Balucan_2011_Optimization of antigorite heat pre-treatment via kinetics modeling of the dehydroxylation reaction for CO2 minera

1© 2011 Society of Chemical Industry and John Wiley & Sons, Ltd | Greenhouse Gas Sci Technol. 1:1–11 (2011); DOI: 10.1002/ghg
Correspondence to: Reydick D. Balucan, Priority Research Centre for Energy, The University of Newcastle, Callaghan,
NSW 2308, Australia. E-mail: reydick.balucan@uon.edu.au
†This paper is part of the In Focus: Papers from ACEME10 - the Accelerated Carbonation for Environmental and
Materials Engineering conference issue.
Received June 6, 2011; revised and accepted July 21, 2011
Published online at Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/ghg.33
Modeling and Analysis
Optimization of antigorite heat
pre-treatment via kinetic modeling
of the dehydroxylation reaction for
CO2 mineralization†
Reydick D. Balucan and Eric M. Kennedy, The University of Newcastle, Callaghan, NSW, Australia
John F. Mackie, The University of Newcastle and The University of Sydney, NSW, Australia
Bogdan Z. Dlugogorski, The University of Newcastle, Callaghan, NSW, Australia
Abstract: This contribution describes a predictive framework expedient to the thermal processing of
serpentinites for the mineralization of CO2. We demonstrate the optimization of heat treatment of
antigorite, providing a benchmark of an extreme case of activation among serpentine minerals. Antigo-
rite was investigated non-isothermally via thermogravimetry-mass spectrometry and in situ X-ray
powder diffraction, its thermal reaction sequence elucidated, and reaction kinetics subsequently
modeled. Based on the thermally induced structural changes, preferred content of residual hydroxyls
in the dehydroxylated antigorite amounts to 10–40% of those present initially. This degree of dehy-
droxylation minimized the transformation of antigorite into new crystalline phases maximizing the
amorphization of the new structure. The thermal reaction sequence provided both the explanation for
the observed kinetic behavior and the basis for this optimization strategy. The optimal time for heat
activation corresponds to ≤ 30 min, including the heat-up period at a rate of 30 °C min–1
and an iso-
thermal stage at 730 °C. This was successfully modeled using a three-dimensional phase boundary
reaction model (R3), with activation energy Ea of 160 kJ mol–1
and a frequency factor A of 5.7 ± 4.1 ×
105
s–1
(5.7 × 105
s–1
for dynamic and 1.6 × 105
s–1
for static stage). This strategy translates to a fast
and efﬁcient thermal processing in an optimally sized calcining vessel. Furthermore, these results imply
that activation of the more common serpentine minerals lizardite and chrysotile would be signiﬁcantly
faster as their dehydroxylation proceeds at lower temperatures than that of antigorite.
© 2011 Society of Chemical Industry and John Wiley & Sons, Ltd
Keywords: activation; dehydroxylation; heat treatment; serpentinite
Introduction
T
he direct aqueous-phase mineralization of CO2
with heat-activated serpentine minerals is a
technologically feasible CO2 fixation solution and
arguably the best mineral carbonation process to-
date.1–9
On the other hand, its economic viability
remains vague.10
This uncertainty is largely due to
the energy requirements, in particular, the thermal
pre-treatment stage that is sometimes deemed

RD Balucan et al. Modeling and Analysis: Thermal activation of antigorite for the mineralization of CO2
2 © 2011 Society of Chemical Industry and John Wiley & Sons, Ltd | Greenhouse Gas Sci Technol. 1:1–11 (2011); DOI: 10.1002/ghg
prohibitive and economically non-viable.11,12
It must
be noted, however, that previous energy and cost
estimates were based on electrical heating at 630 °C
for 2 h and generally implemented irrespective of the
serpentine mineral composition. Previous energy
calculations represented overestimates, that did not
distinguish between heat and power duties,13
and
considered no heat integration and/or recovery of
sensible and latent heat into the process. By using heat
instead of electricity in thermal pre-treatment, the
energy requirement can be lowered by at least ~ 30%.9
Furthermore, thermal treatment via direct heating
using heat of combustion with carbonaceous or
hydrocarbonaceous fuel is not only inexpensive and
more efficient as compared to electric heating,9,14
but
also allows for processing at higher temperatures.
