2480 |Energy Environ. Sci., 2020, 13, 2480--2500 This journal is ©The Royal Society of Chemistry 2020
Cite this: Energy Environ. Sci.,
2020, 13,2480
Establishing reactivity descriptors for platinum
group metal (PGM)-free Fe–N–C catalysts
for PEM fuel cells†
Mathias Primbs, ‡
a
Yanyan Sun,‡
a
Aaron Roy,
b
Daniel Malko,
c
Asad Mehmood,
c
Moulay-Tahar Sougrati,
b
Pierre-Yves Blanchard,
b
Gaetano Granozzi,
d
Tomasz Kosmala,
d
Giorgia Daniel,
d
Plamen Atanassov,
e
Jonathan Sharman,*
f
Christian Durante, *
d
Anthony Kucernak, *
c
Deborah Jones,*
b
Fre
´de
´ric Jaouen *
b
and Peter Strasser *
a
We report a comprehensive analysis of the catalytic oxygen reduction reaction (ORR) reactivity of four
of today’s most active benchmark platinum group metal-free (PGM-free) iron/nitrogen doped carbon
electrocatalysts (Fe–N–Cs). Our analysis reaches far beyond previous such attempts in linking kinetic
performance metrics, such as electrocatalytic mass-based and surface area-based catalytic activity with
previously elusive kinetic metrics such as the active metal site density (SD) and the catalytic turnover
frequency (TOF). Kinetic ORR activities, SD and TOF values were evaluated using in situ electrochemical
NO
2
reduction as well as an ex situ gaseous CO cryo chemisorption. Experimental ex situ and in situ Fe
surface site densities displayed remarkable quantitative congruence. Plots of SD versus TOF (‘‘reactivity
maps’’) are utilized as new analytical tools to deconvolute ORR reactivities and thus enabling rational
catalyst developments. A microporous catalyst showed large SD values paired with low TOF, while
mesoporous catalysts displayed the opposite. Trends in Fe surface site density were linked to molecular
nitrogen and Fe moieties (D1 and D2 from
57
Fe Mo
¨ssbauer spectroscopy), from which pore locations of
catalytically active D1 and D2 sites were established. This cross-laboratory analysis, its employed
experimental practices and analytical methodologies are expected to serve as a widely accepted
reference for future, knowledge-based research into improved PGM-free fuel cell cathode catalysts.
Broader context
Polymer electrolyte membrane fuel cells (PEMFC) have reached the commercial stage and ever wider deployment is imminent. To further reduce the loading
of platinum group metal (PGM) catalysts in PEMFC electrodes, PGM-free, iron and nitrogen-doped carbon oxygen reduction (ORR) electrocatalysts (Fe–N–C)
were developed over past decades. Recent advances in activity and stability of Fe–N–C are impressive, yet methods to evaluate the number of catalytic active
Fe sites at the surface and intrinsic turn over frequency remained elusive. This changed with the advent of CO cryo-sorption and in situ nitrite
stripping techniques that yielded these intrinsic reactivity descriptors. Never before, however, have these two complementary specific adsorption/stripping
techniques been compared and combined with other chemical and spectroscopic analytics for an in-depth analysis of catalytic reactivity of Fe–N–C ORR
electrocatalysts. The present study addresses this issue and presents a comprehensive analysis of the reactivity of the four state-of-the-art Fe–N–C PEMFC
electrocatalysts. The study provides a deeper understanding of the origin and difference in catalytic performance through the combination of a host of
different surface sensitive and bulk analysis methods. The methodologies and analyses of this benchmark catalyst study will benefit future developments in
Fe–N–C catalysis.
a
Department of Chemistry, Chemical Engineering Division, Technical University of Berlin, 10623 Berlin, Germany. E-mail: pstrasse[email protected]
b
ICGM, Univ., Montpellier, ENSCM, Montpellier, France. E-mail: Deborah.Jones@umontpellier.fr, frederic.jaouen@umontpellier.fr
c
Department of Chemistry, Imperial College London, South Kensington, SW7 2AZ, London, UK. E-mail: anthony@imperial.ac.uk
d
Department of Chemical Sciences, University of Padova, Via Marzolo 1, 35131 Padova, Italy. E-mail: christia[email protected]
e
Department of Chemical & Biomolecular Engineering and National Fuel Cell Research Center, University of California, Irvine, CA 92697, USA
f
Johnson Matthey Technology Center, Blount’s Court, Sonning Common, Reading RG4 9NH, UK. E-mail: jonathan.sharman@matthey.com
†Electronic supplementary information (ESI) available. See DOI: 10.1039/d0ee01013h
‡These authors contributed equally.
