T C de Goede1, N Laan1, K G de Bruin1,2, D Bonn1. 1. Van der Waals-Zeeman Institute, Institute of Physics , University of Amsterdam , Science Park 904 , 1098 XH Amsterdam , Netherlands. 2. Netherlands Forensic Institute , Laan van Ypenburg 6 , 2497 GB The Hague , Netherlands.
Abstract
We investigate the impact velocity beyond which the ejection of smaller droplets from the main droplet (splashing) occurs for droplets of different liquids impacting different smooth surfaces. We examine its dependence on the surface wetting properties and droplet surface tension. We show that the splashing velocity is independent of the wetting properties of the surface but increases roughly linearly with increasing surface tension of the liquid. A preexisting splashing model and simplification are considered that predict the splashing velocity by incorporating the air viscosity. Both the splashing model and simplification give a good prediction of the splashing velocity for each surface and liquid, demonstrating the robustness of the splashing model. We also show that the splashing model can also predict the splashing velocity of blood, a shear-thinning fluid.
We investigate the impact velocity beyond which the ejection of smaller droplets from the main droplet (splashing) occurs for droplets of different liquids impacting different smooth surfaces. We examine its dependence on the surface wetting properties and droplet surface tension. We show that the splashing velocity is independent of the wetting properties of the surface but increases roughly linearly with increasing surface tension of the liquid. A preexisting splashing model and simplification are considered that predict the splashing velocity by incorporating the air viscosity. Both the splashing model and simplification give a good prediction of the splashing velocity for each surface and liquid, demonstrating the robustness of the splashing model. We also show that the splashing model can also predict the splashing velocity of blood, a shear-thinning fluid.
When impacting a dry, smooth surface,
a droplet either spreads
over the surface (for low-impact velocities) or disintegrates into
smaller droplets (for high-impact velocities). This so-called splashing
phenomenon has been the subject of numerous studies over the last
several decades and is of relevance for a wide range of practical
applications such as crop spraying,[1,2] rain drops
impacting porous stones,[3,4] and forensic research.[5−7] The splashing velocity vsp is defined
as the critical value of the impact velocity of the droplet beyond
which splashing occurs (Figure ). Many studies have tried to find an empirical relation between
the splashing velocity and fluid parameters[8−13] and between the splashing velocity and surface properties.[14−17] In addition, Xu et al.[18] showed that
the atmospheric conditions have a significant influence on droplet
splashing,[13,17,19] implying that the air viscosity is also an important parameter.
To include the air viscosity, Riboux and Gordillo recently proposed
a theoretical model for impact and splashing on smooth surfaces.[20] They postulated that splashing occurs because
of the breakup of a small liquid film that lifts off the surface just
after the impact due to the lift force generated by the surrounding
air. In the model, the fluid and substrate properties govern the splashing
as well as the air viscosity; in ref (20), a quantitative agreement was found between
the model and experiments on a single substrate.
Figure 1
(a) Droplet impact for v < vsp where no splashing
occurs. (b) Droplet impact for v ≥ vsp where splashing
occurs.
(a) Droplet impact for v < vsp where no splashing
occurs. (b) Droplet impact for v ≥ vsp where splashing
occurs.Numerous experimental studies
have investigated splashing;[8−19] however, the influence of the wetting properties of the surface
on splashing has not been considered in detail. It has recently been
shown that the wetting properties of the surface affect droplet spreading
at low-impact velocities.[21,22] In the model of Riboux
and Gordillo, the splashing velocity also depends on the surface properties.[20] The surface tension and the wetting properties
of the surface are closely linked through Young’s law.[23] Therefore, the dependence of the splashing velocity
on surface tension should also be taken into account for a droplet
of a given size. Furthermore, the splashing model has not yet been
tested for more complex fluids such as, for example, blood. In forensics,
being able to determine when blood splashes could help in distinguishing
between the stains that are formed from the droplet impact (impact
stain) or the stains formed by absorbing blood during contact with
a blood source (transfer stain).[7,24] Blood is a shear-thinning
fluid, but studies have shown that blood can be approximated as a
Newtonian fluid when it is subjected to high shear rates.[25−27] Laan et al. showed in 2014 that the spreading of blood is similar
to the spreading of Newtonian fluids, which was attributed to the
high shear rate inside the droplet during spreading.[21] As splashing occurs during spreading (Figure b), the questions are whether
blood can also be approximated as a Newtonian fluid during splashing
and whether the splashing velocity of blood can also be predicted
using the splashing model for Newtonian fluids of ref (20).In this paper,
we systematically investigate the effect of surface
tension of the liquid and the wetting properties of the surface on
the splashing velocity of the droplet. Using high-speed camera footage,
we measure the splashing velocity of a set of Newtonian ethanol–water
mixtures and shear-thinning blood impacting on different surfaces
at laboratory conditions. We compare the results with the splashing
model of Riboux and Gordillo.[20] We show
that the splashing model predicts the splashing of both ethanol–water
mixtures and blood very well. Although the model is consistent with
the experimental data, the calculation is complex and depends on several
parameters that have to be inferred from the experimental conditions
and have to be calculated separately. We therefore use a simplification,
also given by Riboux and Gordillo, valid for low Ohnesorge numbers
and atmospheric conditions, which is the situation that pertains to
most practical applications and show that it predicts the splashing
velocity very well. These results show that the splashing velocity
is independent of the surface wetting properties and that blood can
be approximated as a Newtonian fluid during splashing.
