Effect of Nanoparticle Concentration on Physical and Heat-Transfer Properties and Evaporation Characteristics of Graphite/n-Decane Nanofluid Fuels.

n-Decane-based nanofluid fuels could be one of the most promising alternative fuels as aviation kerosene for aerospace application. However, the physical and heat-transfer properties of n-decane-based nanofuels have been rarely studied, and the influence of the concentration of nanoparticles on the evaporation characteristics of n-decane-based fuels has been sparsely investigated. This paper investigated physical and heat-transfer properties and evaporation characteristics of graphite/n-decane nanofluid fuels and emphasized the concentration effect of adding graphite nanoplatelets (GNPs) on these characteristics. It was found that there are a linear increase of density and thermal conductivity, a binomial increase of viscosity, and a binomial influence on surface tension as GNP concentration increases, while the boiling point almost remains constant, and the latent heat of vaporization largely decays. There exists a critical GNP concentration of 1.75 wt % for the evaporation performance. At 0∼1.75 wt %, the increase of GNP concentration benefits the evaporation. At 1.75∼4.0 wt %, the enhancement of GNP concentration deteriorates the evaporation performance. A detailed discussion of this evaporation behavior was made, which could be attributed to multiple factors, for example, the aggregation of nanoplatelets, the changes of physical and heat-transfer properties owing to the nanoparticle concentration effect, the surfactant concentration, and the ambient temperature. The concentration of surfactants has a binomial effect, and the ambient temperature has a linear effect on the evaporation rate. This study would promote in depth understanding of physical and heat-transfer properties and evaporation characteristics of nanofluid fuels and develop the application in turbine engines and ramjet engines.

Introduction

In turbine engines and ramjet engines, n-decane has been considered as a promising alternative fuel for aviation kerosene. n-Decane has good thermal stability, low saturated vapor pressure, and so on; thus it can meet the large amounts of energy consumption needs and reduce the CO2 emission.[1,2] The literature revealed that single n-decane species as well as its binary blends could be used as alternative fuels. For example, Dagaut et al. indicated that n-decane had comparable high-pressure oxidation and combustion performance to kerosene.[3,4] Vukadinovic et al. reported that n-decane had similar laminar burning velocity to kerosene Jet A-1 and confirmed the suitability of n-decane as a surrogate fuel.[5] Other studies demonstrated that the binary blends of n-decane with other fuels could be suggested as diesel,[6,7] gasoline,[8] and kerosene[9] surrogates, such as n-decane + n-hexane, n-decane + n-propylbenzene, n-decane + benzene, n-decane + toluene, n-decane + ethylbenzene, n-decane + trimethylbenzene, and n-decane + propylcyclohexane.[10−14]

To further improve the utilization efficiency of n-decane, one possible method is to add nanoparticles (NPs) into n-decane to form suspensions, that is, n-decane-based nanofluid fuels. Nanofluid fuels are a relatively new class of fuels by suspending NPs (1∼100 nm) within a base fuel and have demonstrated their potential use in energy conversion and management systems intended for industrial applications such as automobiles (IC engines), electronics, nuclear power, and power generation.[15,16] These suspended NPs can be mainly classified into three groups: (1) metallic NPs (Al,[17−20] B,[21,22] Ce, etc.[23]); (2) metal-oxide NPs (Al2O3,[24−26] CeO2,[27,28] Fe3O4,[29,30] TiO2,[31] ZnO,[32] CuO,[24] NiO, etc.[33]); and (3) carbon-based NPs (graphite,[34] carbon nanotube,[35] graphene,[36−38] and graphene oxide[39]). The literature has revealed that the suspended NPs make significant promotion to the evaporation and combustion characteristics of the base fuels.