Received 31st March 2020,
Accepted 24th June 2020
DOI: 10.1039/d0ee01013h
rsc.li/ees
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1. Introduction
Currently, proton exchange membrane fuel cells (PEMFCs) are
on the verge of massive deployment, in the transport sector in
particular, but still require expensive and scarce platinum-
group-metal (PGM)-based electrocatalysts to promote the slug-
gish oxygen reduction reaction (ORR) occurring at the cathode
of PEMFCs.
1–8
This is the reason why much international effort
is now being devoted to a rational design and development
of lower-cost PGM-free ORR electrocatalysts. Large research
consortia, such as the ElectroCat network
9
funded by the US
Department of Energy and the EU projects CRESCENDO
10
and
PEGASUS
11
funded by the Fuel Cells and Hydrogen Joint
Undertaking (FCH-JU), are working to meet specific perfor-
mance targets. The latter are defined so that fuel cell stacks
with PGM-free ORR catalysts become cost- and performance-
competitive with PGM-based catalysts, even for the highly
demanding automotive application.
4–6,12–22
The most promi-
nent example of PGM-free ORR electrocatalysts for acidic
medium is the family of iron- (or cobalt-) and nitrogen-doped
high surface area carbon matrix, typically referred as ‘‘Fe–N–C’’
catalysts, with atomically-dispersed Fe cations coordinated with
nitrogen atoms as the recognized most active sites.
5,23–32
Unlike
PGM-based single atom catalysts, where the atoms exist in a
carbon matrix as a sole atoms
33,34
or dimeric compounds,
35
iron generally has to be coordinated with hetero atoms. Several
general approaches have been established in order to control
the carbon micro and/or meso-porosity in M–N–C catalysts, a
key for high performance: functionalisation of microporous
carbon blacks with metal and N precursors,
4
hard-templating
of C and N precursors with e.g. silica,
36
adding porogens before
pyrolysis,
37
using reactive gases such as ammonia or CO
2
during pyrolysis,
38
and last but not least by soft templating
with e.g. metal organic frameworks
39,40
or porous organic
polymers.
36,40–60
Despite the impressive achievements in the
catalytic performance of Fe–N–C catalysts, further improve-
ments in their ORR activity and, in particular, durability are
needed before their large-scale deployment in commercial
PEMFCs becomes a reality.
12,26,61–63
Over the past decades, studies to identify more active
Fe–N–C catalysts have largely relied on empirical approaches
involving the systematic variation of elemental precursors
and/or synthesis conditions to prepare Fe–N–C materials and
their correlation with the resulting kinetic current density ( J
kin
)
and other lump performance metrics of ORR catalysts.
7,36,64–66
While this approach has had some success in the early stages of
Fe–N–C materials development, it now seems to have reached
its limitation, with stalled progress in the power and durability
performance of Fe–N–C cathodes in PEMFCs in the last years,
despite intense international efforts. Novel and more rational
approaches are needed in order to deconvolute the overall
activity and durability of Fe–N–C catalysts into the contribu-
tions arising from different Fe-based active sites, in order to
identify the most active and/or most durable sites and to
develop synthetic strategies to selectively optimize the number
of such sites.
31,67
The first step towards this goal implies the
development of experimental methods that evaluate the
number of Fe-based catalytic sites that are located at the surface
ofthecatalyst(sitedensity,SD).TheSDvalueisthencombined
with the kinetic current density, J
kin
, and elemental electric
charge, e, in order to extract the average intrinsic turn over
frequency (TOF) of the Fe-based active sites in a given Fe–N–C
catalyst, according to
68
J
kin
[A g
1
] = TOF [electron site
1
s
1
]SD [site g
1
]
e[C electron
1
] (1)
TOF and SD are fundamental descriptors of catalytic reactivity
and can provide guidelines for the synthesis of more active
catalysts. Efforts to improve the overall activity of a catalyst
may now focus on synthetic strategies to increase, separately or
combined, the SD value or to enhance the intrinsic TOF value of
the active sites.