Materials and Methods
To measure the splashing velocity vsp, droplet impacts were recorded using a high-speed
camera (Phantom
Miro M310). The droplets were generated from a blunt-tipped needle
(needle diameter 0.4 mm) using a syringe pump, where the needle was
suspended above the substrate at a certain height. By systematically
increasing the height of the needle and checking whether the droplet
merely spreads over the surface (Figure a) or splashes (Figure b) for each height, we determined the initial
droplet diameter D0 and impact velocity v at the onset of splashing for each liquid. The fluid parameters
of each liquid are given in Table . Three different surfaces were investigated for the
ethanol–water mixtures: stainless steel, glass (Objektträger,
Menzel Glaser, Thermo Scientific), and parafilm. All three surfaces
were considered smooth, each having an arithmetic average roughness Ra below 0.5 μm.[22] For blood, the splashing velocity was determined from blood droplet
impact footage on glass (θst ≈ 20°; where
θst is the static contact angle of water[21]), acrylic glass [poly(methyl methacrylate),
PMMA; θst ≈ 70°], Trespa (θst ≈ 82°), and polyoxymethylene (POM; θst ≈ 79°) surfaces using the data of ref (21). The density (1055 kg/m3), surface tension (59 mN/m), and viscosity (4.8 mPa·s)
of the blood used are also given by Laan et al.[21] Both the impacts of Newtonian fluids and blood were measured
at 21 °C and atmospheric pressure. During the experiments with
blood, the anti-coagulant ethylenediaminetetraacetic acid was added
to prevent the coagulation of blood.
Table 1
Ethanol
Mass Fraction, Density, Surface
Tension, and Viscosity Values of Water, Ethanol, and Ethanol–Water
Mixtures Used in This Studya
wt (%)
density (kg/m3)
surface
tension (mN/m)
viscosity (mPa·s)
0
997.0
72.0
0.89
5
989.0
56.4
1.23
10
981.9
48.1
1.50
15
975.3
42.7
1.82
20
968.7
38.0
2.14
40
935.3
30.2
2.85
60
891.1
26.2
2.55
80
843.6
23.8
1.88
100
789.3
21.8
1.20
Source: refs (28) and (29).
Source: refs (28) and (29).
Results and Discussion
For each ethanol–water
mixture, the contact angle θ
on steel, glass, and parafilm was measured using the sessile drop
method.[30,31] Because of surface inhomogeneities, a droplet
deposited on a surface does not have a unique contact angle but attains
a contact angle that ranges between the advancing (θa) and receding (θr) contact angle.[32] In Figure a, θa is plotted as a function of the surface tension.
In glass, the contact angles of each fluid were too small to be determined.
Therefore, each fluid is considered to be completely wetting the glass
surface (θa ≈ 0°). Do note that the glass
used in this study has a lower contact angle compared to the glass
used in the study of ref (21). All liquids have a similar receding angle of roughly 20°
when deposited on steel. When deposited on parafilm, the receding
contact angles of all liquids were consistently 10° lower than
their corresponding advancing angle.
Figure 2
(a) Advancing contact angle as a function
of surface tension for
steel (blue circles), glass (yellow squares), and parafilm (red diamonds)
substrates. (b) Cosine of θa as a function of surface
tension. The blue solid, yellow dashed, and red dotted lines depict
the linear fits of the static contact angles for water, glass, and
parafilm, respectively.