Among three types of NPs, metallic and metal-oxide NPs may cause the blockage of combustion systems and also may have toxic effects on living organisms, although they have high energy value. While carbon-based NPs are eco-friendly because only carbon dioxide and water would be formed after combustion.[34−39] This motivates us to carry out the study on the n-decane-based nanofluid fuel with adding graphite nanoplatelets (GNPs). The quantities of added GNPs are critical to influence the physical and heat-transfer properties, the rise rate of temperature, and the vaporization rate. Moreover, during evaporation, the GNP concentration gradually increases as the vaporization of the base fluid evolves, which would possibly deviate the classical d2-Law.

Researchers have sparsely investigated the influence of concentration of NPs on the evaporation characteristics of the base fuels.[19,40] For example, Javad studied the evaporation behavior of kerosene droplets containing dense concentrations (2.5, 5.0, and 7.0% by weight)[19] and dilute concentrations (0.1, 0.5, and 1.0% by weight)[40] of aluminum (Al) NPs, but the critical concentration of NPs remained unrevealed. However, the detailed concentration effect of adding NPs on the evaporation performance of base fuels has not been studied in depth, and their promotion mechanism has not been fully revealed. Moreover, the physical and heat-transfer properties of carbon-based nanofluid fuels have not been measured and compared in detail with those of the base fuels.

Therefore, this paper mainly aims to: (1) examine the GNP concentration effect on the physical and heat-transfer properties including density, surface tension, dynamic viscosity, thermal conductivity, boiling point, and latent heat of vaporization of the prepared GNP/n-decane nanofluid fuels and then compare with the properties of n-decane and (2) obtain the critical concentration of GNPs affecting the evaporation behavior and characteristics at the optimum surfactant concentration at different ambient temperatures and further reveal the promotion mechanism of adding GNPs on the evaporation performance of n-decane.

Results and Discussion

Density of GNP/n-Decane Nanofluid Fuels

Density measurement experiments of GNP/n-decane nanofluid fuels under different GNP concentrations (0, 0.1, 0.2, 0.5, 1.0, 2.0, 3.0, and 4.0 wt %) were repeatedly conducted for five runs. The average densities and the random errors are shown in Figure . Compared to the base fuel, the density of GNP/n-decane nanofluid fuels linearly increased with the increase of GNP concentration, and the relationship between the density ρnf and the GNP concentration φ follows the formula:

Figure 1

Density of GNP/n-decane nanofluid fuels under different GNP concentrations (SP-80 of 0.5 vol %, 25 °C).

Dynamic Viscosity of GNP/n-Decane Nanofluid Fuels

Dynamic viscosity measurements of GNP/n-decane nanofluid fuels at each GNP concentration were repeatedly conducted for 10 runs. Figure illustrates that, at a low GNP concentration of 0∼1.0 wt %, the dynamic viscosity slightly increased with the added GNPs (the increase ratio was below 5%) compared to the base fuel. However, at a high GNP concentration of 2.0∼4.0 wt %, the dynamic viscosity significantly increased with the increasing GNP concentration, resulting in the intensified shear effect.[41]

Figure 2

Dynamic viscosity of GNP/n-decane nanofluid fuels under different GNP concentrations (SP-80 of 0.5 vol %, 25 °C).

In this work, the dynamic viscosity of GNP/n-decane nanofluid fuels was a binomial function of GNP concentration:

In which μ represents the dynamic viscosity. A similar binomial relationship between the dynamic viscosity of nanofluids and the nanoparticle concentration was demonstrated in some literature studies, listed in Table . The dynamic viscosity represents the volume stress system of nanofluids, and there are coupled or interactive stable thermodynamic forces between NPs. This kind of thermodynamic force not only directly affects the volume stress, but also indirectly affects the relative position of NPs to the volume stress. The direct and indirect contributions of thermodynamic force to volume stress correspond to the first- (φ) and second-order (φ2) terms, respectively.[42]

