Dataset for H2, CH4 and Organic Compounds Formation during Experimental Serpentinization

Abstract

Serpentinization refers to the alteration of ultramafic rocks that produces serpentines and secondary (hydr)oxides under hydrothermal conditions. Serpentinization can generate H2, which in turn can potentially reduce CO/CO2 and produce organic molecules via Fischer–Tropsch type (FTT) and Sabatier type reactions. Over the last two decades, serpentinization has been extensively studied in laboratories, mainly due to its potential applications in prebiotic chemistry, origin of life in extreme environments, development of carbon‐free energies and CO2 sequestration. However, the production of H2 and organics during experimental serpentinization is hugely variable from one publication to another. The experiments span over a large range of pressure and temperature conditions, and starting compositions of fluid and solid phases are also highly variable, which collectively adds up to more than a hundred variables and leads to controversial results. Therefore, it is extremely difficult to compare results between studies, explain their variability and identify key parameters controlling the reactions. To overcome these limitations, we collected and analysed 30 peer‐reviewed articles including over 100 experimental parameters and ca. 30 mineral and organic products, hence building up a database can be completed and implemented in future studies. We then extracted basic statistical information from this dataset and demonstrate how such a comprehensive dataset is essential to better interpret available data and discuss the key parameters controlling the effectiveness of H2, CH4 and other organics production during experimental serpentinization. This is essential to guide the design of future experiments.

Full text

90
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Geosci Data J. 2021;8:90–100.
wileyonlinelibrary.com/journal/gdj3
Received: 2 September 2019
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Revised: 10 July 2020
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Accepted: 13 July 2020
DOI: 10.1002/gdj3.105
SPECIAL ISSUE DCO
Dataset for H2, CH4 and organic compounds formation during
experimental serpentinization
FangHuang1,2
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SamuelBarbier3,4
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RenbiaoTao3
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JihuaHao3
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PabloGarcia del Real3
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StevePeuble3
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AndrewMerdith3
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VladimirLeichnig3
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Jean-PhilippePerrillat3
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KathyFontaine1
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PeterFox1
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MurielAndreani3
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IsabelleDaniel3
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original
work is properly cited.
© 2020 The Authors. Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd.
Huang and Barbier are co-first authors
Dataset
Identifier: http://info.deepcarbon.net/individual/n1819
Creators: Samuel Barbier, Fang Huang, Renbiao Tao, Jihua Hao, Pablo Gracia del Real, Steve Peuble, Andrew Merdith, Vladimir Leichnig, Valentine
Megevand, Jean-Philippe Perrillat, Isabelle Daniel, Muriel Andreani
Title: Dataset for H2, CH4 and Organic Compounds Formation during Experimental Serpentinization
Publisher: Deep Carbon Observatory
Publication year: 2019
Resource type: Dataset
Version: 1.0
1Tetherless World Constellation, Rensselaer
Polytechnic Institute, Troy, NY, USA
2CSIRO Mineral Resources, Kensington,
WA, Australia
3Univ Lyon, Univ Lyon 1, ENSL, CNRS,
LGL-TPE, Villeurbanne, France
4Total CSTJF, Pau, France
Correspondence
Fang Huang, CSIRO Mineral Resources,
Kensington, 26 Dick Perry Ave, WA 6151,
Australia.
Email: f.huang@csiro.au
Funding information
TOTAL EP R&D Project MAFOOT; Deep
Carbon Observatory through Alfred P.
Sloan Foundation, Grant/Award Number:
G-2018-11204
Abstract
Serpentinization refers to the alteration of ultramafic rocks that produces serpen-
tines and secondary (hydr)oxides under hydrothermal conditions. Serpentinization
can generate H2, which in turn can potentially reduce CO/CO2 and produce organic
molecules via Fischer–Tropsch type (FTT) and Sabatier type reactions. Over the last
two decades, serpentinization has been extensively studied in laboratories, mainly
due to its potential applications in prebiotic chemistry, origin of life in extreme en-
vironments, development of carbon-free energies and CO2 sequestration. However,
the production of H2 and organics during experimental serpentinization is hugely
variable from one publication to another. The experiments span over a large range
of pressure and temperature conditions, and starting compositions of fluid and solid
phases are also highly variable, which collectively adds up to more than a hundred
variables and leads to controversial results. Therefore, it is extremely difficult to
compare results between studies, explain their variability and identify key param-
eters controlling the reactions. To overcome these limitations, we collected and ana-
lysed 30 peer-reviewed articles including over 100 experimental parameters and ca.