Although thermal reactions of serpentine minerals
had been subjected to numerous studies,15–26
an
optimized processing strategy for CO2 mineralization
applications is scarce.27,28 In general, the enhanced
reactivity of thermally activated serpentine minerals
was attributed to the destruction of mineral crystal-
linity with the removal of structurally bound hy-
droxyl groups, resulting in improved Mg mobility in
the subsequent aqueous carbonation stage.27 This
information alone is insufficient and requires crucial
knowledge of the optimal structure for each ore and
its respective optimal dehydroxylation temperature.
These two dictate the required time (at a given heating
rate) necessary to design a practical dehydroxylation
process. The importance of mineral considerations, as
was exemplified by the huge disparity of serpentine
conversion on identically heat-treated serpentine
minerals, with antigorite achieving 92% while lizard-
ite only achieved 40%.11
Despite their mineralogical
differences both had been treated identically. It can
then be deduced that an optimal structure exists, and
varies from ore to ore. Once the idealized activated
structure for a particular feedstock has been identi-
fied, modeled, and predicted, only then can actual
energy requirements be reasonably estimated.
Serpentine dehydroxylation is complex and in-
cludes phase transition and formation of intermedi-
ate mineral phases.22,27
Obtaining the exact kinetic
data solely from non-isothermal thermogravimetry
is difficult, hence, in practice, one employs apparent
kinetic parameters. This approach relies on the
measurement of the overall weight change during the
dehydroxylation, as the evolution of water from
structurally bound hydroxyls relates to the degree of
dehydroxylation with time. Non-linear regression of
the derivative thermogravimetric curve then pro-
vides a direct and rapid method to estimate the
apparent kinetic parameters. The direct non-linear
regression reconstructs experimental measurements
more accurately than classical linearization meth-
ods.29,30
This is because the direct methods avoid the
assumption of high energy of activation and do not
rely on an incomplete expression of the Taylor
expansion.
Previous studies on serpentine kinetics do not reflect
the particle size of interest for direct aqueous mineral
carbonation, but rather involve either coarse
(> 150 μm) or too fine particles < 10 μm.17,19,20,25
Serpentine feedstock for direct aqueous carbonation
uses 38 to 75 μm particles to provide reasonable
reactivity at manageable energy penalties.2,4 The
reported activation energy values for serpentine
minerals vary from 184 to 630 kJ mol–1 in various
reaction mechanisms.17,19,20 This huge, and chemically
unrealistic, variation in activation energy had been
attributed to the presence of water vapor, differences
in experimental apparatus, processing history,
methods of kinetic analysis, ore purity and mineral
assemblages.15–21,23–25,31 In particular, the presence of
water vapor may engender a reverse reaction. If this
occurs, the rate measurements become a function of a
local concentration of water vapor, resulting in poorly
controlled experimental conditions, leading to
unreasonable values of activation energies derived
from such experiments. Fundamentally, the problem
resides in modeling the dehydroxylation process by a
forward step, whereas both forward and reverse steps
occur; i.e. the reaction takes place under near-
equilibrium conditions. Experiments must either be
performed under an imposed well-defined
concentration of water vapor or replicate runs must be
carried out at different flows of purge gas (as done in
the current study) to establish the validity of the
non-equilibrium conditions.
The present situation, of uncertain kinetic
parameters for dehydroxylation of serpentine
minerals, needs redressing, both for fundamental and
practical reasons. The latter would then facilitate the
prediction of the optimum processing conditions
appropriate for serpentine minerals to enable the
design of efficient unit operations for mineral
processing. In this study, we present a new set of
precise experimental measurements acquired under
well-controlled conditions, allowing us to develop

Modeling and Analysis: Thermal activation of antigorite for the mineralization of CO2 RD Balucan et al.
accurate and practical models of serpentine
dehydroxylation. We used serpentinite which
contained mostly antigorite (antigorite has the highest
dehydroxylation temperature among serpentine
minerals) to represent the extreme case of thermal
activation.
