ORIGINAL RESEARCH
published: 17 March 2022
doi: 10.3389/feart.2022.812311
Vesiculation of Rhyolitic Melts Under
Oscillatory Pressure
Gilles Seropian 1*, Ben M. Kennedy 1, Jackie E. Kendrick 2,3, Yan Lavallée 2,
Alexander R. L. Nichols 1, Felix W. von Aulock 2, Donald B. Dingwell 4, Kai-Uwe Hess 4,
Anthony Lamur 2, Jenny Schauroth 2, Jérémie Vasseur 4 and Fabian B. Wadsworth 5
1
School of Earth and Environment, University of Canterbury, Christchurch, New Zealand, 2Department of Earth, Ocean and
Ecological Sciences, University of Liverpool, Liverpool, United Kingdom, 3School of Geosciences, University of Edinburgh,
Edinburgh, United Kingdom, 4Department of Earth and Environmental Sciences, Ludwig-Maximilians-Universität München,
Munich, Germany, 5Department of Earth Sciences, Durham University, Durham, United Kingdom
Edited by:
Finnigan Illsley-Kemp,
Victoria University of Wellington,
New Zealand
Reviewed by:
Simon James Barker,
Victoria University of Wellington,
New Zealand
Benjamin James Andrews,
Smithsonian Institution, United States
*Correspondence:
Gilles Seropian
[email protected]
Specialty section:
This article was submitted to
Volcanology,
a section of the journal
Frontiers in Earth Science
Received: 10 November 2021
Accepted: 02 February 2022
Published: 17 March 2022
Citation:
Seropian G, Kennedy BM, Kendrick
JE, Lavallée Y, Nichols ARL, von
Aulock FW, Dingwell DB, Hess K-U,
Lamur A, Schauroth J, Vasseur J and
Wadsworth FB (2022) Vesiculation of
Rhyolitic Melts Under
Oscillatory Pressure.
Front. Earth Sci. 10:812311.
doi: 10.3389/feart.2022.812311
Magma ascending in the Earth’s crust can undergo oscillations in pressure, from ultra-low
frequency changes associated with tectonics, to relatively higher frequency oscillations
associated with seismicity. Seismic waves travelling through shallow magma bodies can
lead to a range of unrest phenomena and potentially trigger volcanic eruptions. The
mechanisms by which pressure oscillations can induce unrest or eruption remain debated.
Here, we experimentally impose pressure oscillations on magma and study how they affect
vesiculation processes. We use cylindrical samples (4.00 mm long, 4.85 mm diameter) of
hydrous rhyolitic obsidian (0.11 ± 0.01 wt% H2O) placed in alumina (AL23) crucibles and
vary pressure by the uniaxial loading of an alumina plunger in a thermo-mechanical
analyzer. We monitor vesiculation at temperatures of 950–990°C and confining
pressure of 177 kPa. We perform two types of experiment: 1) “static” experiments (at
constant pressure) and 2) “oscillating” experiments in which we impose sinusoidal
pressure oscillations of up to 71 kPa upon the static pressure (i.e., between 106 and
250 kPa). In both cases, we dilatometrically observe sample expansion driven by
vesiculation. Post-experimental bubble textures reveal that bubbles formed
preferentially at the sample margins. For the oscillating experiments, the sample
expansion rate is lower than in the static experiments, and there are fewer vesicles at
the sample margins. We examine the constituent processes of bubble formation
(nucleation, growth, coalescence) and gas loss (diffusion, permeable flow) occurring
during static experiments and with the added element of pressure oscillations. The
most likely mechanism responsible for reduced sample expansion is that pressure
oscillations drive the sample in and out of water saturation conditions and thus reduce
the fraction of residence time over which bubble nucleation and/or growth are driven.
Future work will be needed to confirm this hypothesis. These results are relevant to the
study of earthquake-volcano interactions, where a magma body that sits close to volatile
saturation is subject to pressure fluctuations.
Keywords: vesiculation, bubbles, pressure oscillations, rhyolite, high temperature, experimental
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Vesiculation Under Oscillatory Pressure
1 INTRODUCTION
et al., 1999). This dilatometric approach enables the
volumetric monitoring of vesiculation. We report the results of
a series of high temperature (950–990°C) experiments where
pressure oscillations are imposed on vesiculating rhyolitic
melt. We focus on how the various bubble processes
(nucleation, growth, coalescence and gas loss) are affected by
the oscillations. We then explore the relevant geological
conditions where our results could be applied and examine the
potential applications of this novel type of experiment.
Gas bubbles play a fundamental role in driving, modulating, and
recording volcanic and magmatic processes. Characterizing the
kinetics of processes associated with vesiculation is thus a key goal
of modern volcanology. The processes related to the nucleation,
growth, coalescence and loss of bubbles are complex, often nonlinear, and with numerous potential feedbacks (e.g., Sparks, 1978;
Gonnermann and Manga, 2007). High-temperature experiments
provide useful phenomenological insights into how bubbles
might behave in magma in nature, whilst minimizing the
scaling issues associated with using non-magmatic analogue
liquids (Fiege and Cichy, 2015). In the majority of high
temperature experiments to date, vesiculation has been
triggered by inducing supersaturation via isothermal
decompression (e.g., Hurwitz and Navon, 1994; Lyakhovsky
et al., 1996; Gardner et al., 1999; Mourtada-Bonnefoi and
Laporte, 1999; Mangan and Sisson, 2000; Martel and Bureau,
2001; Mourtada-Bonnefoi and Mader, 2001; Mourtada-Bonnefoi
and Laporte, 2002; Gardner and Denis, 2004; Mourtada-Bonnefoi
and Laporte, 2004; Mangan et al., 2004a,b; Mangan and Sisson,
2005; Gardner, 2007; Cluzel et al., 2008; Hamada et al., 2010;
Cichy et al., 2011; Gondé et al., 2011; Nowak et al., 2011;
Pichavant et al., 2013; Fiege et al., 2014; Fiege and Cichy,
2015; Martel and Iacono-Marziano, 2015; Gardner et al., 2018;
Hajimirza et al., 2019) or isobaric heating (e.g., Murase and
McBirney, 1973; Bagdassarov et al., 1996; Stevenson et al.,
1997; Yamashita, 1999; Liu and Zhang, 2000; Bai et al., 2008;
Yoshimura and Nakamura, 2008; Lautze et al., 2011; Baker et al.,
2012; Fife et al., 2012; Masotta et al., 2014; Pistone et al., 2015;
Ryan et al., 2015; von Aulock et al., 2017; Pleše et al., 2018;
Cáceres et al., 2020). Only recently has experimentation focused
on vesiculation processes under oscillatory pressure conditions
(Masotta and Keppler, 2017), which may be of importance in
magmatic scenarios.
Pressure fluctuations are highly likely to occur during magma
storage and transport. The source of pressure oscillations may be
external (e.g., earthquake or tidal; Manga and Brodsky, 2006;
Girona et al., 2018) or internal (e.g., unsteady and pulsatory
magma flow or gas-filled cavity resonance; Chouet, 1996; Wylie
et al., 1999; Longo et al., 2012). In particular, constraining the
effects of seismic waves on vesiculating magma is one key to
understanding earthquake-volcano interactions, as evidence
indicates that seismic waves can trigger a range of volcanic
responses (e.g., Hill et al., 2002; Manga and Brodsky, 2006;
Eggert and Walter, 2009; Sawi and Manga, 2018) depending
on specific conditions dictated by the volcano type and the
earthquake characteristics (Seropian et al., 2021).