30 mineral and organic products, hence building up a database can be completed and

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HUANG et Al.
1
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INTRODUCTION
Earth's mantle is predominantly composed of peridotites,
a type of rock made of Mg- and Fe-rich silicate minerals
such as olivine and pyroxene. Though modern Earth's crust
is not ultramafic, plate tectonics bring ultramafic rocks to
the surface of Earth at various geologic settings, such as
slow mid-ocean ridges (e.g. Mid Atlantic Ridge, Southwest
Indian Ridge), oceanic transform faults (e.g. Vema OTF in
the Atlantic, São Pedro and São Paulo Archipel OTFs in
the Equatorial Atlantic, Shaka and Prince Edward OTFs in
the South-West Indian Ocean) and at convergent margins
(e.g. Oman, New Caledonia). The alteration and hydration
of peridotite result in the formation of serpentine group
minerals (e.g. lizardite, chrysotile and antigorite) and
secondary (hydr)oxides (e.g. brucite, magnetite). These
serpentine-forming reactions are called serpentinization.
During serpentinization, the ferrous iron in olivine and py-
roxene is often oxidized to ferric iron, which produces H2
through the reduction of water. As a consequence, CO or
CO2 could be reduced by H2 through Sabatier type (R1)
or Fischer–Tropsch type (R2) reaction to form CH4 and/or
other organic compounds.
Analyses of many natural samples have shown abundant
release of H2, CH4 and other organic compounds in fluids
from natural serpentinization areas and questioned the exact
reactions mechanisms involved (Barnes et al., 1967; Wenner
and Taylor, 1973; Charlou et al., 2002; Proskurowski et al.,
2006, 2008; Konn et al., 2009). For instance, ultramafic rocks
were abundant on the primitive Earth and possibly other
rocky planetary bodies (Ehlmann et al., 2010; Zahnle et al.,
2011; Holm et al., 2015; Etiope et al., 2018), so their obser-
vation raises several major scientific questions related to ser-
pentinization (Sleep et al., 2004; Schulte et al., 2006; Russell
et al., 2010; Hellevang et al., 2011; Guillot and Hattori, 2013;
Mayhew et al., 2013; McCollom and Seewald, 2013; Brazil,
2017; Ménez et al., 2018): What is the role of serpentiniza-
tion in the origin of life—on Earth, and elsewhere? Could
the serpentinization reaction sustain microbial communities
in the primitive and modern ocean? Could our modern societ-
ies use the H2 produced by serpentinization reactions to help
reduce anthropogenic CO2 emission?
To address these questions, there is an urgent need to un-
derstand the serpentinization process and more specifically
its capacity to generate reducing conditions and produce abi-
otic organics. Therefore, tens of experiments have attempted
to provide answers to this question. Although they all agree
on the production of H2 by serpentinization (Sleep et al.,
2004; Seyfried et al., 2007), the production of CH4 and more
complex hydrocarbons (e.g. C2H6, C3H8) via FTT or Sabatier
reactions has always been and is still highly debated (e.g.
Evans et al., 2013; McCollom and Seewald, 2013; McCollom
et al., 2015). Despite the tremendous collaborative efforts of
the community all over the world, we still do not fully un-
derstand why similar experimental incentives lead to so con-
trasted, if not contradictory results. A strong limitation is that
those numerous serpentinization experiments have been run
under very different conditions using various creative proto-
cols. In order to understand the similarities and discrepan-
cies between results, it requires us to compare more than a
hundred variables not even fully identified before the present
study. Therefore, we carefully read 30 peer-reviewed publica-
tions that described experimental serpentinization and other
publications for comparison, analysed 195 experiments and
compiled parameters in the dataset described in Section 2.