The present contribution aims to demonstrate a
novel approach of optimizing the heat treatment stage
of serpentine minerals as feedstock for the direct
aqueous reaction with carbon dioxide. This involves
the identification of mineralogical changes associated
with the degree of dehydroxylation, elucidation of the
thermal reaction sequence and subsequently modeling
the kinetics of the reaction at the phenomenological
level. We then identify, predict, and validate the
optimal pre-treatment strategy for this particular
serpentinite sample, which consists of the desired
degree of dehydroxylation, optimal treatment tem-
perature, and reaction time.
Experimental
Antigorite-containing serpentinite, from the Great
Serpentine Belt of New South Wales, Australia, was
wet ground to 80% passing -75 μm, wet demagnetized,
dried at 105 °C, and then used in experiments without
further purification. Volumetric particle size distribu-
tion was determined by LALLS with Malvern Master-
sizer 2000 laser sizer, with measurements and valida-
tions conducted in aqueous media. Phase
identification by X-ray powder diffraction (XRPD)
was performed in Philips X’Pert Pro multipurpose
diffractometer using Cu Kα radiation in the range of
6-90° 2θ, with a step size of 0.02° and collection time
of 1 s step–1
. In situ hot-stage XRPD, at various
temperatures from 30–1100 °C each at 5 min scans,
was accomplished using an Anton Parr HTK16 fitted
with a platinum strip hot-stage. Temperature verifica-
tion was achieved by running standard minerals with
well-known phase reactions. The generated patterns
were matched against the International Centre for
Diffraction Data
®using X’pert Highscore
®, then
manually compared and checked for validity prior to
acceptance.32
A Spectro X’lab 2000 apparatus served
to analyze the chemical composition by polarized
energy dispersive X-ray fluorescence. Morphological
examination with scanning electron microscopy on
gold-coated samples was performed with Philips
XL30 SEM, operated at 15 kV and using a secondary
electron detector. Amdel Mineral Processing
Laboratories provided measurements for total organic
carbon and total carbon content.
Thermogravimetry analysis-mass spectrometry
(TGA-MS) for kinetic analysis was performed in a
Setaram Setsys Evolution 1200 TGA coupled to a
Pfeiffer Thermostar quadruple mass spectrometer.
Typically, samples of 5.50 ± 0.1 mg were heated in an
open alumina crucible under argon flowing at 20 and
200 ml min–1
, with imposed heating rates of 10, 20,
and 30 °C min–1
from 30 to 1000 °C. Duplicates for
kinetic runs were employed to ensure reproducibility
and accepted when within ± 0.1% of the total mass
loss. Blank runs involving empty crucibles for buoy-
ancy correction were carried out under identical
flow-rate and heating-rate to the actual kinetic runs.
The derivative thermogravimetric (DTG) curves were
then obtained via proprietary electronic differentia-
tion of the TG signal using the SetSoft 2000 software.
Kinetic analysis and modeling
Typical solid-state thermal processes, generally
represented by Eqn (1), involve heterogeneous decom-
position reactions. For kinetic studies, either an
appropriate flow of inert gas or vacuum is continu-
ously applied to the reaction system for immediate
depletion of any generated volatile products. This
negates reaction reversibility and ensures the reaction
occurring far from equilibrium. The mass change
with time then directly relates to the forward reaction
rate.
A(s) → B(s) + C(g) (1)
The reaction rate is commonly expressed in Eqn (2).