Table 1

Relationship between the Dynamic Viscosity of Nanofluids and Nanoparticle Concentration

authors	relationship
Batchelor et al.[41]	μnf = μbf(1 + 2.5φ + 6.5φ2)
Chen et al.[42]	μnf = μbf(1 + 10.6φ + 10.6φ2)
Wang et al.[43]	μnf = μbf(1 + 7.3φ + 123φ2)
Lundgren et al.[44]	μnf = μbf[1 + 2.5φ + 6.25φ2 + f(φ3)]
Nguyen et al.[45]	μnf = μbf(1 + 0.0025φ + 0.015φ2)
Zhuo et al.[46]	μnf = μbf(1 + 0.0068φ + 0.0002φ2)

Surface Tension of GNP/n-Decane Nanofluid Fuels

Measurement of surface tension was repeatedly conducted for 10 runs at each GNP concentration, and the results are shown in Figure . As the GNP concentration increased, the surface tension of nanofluid fuels first increased and then decreased, that is, there was a local maximum at a GNP concentration of ∼2.0 wt %. The phenomenon has been observed in the Al/n-decane nanofluid fuels.[46] For Al/n-decane nanofluid fuel, there was a parabolic influence of Al nanoparticle concentration on the surface tension. The surface tension followed a trinomial fitting relationship with the Al nanoparticle concentration. In this work, the surface tension had a binomial function to the GNP concentration.

Figure 3

Surface tension of GNP/n-decane nanofluid fuels under different GNP concentrations (SP-80 of 0.5 vol %, 25 °C).

Bhuiyan et al.[47] and Chinnam et al.[48] explained that, at lower concentrations, the NPs tend to accumulate on the liquid/gas interface and try to get close to each other. As a result, the gravitational potential energy (Van Der Waals force) among the NPs increases, thus reducing the average distance between NPs and base liquid molecules and eventually leading to the increase of surface tension. As quantities of GNPs were added into the base fuel n-decane, the surface tension gradually increased as the GNP concentration increased.

Yu et al.[49] demonstrated that, as the concentration is further increased, the increase of conformation energy of the nanoparticle aggregates will enhance the tendency of dissociation, resulting in a reduction of the surface tension. As the GNP concentration was increased over than ∼2.0 wt %, the dissociation phenomenon of GNP aggregates suspended into n-decane would account for the decrease of surface tension of GNP/n-decane nanofluid fuels.

Thermal Conductivity of GNP/n-Decane Nanofluid Fuels

GNPs have low sphericity, which were estimated as 0.1∼0.3 in this work. Figure demonstrates the thermal conductivity of GNP/n-decane nanofluid fuels calculated by eq at each sphericity. The lower sphericity is, the higher thermal conductivity becomes. The thermal conductivity of nanofluid fuels linearly increases as the GNP concentration increases. It should be attributed to the mixing effect of the base fuel directly adjacent to the NPs. Brownian motion and induced microconvection and mixing possibly significantly enhance the macroscopic heat transfer in nanofluid fuels.[50]

Figure 4

Thermal conductivity of GNP/n-decane nanofluid fuels under different GNP concentrations (without the surfactant of SP-80).

Boiling Point and Latent Heat of Vaporization of GNP/n-Decane Nanofluid Fuels

The boiling-point temperature is one of the critical parameters in determining the evaporation rate of liquid fuels. Its measurement was conducted for only two runs because the temperature differences among runs were relatively tiny. Figure shows that the GNP concentration has little effect on the boiling-point temperatures of GNP/n-decane nanofluid fuels. The maximum boiling-point difference is ∼1 °C (<0.6%) in the range of GNP concentrations of 0∼4.0 wt %.

Figure 5

Boiling points and latent heat of vaporization of GNP/n-decane nanofluid fuels under different GNP concentrations (without the surfactant of SP-80).

The latent heat of vaporization of nanofluid fuels should be a function of enthalpy of vaporization of base fuel and NPs and also NP concentration.[51] From eq , the calculated latent heat of vaporization of GNP/n-decane nanofluid fuels at each GNP concentration is shown in Figure . It is observed that the concentration has a significant effect on the latent heat of vaporization of nanofluid fuels, and the values decay over 3.6% as the concentration increases by 4%. Chen et al.[52] reported that, during vaporization, the variation in the latent heat of vaporization made the droplet regression deviate from classical d2 Law.