(a) Advancing contact angle as a function
of surface tension for
steel (blue circles), glass (yellow squares), and parafilm (red diamonds)
substrates. (b) Cosine of θa as a function of surface
tension. The blue solid, yellow dashed, and red dotted lines depict
the linear fits of the static contact angles for water, glass, and
parafilm, respectively.To characterize the difference in wetting properties of the
three
substrates, Young’s law is used, which describes the force
balance between the interfacial tensions of the substrate, liquid
droplet, and the surrounding vapor[23,33]where σLV is the liquid–vapor
interfacial tension of the liquid. σSV and σSL are the solid–vapor and solid–liquid interfacial
tensions, respectively. Zisman assumed that the difference between
σSV and σSL is a property of the
solid that gives the surface free energy of the substrate.[23,31,34] (σSV –
σSL) can be determined by finding the critical surface
tension from the contact angle measurements: the surface tension at
which a droplet completely wets the surface. By plotting the cosine
of the measured contact angles as a function of surface tension (Figure b), (σSV – σSL) is found by fitting a straight
line through the data using the least squares method and extrapolating
the fits to the surface tension for which the liquid would fully wet
the surface (cos(θ) = 1). Because glass is completely wetted
by all evaluated liquids, the critical surface tension of glass is
higher than 71.99 mN/m. For steel and parafilm, a critical surface
tension of 14 ± 1 and 19 ± 1 mN/m is found, respectively.
Therefore, liquids wet the parafilm less compared to the steel surface.The measured splashing velocities of the ethanol–water mixtures
are plotted as a function of liquid surface tension in Figure a. The graph shows that the
splashing velocity increases roughly linearly with the surface tension.
For pure water droplets, no splashing was observed within the velocity
range investigated here (0.1 < v < 4.7 m/s).
No significant difference between the three evaluated surfaces is
observed, implying that the splashing velocity is independent of the
wetting properties of the substrate. The same holds for blood (Figure b), where the splashing
velocity remains constant (∼3.47 m/s) for all observed substrates.
These results suggest that the wetting properties of the substrate
do not influence the splashing velocity of both ethanol–water
mixtures and blood, which is the first useful conclusion. This is
remarkable as the droplet is in full contact with the substrate during
splashing.[35,36] However, in ref (35), it was also observed
that just before splashing, the edge of the liquid sheet dewets the
surface from which the satellite droplets are formed (see Figure a–d).
Figure 3
(a) Measured
splashing velocity as a function of surface tension
for stainless steel (blue circles) and borosilicate glass (yellow
squares). The green line depicts the splashing velocity as given by
the full splashing model [eq ], whereas the red dashed line shows the splashing velocity
as calculated from the simplified model [eq ]. (b) Measured splashing velocity of blood
(dark blue) for glass (circle), PMMA (square), POM (diamond), and
Trespa (triangle) compared to the predicted splashing velocity of
the full splashing model (open green symbols) and simplification (open
red symbols).
Figure 4
(a–d) High-speed
camera footage of the lifted liquid sheet
after impact (with t = 0 s, the moment of droplet
impact). (e) Averaged measured wedge angle α (green circles)
as a function of time on stainless steel. The error bar is given by
the SD. The black dotted line is the best linear fit of wedge angle
measurements. The vertical red lines depict the different stages of
liquid sheet spreading as given in (a–d): the emergence of
the liquid sheet from the droplet (a), radial expansion (b), formation
of liquid fingers at the front of the liquid (c), and droplet detachment
(d).
(a) Measured
splashing velocity as a function of surface tension
for stainless steel (blue circles) and borosilicate glass (yellow
squares). The green line depicts the splashing velocity as given by
the full splashing model [eq ], whereas the red dashed line shows the splashing velocity
as calculated from the simplified model [eq ]. (b) Measured splashing velocity of blood
(dark blue) for glass (circle), PMMA (square), POM (diamond), and
Trespa (triangle) compared to the predicted splashing velocity of
the full splashing model (open green symbols) and simplification (open
red symbols).(a–d) High-speed
camera footage of the lifted liquid sheet
after impact (with t = 0 s, the moment of droplet
impact). (e) Averaged measured wedge angle α (green circles)
as a function of time on stainless steel. The error bar is given by
the SD. The black dotted line is the best linear fit of wedge angle
measurements. The vertical red lines depict the different stages of
liquid sheet spreading as given in (a–d): the emergence of
the liquid sheet from the droplet (a), radial expansion (b), formation
of liquid fingers at the front of the liquid (c), and droplet detachment
(d).Although surface roughness is
not considered in this paper, it
can also influence splashing.[16,17] On rough surfaces,
the liquid sheet does not detach from the surface prior to breakup,
giving rise to a different splash known as a “prompt splash”.[9,17] The influence of surface roughness was not considered in the splashing
model of ref (20).