This dataset will be continuously updated as news results be-
come available and used for various purposes related to ser-
pentinization and associated reactions.
2
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DATASET DESCRIPTION
2.1
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Overview of the dataset
We have collected the data in 30 relevant experimental articles
that report measured H2 and organic compounds (OC) pro-
duction related to the serpentinization reaction (Berndt et al.,
(1)
4H2
+CO
2
=CH
4
+2H
2O
(2)
(3n +1)H2+nCO2=CnH2n+2+2nH2O
implemented in future studies. We then extracted basic statistical information from
this dataset and demonstrate how such a comprehensive dataset is essential to better
interpret available data and discuss the key parameters controlling the effectiveness
of H2, CH4 and other organics production during experimental serpentinization. This
is essential to guide the design of future experiments.
KEYWORDS
abiotic hydrogen, abiotic methane, experimental serpentinization, hydrothermal

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1996; Horita and Berndt, 1999; McCollom and Seewald, 2001;
McCollom and Seewald, 2003; Allen and Seyfried, 2003;
Foustoukos and Seyfried, 2004; Seewald et al., 2006; Seyfried
et al., 2007; Fu et al., 2007, 2008; Ji et al., 2008; Dufaud
et al., 2009; Jones et al., 2010; McCollom et al., 2010, 2016;
Marcaillou et al., 2011; Neubeck et al., 2011, 2014; Lafay
et al., 2012; Lazar et al., 2012, 2015; Klein and McCollom,
2013; Okland et al., 2014; Klein et al., 2015; Huang et al.,
2015, 2016; McCollom, 2016; McCollom and Donaldson,
2016; Miller et al., 2017; Grozeva et al., 2017). The vast ma-
jority of these studies report on experimental serpentinization
starting with olivine or peridotites, but a couple of studies are
included in the dataset on purpose, to investigate FTT reac-
tions without olivine as a starting mineral (Foustoukos and
Seyfried, 2004; Fu et al., 2007; Ji et al., 2008). The latter
bypasses the serpentinization reaction and uses formic acid,
which decomposes into H2 and CO/CO2 at temperatures and
pressures similar to those typical of hydrothermal serpentini-
zation and could react to form abiotic organic compounds.
The reported experiments covered a large range of exper-
imental conditions, including the temperature (T), pressure
(P), experiment duration, chemical compositions of both
reactants and products, as well as types of reactors, origins
of mineral samples. We summarized the information into a
single large Excel spreadsheet of 133 columns and 733 rows.
The spreadsheet columns are divided into 3 main sections
(Figure1): article information (green header), experimental
conditions (blue header); and results (yellow header). The
section on article information includes details of all published
articles of this dataset: data ID, article title, year of publica-
tion, authors and DOI numbers, which help the readers of the
present contribution to trace back the original studies. The
733 rows describe 195 experiments that include sometimes
multiple samplings on the course of the experiments to eval-
uate the reaction kinetics.
Before moving into the details of each section of the
dataset, there is some important general information. In the
section dedicated to experimental conditions, it is import-
ant to keep in mind that most parameters are independent
of each other, but a few of them are dependent. For exam-
ple, the magnesium content of olivine ‘Mg#(Ol)’ displays a
value only for experiments that include olivine as a reactant.
Another example, the total of the reacting minerals sums at
100% and is expressed as wt%. In order to analyse the dataset,
a feature is assigned to each cell as explained in the header
of each column.
FIGURE 1 Screenshot of a representative version of the Excel spreadsheet for experimental parameters and results. The current dataset
has 134 columns (parameters/variables) and 733 rows (measurements). The dataset is divided into three parts—article information, experimental
conditions and results

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HUANG et Al.
Some programs cannot handle dataset with empty cells,
so we assigned ‘nan’ (not a number) to values that were either
not measured or not reported, and ‘0’ to measurements that
were below detection limits or reported as ‘not observed’ in
the original paper. We also paid attention to assign to each
parameter a dedicated format that is given in Tables1-9 of
the present contribution:
1. Numeric: data that are integers and float numbers. For
example, temperature data are mostly integers and NaCl
concentration data are float numbers.
2. Categorical: data that are not quantitative but categories,
such as the rock type and degree of alteration.