The temperature dependence of rate constant, k, is
given by the Arrhenius equation; where A is the
frequency factor, Ea the activation energy, T the
absolute temperature, R the gas constant, f(α) a
reaction or diffusion model (defined in Table 4 for the
present study), and α the conversion fraction.
kf( ) = Aexp
−E
RT
a
=
d
dt
α
α f( )α (2)
Equation (3) defines the fraction reacted, α, where mi,
mt and mf are initial mass, mass at time t and final
mass, respectively.
mi mt−
mi mf−
α = (3)

Simulation of the mass loss curve, for a particular
reaction model was carried out using Eqn (4). For
serpentinite, the DTG curves relate to the dehydroxy-
lation rate, where mc corresponds to the total mass of
evolved water.
m=
d
dt
m
sim
c
d
dt
α
= cm Aexp
−E
RT
a
f( )α− (4)
The apparent kinetic parameters were obtained via
non-linear regression employing the LM algorithm for
simultaneously fitting Ea and A using literature values
as initial estimations. This iterative solution method
minimized the sum of the squared difference between
the experimental DTG curve, −(dm/dt)exp, and the
fitted curve, −(dm/dt)sim (Eqn (5)). The quality of the
fitted parameters was assessed and accepted based on
the regression coefficient (r2), confidence intervals at
95% and residual plots.
OF
d
dt
m
exp
d
dt
m
sim
−= ∑
2
(5)
Model validations, predictions and simulations of
DTG curves were accomplished via RKF56 algorithm
to provide highly precise numerical solution for a
system of ordinary differential and algebraic
equations. Solvers for non-linear regression and
ordinary differential equations, embedded in POLY-
MATH 6.1 software, facilitated data processing.
Results and discussion
The serpentinite sample was predominantly crystal-
line antigorite (Antigorite-8.0M, ref. code: 00-007-
0417) with relatively minor phase of magnetite
(Triiron oxide, ref. code: 01-089-0691 and periclase
(MgO, ref. code: 01-077-2364). Following wet mag-
netic separation to remove magnetite, the serpentinite
ore grade was estimated at 98%. Figure 1 shows the
X-ray diffraction pattern of the sample before and
after demagnetization. As antigorite was the crystal-
line serpentine mineral identified, from now on the
serpentinite sample will be interchangeably referred to
as antigorite.
Characteristic volumetric size distribution, shown in
Table 1, reflects that of the targeted mineral carbon-
ation feed material at 80% passing 75 μm. This distri-
bution represented the comminution operation where a
mixture of fines and oversized particles was generated.
As shown in Table 2, chemical composition of the
demagnetized material is typical for antigorite, having
relatively low value of the loss on ignition at 1000 °C
and high Fe content among serpentine minerals. The
LOI1000v denotes mass of volatiles evolved from
Figure 1. X-ray powder diffraction patterns of natural and demagnetised serpentinite (antigorite). Intensity
of the demagnetised sample is stacked vertically by 20,000 units.

mineral samples when heated to 1000 °C; usually, this
corresponds to free and crystalline water, as well as
CO2 from the decomposition of carbonates. Elemental
impurities include Al and trace amounts of Mn, Ca,
K, P, S, and Ti. Organic carbon comprises 0.3 mg g–1
while the inorganic carbon content is at 0.5 mg g–1
.
Should carbonate decomposition occur at the dehy-
droxylation region, the inorganic carbon content is no
more than 0.05%w/w, and is therefore negligible. Based
on this composition, a RCO2
value of 2.2, pertaining to
the minimum tonnage of mineral for fixing 1 tonne of
CO2 was calculated assuming complete (stoichiomet-
ric) carbonation of Mg and Fe.
Antigorite particles, as illustrated in Fig. 2, exhibited
angular morphology where edges and exposed
surfaces smoothened-out upon thermal treatment.
The well-known serpentine transformation to forster-
ite and enstatite is physically evident as a geometric
modification of the mineral. The formation of new
mineral phases normally proceeds via nucleation,
hence, in the kinetic analysis, this study employed
models of phase-boundary and nucleation reaction.