Evaporation Characteristics of GNP/n-Decane Nanofluid Fuels

Evaporation experiments were first performed for GNP/n-decane nanofluid fuels under GNP of 0.1 wt %, SP-80 of 1.0 vol %, and Tair of 600 °C. The evaporation was found to mainly underwent three stages (Figure ): Stage I, Nonisothermal evaporation; Stage II, Isothermal evaporation; Stage III, Dry out. During isothermal evaporation, the evaporation rate of a single nanofluid fuel droplet is governed by the so-called d2-Law, which says that the d2 decreases linearly with the evaporation time:

Figure 6

Evaporation of GNP/n-decane nanofluid fuel (GNP of 0.1 wt %, SP-80 of 1.0 vol %, and Tair of 600 °C).

In which t is the evaporation time, d0 is the initial droplet diameter, d is the droplet diameter at the evaporation time t, and Ke is the evaporation rate constant.

In convection, the evaporation rate constant of nanofluid droplets can be expressed as

In which BT is the Spalding mass number, λg and cp,g represent the thermal conductivity and specific heat capacity of the gas-phase base liquid, and Tair and Tboil are the temperature of ambient hot air and the boiling point of the nanofluid, respectively. Nu is the Nusselt number, Nu = 2[1 + Re1/2Pr1/3/3], in which Re and Pr represent the Reynolds number and Prandtl number. eq shows that the evaporation rate constant depends on the comprehensive physical and heat-transfer parameters including density, dynamic viscosity, thermal conductivity, specific heat capacity, boiling point, latent heat of vaporization, and so on, which would be discussed as follows.

To eliminate the effect of the initial diameter of droplets on the evaporation in discussion, eq could be normalized as:

Thus, the evaporation rate constant can be obtained by linearly fitting d2/d02 ∝ t/d02.

Effect of Ambient Temperature on the Evaporation

In eq , the temperature of ambient hot air significantly affects the evaporation rate constant. Figure a illustrates the isothermal evaporation rates of GNP/n-decane nanofluid fuels (GNP 0.1 wt %, SP-80 1.0 vol %) at different ambient temperatures of 300, 400, 500, 600, and 700 °C. Experiments under each condition were repeatedly carried out for three runs. The evaporation rate constants were obtained and plotted in Figure b with different ambient temperatures. With increasing ambient temperature, the evaporation rate constant significantly increased, and the relationship is as follows:

Figure 7

(a) Normalized droplet diameter at different ambient temperatures (GNP of 0.1 wt %, SP-80 of 1.0 vol %). (b) Evaporation rate constants with different ambient temperatures.

By the Taylor series expansion, eq can be expressed as

Equation can keep the same expression as eq through appropriately first-order truncating, that is,

Equations and 8 confirm that the evaporation rate constant linearly correlates with the ambient temperature, suggesting that the ambient temperature scarcely influenced the coefficients a and b which rely on the physical and heat-transfer properties.

Effect of Surfactant Concentration on the Evaporation

Surfactant SP-80 concentration has an effect on the physical and heat-transfer properties, resulting in the effect of surfactant concentration on the evaporation of GNP/n-decane nanofluid fuels. GNP concentration was of 0.1 wt %, and the ambient temperature was kept at 600 °C. Experiments under each condition were repeatedly carried out for three runs. Figure obviously shows that with the addition of SP-80, the evaporation rates greatly decreased, because the surfactant SP-80 has higher density, dynamic viscosity, boiling point, latent heat of vaporization, and lower thermal conductivity, compared to the base fuel n-decane.

Figure 8

(a) Normalized droplet diameter under different SP-80 concentrations (GNP of 0.1 wt %, Tair of 600 °C). (b) Evaporation rate constants with different SP-80 concentrations.