3. Binary: Data that are either 0 (no) or 1 (yes), such as the
reactor types.
4. Ternary: Data that are 0 (no), 1 (yes) or 2 (yes with 13C).
For example, in the Carbon_in_solid column, 2 means
carbon is 13C labelled.
2.2
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Experimental parameters
2.2.1
|
Reaction conditions and reactor
information
The reaction conditions are listed first in Table1: temperature
(T) ranges between 25 and 500°C, pressure (P) between 0.1
and 350MPa, and experimental durations are between 0 and
20,499hrs. In most experiments, intermediate sampling was
performed to study reaction kinetics and thus is reported in the
dataset as a parameter—0 means no intermediate sampling
performed whilst 1 means that the experiments were sampled
through time. With 733 measurements and 195 experiments,
each experiment on average takes 3.75 measurements.
Different types of reactors are used depending on the
experimental P-T conditions, experimental protocols and
sample volumes (Table2). The reactor materials are also in-
dicated since they are made of metals, whose catalytic role
has often been suggested. For each experiment, one of the
columns dedicated to the nature of the reactor has a value
of 1, others are 0. For instance, a reactor made of both Au
and Ti corresponds to ‘1’ in the column Reactor_Au/Ti, other
columns display a ‘0’ for that experiment.
2.2.2
|
Starting mineral, fluid and gas
compositions
The information on the composition of rocks, minerals,
solutes in the aqueous phase and gas is summarized in
Tables 3-5. Table3 contains the provenance of samples,
the type of rock, the degree of alteration (when indicated
by the authors), the composition of the rocks (expressed in
weight per cent of each mineral normalized to reach 100%),
the Mg# (olivine only), the grain size and other information
on the starting mineral phases that we considered useful.
The provenance of a sample is either its original geological
location or the name of the company where it was syn-
thesized. The estimated degree of alteration is based on
Parameters Min Max Average
Number of
‘nan’
Data
type
No_of_experiments 1 22 – 0 Numeric
Temperature_C 25 500 217.55 0 Numeric
Pressure_MPa 0 350 40.04 0 Numeric
Duration_hr 0 20,499 1647.58 0 Numeric
TABLE 1 Summary of experimental
conditions, pressure, temperature, duration
and number of experiments. Temperature is
in °Celsius, pressure in MPa and duration
in hours
Parameters
Number
of 0
Number
of 1 Average
Number
of ‘nan’
Data
type
Reactor_Flexible_autoclave 321 412 – 0 Binary
Reactor_Parr_type 728 5 – 0 Binary
Bottle_in_oven 549 184 – 0 Binary
Reactor_Au 281 452 – 0 Binary
Reactor_Au/Ti 371 362 – 0 Binary
Reactor_Ti 370 363 – 0 Binary
Reactor_Hastelloy 728 5 – 0 Binary
Reactor_Glass 495 238 – 0 Binary
Reactor_Platinum 718 15 – 0 Binary
Reactor_Teflon_Plastic 473 260 – 0 Binary
TABLE 2 Statistics and information on
the type of reactors used for experimental
serpentinization

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HUANG et Al.
mineral descriptions in the original articles—fresh (nearly
0% altered), altered (nearly 100% altered) and medium al-
tered. The missing values for the degree of alteration are
mainly from experiments started without a mineral phase,
which are dedicated to carbon speciation at high P and T.
Information of grain size (max and min) and surface area
(SSA, cm2/g of rock) that are very important for the kinetics
of the reaction is also reported in this section when avail-
able, otherwise they are labelled as ‘nan’. Simple statistics
analyses of these parameters are displayed in Tables3-5,
which helps readers to decide if this dataset contains useful
data for them.
The chemical composition of the starting aqueous solu-
tion is described in Table4. The solutes include many organic
and inorganic salts whose concentrations are given in mol/kg
(molal) as volumes change significantly under hydrothermal
conditions. When articles reported in their experimental sec-
tion that milli-Q water (18.2MΩ/cm) was used, the column
‘precised_water_clean’ displays a value of ‘1’, otherwise the
value is ‘0’. Values of the pH of the starting solution are also
given as ‘initial pH’ when available. The initial amount of
carbon among starting chemicals is one important aspect in
this study, which allows comparing between studies the pro-
duced reduced carbon compounds through FTT or Sabatier
reactions or any other reaction. We created a column ‘CO2_
initial’ that tells whether authors flushed their system or not.