Theoretical–computational research has offered a much
clearer, albeit not fully resolved, picture of the chemical
structure of favorable, catalytically active Fe–N
x
single metal
sites.
16,69
Advanced experimental analytical techniques such as
57
Fe Mo
¨ssbauer spectroscopy and high resolution STEM-EELS
microscopy have now qualitatively proven the existence of such
sites in active Fe–N–C materials.
13–15,26,60,70–73
A serious hurdle
in the rational improvement of the catalytic activity of Fe–N–C
catalysts, however, has been the lack of suitable methods that
accurately enumerate the electrochemically accessible Fe–N
x
sites (SD). Even for model Fe–N–C materials comprising only
Fe–N
x
sites, the SD value cannot be accessed with the sole
knowledge of the total Fe content, due to the location of a
significant fraction of Fe–N
x
sites not only on the surface but
also in the bulk of the carbon matrix. This issue results from
the pyrolytic process employed to form such active sites.
A range of spectroscopic methods based on X-rays and g-rays
have been applied in order to probe and quantify bulk and/or
surface Fe-based sites, namely X-ray photoelectron spectro-
scopy (XPS), X-ray absorption spectroscopy (XAS) and
57
Fe
Mo
¨ssbauer spectroscopy.
7,13,15,31,63,70,71
However, there exist
inherent shortcomings for each of these analysis methods. XAS
and
57
Fe Mo
¨ssbauer spectroscopy are inherently bulk methods, so
they identify both electrochemically accessible and inaccessible
Fe-based sites. X-ray photoelectron spectroscopy (XPS) are element
specific but not surface sensitive for carbon-based materials with
high surface area, due to the escape path of several nm of
photoelectrons throughthecarbonmatrix.
74
Synchrotron-based
XPS with tuned energy of the X-rays has improved the surface
sensitivity for carbon-based materials, and been successfully
applied to study Fe–N–C materials.
75,76
While synchrotron-based
XPS can give information on surface elemental composition, it
however cannot yield absolute numbers of metal-based sites in the
overall sample. In addition, while XPS successfully distinguishes
the presence of different oxidation states of a metal, it is not
powerful at discriminating between different environments. For
example, iron in ferric oxide and Fe(III)N
x
sites cannot be distin-
guished with XPS, and the root for this is that the detected photo-
electrons come from the core.
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Adsorption/desorption techniques involving probe molecules
are inherently well suited to count sites on the surface, yet often
lack chemical specificity.
77
Probe molecules such as CO,
78
NO,
79
CN
(ref. 80) or SCN
have been explored as surface probes for
Fe–N–C materials under electrochemicalconditions, however
none was successfully applied for a quantitative evaluation
of surface sites.
81
For example, both CN
and tris(hydroxy-
methyl)aminomethane (Tris) have been successfully employed
in partial poisoning studies of Fe–N
x
surface sites of Fe–N–C
catalysts.
80,82
This implies that counting the number of Tris
molecules or cyanide ions irreversibly adsorbed on Fe–N–C (after
washing the surface with electrolyte free of such probe species)
would underestimate the total number of surface-located Fe-based
sites, due to too weak adsorption on some sites. Recently, new
complementary adsorption/desorption techniques were speci-
fically developed for Fe–N–C materials and validated, one
based on low-temperature CO adsorption
83
and the other on
ambient-temperature NO
2
/NO adsorption.
84
The ex situ, low-
temperature CO cryo pulse chemisorption/desorption techni-
que featured good specificity to Fe sites and resulted in
reproducible SD values for different single metal active sites,
in particular for Fe–N–C materials.
68,85,86
The technique relies
on rapid adsorption rates and strong binding at 80 1C
between CO molecules and atomically dispersed single Fe–N
x
sites embedded in a carbon framework. Possible pitfalls of this
technique include overestimation, because it is not possible to
show that ORR is blocked by CO and due to the possibility of
single sites to bind more than one CO molecule. Also, initial
poisoning of a fraction of the single Fe sites may alter the
subsequent CO uptake amount, leading to undersampling.