Effect of GNP Concentration on the Evaporation

GNP concentration plays an important role in the physical and heat-transfer properties of GNP/n-decane nanofluid fuels, leading to a significant effect on the evaporation behavior. From Figure , the evaporation rate constant was enhanced by adding GNPs into n-decane compared with that of pure n-decane. In Figure , experiments under each concentration were repeatedly carried out for five runs. However, the evaporation rate constant decreased with the further increase of GNP concentration. The transforming GNP concentration might exist at a GNP concentration of 1.0∼2.0 wt %. The relationship between the evaporation rate constant and GNP concentration was obtained by fitting:

Figure 9

Evaporation rate constants of GNP/n-decane nanofluid fuels under different GNP concentrations (SP-80 of 1.0 vol %, Tair of 600 °C).

The maximum evaporation rate constant could be calculated by derivation of eq . It can be concluded that the maximum evaporation rate constant was 1.03 mm2/s, when the GNP concentration was of φmax = 1.75 wt%. Compared to the base fluid, the evaporation rate constant increased by 12.6%.

Assuming that the ratio λgNu/ρnfcp, gremains an appropriate constant, eq could be similar to eq through appropriately second-order truncating, that is,

It suggests that the latent heat of vaporization controlled by nanoparticle concentration is one of the critical parameters to the evaporation performance, which has been confirmed by Lee et al.[51,53]

The discussion stated above concerned with the effect of increasing the initial nanoparticle concentration dispersed into the base fluid on the evaporation performance. In addition to the discussion, more importantly, the enhancement of nanoparticle concentration along with the evolution of nanofluid evaporation has a significant effect on the evaporation. Generally, the boiling-point temperatures of the base fuels are further lower than those of solid NPs, and during the evaporation of the base fuels, the NP concentration gradually increases. It would result in that the aggregation intensifies, the physical and heat-transfer properties change, the evaporation rate correspondingly nonlinearly fluctuates. To analyze the relationship between the aggregation of NPs and evaporation characteristics, the traditional dimensionless number (CR) was introduced.[54] It is defined as the ratio of particle migration time (τp) to droplet evaporation time (τe), that is,

The migration time can be expressed aswhere Lm is the mean distance between two adjacent NPs, Lm = (Vd/n)1/3, Vd is the volume of an individual nanofluid droplet, and n is the number of NPs within the nanofluid droplet. Dp is the diffusion coefficient of NPs, Dp = kBT/6πμr, kB is Boltzmann’s Constant, T is the temperature of the nanofluid droplet, and r is the radius of the nanoparticle.

In this work, the initial diameters of nanofluid fuel droplets are ∼1.0 mm, and the average migration time takes ∼6.4 ms at a GNP concentration of 0.1 wt %. As the GNP concentration was enhanced until 4.0 wt %, the migration time shortens until ∼0.6 ms. In any GNP concentration range of 0.1∼4.0 wt %, the migration time of NPs is lower two orders of magnitude than the evaporation time. It means that the dimensionless number CR calculated from eq is much smaller than 1, and the NPs migrate more quickly to the droplet surface than the sufficiently long evaporation time. It would result in forming the assembly structure or aggregates.[54] Therefore, at lower GNP concentrations (≤1.75 wt %), the aggregation was relatively weak, and the evaporation rates were enhanced with the increase of GNP concentration. Whereas as the GNP concentration further increased (>1.75 wt %), the number density increased, the average distances between NPs were largely reduced. This effect will reduce the aggregation time and increases aggregation intensity. In particular, at longer times, at the droplet surface, the agglomerates would generate porous shell structures,[55] resulting in a reduction of the evaporation rate.

Conclusions

The concentration (0∼4.0 wt %) of GNPs into n-decane-loaded surfactant SP-80 has a significant effect on the stability, physical and heat-transfer properties, and evaporation characteristics. We obtained the best stability of GNP/n-decane nanofluid fuels, as the optimum surfactant SP-80 concentration was of 0.5 vol %, while the optimum ultrasonication time was of 10 min under a GNP concentration of 0.1 wt %. Single physical and heat-transfer properties like density, surface tension, dynamic viscosity, thermal conductivity, boiling point, and latent heat of vaporization relate to the GNP concentration. As the GNP concentration increases, the density and thermal conductivity linearly increase; the viscosity has a binomial increase, and the surface tension has a piecewise influence. The boiling point almost remains constant, and the latent heat of vaporization largely decays.