Masotta and Keppler (2017) employed a hydrothermal
moissanite cell, enabling direct optical observation of bubbles
growing in a melt under pressure oscillations. They investigated
mean pressures of 50 and 60 MPa, with oscillation amplitudes
between 5 and 40 MPa, but their experiments were limited to
samples <100 µm thick. We seek to extend their analysis to larger
samples. Here, we employ thicker samples (4 mm), in
experiments based on confined or “contained” dilatometry
(Bagdassarov et al., 1996; Stevenson et al., 1997; Gottsmann
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2 MATERIALS AND METHODS
2.1 Starting Material
All samples employed here were prepared from a single ~20 ×
10 × 10 cm block of aphyric, bubble-free peraluminous rhyolitic
obsidian, collected from the AO sample site of Tuffen and Castro
(2009) at Hrafntinnuhryggur, Krafla, Iceland (Figure 1A;
Table 1). We drilled cylindrical cores (4.85 ± 0.05 mm
diameter) from the block, and cut them into 4.00 ± 0.05 mmlong samples using a diamond wire saw. A thin disc was also
obtained from between each successive sample, and prepared as a
free-standing wafer, polished on both surfaces, for Fouriertransform infrared (FTIR) spectroscopy.
Water content was determined via FTIR spectroscopy using a
Bruker Vertex 70 spectrometer attached to a Bruker Hyperion
2000 IR-microscope at the University of Canterbury. The
spectrometer is equipped with a Globar source, an MCT
detector cooled with liquid N2 and a KBr beamsplitter. The
spectrometer and microscope were continuously purged with
N2 gas. Samples were resting on an IR-invisible BaF2 window.
Transmittance spectra were recorded at 10 aligned spots, with a
100 µm square aperture limiting the beam, in the wavenumber
range 6,800–400 cm−1, with a resolution of 4 cm−1, using 128
scans and corrected against a background measured before each
set of sample measurements. We measured the height of the
3,570 cm−1 peak above a linear baseline and used a density of
2,460 kg m−3, calculated with DensityX, for the composition
given in Table 1 at 20°C and 1 bar (Iacovino and Till, 2018).
Similarly to Tuffen and Castro (2009), we assumed that all of the
water is present as OH− and used a molar absorptivity coefficient
of 100 ± 2 L mol−1 cm−1 (Newman et al., 1986). Reflectance
spectra were also collected at all measurement locations and
used to calculate local thickness where possible, following the
method of Wysoczanski and Tani (2006) with a refractive index
of 1.5, appropriate for rhyolite glasses (Long and Friedman,
1968). Alternatively, in cases where reflectance spectra did not
allow thickness to be determined, we measured thickness
manually with a digital displacement micrometer (following
von Aulock et al., 2014). All our samples are homogeneous
within measurement uncertainty with an average water
content of 0.11 ± 0.01 wt% (Figure 1B, full details in
Supplementary Material).
2.2 Experimental Apparatus and Procedure
Our experimental setup is illustrated in Figures 1C, D. The
geometry is similar to that of Bagdassarov et al. (1996),
2
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Vesiculation Under Oscillatory Pressure
FIGURE 1 | (A) Backscattered electron image of the obsidian used in the experiments, showing the absence of microlites and vesicles. (B) Water contents of the
original obsidian measured by FTIR spectroscopy, across slices cut from the end disks of seven samples; the average is shown as a black dashed line and the gray
shaded region represents the analytical uncertainty. (C) Photograph and (D) schematic diagram of the experimental setup.
was inserted above the obsidian sample, inside the crucible, to act
as a plunger. Plungers were cut to lengths of ~10 mm and lathed
to a diameter of ~4.9 mm so that they could fit snugly inside the
crucible but still slide without resistance. The pre-experimental
smooth sliding indicates the existence of a narrow space between
the plunger and the crucible, such that the sample assembly can
be assumed not to be gas-tight during the experiments. Every
piece of ceramic used in the experiments was first heat-treated at
1200°C for 3 h, to remove impurities, and minimize potential
geometrical changes to the sample assembly during the
experiments.
These dilatometric experiments were performed in a
NETZSCH TMA 402F1 Hyperion thermo-mechanical analyzer
(TMA) at the University of Liverpool. The TMA consists of a
sample holding platform and a vertical alumina push-rod, all
enclosed in a silicon carbide furnace. The digital resolution of the
push rod vertical position is 0.125 nm and resolution of the
applied force is <0.01 mN. A fixed frame limits the rod’s
upward motion, and serves as support for a K-type
thermocouple, which is located within 5 mm of the sample,
and exposed to the furnace gas. The crucible containing the
obsidian sample and ceramic plunger was placed onto the
TABLE 1 | Glass chemical composition of our starting material, determined by
electron probe microanalysis by Tuffen and Castro (2009). The mean and
standard deviation were computed from 100 analyses.
Oxide
Mean (wt%)
St. Dev.
SiO2
TiO2
Al2O3
FeOt
MnO
MgO
CaO
Na2O
K2O
Total
75.17
0.22
12.02
3.13
0.11
0.09
1.66
4.58
2.88
99.86
0.41
0.02
0.16
0.18
0.04
0.02
0.10
0.09
0.11
0.41
Stevenson et al. (1997) and Gottsmann et al. (1999). The prepared
obsidian samples were placed inside crucibles composed of an
alumina ceramic tube (DEGUSSIT AL23 produced by Friatec)
with outer and inner diameters of 8 and 5 mm (±5%),
respectively, and lengths of ~12 mm. Tight-fitting cylindrical
bases of the same material were prepared and inserted at the
bottom, in order to avoid leaks. A cylinder of the same material
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Vesiculation Under Oscillatory Pressure
platform, resting on the oscillating rod. For each experiment,
initially a calibration was performed using a ceramic standard
with dimensions that were within 3% of those of the obsidian
sample, in order to quantify the geometrical response of the
system (i.e., push-rod, crucible, base plate and plunger) to the
precise temperature path. These calibration data were then
subtracted from the data obtained during experiments on the
actual sample to constrain precisely the sample response.
Experiments were run in an Ar atmosphere to avoid melt
hydration and inhibit melt oxidation. In order to reduce
discrepancies between experiments, we first applied a constant
force of 1 N for 10 min, at a temperature of 50°C. Next, a load of
1.5 N was applied and maintained as the temperature was
increased to the target isothermal value (between 950 and
990°C) at a constant heating rate of 10°C min−1. The force
applied by the rod, the vertical position of the rod, the furnace
temperature and the Ar flow rate were monitored at a sampling
rate of 2 Hz throughout the experiment. At the end of the
experiment, the samples were cooled at 10°C min−1.
timescale of oscillation and elastic forces dominate. Conversely,
at De << 1, the material can relax and elastic forces may be
negligible. The shear relaxation timescale of the melt can be
computed as τ rlx η/G, where η is the shear viscosity and G ≈
1010 Pa is the elastic shear modulus (Dingwell and Webb, 1989).
At our experimental conditions, we obtain relaxation timescales
in the range 10−3.1–10−2.6 s. The highest oscillation frequency, f,
experimentally employed here is 0.1 Hz, i.e., an observation
timescale of 10 s. The Deborah numbers of our experiments
therefore lie in the range 10–4.1–10–3.6. Our highest Deborah
number is 10–3.6 << 1, implying that we can neglect elastic
effects. All the symbols used in the text are summarized in
Table 2.
During an experiment, lateral melt expansion is contained by
the presence of the crucible. The experiments have also been
designed such that the space between the plunger and the
crucible is too narrow to permit melt extrusion along the
narrow annulus between the containers’ end pieces and
cylinder during these experiments (e.g., Gotsmann et al.,
1999; Yoshimura and Nakamura, 2008). Thus, the melt
cylinder is effectively trapped between the plunger above and
the crucible end piece underneath, and the crucible surrounding
it radially. Under such circumstances the uniaxial loading of the
plunger generates a bulk stress, transmitted through the melt
body resulting in its transient pressurization. The viscous state
of the melt on the timescale of the pressurization step ensures
that the pressure is homogeneously distributed throughout the
melt according to Pascal’s law. It can be estimated as the force
applied by the rod divided by the contact area with the obsidian
sample. Here, the contact area is a disk with a diameter of 5 mm,
i.e., ~20 mm2. The force (and thereby volume stress or pressure)
can be set to either a constant value or to follow sinusoidal
oscillations, corresponding to static and oscillating experiments,
respectively. In static experiments, a constant force, F0 , of 1.5 N
(i.e., a pressure P0 = 76 ± 8 kPa) is continuously applied to the
sample (including during the heating phase). Moreover, the
furnace chamber is kept at atmospheric pressure (101 kPa);
therefore the effective pressure during a static experiment is
177 kPa.