A careful pretreatment procedure is therefore necessary to
desorb oxygenates quantitatively from all surface Fe-based sites
site prior to CO uptake. A standardized thermal pretreatment
protocol of Fe–N–C now ensures reproducible CO uptake values
on oxygen-free Fe(II)N
x
sites.
85,86
Second, a complementary in situ electrochemical nitrite
adsorption/NO electrostripping technique was put forward by
Kucernak’s group.
77
The method relies on the very specific and
strong interaction of Fe–N
x
sites with nitrite anions resulting in
NO adsorption, followed by electrochemical reductive stripping
of NO into ammonia.
87
Thus, a quantification of Fe–N
x
sites is
achieved by means of the stripping charge of the five-electron
process. Issues related to this method include the fact that
it requires a moderately acidic pH of about 5, which is less
acidic than the conditions prevailing at a PEMFC cathode.
Furthermore, although the majority of ORR current is blocked
by NO adsorption (470%), some ORR current remains suggesting
thepresenceofmultipletypesofFe–N
x
sites. NO may poison only
a fraction of the exposed sites due to its very high chemical
specificity, which leads to undersampling. Together, the ex situ
CO cryo probe technique and the in situ NO probe technique offer
a powerful pair of complementary physico-chemical strategies to
quantify the number of Fe–N
x
sites on the surface of Fe–N–C
catalysts. Together, both methods may yield a balanced and
reliable range of quantitative values for (i) the SD and (ii) after
combination with ORR activity measurements, for the TOF.
This enables a rational, knowledge-driven improvement of the
reactivity of Fe–N–C catalysts. However, hitherto these two SD
probe techniques have never been combined to study and analyze
the catalytic ORR reactivity of a same set of PGM-free catalysts to
extract their SD and TOF values and to cross-compare the values
obtained with the two techniques. Likewise, no study has hitherto
attempted to draw useful correlations between the composition
and structural or morphological characteristics of Fe–N–C cata-
lysts and their fundamental reactivity parameters such as TOF
and SD. The objectives of this contribution are to compare the SD
and TOF values determined for several Fe–N–C catalysts with the
nitrite stripping and CO cryo chemisorption techniques, as well as
to establish novel structure–reactivity correlations, deconvoluting
the reactivity into SD and TOF values, moving beyond the lump
ORR activity descriptor used hitherto.
Here, we present the first comprehensive analysis of trends
in the two fundamental descriptors of the electrocatalytic
reactivity of today’s state-of-art Fe–N–C catalysts, namely SD
and TOF, as measured with the ex situ CO cryo probe technique
and the in situ NO probe techniques. We then establish novel
correlations between SD and/or TOF descriptors and several
descriptors of the structure, morphology and/or elemental
composition of Fe–N–C catalysts. What sets this study apart is
not only the fact that the catalytic ORR reactivity of four of the
most active Fe–N–C catalysts is deconvoluted into SD and TOF
contributions, but also that the presented data, trends and
conclusions are based on the combination of the independent
analyses of four different laboratories. Furthermore, outcomes
include both new and in part quite surprising correlations
between the SD data resulting from ex situ CO and in situ NO
techniques, as well as and more importantly previously unavail-
able fundamental insights into the origin of the catalytic ORR
reactivity of these four benchmark catalysts.
More specifically, starting from the rotating ring-disk elec-
trode (RRDE) based ORR mass activity (MA), we derive quanti-
tative values for (i) SD for each benchmark catalyst, on a mass-
basis and/or surface-area basis, and (ii) TOF values. In parallel,
the Fe–N
x
coordination environment and elemental composition
in the bulk of the sample were determined by
57
Fe Mo
¨ssbauer
spectroscopy and XPS, respectively. The pore structure and
specific surface area were evaluated with nitrogen sorption
isotherms. Previously inaccessible mass activity maps were
established from the knowledge of the SD and TOF values of
the catalysts, on the one hand, and between SD or TOF values
and the experimentally determined type and quantity of
Fe–N
x
sites, on the other hand. Our analyses offer rational
guidelines how to achieve further improvements in the PGM-
free ORR activity in order to reach future targeted performance
characteristics.
