ULIBTK19), pp 162-166

81. Zohuri B, Lam S, Forsberg C (2020) Heat-pipe heat exchangers for salt-cooled fission and fusion reactors to avoid salt freezing and control tritium: a review. Nucl Technol 206(11):1642-1658. https://doi.org/10.1080/00295450.2019.1681222

82. Başaran A (2022) Experimental investigation of R600a as a low GWP substitute to R134a in the closed-loop two-phase thermosyphon of the mini thermoelectric refrigerator. Appl Therm Eng 211(January). https://doi.org/10.1016/j.applthermelaeng.2022.118501

83. Russo GM, Krambeck L, Nishida FB, Santos PHD, Alves TA (2016) Thermal performance of thermosyphon for different working fluids. Rev Eng Term 15(1):03. https://doi.org/10.5380/reterm.v15i1.62150

84. Baraya K, Weibel JA, Garimella SV (2019) Simultaneous wick and fluid selection for the design of minimized-thermal-resistance vapor chambers under different operating conditions. Int J Heat Mass Transf 136:842-850. https://doi.org/10.1016/j.ij heatmasstransfer.2019.03.025

85. Dussinger P, Anderson W, Sunada E (2005) Design and testing of titanium-cs and titanium-k heat pipes. In: 3rd International Energy Conversion Engineering Conference, American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2005-5631

86. Ghadim HB, Godin A, Veillere A, Duquesne M, Haillot D (2025) Review of thermal management of electronics and phase change materials. Renew Sustain Energy Rev 208:115039. https://doi.org/10.1016/j.rser.2024.115039

87. What are the differences between ambient temperature, junction... — intel.com. https://www.intel.com/content/www/us/en/support/programmable/articles/000073846.html. Accessed 10 Feb 2025

88. Franco A, Filippeschi S (2010) Experimental analysis of heat and mass transfer in small dimension, two-phase loop thermosyphons. Heat Pipe Science and Technology An International Journal 1(2):163-182. https://doi.org/10.1615/heatpipescitech.v1.i2.40
89. Intergovernmental Panel on Climate Change (IPCC) (2023) Sixth assessment report (ar6): Climate change 2021–2023 — the physical science basis, impacts, adaptation and vulnerability, mitigation of climate change, and synthesis report. https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=OJ:L_202400573#ntr3-L_202400573EN.005901-E0003. Accessed 27 Oct 2025

90. (2024) Regulation (eu) 2024/573 of the european parliament and of the council of 7 february 2024 on fluorinated greenhouse gases, amending directive (eu) 2019/1937 and repealing regulation (eu) no 517/2014. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32024R0573. Text with EEA relevance

91. Mangotra A, Singh SK (2024) Volatile organic compounds: a threat to the environment and health hazards to living organisms - a review. J Biotechnol 382:51–69. https://doi.org/10.1016/j.jbiotec.2023.12.013

92. US Environmental Protection Agency (2025) Understanding global warming potentials. https://www.epa.gov/ghgemissio ns/understanding-global-warming-potentials. Accessed 27 Oct 2025

93. ASHRAE(2019) ASHRAE Refrigerant Designations. https://www.ashrae.org/technical-resources/standards-and-guidelines/a shrae-refrigerant-designations Accessed 17 Apr 2025

94. Calm JM, Hourahan GC (2011) Physical, safety, and environmental data for current and alternative refrigerants. In: Proceedings of 23rd international congress of refrigeration (ICR2011), Prague, pp 21–26

95. Froid DU (2001) Classification of refrigerants. Int Inst Frig Cl 3(2):1–6

96. Brooks J (2020) Aircraft Cargo Fire Suppression Using Low Pressure Dual Fluid Water Mist and Hypoxic Air. Accessed 17 April 2025. https://www.nist.gov/publications/aircraft-cargo-fire-suppression-using-low-pressure-dual-fluid-water-mist-an d-hypoxic

97. Nilsson M, van Hees P (2014) Advantages and challenges with using hypoxic air venting as fire protection. Fire Mater 38(5):559–575. https://doi.org/10.1002/fam.2197