In the oscillating experiments, F0 was continuously applied
during heating and for 10 min of thermal equilibration at the
isotherm. The force with time is then set to:
2.3 Post-Experimental Analysis
After each experiment, the samples were mounted in epoxy and
cut parallel to the ends into halves: one half for textural analysis
and one to measure water contents.
The first half was polished and gold coated for observation
with a JEOL IT-300 scanning electron microscope (SEM) at the
University of Canterbury. Backscattered electron (BSE) images
were acquired with a 15 kV accelerating voltage and a 40 nA beam
current at a 10 mm working distance. We quantitatively
estimated the bubble fraction using the BSE images. We first
manually delineated bubbles in Inkscape and produced
segmented ternary images with pixel colors representing either
glass (black), vesicles (white) or crucible (gray). Bubbles were
further manually divided between core and rim bubbles. Bubble
fraction was then computed from the number of relevant bubble
pixels (core or rim) divided by the sum of bubble and melt pixels.
The second half of the sample was polished on both sides to
create a wafer for FTIR spectroscopy. Post-experimental water
contents were determined via FTIR spectroscopy following the
same procedure as was employed for measuring pre-experimental
water contents.
2.4 Experimental Conditions
F(t) F0 + ΔF sin2πft,
Preliminary experiments were undertaken in order to assess our
experimental methods, to optimize our sample and crucible
preparation, and to identify “ideal” experimental conditions
(i.e., windows of temperature and timescale where vesiculation
occurs at a manageable rate and is reproducible). We chose
temperatures in the range 950–990°C, yielding viscosities of
107.4–106.9 Pa s, for a water content of 0.11 wt%, according to
the viscosity model of Giordano et al. (2008). To ensure our
samples reach a relaxed state during experiments, we compare
the shear relaxation timescale τ rlx to the time of observation
τ obs , via analysis of the Deborah number De τ rlx /τ obs . The
Deborah number allows us to assess whether a material has time
to viscously relax a stress in the time of interest (e.g., Wadsworth
et al., 2018). At De >> 1, viscous relaxation is inefficient on the
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(1)
where F0 is the constant baseline force, ∆F is the oscillation
amplitude and t is time. For the majority of the oscillating
experiments, we set ∆F = 1.4 N, and the pressure therefore
oscillates between 106 ± 1 and 250 ± 10 kPa, during an
oscillating experiment. The maximum instantaneous pressure
change rate dP/dt is then 45 kPa s−1. Our experimental setup
is impermeable to melt but permeable to water vapour due to the
narrow annulus between the plunger and crucible, and the very
low permeability of the alumina ceramic. Experiments were run
in an Ar atmosphere, thus the ambient partial pressure of water is
lower than atmospheric. Therefore, a water pressure gradient
exists between the pressurized melt and the furnace atmosphere,
which leads to water loss by diffusion through the sample’s free
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Vesiculation Under Oscillatory Pressure
TABLE 2 | List of symbols used in the text and equations.
Symbol
b
D
De
f
F0
F(t)
ΔF
g
G
k
kB
LD
P
H2 O
Patm
Pn
Psat
P0
P(t)
Pmax
Pmin
ΔP
R
Rc
Rc,0
Rc(t)
t
tDarcy
tosc
ttotal
T
vSt
VH2O
Γ(P, T)
η
ηg
ρ
σ
τe
τobs
τrlx
Definition
Typical value in this
study
Crucible wall thickness
Water diffusivity
Deborah number
Frequency of oscillations
Force applied during a static experiment
Time-dependent force applied during an oscillating experiment
Amplitude of the force oscillations
Gravitational acceleration
Infinite frequency shear modulus
Ceramic permeability
Boltzmann constant
Diffusion length
Pressure in the melt
Partial pressure of water in the furnace atmosphere
Pressure inside bubble nucleus
Saturation pressure
Pressure in the melt in a static experiment
Time-dependent pressure in the melt during an oscillating experiment
Maximum pressure reached during an oscillating experiment
Minimum pressure reached during an oscillating experiment
Amplitude of pressure oscillations
Bubble radius
Bubble nucleation critical radius
Bubble nucleation critical radius during static experiments
Time-dependent bubble nucleation critical radius during oscillating experiments
Time
Time to deplete a half-bubble via porous flow
Duration of oscillations
Total time spent at isotherm during an experiment
Temperature
Bubble migration velocity
Volume of water molecules
Fugacity of water
Melt viscosity
Gas viscosity
Melt density
Surface tension
Bubble expansion timescale
Observation timescale
Shear relaxation timescale
190 kPa
190 kPa
177 kPa
P0 + ΔP sin(2πft)
250 kPa
106 kPa
71 kPa
3 × 10−7 − 3 × 10−3 m
5–50 × 10–6 m
7 × 10–7 − ∞ m
0.1 s − 32 years
50–110 min
1–2 h
965°C
5.0 × 10–10 m s−1
4.6 × 10–29 m3
1
107 Pa s
10–5 Pa s
2,370–2,460 kg m−3
0.03 − 0.3 N m−1
190 s
10 s
10–3 s
3 RESULTS
surface. The implications of this are discussed in further detail in
the discussion below (Section 4.2).
Our samples initially contain 0.11 ± 0.01 wt% water so
depending upon the water solubility in the melt at experimental
P-T conditions, water will either exsolve (supersaturated case) or
remain in the melt (undersaturated case). Water solubility in the
melt can be estimated for our experimental conditions using the
empirical model of Liu et al. (2005) (Figure 2). During a static
experiment at 965°C and 177 kPa, our samples are within the
saturation uncertainty of the model, which does not allow a priori
assessment of whether vesiculation will occur or not. Therefore, we
explored whether vesiculation occurs by comparing expansion
during static experiments of 1) a standard borosilicate dry glass
(NIST SRM 717a) and 2) our hydrous obsidian, as starting
materials. During oscillating experiments, samples alternate
between supersaturated and undersaturated conditions, beyond
the uncertainty of the model (Figure 2).
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3 × 10−3 m
6.0 × 10–13 m2 s−1
10–4
0.1 Hz
1.5 N
F0 + ΔF sin(2πft)
1.4 N
9.81 m s−2
1010 Pa
10–25 − 10–18 m2
1.38 × 10–23 m2 kg s−2 K−1
50 − 70 × 10–6 m
0
3.1 Tracking Vesiculation With Sample
Expansion
As noted above, we tested whether the TMA can track
vesiculation by comparing length changes (i.e., expansion)
during static experiments with 1) a standard borosilicate
dry glass (NIST SRM 717a) and 2) our hydrous obsidian as
starting material (Figure 3). For each experiment, strain was
computed by normalizing sample length to the initial length,
whereby positive strain is defined as corresponding to
expansion. Figure 3 shows typical examples of the strain
evolution during experiments, including the heating and
dwell phases. The initial trends are identical in both dry
and hydrous experiments. Initially volume increases due to
thermal expansion of the glass samples, increasing in rate as
the samples cross the glass transition (e.g., Gottsmann et al.,
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FIGURE 2 | Temperature-pressure conditions of our experiments. The predicted P-T conditions of saturation for a rhyolite containing 0.11 ± 0.01 wt% of water are
shown as a dashed line with a blue shaded region representing uncertainty, using the model from Liu et al. (2005). Above and left of this region, the sample is
supersaturated in water. Below and right of this region, the sample is undersaturated. The pressure during static experiments is P0 = 177 ± 8 kPa and displayed as a red
vertical dotted line (with red shaded regions representing uncertainty). The minimum and maximum pressures reached during oscillations, Pmin = 106 ± 1 and Pmax
= 250 ± 10 kPa respectively, are shown as black vertical dotted lines (with gray shaded regions representing uncertainty). The horizontal double-headed arrow is located
at T = 965°C, where the majority of experiments were performed.