The evaporation performance depends on the comprehensive physical and heat-transfer parameters that are related to the nanoparticle concentration. The evaporation rate constant increases at lower GNP concentrations because the migration time of NPs is lower two orders of magnitude than the evaporation time, whereas the evaporation rate constant decreases with continuously increasing GNP concentration because of the formation of porous shell structures at the droplet surface. The evaporation rate constant of GNP/n-decane nanofluid fuels reaches maximum at a GNP concentration of 1.75 wt %, which is enhanced by 12.6% compared to the base fuel n-decane. Among these physical and heat-transfer properties, the latent heat of vaporization is one of the best crucial parameters to affect the evaporation performance. Additionally, the evaporation rate constant has a linear function as the temperature of ambient hot air and also depends on the concentration of the surfactant SP-80.

Experimental Section

Materials

GNPs were purchased from Deke Daojin Science and Technology Co., Ltd., Beijing, China. The purity reached ∼99.9% as observed using inductively coupled plasma analysis. The specific surface area was found to be 180 m2/g by Brunauer–Emmett–Teller analysis. The size distribution of GNPs was found to be 100 nm∼1.0 μm using a particle size analyzer (Nanotrac Flex, Microtrac Co., America). GNPs were characterized using a scanning electron microscope (SEM, Quanta 600FEG). The morphology (Figure ) illustrates that the GNPs had a layered, planar structure, and the layer thickness was of ∼35 nm. The base fuel n-decane and the surfactant Sorbitan monooleate (SP-80) were purchased from Macklin Biochemical Co., Ltd., Shanghai, China. The purity of n-decane and the surfactant was 98 and 99.5%, respectively. Their physical properties have been demonstrated in our previous work.[46]

Figure 10

SEM morphology of GNPs.

Preparation of GNP/n-Decane Nanofluid Fuels

The n-decane-based nanofluid fuels with various GNP concentrations were prepared using the two-step method: (1) Certain weight of GNPs were added into the certain volume mixture of n-decane and SP-80 to produce suspensions. (2) A sonicator (frequency of 40 KHz, power of 120 W, YD0203, Shenzhen Yunyi Technology Co., Ltd., P.R. China) was then used and ultrasonic waves were exerted for certain time to disperse GNPs evenly in n-decane to avoid agglomeration among GNPs.

The stable dispersibility of NPs is a critical issue in the research and applications of NPs in liquid fuels. The stability of nanofluid fuels mainly rests on three aspects, that is, NP concentration, surfactant concentration, and ultrasonication time. In the present work, the effects of GNP concentration, surfactant SP-80 concentration, and ultrasonication time on the stability of GNP/n-decane nanofluid fuels were investigated in detail. Better stability was observed under lower GNP concentrations. The obtained optimum surfactant SP-80 concentration was 0.5 vol %, while the optimum ultrasonication time was 10 min under a GNP concentration of 0.1 wt % (see Supporting Information). In general, the homogeneous suspension as prepared in this manner could remain stable for 1 h without significant sedimentation of GNPs (see Figure ), which is sufficient to conduct the physical and heat-transfer property and evaporation characteristic test experiments in this work. The long-term stable dispersibility of NP suspending tens of days/weeks would need to be further improved.

Figure 11

Pictures of as-prepared GNP/n-decane nanofluid fuels in sequence (GNP of 0.1 wt %, SP-80 of 0.5 vol %, and ultrasonication time of 10 min).