If not, we assumed that fluids were at equilibrium with pres-
ent day atmospheric CO2, which leads to a CO2 concentration
of 0.01millimole per kg H2O.
When an experiment contained a headspace filled with gas,
we reported as much as we could the gas composition. It is
given in relative volume percentage of N2, CO2, H2, CO, CH4
Parameters Min Max Average
Number
of ‘nan’ Data type
Provenance_of_sample – – – 0 Categorical
Rock_type – – – 0 Categorical
Degree_of_alteration – – – 73 Categorical
Olivine_wt% 0 100.00 49.50 33 Numeric
Mg#(Ol) 0 92 70.28 231 Numeric
Clinopyroxene_wt% 0 40 1.52 5 Numeric
Orthopyroxene_wt% 0 100 4.13 5 Numeric
Pyroxene_wt% 0 100 5.38 0 Numeric
Spinel_wt% 0 5 0.25 0 Numeric
Magnetite_wt% 0 100 4.30 0 Numeric
Haematite_wt% 0 92.6 0.76 0 Numeric
Serpentine_wt% 0 100 3.37 0 Numeric
Brucite_wt% 0 6 0.30 0 Numeric
Talc_wt% 0 1 0.05 0 Numeric
Carbonate_wt% 0 0.25 0.01 0 Numeric
Amphibole_wt% 0 5 0.09 0 Numeric
Chlorite_wt% 0 1 0.02 0 Numeric
Phlogopite_wt% 0 1 0.05 0 Numeric
Chromite_wt% 0 100 2.00 0 Numeric
Clinochlore_wt% 0 1 0.04 0 Numeric
GLASS 0 75 1.39 0 Numeric
SiO2_wt% 0 100 0.82 0 Numeric
Fe_wt% 0 100 5.59 0 Numeric
NiFe_wt% 0 100 6.92 0 Numeric
FeO_wt% 0 100 1.34 0 Numeric
Fes_wt% 0 50 0.35 0 Numeric
NiO_wt% 0 50 0.34 0 Numeric
Grain_size_min 0 300 51.88 195 Numeric
Grain_ size_max 0 3,000 213.04 207 Numeric
SSA 0 71,000 7832.77 535 Numeric
TABLE 3 Summary of starting mineral
compositions and relevant parameters

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HUANG et Al.
and Ar in the headspace, as the description in the experiment
methods section in the articles seldom provided detailed infor-
mation on the gas composition (Table5). For each experiment,
the initial concentrations of these gases are therefore reported
as vol%, and the sum of these species in the headspace equals
arbitrarily 100% or 0 when information is missing.
2.2.3
|
Potential catalysts and
carbon sources
Previous studies (Fu et al., 2008; Andreani et al., 2013; Mayhew
et al., 2013) have shown that the serpentinization reaction and
the production of H2 and organic species (CH4, formate, ac-
etate, etc.) can be largely influenced by the presence of cati-
ons in solution or solid catalysts (accessory mineral surfaces).
In industrial H2 and CH4 production, metal-bearing catalysts
are critical. Platinum, rhodium, ruthenium, cobalt and other
metallic materials are well-known catalysts for methanization
of dry gas by FTT or Sabatier reaction (McKee, 1967; Melaet
et al., 2014; Stangeland et al., 2017). In natural environments, a
large number of metallic phases are present in ultramafic rocks
and minerals, and also in experimental materials as impurities.
Variabilities of the kinetics of serpentinization and H2 and CH4
formation, both in nature and experiments, could be due to the
effect of catalysts either in their mineral form or as solute (e.g.
Andreani et al., 2013; Mayhew et al., 2013; Etiope and Ionescu,
2015). Therefore, we created a list of minerals with potential
or expected catalytic effects and recorded their presence or ab-
sence in each experiment (Table6).