FIGURE 3 | Comparison of static experiments using (A) standard borosilicate dry glass NIST SRM 717a and (B) hydrous obsidian from Hrafntinnuhryggur, Iceland
as starting material. After an initial phase of compressive strain (blue line) as the samples are pressed inside the crucible, strain then remains flat in the case of a dry glass
(A) but strain reverses in the case of a hydrous glass during the isotherm (B) indicating vesiculation. Temperature (orange line, normalized to target isothermal value,
namely 640°C in (A) and 965°C in (B)) is also plotted. Time (since the beginning of the experiment) was normalized to the total experiment time, namely 9 h in (A) and
2 h in (B).
1999). At temperatures above the glass transition, the samples
viscously relax the applied stress, and as a result viscously
adjust, accommodate themselves and spread inside the
crucible, corresponding to a sudden phase of compressive
strain (Figure 3). As the isotherm is reached and the melt
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sample fills the crucible, the strain curve flattens. Once the
samples are viscously accommodated within the crucibles, the
strain remains constant with time in the case of the dry NIST
sample (Figure 3A), whereas the sample length begins to
increase in the case of the hydrous obsidian (Figure 3B),
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TABLE 3 | Summary of experimental conditions. T is temperature, ttotal is the total time spent at isotherm temperature, ΔF is the oscillation amplitude, f is the oscillation
frequency and tosc is the duration of oscillation. For the final volume change, + symbol indicates an increased in volume (i.e., sample expansion).
Exp #-
Type-
T(°C)
ttotal (hh:mm)
F (±0.001 Hz)
tosc (hh:mm)
1.4
0.7
1.4
1.4
0.1
0.1
0.01
0.1
01:50
01:50
01:50
00:15
1.4
0.1
00:50
1.3
0.03
11:50
1.4
0.1
04:55
ΔF
(N)
L19
L20
L21
L22
L23
L25
L26
KG21
KG22
KG23
L01
L04
L05
L06
Static
Oscillating
Oscillating
Oscillating
Oscillating
Static
Oscillating
Static
Oscillating
Static
Static
Static
Static
Oscillating
965
965
965
965
965
965
965
950
950
950
950
990
990
990
02:00
02:00
02:00
02:00
02:00
01:00
01:00
12:00
12:00
12:00
12:00
05:00
05:00
05:00
+ 10.6
+ 7.3
+ 13.5
+ 4.1
+ 5.6
+ 4.6
+ 0.1
+ 0.7
+ 0.3
+ 0.5
+ 0.3
+ 20.5
+ 6.6
+ 7.2
3.2.1 Vesiculation During Static vs Oscillating
Experiments
Figure 4 shows experimental data from two static and two
oscillation experiments at 965°C. We first describe the results
from static experiments, and then compare them with the results
from oscillation experiments.
The two static curves (obtained over 1- and 2-h periods) follow
similar trends, reflecting our experimental reproducibility.
Initially, the volume change curve remains flat, close to zero,
as the sample lengths do not vary. After 18–25 min, volume
increases as the samples expand. The expansion rate remains
approximately constant for 1 h, before slightly reducing
(observed in experiments with sufficient duration, Figure 4).
Once started, sample expansion proceeds continuously until the
end of the experiment. Therefore, longer experiment durations
yield larger volumes, as indicated by the higher final volume
change values in the 2-h experiments compared to those of 1-h
experiments (Figure 4). These results are consistent with
previous static dilatometry experiments (Bagdassarov et al.,
1996; Stevenson et al., 1997). Sample expansion is attributed
to water vapour bubbles nucleating and growing in the melt. The
initial flat segment, termed “incubation period” by Bagdassarov
et al. (1996), corresponds to the time required for bubbles to
nucleate and grow to a detectable size after supersaturation is
established. The incubation period in our static experiments
(~20 min, Figure 4) is similar to observations from Ryan et al.
(2015) and Cáceres et al. (2020) who performed static
vesiculation experiments with the same starting material, at
similar temperatures and at atmospheric pressures.
During pressure oscillation experiments, the volume change
curves are initially flat, similar to the static case, as the samples
undergo a period of incubation of 20–40 min before expansion
starts. After the incubation period is complete, the trend differs in
two ways: 1) the expansion rate is unsteady with successive
acceleration and deceleration, and 2) the volume change
values are consistently lower than in the static cases. These
observations suggest that, in the oscillating cases, the samples
FIGURE 4 | Volume change as a function of time for four experiments at
965°C, two static (black) and two oscillating (blue). Time is set to zero 5 min
after the isotherm is reached (the heating phase is not shown). The uncertainty
on the volume change is smaller than the line thickness.
indicating vesiculation. The obsidian samples can therefore be
concluded to be supersaturated in water at the test conditions
(T = 965°C and p = 177 kPa).
In comparisons going forward we suppress the reporting of the
heating phase, setting both time and strain to zero 5 min after the
isotherm is reached (as indicated on Figure 3B), thereby
accounting for thermal equilibration of the furnace. At this
point, melt has accommodated its form to the crucible and
can no longer expand radially; therefore longitudinal strain
can be converted to volume change, whereby positive changes
correspond to expansion.
3.2 Experimental Results
We report the results of 14 experiments, seven at static pressure
conditions and seven under oscillating pressure conditions. The
majority of experiments were performed at 965°C. All
experimental parameters are summarized in Table 3.
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Final
volume change (%)
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FIGURE 6 | (A) Segmented images of the experimental products
from the four experiments presented in Figure 4. Glass is in black, the
ceramic crucible is in gray, core bubbles are in blue and rim bubbles are
in orange. Original SEM images used to produce these can be
found in the Supplementary Material. (B) Bubble fractions from the
images in (A), divided between core bubbles (blue) and rim bubbles
(orange).
FIGURE 5 | Volume change as a function of time for varying (A)
oscillation amplitude ΔF, (B) oscillation frequency f, and (c) oscillation duration
tosc . Time is set to zero 5 min after the isotherm is reached. In (C), the
oscillation period for the short oscillation duration experiment (L23) starts
10 min after the isotherm is reached (i.e., t = 5 min on the graph) and is shown
as a double headed black arrow labelled tosc,L23 ; for all other oscillating
experiments, the oscillation starts at t = 5 min and continues until the end of
the experiment at t = 115 min, i.e., for a duration of tosc = 110 min. For each
plot, data from a baseline static (L19, black line) and oscillating (L20, blue line)
experiment are shown. These are the same two 2-h experiments presented in
Figure 4. All experiments are performed at T = 965°C and F0 = 1.5 N. All
experimental parameters are reported in Table 3.
965°C, with an incubation period of <5 min in the static case and
in the oscillating case, sample expansion occurred again at a
relatively slower rate and more erratically.
3.2.2 Varying Oscillation Parameters
We investigated the role of three oscillating parameters on sample
expansion kinematics: 1) oscillation amplitude ∆F, 2) oscillation
frequency f, and 3) oscillation duration tosc. We use the 2-h
experiments presented in Figure 4 (L19 and L20) as a
comparative baseline to understand the effects of each
parameter (Figure 5). We observe that the general trend
remains the same in all cases. All experiments started with an
expand at a slower rate (as evidenced by the overall shallower
slope of the curves) and more erratically (as evidenced by the
greater range of the curves).
We also explored temperatures of 950 and 990°C
(Supplementary Figures S1–S3). At 950°C, the measured
strains remained close to zero in both static and oscillating
experiments, presumably because vesiculation was effectively
inhibited. At 990°C, sample expansion occurred faster than at
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of diameters (0.001–1 mm) with larger bubbles generally
deformed (i.e., not round) and showing evidence of
coalescence (Figure 6A; c.f. Castro et al., 2012). We also
observe a few bubbles in the core of the sample; these tend to
be isolated, spherical and of uniform size (~0.1 mm diameter).