Physical and Heat-Transfer Properties

The physical properties of GNP/n-decane nanofluid fuels including density, surface tension, and dynamic viscosity were measured in detail using the standard density bottle method, Du Noüy Ring Tensiometer, and Ostwald viscometer, respectively. The measurement method and the detailed procedure have been described in our previous work.[46]

The literature shows that the addition of NPs exhibits a significant enhancement of thermal conductivity in comparison to the base fluid. Lee et al.[56] summarized that there are five groups of models by the main underlying mechanism to predict the thermal conduction of nanofluids, including classical effective medium theory (EMT), nanoscale layers, Brownian motion, agglomeration, and other mechanisms. In the current work, the thermal conductivity of GNP/n-decane nanofluid fuels was obtained by the classical EMT. The thermal conductivity of GNPs is 129 W/(m·K), which is much higher than that of n-decane (0.13 W/(m·K)), that is, kp/kbf ≫ 100. According to the model developed by Hamilton and Crosser,[50] taking into account irregular particle geometries by introducing a shape factor of GNPs, the thermal conductivity of GNP/n-decane nanofluid fuels can be expressed as:where k is the thermal conductivity, and the subscripts nf, bf, and np represent the nanofluid fuel, base fuel, and NPs, respectively. φ represents the GNP concentration, n is the empirical shape factor n = 3/ψ, and ψ is the particle sphericity.

The boiling points of n-decane, SP-80, and GNPs at atmospheric pressure (0.1 MPa) are 447, 852, and 5100 K, respectively. The boiling points of GNP/n-decane nanofluid fuels were measured by the atmospheric distillation method.[57] The latent heat of vaporization of GNP/n-decane nanofluid fuels was calculated by a formula proposed by Mehregan et al.:[58]where hfg is the latent heat of vaporization, ρ is the density, and Tb is the boiling point. The latent heat of vaporization of n-decane is 363 kJ/kg at atmospheric pressure and room temperature.[59] The latent heat of vaporization of solid GNPs is replaced by the heat of sublimation, that is, 714 kJ/kg.[60]

Experimental Setup for Evaporation

Figure shows the schematic of the experimental setup, including the hot-air supply module, droplet suspension and position module, high-speed imaging and thermal imaging module, and illumination module. In the hot-air supply module, cold air intake was compressed by an air compressor and heated in the heating pipe to produce hot air. The volume flux was adjusted by the intake valve and mass flow controller, and the volume flow ranged 0∼3 L/min. The temperature of hot air was controlled by a heating power controller, ranging from room temperature to 850 °C with a relative uncertainty of less than 2%. The temperature distribution of hot air in the outlet region of the heating pipe was calibrated by a K-type thermal couple. Figure shows a calibration example of temperature field at the outlet of heating tube at a hot air temperature of 600 °C. It is noted that the droplets should be placed into the region marked “a” and “b” to guarantee the accuracy of heating temperature.

Figure 12

Schematic of the experimental setup.

Figure 13

Calibration graph of temperature field at the outlet of the heating tube (Tair of 600 °C).

Therefore, in the droplet suspension and position module, a precise manipulator was used to position the droplets into the hot air with an uncertainty of ±50 μm. In experiment, a droplet was first produced by an accurate syringe. The droplet was then transferred and suspended on the tip of the silicon fiber. The silicon fiber installed at the arm ending of the precise manipulator was moved into the hot air and ensured the droplet in the temperature region as required. The initial diameters of droplets almost remained at ∼1.0 mm. In the high-speed imaging and thermal imaging module, a high-speed camera (Phantom 310R, America) with a lens (AT-X M100 AF PRO, Tokina, Japan) was used to record the evaporation videos at a frame ratio of 30,000 fps. An infrared thermal imaging camera (FLIR 655sc, America) with a lens of 25 μm resolution was fixed to acquire the surface temperatures of droplets at a frame ratio of 200 fps. The two cameras were controlled by a synchronizer to keep the time accuracy of sampling time. In the illumination module, backlight illumination with a light-emitting diode lamp and a condenser were utilized to provide the uniform bright view field for clear imaging.

The diameters of droplets were measured by the digital imaging treatment reported in our previous work.[61]