The carbon source(s) are also recorded in the dataset
in a ‘ternary’ data format (definition in section 2) for two
main goals here: (a) identify if the amount of reduced car-
bon products is favoured by certain carbon-bearing reac-
tants; (b) help readers to easily locate experiments labelled
with 13C and further analyse the influence of background
contaminations.
TABLE 4 Starting fluid chemical compositions and relevant parameters
Parameters Number of 0 Number of 1 Average Number of ‘nan’ Data type
Precised_water_clean 270 463 – 0 Binary
Parameters Min Max Average Number of ‘nan’ Data type
NaCl_molal 0 1.71 0.287 0 Numeric
CH4_initial_mmolal 0 24 0.098 0 Numeric
CO_initial_mmolal 0 80 1.746 0 Numeric
CO2_initial_mmolal 0 200 6.968 0 Numeric
HCO3_mmolal 0 2.2 0.158 0 Numeric
NaHCO3_molal 0 0.172 0.008 0 Numeric
HCOOH_molal 0 0.37 0.026 0 Numeric
KCl_molal 0 0.034 0.004 0 Numeric
CalCl2_molal 0 0.1 0.004 0 Numeric
MgCl2_molal 0 0.6 0.021 0 Numeric
NH4Cl_molal 0 0.019 0.001 0 Numeric
K2HPO4_molal 0 2.87E-04 1.55E-05 0 Numeric
KNO3_molal 0 5.01E-05 2.46E-06 0 Numeric
Ca(OH)2_molal 0 1.00E-04 4.92E-06 0 Numeric
CaSO4_H2O_molal 0 2.00E-04 9.82E-06 0 Numeric
Mg(SO4)2_7H2O_
molal
0 5.00E-05 2.48E-06 0 Numeric
C2H2O4_molal 0 2.25E-04 2.64E-06 0 Numeric
NaOH_molal 0 1.00 0.03 0 Numeric
Initial_pH 2 13.50 6.50 319 Numeric
TABLE 5 Starting gas compositions
Parameters Min Max Average
Number
of ‘nan’
Data
type
Gas_N2% 0 100 29.90 0 Numeric
Gas_CO2% 0 100 4.07 0 Numeric
Gas_H2% 0 100 0.14 0 Numeric
Gas_CO% 0 100 2.18 0 Numeric
Gas_CH4% 0 100 0.41 0 Numeric
Gas_Ar% 0 100 0.68 0 Numeric

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HUANG et Al.
TABLE 6 Potential catalysts and carbon source
Parameters Number of 0 Number of 1 Number of 2 Average
Number of
‘nan’
Data
type
Catalyst_Spinel 571 162 – – 0 Binary
Catalyst_Magnetite 603 130 – – 0 Binary
Catalyst_Chromite 584 149 – – 0 Binary
Catalyst_Ni_bearing 628 105 – – 0 Binary
Catalyst_Fe_bearing 624 109 – – 0 Binary
Carbon_in_Solid 688 45 0 – 0 Ternary
Carbon_in_Liquid 172 429 132 – 0 Ternary
Carbon_in_Gas 584 121 28 – 0 Ternary
TABLE 7 Other information related to experimental conditions
Parameters Number of 0 Number of 1 Average Number of ‘nan’ Data type
isBlank 609 124 – 0 Binary
Add_Solids 140 593 – 0 Binary
Add_Liquids 0 733 – 0 Binary
Add_Gases 478 255 – 0 Binary
Intermediate_sampling 167 566 – 0 Binary
Parameters Min Max Average Number of ‘nan’ Data type
Total_volume_ml 0.31 250.00 81.82 412 Numeric
Mass_solids 0 120 10.70 42 Numeric
Mass_liquids 0 180 37.58 92 Numeric
Water_Rock 0 400 13.26 170 Numeric
TABLE 8 Mineral products of experimental results
Parameters Number of 0 Number of 1 Average Number of ‘nan’
Data
type
Chrysotile_product 330 74 – 328 Binary
Lizardite_product 444 28 – 261 Binary
Antigorite_product 471 0 – 262 Binary
Phyllosilicate_product 325 134 – 274 Binary
Talc_product 293 10 – 430 Binary
Brucite_product 354 44 – 335 Binary
Magnetite_product 219 96 – 418 Binary
Haematite_product 180 0 – 553 Binary
Chromite_product 249 15 – 469 Binary
Pentlandite_product 263 2 – 468 Binary
Heazlewoodite_product 225 4 – 504 Binary
Carbonate_product 145 67 – 521 Binary
Siderite_product 129 7 – 597 Binary
Iowaite_product 261 10 – 462 Binary
Ni_Fe_phase_product 170 62 – 501 Binary
Reduced_carbon_product 52 17 – 664 Binary
Unidentified_phase_product 132 17 – 584 Binary

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HUANG et Al.