The bubble textures in samples from oscillating experiments
are broadly similar to the static cases. Again, bubbles are unevenly
distributed with 1) a polydisperse, deformed and coalesced
population on the outer margin, and 2) a more monodisperse
spherical population in the core. Core bubble populations are
indistinguishable between static and oscillating experiments but
we observe fewer bubbles on the rim of the samples that have
undergone pressure oscillations.
We used the segmented images of the samples to assess the
relative proportions of core and rim bubbles (Figure 6B). This
quantitative analysis supports our observations that the majority
of the bubbles are found on the outer margin and that longer
experiment durations lead to larger volumes. Comparison
between the bubble fractions formed during static versus
oscillating tests confirms that 1) core bubble fractions are
similar, and 2) bubble fractions on the rim are reduced in the
oscillating case compared to the static case.
FIGURE 7 | Post-experimental water contents (from FTIR spectroscopy)
as a function of the distance to the nearest edge or bubble for the two 1-h
experiments presented in Figures 4 and 6, L25 (static) and L26 (oscillating).
The range of water contents in the original samples are indicated as grey
bands for comparison.
3.4 Post-Experimental Water Content
Water contents were measured post-experimentally, where
possible, using FTIR spectroscopy (Figure 7, full details in
Supplementary Material). The average post-experimental
water content is 0.11 ± 0.01 wt%. Post-experimental water
contents are therefore indistinguishable from pre-experimental
water contents. Additionally, we do not observe any correlation
between post-experimental water contents and distance to the
nearest sample edge (Figure 7).
incubation period of 20–40 min (at 965°C), before the onset of
sample expansion.
When the force was halved (∆F = 0.7 N instead of 1.4 N,
Figure 5A), the volume increased to values similar to those
observed in the static experiment, despite a delayed onset.
Hence for forces low enough, sample expansion is not affected
by pressure oscillations. Thus the oscillation amplitude appears to
exert a control on sample expansion, with larger amplitudes
leading to lower total volumes. In contrast, with either a
reduced oscillation frequency (f = 0.01 Hz instead of 0.1 Hz,
Figure 5B) or reduced oscillation duration (15 min as opposed
to 110 min, Figure 5C), the volume change curve matches the
original oscillating experiment (L20). Therefore, pressure
oscillations with either a low frequency or a short duration
appear to reduce sample expansion. Thus, under our
experimental conditions, oscillation amplitude exerts the
greater influence on sample expansion kinematics.
4 DISCUSSION
4.1 Static Experiments
In all static experiments, samples expanded (Figure 4), indicating
that vesiculation occurred, as later confirmed in physical
examination (Figure 6). Vesiculation consists of three main
processes: bubble nucleation, growth and coalescence (e.g.,
Burgisser and Degruyter, 2015). Most of the observed
expansion likely results from the formation and/or
accumulation of bubbles on the outer margin (Figure 6). A
rim of bubbles (also termed “fringe” of bubbles by Mangan
and Sisson, 2000) is a common occurrence in contained
vesiculation experiments (e.g., Mangan and Sisson, 2000;
Mourtada-Bonnefoi and Laporte, 2002; Fiege and Cichy,
2015). These bubbles are interpreted to result from a
combination of heterogeneous nucleation at the contact with
the crucible (e.g., Mangan and Sisson, 2000; Mourtada-Bonnefoi
and Laporte, 2002) and diffusion into interstitial air trapped at the
sample-crucible interface (e.g., Wiesmaier et al., 2015). It is very
unlikely that bubbles migrated within the sample during the
experiments, due to the high melt viscosity (ca. 107 Pa s). Bubble
migration velocity for a bubble with radius R can be estimated
using Stokes’ law as:
3.3 Textural Analysis
Following our experiments, the samples recovered from both
static and oscillating experiments contain bubbles, consistent
with the interpretation that the volume increase is driven by
vesiculation. Segmented images of horizontal cross sections from
the final experimental products of the four experiments shown in
Figure 4 are presented in Figure 6A.
In the static cases, bubbles are unevenly distributed. Most
bubbles are located on the outer margin of the samples, at the
boundary with the ceramic crucible, forming a rim of bubbles.
The bubbles on the rim are densely packed, exhibit a wide range
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Ostwald ripening (the spontaneous growth of large bubbles at the
expense of smaller ones) might also occur due to the variety of
bubble sizes observed in the rim, but, at such high viscosities,
ripening effects generally become significant on timescales of days
to weeks, i.e., orders of magnitude longer than the duration of our
experiments (e.g., Lautze et al., 2011; Masotta et al., 2014).
As our experimental apparatus is permeable to volatiles, some
gas may progressively escape from the system, diminishing the
driving force for bubble growth. There are two possible escape
routes for water vapor: either via direct diffusion through the
narrow space between the plunger and the crucible, or via porous
flow through the ceramic crucible. In the case of the former, there
is a thin ring of melt in direct contact with the furnace
atmosphere around the base of the plunger. Here, water will
diffuse from the pressurized melt into the furnace, due to the low
partial pressure of water in the Ar atmosphere. This diffusion
process will lead to the formation of a low water content, bubblefree, impermeable skin which effectively seals the system
(Yoshimura and Nakamura, 2008; von Aulock et al., 2017).
The thickness
√ of this skin scales with the diffusion length
LD Dttotal , where D is water diffusivity in the melt and
ttotal is the total time spent at the isotherm (von Aulock et al.,
2017). We use the diffusivity model of Zhang and Ni (2010) and
estimate D = 6.0 × 10−13 m2 s−1 at T = 965°C, p = 177 kPa and a
water content of 0.11 wt%. The diffusion lengths are then c. 50
and 70 µm for experiment durations of 1 and 2 h, respectively. A
dehydrated skin will thus form wherever direct diffusion into the
furnace atmosphere is allowed, but its thickness will remain
<70 μm, which is below the resolution of our FTIR analyses.
The second gas loss mechanism is permeable gas flow through
the crucible walls. We can rearrange Darcy’s law to estimate the
time necessary to evacuate a half-bubble of radius R via porous
flow through the ceramic wall as (see geometry of the problem in
Figure 8A):
FIGURE 8 | Time tDarcy necessary to deplete a half-bubble of gas via
permeable flow through the ceramic crucible. (A) Geometry of the problem
and (B) colour map of tDarcy as a function of the permeability of the ceramic
material k (m2) and bubble radius R (μm). Solid lines are isochrones,
plotted for every log10 unit. Experimental durations (1 and 2 h) are displayed as
dashed lines.
tDarcy
vSt
2ρgR2
9η
(2)
H2 O ,
3kP0 − Patm
(3)
where the thickness of the ceramic crucible wall b = 3 mm, the
viscosity of the gas ηg 10−5 Pa s, k is the permeability of the
ceramic, P0 is the pressure experienced by the sample (=177 kPa),
2O
and PH
atm is the partial pressure of water in the furnace
atmosphere. Experiments are run in an Ar atmosphere, so, we
H2 O
2O
consider an ideal value of PH
atm 0. In practice, Patm is likely
small but not zero, hence our calculations will provide minimum
estimates of tDarcy (i.e., the fastest scenario). We attempted to
measure the permeability of the ceramic material k using a Vinci
Technologies benchtop gas permeameter with a Bronkhorst
flowmeter, but the measurement was below the 10–17 m2
detection limit of the instrument. We thus consider a range of
permeability values between 10−25 and 10−18 m2. The necessary
tDarcy to evacuate half-bubbles with radii between 0.3 µm and
3 mm are shown in Figure 8B. The analysis suggests that gas loss
by permeable flow through the ceramic crucible can be discarded
altogether if the crucibles’ permeabilities are below 10−23 m2, but
it can be efficient (tDarcy < 10 s) for permeabilities >10−20 m2 and
R < 50 µm, which is smaller than most of the observed bubbles.
where ρ is the melt density (=2,370 kg m−3, computed with
DensityX, at T = 965°C and P = 177 kPa; Iacovino and Till,
2019), η is the melt viscosity (= 107 Pa s) and g is the gravitational
acceleration (=9.81 m s−2). This yields maximum velocities of 5 ×
10−10 m s−1 for a large bubble with R = 1 mm, corresponding to a
maximum travelled distance of 3 µm in 100 min (representing a
2-h experiment with a 20-min incubation period), which is
negligible. Thus we exclude the possibility that bubble
migration led to accumulation at sample margins, and
conclude that these bubbles must have formed in-situ at the
margins of the samples.