Figures 3(a)–3(b) confirm that the mass loss (11.4 ±
0.2%) results from the evolution of crystalline (hy-
droxyl-derived) water. No change in mass was ob-
served below 105 °C, indicating negligible content of
free water. Mass loss was prominent within the
500–800 °C region, bracketing the expected tempera-
ture range of antigorite dehydroxylation. The dehy-
droxylation rate attains maximum, -(dm/dt)max, of
(9.7 ± 0.3) × 10–4
mg s–1
, at around 730 °C. The
relatively high doublet peak temperature, Tp,33
charac-
teristic of antigorite, corresponds to Tp1 and Tp2 at
712 °C and 731 °C, respectively. These peaks signify
the subsequent formation of the mineral forsterite
(Mg2SiO4) and an intermediate phase (denoted as D2)
to be discussed in more detail in subsequent sections.
The in situ generated intermediate mineral phases
during the thermal treatment of antigorite, seen in
Fig. 4(a), were similarly observed for lizardite and
chrysotile.22,27 For antigorite, the formation of the
intermediate phases occur at relatively high tempera-
tures. The crystalline phase was predominantly
antigorite until 600 °C, where a low angle feature
appears at 6–7.5° 2θ. This reflection, corresponding to
d3,2 (µm) d4,3 (µm) d90 (µm) d50 (µm) d10 (µm)
5.31 44.2 128 16.0 1.86
Table 1. Volumetric particle size distribution
of the antigorite sample.
SiO2 MgO Fe2O3 Al2O3 CaO Na2O MnO SO3 P2O5 TiO2 K2O LOI1000
43.2 38.2 4.82 1.04 0.13 0.11 0.08 0.03 0.02 0.01 0.01 11.9
Table 2. Chemical composition of the antigorite sample by weight as % oxide.
Figure 2. SEM micrographs of (a) untreated and (b) thermally treated serpentinite
(antigorite).

d spacing of 14 Å, is likely caused by doubling of the
interlamellar spacing at (001) (d spacing = 7 Å).
Forsterite was then first observed by 725 °C. At
750 °C, another low angle feature appears at 7.5–
10° 2θ. This reflection corresponds to d spacing of
10 Å, and could be doubling of 17° 2θ reflection (d
spacing = 5 Å). The doubling of d spacings indicates
voids in the octahedral layers due to progressive
dehydroxylation. Both low-angle reflections were
designated similarly to the intermediates formed in
thermal treatment of chrysotile,22
as dehydroxylates 1
and 2 (D1 and D2). By 800 °C, characteristic reflec-
tions of antigorite along (001) and (002), correspond-
ing to 12 and 24° 2θ, disappear, signifying the collapse
of interlamellar spacings.
At higher temperatures ~ 800–825 °C, another
crystalline phase, corresponding to mineral enstatite
(MgSiO3) forms, and persists alongside forsterite. As a
chain silicate (pyroxene), estatite is unreactive to
carbonation.27,34
Hence, the reactivity of antigorite,
thermally treated in excess of 800 °C, will decline
proportionally to its enstatite content.
Numerical integration of the three main antigorite
reflections at 11–13, 24–26, 35–46° 2θ and one for
platinum at 65–67° 2θ produced a series of area
counts tracking antigorite dehydroxylation. The
antigorite-platinum ratio, as shown in Fig. 4(b),
follows that of the TGA-derived content of OH
content. This directly relates the OH content of the
bulk rock to the in situ generated phases via the
temperature measurements where these phases were
observed. Table 3 summarizes the corresponding
content of OH for the observed minerals phases.
Table 4 summarizes the apparent kinetic parameters,
where random nucleation model (F1) yields the highest
Ea and A values followed by the phase-boundary
Figure 4. Plots for (a) in-situ XRPD patterns at various temperatures and (b) correlation of non-isothermal XPRD
and TGA. The crystalline minerals and hypothetical intermediate phases are labelled as A: antigorite, D1:
dehydroxylate 1, D2 : dehydroxylate 2, F: forsterite and E: enstatite.
Figure 3. Typical curves for (a) TGA-DTG and (b) MS depicted as ion current intensities for H2O (m/z = 18) and CO2
(m/z = 44) during serpentinite (antigorite) dehydroxylation reaction.