98. Hosseinzadeh K, Erfani Moghaddam M, Hatami M, Ganji D, Ommi F (2022) Experimental and numerical study for the effect of aqueous solution on heat transfer characteristics of two phase close thermosyphon. Int Commun Heat Mass Transf 135:106129. https://doi.org/10.1016/j.icheatmasstransfer.2022.106129

99. Smith K, Robinson A, Kempers R (2018) Confinement and vapour production rate influences in closed two-phase reflux thermosyphons part B: heat transfer. Int J Heat Mass Transf 120:1241–1254. https://doi.org/10.1016/j.ijheatmasstransfer.20 17.12.046

100. 3M (n.d.) 3M™ Novec™ 7000 Engineered Fluid. https://www.3m.com/3M/en_US/p/d/b5005006004/. Accessed 14 July 2025

101. Aminian A, Celný D, Mickoleit E, Jäger A, Vinš V (2022) Ideal gas heat capacity and critical properties of hfe-type engineering fluids: Ab initio predictions of cpig, modeling of phase behavior and thermodynamic properties using peng-robinson and volume-translated peng-robinson equations of state. Int J Thermophys. https://doi.org/10.1007/s10765-022-03006-z

102. Cai Y, Hu X, Lu J, Li Y, Tang D, Hu C (2025) Impact of working fluid properties on heat transfer and flow characteristics of two-phase loop thermosyphon with high filling ratios. Int J Heat Mass Transf 238:126482. https://doi.org/10.1016/j.ijheatmasstransfer.2024.126482

103. Smith K, Kempers R, Robinson A (2018) Confinement and vapour production rate influences in closed two-phase reflux thermosyphons part A: flow regimes. Int J Heat Mass Transf 119:907–921. https://doi.org/10.1016/j.ijheatmasstransfer.2017.10.049

104. Voirand A, Lips S, Sartre V (2020) Heat transfer and flow visualizations in a flat confined two-phase thermosyphon. Int J Heat Mass Transf 148:119056. https://doi.org/10.1016/j.ijheatmasstransfer.2019.119056

105. Lin MC, Chun LJ, Lee WS, Chen SL (2003) Thermal performance of a two-phase thermosyphon energy storage system. Sol Energy 75(4):295–306. https://doi.org/10.1016/j.solener.2003.08.028

106. Xia G, Wang W, Cheng L, Ma D (2017) Visualization study on the instabilities of phase-change heat transfer in a flat two-phase closed thermosyphon. Appl Therm Eng 116:392–405. https://doi.org/10.1016/j.applthermaleng.2017.01.096

107. Kim JS, Kim Y, Shin DH, You SM, Lee J (2021) Heat transfer and flow visualization of a two-phase closed thermosiphon using water, acetone, and hfe7100. Appl Therm Eng 187:116571. https://doi.org/10.1016/j.applthermaleng.2021.116571

108. Birajdar MR, Sewatkar CM (2021) Experimental investigation of the loop thermosyphon with different adiabatic lengths charged with different working fluids. Heat Transf 50(5):4171–4191. https://doi.org/10.1002/htj.22070

109. Chen X, Ding T, Wang L, Li Z (2024) Experimental research and energy effectiveness analysis on chip-level two-stage loop thermosyphon system for data centre free cooling. Appl Therm Eng 245:122767. https://doi.org/10.1016/j.applthermaleng.2024.122767

110. ESDU (Engineering Sciences Data Unit) (1981) Heat Pipes: Performance of Two-phase Closed Thermosyphons. Engineering Sciences Data Unit, London. Data item number 81038. https://www.esdu.com/cgi-bin/ps.pl?t=doc&p=esdu_81038c Accessed 17 Apr 2025

111. Baruah A, Krishnan S (2025) Experimental investigation of water-alcohol mixtures as working fluids in a closed-loop two-phase thermosiphon. J Therm Sci Eng Appl. https://doi.org/10.1115/1.4067731

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