Bubble formation (i.e., nucleation and/or growth) is followed by
coalescence, as evidenced by the textures observed on the rim of the
experimental products (Figure 6). Given the high viscosity of the
melt, bubble coalescence most likely results from inter-bubble melt
films stretching and thereby thinning, driven by bubble growth
(e.g., Castro et al., 2012; Masotta et al., 2014; Giachetti et al., 2019).
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4.2 Oscillating Experiments
The same processes of bubble nucleation, growth, coalescence
and gas loss from the crucible occur during the oscillating
experiments, but each of these may potentially be affected by
pressure oscillations. The volume change curves (Figures 4, 5)
are generally similar in the static and oscillating cases,
suggesting that the effects of oscillations tested here remain
moderate. Nonetheless, the expansion curves for the
oscillating experiments lie systematically below those for
static experiments (Figures 4, 5). This is observed
regardless of the duration and frequency of pressure
oscillations across the range tested, but depends on the
oscillation amplitude, with higher amplitudes yielding more
reduced volumes compared with the static case (Figure 5).
These relationships are preliminary and need to be explored
and confirmed by more experiments, ideally accompanied by a
quantification of gas loss from the system, and an analysis of its
potential influence on vesiculation.
Textural evidence (Figure 6A) shows that bubbles in the
sample cores are of similar size, shape and present in similar
amounts in static vs oscillating tests, but that the amount of
bubbles located on the rim is lower in oscillation experiments
(Figure 6B). We propose that these observations can be
explained by either: 1) reduced bubble formation
(nucleation and/or growth), 2) increased gas loss, or 3) a
combination of the two. Below, we explore how pressure
oscillations may impact the different processes occurring
during an experiment.
FIGURE 9 | (A) Pressure, (B) critical radius for bubble nucleation Rc (t)
(Eq. 6) and (C) time to evacuate a half-bubble via permeable flow tDarcy (Eq.
10) as a function of time during an oscillating experiment (three oscillation
cycles are shown). Rc (t) and tDarcy are both normalized to the static case
value (shown as horizontal dashed lines), and plotted on a logarithmic scale.
4.2.1 Bubble Nucleation
Bubble nucleation events do not produce a significant volume
change and thus cannot be monitored directly with our
experimental setup. We can nevertheless interrogate the
classical nucleation theory (CNT) to assess the effects of
pressure oscillations on the phenomenon, and build a
hypothesis to be tested in future work (see Gonnermann and
Gardner (2013) and Shea (2017) for shortcomings of the CNT for
magmatic liquids). According to the CNT, bubbles nucleate from
clusters of water molecules. CNT defines a cluster critical
(minimum) radius Rc above which clusters will form bubbles
and under which they will dissolve by diffusion as (Hurwitz and
Navon, 1994):
Rc
2σ
,
Pn − P
Rc (t)
Pn − P0
.
Pn − P(t)
Rc,0
In general, Pn is given by (Cluzel et al., 2008):
Pn Γ(Psat , T)Psat· exp
(5)
For the experiments presented in Figure 4, P0 177 kPa,
ΔP 71 kPa and f 0.1 Hz. We can then compare the
evolution of the critical radius with time in an oscillating
experiment Rc (t) to the critical radius of a static experiment
Rc,0 as:
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VH2 O
(P − Psat ),
kB T
(7)
where Psat is the saturation pressure, Γ(Psat , T) is the fugacity of
water at saturation, VH2 O is the volume of water molecules and kB
is the Boltzmann constant (=1.38 × 10−23 m2 kg s2 K−1). Γ(Psat , T)
and VH2 O can both be easily computed (see Cluzel et al., 2008, and
references therein), so we are only left with Psat to evaluate. The
solubility model from Liu et al. (2005) indicates that, at T = 965°C
and for a 0.11 ± 0.01 wt% water content, Psat lies in the range
125–190 kPa (Figure 2). We experimentally observed that
samples vesiculated at 177 ± 8 kPa; therefore we suggest that
Psat > 177 ± 8, and chose Psat ≈ 190 kPa. Entering those values
V
into Eq. 7, we find that Γ(Psat , T) exp[ kHB T2 O (P − Psat )] ≈ 1, and
thus Pn ≈ Psat ≈ 190 kPa.
We can then use Eq. 6 to evaluate how the critical radius
changes during pressure oscillations (Figure 9). While the
(4)
where σ is the surface tension between a bubble nucleus and the
melt, Pn is the pressure inside the bubble nucleus and P is the
ambient melt pressure. During oscillations, P varies with time
according to:
P(t) P0 + ΔP sin2πft.
(6)
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pressure oscillations P(t) are symmetrical about P0 (Figure 9A),
the evolution of Rc (t) is not symmetrical about Rc,0 at all
(Figure 9B). When pressure decreases from P0 towards
P0 − ΔP, supersaturation increases and Rc (t) decreases by
about 75%. A reduced critical radius implies that a greater
number of clusters will be sufficiently large to grow into
bubbles, and nucleation will be more efficient (c.f., Masotta
and Keppler, 2017). When the pressure increases towards P0 +
ΔP however, the melt becomes undersaturated because
P(t) > Psat and the critical radius becomes infinite: no cluster
will be large enough to form bubbles, and nucleation will not
occur. Hence there is an imbalance over each pressure oscillation:
bubble nucleation is slightly enhanced during the lower half of the
cycle compared to the static case, but it is completely shut off
during the higher-pressure segment. This leads to the hypothesis
that some of the water clusters resorb when the pressure is
increased, eventually leading to overall reduced bubble
nucleation. The process of cluster resorption is mainly
controlled by the diffusivity of water. The diffusion length
over a half-period of oscillation (5 s) is about 2 µm. We can
compare this length to Rc,0 , to assess whether diffusion would
occur fast enough to dissolve water clusters. Rc,0 can be computed
using Eq. 4, which requires σ to be known. Macroscopic σ for
water-poor rhyolite at low pressures is about 0.3 N m−1
(Bagdassarov et al., 2000), but this value should be reduced by
up to an order of magnitude when considering the microscopic
scale of bubble nuclei (e.g., Gonnermann and Gardner, 2013;
Shea, 2017; Hajimirza et al., 2019). We thus consider σ to be in the
range 0.03–0.3 N m−1, which yields Rc,0 values of 5–50 µm. This
means that, according to the CNT, any existing bubble or cluster
smaller than 5–50 µm will resorb. The lower end value
(corresponding to more realistic σ; e.g., Shea, 2017) is
comparable to the diffusion length scale over half a pressure
oscillation. This preliminary analysis therefore indicates that
pressure oscillations around saturation may effectively reduce
bubble nucleation by momentarily annihilating some of the water
clusters before they are able to form bubbles. We urge future
studies to explore this mechanism further as it was not possible to
assess bubble number density satisfactorily due to the coalesced
bubble rim dominating the gas volume fraction. This problem
could be avoided by using larger samples, hence reducing the
relative importance of rim bubbles, or using a different
pressurization mechanism that does involve an interface with
a container (e.g., Masotta and Keppler, 2017).
bubble number density (BND), which have been shown to
exert significant controls on the resulting growth rate (e.g., Liu
and Zhang, 2000; L’Heureux, 2007; Coumans et al., 2020). The
effects of parameters such as temperature or composition of the
melt are factored into the viscosity, diffusivity and degree of
supersaturation (e.g., higher temperatures correspond to lower
viscosities, higher degrees of supersaturation and higher
diffusivities).