reaction mechanisms (R3) and (R2), respectively. The
Ea value for F1 model (193 ± 2 kJ mol–1) is slightly
lower than previously reported in literature for
serpentine at 202–502 kJ mol–1.17 Activation energy
for R2 model (134 ± 11 kJ mol–1 ) is closer to those
reported for brucite at 146 kJ mol–1,35 while the values
calculated from the R3 model (160 ± 7 kJ mol–1) fall
midway between those reported for brucite and
serpentine. The R3 model, besides providing better fit
in all three heating rates, was confirmed by morpho-
logical observations. Alternatively, the transformation
could initially follow R2 mechanism, shifting to
nucleation mechanism at later stages.
While the kinetic compensation effect (KCE),
including its validity and significance, is beyond the
scope of this paper, this mutual dependence of A and
Ea, were only observed for both R2 and R3 mecha-
nisms (a plot of ln A vs Ea yields a correlation coeffi-
cient r2
close to unity). The isokinetic temperatures, Ti,
for R2 and R3 were estimated at 489 °C and 474 °C,
respectively. While Ea and A values for phase bound-
ary reaction models systematically increased with
heating rate, the increase in Ea values were minimal
(within ~95% confidence interval) as compared to the
A values. This observed compensation effect is prob-
ably a mere computational artifact innate to the
deficiencies of extending the Arrhenius equation to
Table 3. In situ generated mineral phases and the
corresponding bulk % OH content of the rock.
Mineral Phase (in situ XRPD) OH content, % (TGA)
Antigorite 10–100
Dehydroxylate 1 10–88
Forsterite 0–30
Dehydroxylate 2 0–10
Enstatite 0
Heating rate,
°C min–1
Flow rate,
ml min–1
Parameters
Contracting
cylinder (R2)
f(α) = 2(1 − α)0.5
Contracting
sphere (R3)
f(α) = 3(1 − α)0.67
Random
nucleation (F1)
f(α) = (1 − α)
10
20
E, kJ mol–1
95% Confidence
122
5
151
7
196
0.08
A, s–1
95% Confidence
3.4 × 103
1.9 × 103
9.8 × 104
8.0 × 104
1.0 × 108
9.8 × 105
r2 0.8471 0.8969 0.8635
200
E, kJ mol–1
95% Confidence
119
5
146
7
196
0.08
A, s–1
95% Confidence
2.2 × 103
1.1 × 103
5.4 × 104
3.5 × 104
1.0 × 108
8.0 × 105
r2 0.8746 0.9245 0.8987
20 20
E, kJ mol–1
95% Confidence
139
6
164
6
193
0.01
A, s–1
95% Confidence
4.6 × 104
3.3 × 104
7.2 × 105
5.7 × 105
1.0 × 108
1.4 × 105
r2
0.9647 0.9633 0.8877
30 20
E, kJ mol–1
95% Confidence
142
7
164
8
191
0.13
A, s–1
95% Confidence
8.4 × 104
7.5 × 104
8.8 × 105
8.0 × 105
1.0 × 108
1.5 × 106
r2 0.9722 0.9680 0.9199
*Mean
E, kJ mol–1
σ
134
11
160
7
193
2
A, s–1
σ
4.4 × 104
4.1 × 104
5.7 × 105
4.1 × 105
1.0 × 108
0
*Mean values at heating rates of 10, 20, and 30 at a gas flow rate of 20 ml min–1
Table 4. Apparent kinetic parameters for R2, R3, and F1 models at various conditions.

solid-state kinetics. However, if it is not just a math-
ematical consequence, the larger range of A values
compared to Ea may indicate enhancements at high
heating rates largely driven by entropic and much less
by enthalpic contributions (KCE was previously
known as enthalpy-entropy compensation effect). This
means that while the threshold energy transferred
though lattice vibrations do not deviate substantially
with increased heating rates, the resulting increase in
vibratory frequency induces a more efficient release of
volatile component. To account for this effect in
subsequent model validations and predictions with R
models, the mean Ea values were used while A values
were adjusted (but maintained within the range
obtained) to correspond to the imposed heating rate.