2. Experimental section
The present cross-laboratory study was carried out at the
University of Padua, Imperial College London, the Institut
Charles Gerhardt (CNRS – University of Montpellier – ENSCM),
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and at the Technical University Berlin. Some of the analyses were
duplicated at different laboratories using distinct equipment. The
experimental details are described below, by method and/or
laboratory.
2.1 Benchmark catalysts
The four benchmark Fe–N–C catalysts investigated here were
sourced from different laboratories and were used as received.
Their detailed synthesis have been published in the literature.
They are currently considered best-in-class Fe–N–C catalysts
for PEMFC applications. They include a ZIF-derived catalyst
from CNRS/University of Montpellier (henceforth referred to
as CNRS),
88,89
a polymerized di-amino naphthalene based
catalysts from Imperial College London (ICL),
77
two catalysts
synthesized via hard templating with fumed silica, one from
the University of New Mexico (UNM) and another one from
Pajarito Powder Inc. (PAJ). The latter can be obtained as a
commercial product under the name PMF-011904.
2.2 Physicochemical characterization
Nitrogen physisorption. At one laboratory, nitrogen physi-
sorption was performed in a Micromeritics ASAP 2020 instrument.
100 to 150 mg of the catalyst was inserted in a sample tube with
glass wool and filling rods on top. Before the measurement, the
samples were pre-treated under vacuum (300 1C, 20 h) to remove
any species adsorbed on the sample. After cooling to room
temperature, helium was backfilled into the sample tube. During
the measurements, the sample was cooled to 77 K (liquid nitrogen).
The Brunauer–Emmett–Teller (BET) equation was used to estimate
the total surface area. Non-local density functional theory (2D-
NLDFT) was used to model isotherms to calculate pore size
distributions of microporous carbon materials with pores from
0.35 to 25 nm. For the analysis, an assumption of 2D model of
finite slit pores having a diameter-to-width aspect ratio of 4–6–12
was made. At another laboratory, nitrogen physisorption was
conducted on a Micromeritics Tristar II 3020. The analysis tem-
perature was 77 K and the BET equation was also used to estimate
thetotalsurfacearea.Thebestregionforthelinearfitwas
determined by the Rouquerol method.
90
Samples were degassed
and dried overnight at 300 1C under flowing nitrogen prior to the
measurement. Gases used were nitrogen (BIP plus-X47S) for
drying and adsorption and He (BIP plus-X47S) for free-space
measurement. Pore volume was determined as per NLDFT as
implemented in the software Micromeritics ‘‘Microactive for
Tristar II’’. The model was based on a slit shaped pore.
X-ray photoelectron spectroscopy. The XPS measurements
were carried out in a custom-designed UHV system equipped
with an EA 125 Omicron electron analyzer ending with a five
channeltron detector, working at a base pressure of 10
10
mbar.
The photoemission spectra were collected at room temperature
using the Mg K
a
line (hn= 1253.6 eV) of a non-monochromatised
dual-anode DAR400 X-ray source. The survey spectra were
acquired using 0.5 eV energy step, 0.5 s collection time, and
50 eV pass energy. Additionally, single components (C 1s, O 1s,
N1s,Fe2p
3/2
) were acquired with the same parameters in order to
increase accuracy of the calculation of surface composition
(i.e. Fe 2p
3/2
line was acquired 60 times). High resolution spectra
were acquired using 0.1 eV energy steps, 0.5 s collection time,
and20eVpassenergyforthecurvesfitting.
57
Fe Mo
¨ssbauer spectroscopy.
57
Fe Mo
¨ssbauer spectra were
measured with a Rh matrix
57
Co source. The measurements
were performed keeping both the source and the absorber at
room temperature, unless otherwise mentioned. The spectro-
meter was operated with a triangular velocity waveform, and a
gas filled proportional counter was used for the detection of the
g-rays. Velocity calibration was performed with an a-Fe foil. The
spectra were fitted individually with appropriate combinations
of Lorentzian lines. In this way, spectral parameters such as the
isomer shift (IS) and the electric quadrupole splitting (QS), and
the relative resonance areas (A) of the different components were
determined. Isomer shift values are reported relative to a-Fe.
Elemental analysis (EA). Elemental analysis was carried out
using a Thermo Scientific Flash 2000 analyser.
Inductively coupled plasma-mass spectrometry (ICP-MS).