How the surface roughness can be incorporated into the splashing model
is currently unknown and beyond the scope of this paper.To
describe splashing, in ref (20), the ejection time te (the
moment a thin liquid sheet appears from the droplet after impact)
is first calculated numerically using the momentum balance equationwhere and are the Reynolds
and Ohnesorge numbers,
respectively; ρ is the density, μ is the viscosity, σ
is the surface tension of the liquid (equal to σLV), R is the radius (D0/2), and v is the impact velocity of the droplet.
Using the ejection time, the velocity V and thickness H of the thin liquid sheet can be calculatedUsing the sheet velocity and thickness,
the aerodynamic lifting
force, consisting of the suction (∼KlμgV) and lubrication forces (∼KuρgV2H), can then be determined.
Here, μg and ρg are the viscosity
and density of the air, respectively. The suction force is caused
by the negative pressure difference above the liquid sheet due to
the Bernoulli principle, whereas the lubrication force is generated
by the air moving underneath the liquid sheet, creating a positive
pressure difference that pushes the lamella upward. Ku and Kl are constants. While Ku ≈ 0.3 was determined in ref (20) by numerical calculations, Kl can be calculated using the sheet thickness,
mean free path of the molecules λ in the surrounding air, and
wedge angle α, which is the angle between the lifted sheet and
the surfaceAccording to ref (20), the wedge angle is equal to 60° and should
be dependent on
the wetting properties of the surface.[20]Having determined these parameters, a dimensionless number
defined
as the splashing ratio β is calculated, which indicates the
magnitude of the aerodynamic forces needed to overcome the surface
tension to break up the liquid sheet into smaller dropletsComparing eqs and 5 to both their own experiments and previous work,[13,18,37] Riboux and Gordillo determined
that the value of the splashing ratio should be around 0.14.To calculate the splashing velocity from the splashing model of
Riboux and Gordillo, eq is rewritten as a quadratic equation for the splashing velocity vsp, as a function of the fluid parameters and
the ejection timeTo compare the splashing model with our experiments, eqs and 3b are
substituted into eqUsing eqs and 7, the ejection time can be determined numerically,
which in turn can be used to calculate the splashing velocity. For
both Newtonian fluids and blood, the measured droplet radius was averaged.
The best fit of the splashing model on our data (green line, Figure a,b) was determined
by minimizing the sum of square residuals using the splashing ratio
as a fit parameter. The obtained best fit value is equal to 0.135
± 0.008, which is close to the value 0.14 found by Riboux and
Gordillo. The error on the splashing ratio is determined by calculating
the splashing ratio for each fluid and taking the SD of all splashing
ratios. Previously, the splashing model was only verified for borosilicate
glass substrates.[13,37] Here, we show that the splashing
model can be universally applied to any smooth surface. Furthermore,
the splashing model also accurately predicts the splashing velocities
of blood (Figure b),
where the splashing ratio of blood is nearly identical to the splashing
ratio of the ethanol–water mixtures (βblood = 0.141 ± 0.001). The fact that blood can be described with
the splashing model of Riboux and Gordillo suggests that blood behaves
as a Newtonian fluid during splashing, similar to droplet spreading.[21]The wetting properties of the surface
should, according to Riboux
and Gordillo,[20] determine the wedge angle
α. However, Riboux and Gordillo gave no explanation on why the
value of the wedge angle should be 60°. To investigate the time
dynamics of the wedge angle during splashing, we measure the wedge
angle; in our experiments, we let ethanol droplets impact a stainless-steel
surface at an impact velocity comparable to the splashing velocity
(v = vsp). Recording
the impact with the high-speed camera gives the time evolution of
liquid sheet expansion, which is depicted in Figure a–d. We observe that after the moment
of the sheet ejection (Figure a), the liquid sheet starts to radially expand outward (Figure b). After a certain
time, liquid fingers start to form at the edge of the sheet (Figure c), after which satellite
droplets detach from the sheet (Figure d) and splashing occurs.From each recorded frame,
we extracted the instantaneous wedge
angle, which is shown in Figure e. In this graph, the wedge angle seems to increase
linearly with time until the moment of finger formation (Figure c). Assuming that
the wedge angle keeps increasing linearly until droplet detachment,
we can fit a simple linear function (α = At) to the data of Figure e and extrapolate the wedge angle to the moment the droplets
detach from the liquid sheet. Using this method, we obtain an average
wedge angle of α = 59° ± 8° at the moment of
droplet detachment (Figure d), which is similar to the value of the wedge angle postulated
by Riboux and Gordillo. These results, therefore, show that the wedge
angle given in ref (20) should be the wedge angle at the moment of droplet detachment because
the angle varies continuously in time. The important conclusion from
our experiments is that the wedge angle does not depend on the surface
and the behavior found here is therefore universal.Although
the splashing model of Riboux and Gordillo provides a
good prediction of the splashing velocity, the required calculations
are rather complex: substitute eq into eq , numerically solve for te, and use the
result to find the splashing velocity with eq . Furthermore, these calculations depend on
several unintuitive parameters, for instance α and λ.Most practical situations deal with fluids with a low Ohnesorge
number (Oh ≪ 1) and take place at atmospheric
conditions. Riboux and Gordillo also proposed a simplification for
low Oh fluids and found an approximate splash criteria
that also showed good agreement with previous experiments.[10,37] However, no detailed comparison was made between the splashing velocity
prediction of both the simplification and the full-splashing model.