2.2.4
|
Other information
All other information regarding the starting materials
is listed in Table 7. The ‘isBlank’ parameter indicates
whether an experiment is blank or control (1 for no min-
eral within a series of experiments), in order to distinguish
them from experiments and avoid any inaccurate interpre-
tation of the data. The ‘Add_solids’, ‘Add_liquids’ and
‘Add_gases’ are used to indicate the presence of a solid,
liquid or gas phase, respectively (0 means absent). The
‘mass_solids’, ‘mass_liquids’ and ‘Water_rock’ ratio are
also reported when available, as well as the total volume
of the reaction cells.
3
|
RESULTS
The results section of the dataset is divided into two sub-
sections—mineral and gas/fluid products. The columns that
describe mineral products are less populated, since most
contributions focused on the production of gas species
(H2, CH4, etc.) and only a few of them also described the
kinetics of serpentinization and analysed the final mineral
composition.
3.1
|
Mineral products
Analyses of mineral products are reported in Table 8. It in-
cludes all the minerals identified by the authors of the 30
peer-reviewed articles. Each mineral produced during experi-
ments is defined as a parameter, and reading through the col-
umns, one can see that the data available in the literature are
sparse. As a consequence, statistics on the minerals produced
during the reaction is poorly constrained. The presence or ab-
sence of secondary minerals is not always clearly established
in the articles and strongly depends on the details provided by
the authors and characterization technique used in those contri-
butions. In some cases, descriptions of the solid phase did not
mention the experiment number they were referring to. In addi-
tion, in most experimental settings dedicated to the understand-
ing of H2 and CH4 production during serpentinization, solids
are accessible only at the end of the experiments. The mineral
feature is assigned ‘nan’ if the information is not clearly stated.
Hence, this part of the dataset should be used with great care
and we encourage the reader to refer to the original article as
necessary.
3.2
|
H2 and hydrocarbon products in
final fluids
This subsection focuses on the experimental measurements of
H2, CH4 and OC during experimental serpentinization. We as-
signed an individual parameter to each compound. The details
on the analysis of the composition of final fluids are described
in Table9. It is important to take into account that the meas-
urement precision and detection limit of those compounds are
very different across studies and potentially evolved through
time as analytical tools and methods improve. Obviously, the
TABLE 9 H2 and other organic products in final fluids
Parameters Min Max Average
Number of
‘nan’
Data
type
H2_mM 0 2170.25 66.534 82 Numeric
CH4_mM 0 58.2 0.859 189 Numeric
C2H6_mM 0 0.71 0.058 513 Numeric
C2H4_mM 0 0.3 0.026 600 Numeric
C3H6_mM 0 0.45 0.034 602 Numeric
C3H8_mM 0 0.33 0.040 535 Numeric
C4_mM 0 0.3 0.055 647 Numeric
C5_mM 0 0.2 0.032 647 Numeric
C6_mM 0 0.13 0.017 648 Numeric
Formate_mM 0 257 27.344 590 Numeric
CH3OH_mM 0 9 1.179 664 Numeric
Acetate_mM 0 114 3.980 669 Numeric
Propionate_mM 0.0002 0.0136 0.006 722 Numeric
CO2_mM 0 2287.88 35.95 317 Numeric
Alk_meq_mM 0 10.40 1.13 699 Numeric
Final_pH 0 13.50 7.57 339 Numeric

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HUANG et Al.
most commonly measured species are H2 and CH4, given the
topic. Other organic species are measured only in a few studies
and have therefore many missing values (nan) in the dataset.