Water diffusivity scales inversely with pressure, but in our case
the pressure oscillations (with amplitude ∆P = 71 kPa) result in
water diffusivity changes of <0.1% (using the model of Zhang and
Ni, 2010). Additionally, melt viscosity is not significantly, nor
systematically, influenced by pressure (e.g., Ardia et al., 2008). We
therefore anticipate that the effect of pressure oscillations on
water diffusivity and melt viscosity in our tests can be neglected.
Pressure oscillations could however significantly impact the
degree of supersaturation and, potentially, the bubble number
density. Concerning the latter, as discussed in Section 4.2.1,
pressure oscillations may reduce the number of bubble nuclei.
One of the consequences would be an overall reduction in bubble
number density, and thus a reduced sample expansion rate (though
not necessarily reduced individual bubble growth rates; e.g.,
Proussevitch and Sahagian, 1998; Coumans et al., 2020).
Additionally, we saw that the pressure oscillations constantly
change the degree of water supersaturation in the melt (see
Figure 2 and previous section). The supersaturation increases in
the low-pressure part of the cycle, but, in the high pressure part the
degree of supersaturation decreases and eventually vanishes as the
sample is driven into undersaturated conditions. In general, higher
degrees of supersaturation produce faster bubble growth rates (e.g.,
Proussevitch and Sahagian, 1998; L’Heureux, 2007), yet previous
research efforts have generally focused on either constant or
continuously increasing degrees of supersaturation (e.g., Nowak
et al., 2011). Therefore, bubble growth potentially accelerates when
pressure is reduced, and decelerates when pressure is increased and
bubble growth stops when the pressure increases past the
saturation pressure and the sample becomes undersaturated.
Bubbles may then start resorbing (e.g., McIntosh et al., 2014)
but on a timescale beyond that explored in this study. As for the
case of bubble nucleation then, it is probable that even symmetrical
pressure oscillations lead to asymmetrical effects on bubble growth.
If bubble growth cyclically stops as the melt becomes
undersaturated, and if this effect is not counterbalanced by the
bubble growth acceleration when pressure is decreased, then this
mechanism may contribute to the observed reduced sample
expansion rates (Figure 4). The importance of this mechanism
remains to be fully evaluated. We note that for our experiments the
diffusion length over a half-period of oscillation is only 2 µm.
Hence it is possible that our pressure oscillations occur too fast
compared to the diffusion of water, and thus bubble growth would
remain unaffected.
Bubble growth may further be affected by rectified diffusion, if
the sizes of the bubbles oscillate with pressure (Brodsky et al.,
1998; Ichihara and Brodsky, 2006). The necessary timescale for a
bubble to expand and contract in response to pressure
perturbations can be estimated, after Ichihara and Nishimura
(2009), as:
4.2.2 Bubble Growth and Coalescence
Bubble growth is a complex, non-linear phenomenon and it is
not, a priori, evident how pressure oscillations should influence it.
It is important to note that, in our experiments, we monitor the
whole sample volume change, which depends upon, but differs
from, the growth rates of the individual bubbles. In general, for a
given set of initial conditions, bubble growth rate (and thereby the
whole sample expansion rate) is primarily governed by the melt
viscosity and/or the diffusivity of water (e.g., Sparks, 1978;
Bagdassarov et al., 1996; Proussevitch and Sahagian, 1998;
Blower et al., 2001; Lensky et al., 2004). Here, the initial
conditions refer to the initial degree of supersaturation and
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τe
4η
.
3ΔP
k > 10−20 m2), then pressure oscillations would likely hinder the
process, i.e., lead to reduced gas loss, rather than enhance it. On
the contrary, our experiments show that there are less bubbles on
the rim in oscillating experiments, which would require an
enhanced gas loss mechanism, if indeed the differences
observed result from more efficient gas loss rather than
reduced nucleation. Gas escape through the ceramic crucible
therefore does not provide an adequate explanation for our
observations.
(8)
In our experiments, τ e 190 s, which is much greater than the
period of the pressure oscillations (10 s). We thus conclude that
bubble sizes do not vary significantly as pressure oscillates, and
rectified diffusion does not occur. This calculation also suggests
that Bjerknes forces (i.e., translational forces arising from bubble
volume oscillations that could potentially drive coalescence, e.g.,
Igualada-Villodre et al., 2018) are unlikely to play a significant
role in our experiments. We note however that Masotta and
Keppler (2017) observed significant changes in bubble sizes when
imposing larger pressure oscillations (ΔP ~ 104 kPa) on a
haplogranitic melt, in their moissanite cell experiments. The
effects of Bjerknes forces from bubble volume oscillations may
deserve further investigation in studies testing a wider range of
pressure oscillation conditions.
Finally, most coalescence processes directly depend on the
BND and the individual bubble growth rates, with higher BND
and growth rates generally leading to faster coalescence (Castro
et al., 2012). Section 4.2.1 showed that pressure oscillations may
reduce bubble nucleation, hence the resulting BND will be lower,
and pressure oscillations potentially reduce bubble growth rates.
Therefore, if pressure oscillations reduce both BND and growth
rates, then the rate of coalescence should also decrease.
4.3 Limitations and Future Work
The experiments presented in this contribution are exploratory
and in this sense very much in the spirit of other attempts to
understand how melt behaves under disequilibrium conditions
(e.g., Arzilli and Carroll, 2013; Masotta and Keppler, 2017;
Kolzenburg et al., 2018). As such, further work will be needed
to constrain and confirm the results presented here. Below, we
highlight some current limitations and prospects for future work.
Firstly, our observations rely on a small number of
experiments (14 on hydrous samples). While we strived for a
reasonable level of reproducibility, the validity of our results is
pending replication. Future experiments should also aim to
explore saturation states more carefully by investigating
smaller steps in temperature. Similarly, the role of the
different oscillation parameters (amplitude, frequency and
duration) needs to be more closely examined. While we have
highlighted the importance of bubbles, in particular at the margin
of the samples, observation of these processes is currently limited
both in time and space. We only observe a snapshot of the bubble
textures, in 2D, after quenching the sample at the end of an
experiment. A crucial future step would be to have better
temporal resolution, for example by monitoring bubble
textures continuously during in-situ experiments, using X-ray
tomography techniques for instance. Furthermore, as bubbles
grow in the sample, the compressibility of the sample increases,
which has been neglected in our analysis. We tried to mitigate this
issue by focusing on short experiments, with low (<10%) exsolved
phase volumes, but this could constitute an avenue for further
work. Finally, we examined the importance of gas loss through
the crucible walls. An accurate characterization of the
permeability of the ceramic material used will be a critical step
to constrain this mechanism further. Alternatively, a different
material could be used for the crucible. For instance, Gottsmann
et al. (1999) use containers made of Ni metal.
4.2.3 Gas Loss
The last processes that may potentially be affected by pressure
oscillations are related to gas loss to the surrounding furnace
atmosphere; namely, via direct diffusion through cracks between
the plunger and the crucible, and via gas filtration through the
crucible wall. While the former is likely to be negligible (see
Section 4.1), the latter could be significant, contingent upon the
ceramic material having a high enough permeability (k >
10−20 m2, see Section 4.1 and Figure 8). In order to evaluate
tDarcy in oscillating experiments, we replace P0 by P(t) in Eq. 3
and obtain:
tDarcy (t)
2Rbηg
H2 O ,
3kP(t) − Patm
(9)
where P(t) is given in Eq. 5. This implies that the gas loss rate
depends non-linearly on pressure oscillations. We can divide Eq.
9 by Eq. 3, to compare tDarcy in the oscillating and static cases,
yielding:
H2 O
P0 − Patm
P0
H2 O
P(t)
P(t) − Patm
4.4 Geological Implications
(10)
Our experiments investigate the influence of pressure oscillations
on bubble growth in magma. Magma may experience pressure
fluctuations in a range of natural scenarios, in particular in the
case of incoming seismic waves (Hill et al., 2002; Manga and
Brodsky, 2006; Seropian et al., 2021). Although the conclusions
from our experiments remain preliminary, we describe below the
conditions for which our findings would be relevant, in order to
guide future applications.