As in the case of an isothermal stage, the lowest
possible A value within the obtained range (i.e. 1.6 ×
105
s–1
for R3’s 5.7 ± 4.1 × 105
s–1
) was used.
The kinetic parameters were validated via recon-
structions of the of the DTG curves (obtained using
heating rate of 10 °C min–1
) at the 400–800 °C region.
As clearly indicated in Figs 5(a–c), the R3 model
provided a good overall match to the experimental
measurements. The R3 reconstruction matched well
the peak region from 620–800 °C, overall curve shape,
−(dm/dt)max and Tp. While during dehydroxylation,
minerals may undergo several successive steps, only
the R3 mechanism provided a practical, physically
evident and phenomenologically valid model for
simulating the overall thermal behavior of antigorite.
Furthermore, the predictive capability of the R3
model was tested by simulating the effect of sample
Figure 5. Model validation via reconstructions of the experimental DTG curve using (a) contracting cylinder R2,
(b) contracting sphere R3 and (c) random nucleation model F1. Simulation of DTG curves using the R3 model to
predict the effects of (d) sample mass SMx and (e) heating rates HRy.

Figure 6. Degree of dehydroxylation achieved during heat activation at (a) 730 °C showing the good agreement
between experimental and the R3 model prediction (Ea value of 160 kJ mol–1
and A of 5.7 × 105
s–1
for the
dynamic heating rate and 1.6 × 105
s–1
for static heating stage, respectively) and (b) experimentally observed
activation proﬁle at 630 °C and 730 °C. Lizardite activation at 630 °C is included for comparison.
mass and heating rates. Figures 5(d) and 5(e)
demonstrated that these effects were well accounted
for, showing the increasing trend in the dehydroxyla-
tion rates for both process variables, yielding the
correct locations of the −(dm/dt)max and Tp.
Considering that thermal energy is provided directly
from combustion, high-grade heat allows for high
temperature operations. Heat activation of antigorite
is then best performed at the mineral Tp, where the
rate is at its maximum. This heat treatment at 730 °C
was then predicted using R3 with Ea of 160 kJ mol–1
antigorite and A of 5.7 × 105
s–1
for heat-up period at
30 °C min–1
and 1.6 × 105
s–1
for the isothermal stage.
Figure 6(a) shows the good agreement for the pre-
dicted and observed antigorite dehydroxylation
carried out at 730 °C. The overall heat treatment
process for antigorite, which consists of heat-up and
isothermal stages, is complete within 34 min. The
heat-up period, from 30 to 730 °C at 30 °C min–1
requires 24 min, while the isothermal stage at 730 °C
to attain 90% dehydroxylation adds 6 min to the
operation. During the heat-up period, approximately
60% of total hydroxyls were removed from
500–730 °C. Full dehydroxylation requires 10 min of
the isothermal operation at 730 °C. But such opera-
tion is undesirable, as mineral’s reactivity deteriorates
for dehydroxylation in excess of 90%.34
The duration and temperature of dehydroxylation
define the reactivity of the activated mineral during
dissolution step in the aqueous carbonation. It was
observed that ≤ 90% dehydroxylation leads to
optimal reactivity.34 Generally, 120 min had been
previously used to activate both antigorite and
lizardite, with particles −38 μm in size. However,
serpentine conversions were significantly higher for
antigorite at 92% than lizardite at 40%.11 To probe
this difference, we performed isothermal activation
at 630 °C for 2 h on the antigorite sample and on
another serpentinite containing lizardite as a major
phase (both from the Great Serpentinite Belt). Figure
6(b) shows that this heat pre-treatment fully dehy-
droxylated lizardite but only removed ~55% of
antigorite’s hydroxyl content. Furthermore, the
comparison of two activation temperatures for
antigorite point up to the differences in dehydroxyla-
tion rates at 730 °C and 630 °C. Although the opti-
mal degree of dehydroxylation to maximize conver-
sion requires experimental verification, the higher
conversion for antigorite compared to lizardite may
be attributed to the variation in the structural
composition of the two minerals.