Though each organic compound is listed in its own column, all
species other than H2 and CH4 shall be combined in order to
perform some meaningful data analysis.
4
|
DISCUSSIONS AND
PERSPECTIVES
This dataset provides an up-to-date collection of experi-
mental results until early 2019 that can be used to address
the implications of serpentinization and related processes
for the production of H2, CH4 and higher hydrocarbons. It
is well known that P-T conditions largely control experi-
mental results, but they alone could not explain the large
variability of the measured concentrations of H2, CH4 and
higher hydrocarbons. The other parameters investigated
by the experimental community at large are so numerous
that their investigation cannot be done easily and requires a
computing approach that can deal with many parameters at
the same time. We hope that the database is progressively
enriched with upcoming experimental results. As an exam-
ple, we have used data science techniques to extract embed-
ded information and identify key experimental parameters,
which cannot be accessed by checking a limited number of
parameters.
In our recent paper (Barbier et al., 2020), we used net-
work analysis and machine-learning algorithms to analyse
a processed version of this dataset. We found that, as pre-
viously known, pressure and temperature are the two most
important parameters that govern the production of H2
and OC. However, we did not find evidences to support
the occurrence of R1 or R2 reactions. Moreover, by com-
paring the concentrations of final OC with initial carbon
input, we found that the OC products in several studies are
from unidentified sources and likely result from contami-
nation, in agreement with the scarce 13C-labelled studies
(e.g. McCollom et al., 2010; Grozeva et al., 2017). Also,
the measurements of initial and final pH values are often
not reported, despite the important role of pH on the ser-
pentinization kinetics (e.g. Huang et al., 2019; McCollom
et al., 2020). More information and the detailed analytical
methods can be found in Barbier et al. (2020). The dataset
can also be extended to other reactions under similar con-
ditions using different solid reactants, such as mine-tailing
products, to produce H2, CH4 and other carbon species (e.g.
Kularatne et al., 2018; Michiels et al., 2018; Brunet, 2019).
We hope that this dataset and the analysis by Barbier et al.
(2020) stimulate complementary experiments that could
fill the identified gaps; this would allow editing future
versions of this dataset in a few years and potentially help
people better understand the fate of carbon under highly
reducing conditions such as the one produced during
serpentinization.
ACKNOWLEDGEMENTS
This research is supported by the AP Sloan Foundation
through the Deep Carbon Observatory's Deep Energy com-
munity and Data Science team (G-2018-11204). S.B. also
thanks TOTAL EP R&D Project MAFOOT for financial
support. We are grateful to the authors of the 30 publica-
tions used for this analysis. We thank Cécile Bourquin and
Valentine Megevand for their contribution to completing this
dataset. The authors also want to thank the two anonymous
reviewers for their fruitful comments that considerably im-
proved the manuscript.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
OPEN PRACTICES
This article has earned an Open Data badge for making pub-
licly available the digitally-shareable data necessary to repro-
duce the reported results. The data is available at http://info.
deepc arbon.net/indiv idual/ n1819 Learn more about the Open
Practices badges from the Center for OpenScience: https://
osf.io/tvyxz/ wiki
ORCID
Fang Huang https://orcid.org/0000-0002-6017-442X
Samuel Barbier https://orcid.org/0000-0003-1960-1087
Renbiao Tao https://orcid.org/0000-0003-4797-5211
Jihua Hao https://orcid.org/0000-0003-3657-050X
Pablo Garcia del Real https://orcid.
org/0000-0003-2075-0944
Steve Peuble https://orcid.org/0000-0003-0860-7344
Andrew Merdith https://orcid.org/0000-0002-7564-8149
Jean-Philippe Perrillat https://orcid.
org/0000-0002-3073-6241
Kathy Fontaine https://orcid.org/0000-0001-6762-8351
Muriel Andreani https://orcid.org/0000-0001-8043-0905
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How to cite this article: Huang F, Barbier S, Tao R,
et al. Dataset for H2, CH4 and organic compounds
formation during experimental serpentinization.
Geosci. Data J. 2021;8:90–100. https://doi.
org/10.1002/gdj3.105