Seismic waves are a common source for pressure oscillations
on magma bodies. Typical frequencies for seismic waves are in
the range 0.1–10 Hz, though frequencies as low as 0.01 Hz could
2O
assuming that PH
atm 0. The evolution of this ratio with time is
shown in Figure 9C. When pressure increases, so does the
pressure differential between the melt and the furnace
atmosphere, hence gas loss accelerates and tDarcy is reduced by
~30%. Conversely, when melt pressure is reduced, permeable gas
flow is slowed down and tDarcy increases by ~70%. There is again
an imbalance between the higher and lower pressure parts of the
oscillation cycle, with an average increase of tDarcy . Therefore, if
gas loss occurs via filtration through the ceramic material (i.e., if
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Seropian et al.
Vesiculation Under Oscillatory Pressure
be attained for very large earthquakes (Manga and Brodsky,
2006). The amplitude of the stress perturbation depends on
many parameters, including the earthquakes’ magnitude,
distance to the epicentre, focal mechanism and local crustal
structure. Nonetheless typical values lie between 103 and
104 kPa in the near-field (<100–500 km, depending on
magnitude), and reduce to <100 kPa for distances >1,000 km
from the epicentre (e.g., Manga and Brodsky, 2006; Walter et al.,
2007, 2009; Avouris et al., 2017; Farías and Basualto, 2020).
Hence the pressure oscillations in our experiments (f =
0.01–0.1 Hz and ∆P = 71 kPa) are representative of natural
seismic waves following a large distant or moderate local
earthquake. Importantly, in our experiments, pressure
oscillations last for 15–110 min, whereas typical seismic waves
will produce oscillations for <5 min. Figure 5C suggests that
sample expansion is reduced, even in the case of short pressure
oscillations, but further work should aim at reducing this
discrepancy between experimental and natural oscillation
durations, to facilitate application.
The low confinement pressure (177 kPa), low water content
(0.11 wt%) and composition of our experiments correspond to a
very shallow or surficial silicic magma. This is one end-member of
the spectrum of silicic magmas as they are generally stored at
higher confining pressures (100–250 MPa, e.g., Huber et al.,
2019), contain more dissolved water (typically 2–6 wt% in
subduction zones, e.g., Wallace et al., 1995), and are likely to
already contain bubbles. Nonetheless, we surmise that the
asymmetrical response, and effective reduction of bubble
nucleation would remain similar, provided that pressure
oscillations drive the system in and out of water saturation. It
is the pressure relative to the saturation pressure, rather than the
absolute pressure that dictates how bubble nucleation will
respond to pressure oscillations.
At higher water contents, however, melt viscosity will be
significantly reduced. For instance, our rhyolitic melt, in
equilibrium at 150 MPa and 775°C would contain 5.14 wt%
H2O (Liu et al., 2005), and its viscosity would be 105 Pa s
(Giordano et al., 2008). The bubble expansion timescale τ e (Eq.
8) would then be significantly reduced, meaning that the
volume of already existing bubbles could vary significantly
during the oscillations (as observed by Masotta and Keppler,
2017). This would have particularly important implications for
bubble coalescence, and possibly for bubble migration (e.g.,
Iwata et al., 2008; De Corato et al., 2019). Additionally, the
contained nature of our experiments is also relevant to natural
scenarios, where magma is contained and interacts with
variably permeable country rock (e.g., Jaupart and Allègre,
1991).
It is commonly assumed that seismic waves may induce
bubble nucleation in magma, increasing magma overpressure,
and potentially leading to unrest or an eruptive episode (e.g.,
Manga and Brodsky, 2006; Rothery et al., 2007; Cannata et al.,
2010; Hamling and Kilgour, 2020; Seropian et al., 2021), yet
this mechanism has never been validated experimentally. We
did not observe any evidence suggesting that pressure
oscillations triggered bubble nucleation in our experiments.
Our analysis of bubble nucleation suggests that the opposite
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could occur, that is pressure oscillations could hamper bubble
nucleation. We emphasize that the lack of evidence for
increased nucleation at our experimental conditions does
not mean that seismic waves cannot nucleate bubbles in
magma in general; our experiments featured high-viscosity,
crystal-poor, low water content rhyolite, all of which may limit
bubble nucleation processes (Shea, 2017). Hamling and
Kilgour (2020) showed that the necessary P-T and water
content conditions for seismic waves to promote bubble
nucleation form a very tight window, with the optimal case
being partially crystallized basalt. Therefore seismicallyenhanced bubble nucleation remains to be experimentally
tested as a viable mechanism to trigger eruptions and our
experimental data indicate that degree of supersaturation of
the melt is an essential parameter to constrain for oscillating
vesiculating experiments.
5 CONCLUSION
In this contribution we report a series of high-temperature
experiments investigating the effects of pressure oscillations on
magma vesiculation. We designed a novel experimental setup
where melt is contained within a cylindrical ceramic crucible and
pressurized with a piston-style plunger actuated in a thermomechanical analyzer; then vesiculation is studied in two types of
experiments: static (where pressure is maintained) and oscillating
(where pressure fluctuates). We carefully chose P-T conditions so
that the samples would be slightly oversaturated in water and
volatiles would slowly exsolve during an experiment. The
experiments show that vesicles are mostly present near the
sample edge in all cases, with very few vesicles in the sample
core, irrespective of testing conditions. We observe that both
sample expansion and the amount of bubbles present at the outer
margin are reduced when pressure oscillates, compared to the
static case. The oscillation amplitude exerts the strongest control
on this effect. The observed reduced volumes in oscillating
experiments can be explained by reduced vesiculation and/or
increased gas loss. We evaluated different processes which may
occur in the samples during the experiments, and discuss how
they would be affected by oscillatory pressures. This preliminary
analysis suggests that bubble formation could be hindered by
pressure fluctuations if the melt oscillates between over- and
undersaturated conditions. This work highlights the number of
interacting processes happening as magma vesiculates, each of
which is susceptible to modulation by external pressure
perturbations. These processes are particularly relevant to the
study of earthquake-volcano interactions, where a magma body
sits close to volatile saturation and responds to pressure
fluctuations.
DATA AVAILABILITY STATEMENT
The original contributions presented in the study are included in
the article/Supplementary Material, further inquiries can be
directed to the corresponding author.
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Seropian et al.
Vesiculation Under Oscillatory Pressure
AUTHOR CONTRIBUTIONS
(NE/T007796/1). YL was supported by a Research Fellowship of
the Leverhulme Trust (RF-2019–526\4). JV and DD
acknowledge the support of ERC 2018 ADV Grant 834225
(EAVESDROP).
GS, BK, JK, YL and FW conceptualized models and designed the
experiments. GS performed the experiments with the help of FvA,
DD, K-UH, AL, JS and JV. GS and AN carried out H2O analysis.
GS performed SEM imaging and drafted the figures. Numerical
calculations were performed by GS and JV. All authors
contributed to the interpretation of the data and the writing of
the final version of the paper.
ACKNOWLEDGMENTS
We thank Rob Spiers for his help preparing samples, Shaun
Mucalo for his help with SEM observation.
FUNDING
GS and BK acknowledge the Royal Society Te Apārangi Marsden
grant “Shaking magma to trigger eruptions”. GS was also
supported by a DAAD fellowship. JK was funded by an Early
Career Fellowship of the Leverhulme Trust (ECF-2016-325). YL,
FBW and AL acknowledge the support of a NERC standard grant
SUPPLEMENTARY MATERIAL
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Conflict of Interest: The authors declare that the research was conducted in the
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The reviewer SB declared a past co-authorship with the authors to the handling
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March 2022 | Volume 10 | Article 812311