At 40% OH content, only antigorite and dehydroxy-
late 1 were present (Table 3). Forsterite only starts to
form when OH content is less than 30%. At 90%
dehydroxylation, dehydroxylate 2 is visible while both
dehydroxylate 1 and antigorite disappear. This occurs
at 800 o
C, where, as seen from Fig. 4, the interlayer
spacings collapse. It can then be deduced that serpen-
tine activation must not exceed 90% dehydroxylation
to maintain an open, layered structure.

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Conclusion
In this study, we demonstrated the optimization of
antigorite heat treatment, providing a benchmark of
an extreme case of activation among serpentine
minerals. This was made via the development of a
novel predictive framework, affording the optimisa-
tion of the dehydroxylation process as function of
processing temperature and residence time to provide
a methodology for designing practical unit operations
for thermal processing of serpentinite ores. Based on
the observed structural changes, a properly activated
antigorite appears to contain between 10 and 40%
residual hydroxyls. The optimum activation strategy
inferred from the combined kinetic and mechanistic
considerations amounts to the production of a 60–
90% dehydroxylated mineral, isothermally at 730 °C
for ≤ 6 min. On the other hand, the present results
indicate that the reason of low activity of lizardite,
reported in literature,11 rests with excessive duration
of activation that led to the collapse in the mineral
structure and formation of relatively unreactive
enstatite upon full dehydroxylation. Generally, the
suggested heat treatment strategy translates to a fast
and efficient thermal processing in an optimally sized
calcining vessel. The activation of the more common
serpentine minerals lizardite and chrysotile is ex-
pected to be significantly faster as dehydroxylation
proceeds at lower temperatures than antigorite. Due
to mineralogical differences and composition of
serpentinites, heat treatment and its optimization
must be unique for each ore.
Acknowledgements
This study was funded in part by an internal grant
(Ref. No. G0189103) from the University of Newcastle.
D. Phelan and J. Zobec (EM-X-ray Unit, University of
Newcastle) assisted with SEM, XRF and XRD analy-
ses. Discussions with Prof. Erich Kisi, Dr Judy Bailey,
and Ms Monica Davis are greatly appreciated. Reydick
Balucan thanks the University of Newcastle for the
postgraduate research scholarship.
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Reydick Balucan
Reydick D. Balucan is a post-graduate
researcher working on mineral carbon-
ation at the Priority Research Centre
for Energy, University of Newcastle.
His focus is in the optimization of
direct aqueous mineral carbonation of
serpentine minerals. He holds a BSc in
Chemistry from Negros Oriental State University
(Philippines) and will ﬁnish his PhD (Chemical Engineer-
ing) by 2012.
Eric Kennedy
Professor Eric M. Kennedy is the
Deputy Director of the Priority Re-
search Centre for Energy, The Univer-
sity of Newcastle. He holds a BSc
(New South Wales) in Pure and
Applied Chemistry and a PhD (New
South Wales) in Physical Chemistry.
His interests include mitigation of ozone-depleting
gases as well as CO2 capture and storage.
John Mackie
Professor John F. Mackie is a conjoint
professor in Chemical Engineering at
the University of Newcastle. He holds
a DSc (Sydney) in Chemistry. He
specializes in chemical kinetics,
quantum chemistry and high tempera-
ture chemistry. He is a member of the
Priority Research Centre for Energy, University of
Newcastle.
Bogdan Dlugogorski
Prof. Bogdan Z. Dlugogorski is a
Fellow of the Australian Academy of
Technological Sciences and Engineer-
ing and the Director of the Priority
Research Centre for Energy, University
of Newcastle. He holds a BSc (Cal-
gary) in Chemical Engineering and
Geophysics, and an MEng (McGill), a PhD (Montreal)
and a DSc (Newcastle). His research interests are in
process safety and environment protection, including
CO2 storage.

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