It is unknown whether the deviation between the full splashing model
and simplification is small enough to provide an accurate splashing
velocity prediction with simplification. Therefore, we will follow
the same approximations given by Riboux and Gordillo and compare the
splashing velocity given by both the full splashing model and simplification.If we evaluate eq for low Ohnesorge numbers, the first term on the left side in the
equation dominates, allowing us to write the ejection time as a function
of the Weber number We asConsequently, the lamella thickness
and spreading velocity are
given byFurther simplification
can be made for the constant Kl [eq ].
If H is calculated with
the measured splashing velocity and initial diameter of the drops,
an average value of 7.41 × 10–6 m is obtained.
Because λ ≈ 10–8 m, the ratio λ/H is in the order of 10–3. As λ/H is small, the second logarithmic term can be approximated
with the first term of the Taylor approximationBecause for , the above term can be neglected, giving
a simplified equation for KlThe final assumption is that the lubrication force dominates
over
the suction force under atmospheric conditions,[20] implying that eq can be simplified toFinally, by substituting the simplified
terms of V [eq ] and Kl [eq ], β can be rewritten as
a function of splashing velocity vsp,
initial diameter D0, density ρ,
surface tension σ, wedge angle α, and viscosity of the
air μgThus, it is possible to significantly simplify Riboux and
Gordillo’s
splashing model for low Ohnesorge number fluids and atmospheric conditions,
where the splashing ratio is only dependent on the fluid parameters
and viscosity of the air, as the wedge angle seems to be identical
for all smooth surfaces.To compare the simplification with
the experimental data, eq can be rewritten into
a simple analytical expression for the splashing velocityThen, the splashing velocity is uniquely
determined by density,
surface tension, and initial diameter of the droplet, viscosity of
the air, wedge angle, and splashing ratio. The simplification (red
dashed line), when plotted together with the experimental data and
the full splashing model, as shown in Figure , shows good agreement. Again, the splashing
ratio (βsimpl) was used as a fitting parameter, where
the best fit value of βsimpl of the ethanol–water
mixtures is equal to 0.120 ± 0.008, which is slightly lower than
the splashing ratio of the full splashing model. This is expected
as the suction force term is neglected in the simplification. For
blood (red open symbols; Figure b), the splashing ratio also decreases (βsimpl,blood = 0.112 ± 0.001), but still attains a similar
value as the splashing ratio of the ethanol–water mixtures.
The predicted values of the full splashing model and the simplification
are similar, which shows that the simplification gives a relatively
good prediction of the splashing velocity for both ethanol–water
mixtures and blood.
Conclusion
To summarize, we systematically
investigated the influence of the
wetting properties of the surface on the splashing velocity of Newtonian
fluid and blood (a shear thinning liquid) droplets impacting a smooth
surface. We showed that the wetting properties do not influence the
splashing velocity for both Newtonian fluids and blood, indicating
that splashing is independent of the wetting properties of the surface.
Then, we compared the experimental data with a preexisting splashing
model and showed that the model can be universally applied to any
smooth surface. Furthermore, the splashing model can also be used
to predict the splashing velocity of blood. By measuring the wedge
angle, we confirmed that the wedge angle used in the splashing model
is equal to 60° at the moment of droplet detachment from the
liquid sheet. Finally, we evaluated a simplification of the preexisting
splashing model for low Ohnesorge number fluids at atmospheric conditions.
We showed that the predictions of the simplification are comparable
to the full splashing model, allowing for an easier prediction of
splashing of low Ohnesorge number fluids at atmospheric conditions
for any smooth surface.
Authors: John M Kolinski; Shmuel M Rubinstein; Shreyas Mandre; Michael P Brenner; David A Weitz; L Mahadevan Journal: Phys Rev Lett Date: 2012-02-15 Impact factor: 9.161
Authors: Andrzej Latka; Ariana Strandburg-Peshkin; Michelle M Driscoll; Cacey S Stevens; Sidney R Nagel Journal: Phys Rev Lett Date: 2012-07-31 Impact factor: 9.161