An Agilent Technologies 7700x ICP-MS was employed for
inductively coupled plasma mass spectroscopy analysis. The
samples (15 mg) for ICP analysis were treated with 2 mL of nitric
acid (69% w/w) and heated at 100 1Cfor1h.Themixtureswere
diluted up to 40 g with Milli-Q water and after filtration, 2 mL of
the solutions were analyzed. For ICP analysis, another protocol was
tested using a microwave system CEM EXPLORER SP.D PLUS at a
heating rate of 40 1Cmin
1
from room temperature to 220 1Cwith
a pressure of 400 psi and a power a 300 W. In the latter method the
samples were dispersed in 2 mL of nitric acid, 6 mL of hydrochloric
acid (37% w/w) and 3 mL of sulfuric acid (93–98% w/w).
2.3 Electrochemical measurements
The electrochemical measurements consisted of the determi-
nation of the catalytic ORR activity and selectivity using rotating
ring-disk electrode (RRDE) set-ups at two different geometric
catalyst loadings of 0.2 and 0.8 mg cm
2
on the disk electrode,
in order to study the influence of layer thickness on the catalyst
performance. All laboratories involved in this study performed
RRDE testing, and error bars originated from the variations of
data across the laboratories.
Ink formulations. The catalyst ink consisted of a slurry of
the catalyst, isopropanol and ultrapure water in a water to
isopropanol mass ratio of 1 : 1, and Nafion (5 wt%, Sigma-
Aldrich). The catalyst content was either 0.5 wt% (0.2 mg cm
2
loading) or 2.0 wt% (0.8 mg cm
2
loading) of the total ink with
a mass ratio of water to catalyst of 1 : 10 and 1 : 40 respectively.
The ionomer to catalyst ratio is 1 : 2. The suspension was ultra-
sonicated until a stable suspension was reached.
Electrochemical set-ups. The electrolyte was 0.5 M H
2
SO
4
(ANALR grade or EMSURE Merck Millipore, as available to all of
the project partners). All the measurements were performed in
a glass jacket cell at 25 1C with a reversible hydrogen electrode
(RHE) reference electrode, a graphite counter electrode, and a
glassy carbon disk with a platinum or gold ring as working
electrode. The ring-disk electrodes were polished and cleaned
in an ultra-sonication bath with isopropanol and ultrapure
water. The cleaned electrodes were dried in nitrogen and the
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ink was deposited on the disk surface and dried at room
temperature or in an oven at 50 1C.
Break-in procedures. The activation of the catalyst was
performed in N
2
-saturated electrolyte via cyclic voltammetry
(0.0–1.0 V
RHE
,10mVs
1
) with a minimum of five cycles until
the change in capacitance in the 0.95–1.0 V
RHE
region between
two successive scans was less than 2%.
ORR activity and selectivity measurements. Cyclic voltam-
metry was performed in an O
2
-saturated electrolyte (0.925–0.00
V
RHE
, 1–2 mV s
1
, rotation rate 1600 rpm, ring potential 1.5
V
RHE
) starting from open circuit potential (OCP) to the lower
potential of 0.0 V
RHE
and a back scan to 0.925 V
RHE
. The scan
rates are low enough to neglect non-faradaic currents.
Accelerated stress tests (AST). AST was performed with a
catalyst loading of 0.2 mg cm
2
in sequence with the oxygen
reduction reaction (ORR) activity measurement. The electrolyte
was saturated with nitrogen and cyclic voltammetry applied
(0.60–0.925 V
RHE
, 100 mV s
1
, 10 000 cycles).
Data analysis. For the determination of the kinetic current
density J
kin
the forward and backward scans of the cyclic
voltammetry of the disc current densities, J, were first averaged
to correct for minimum interfacial capacitance at 1–2 mV s
1
and/or memory effects due to the direction of the scan. Then,
the Koutecky´–Levich equation was used to calculate the kinetic
current density (J
kin
) from the averaged geometric current
density, J, at 0.80 and 0.85 V
RHE
, according to
1
J¼1
Jkin
þ1
Jlim
(2)
Jkin ¼JJlim
Jlim J(3)
where J
lim
is the diffusion-limited current density, measured at
0.20 V
RHE
. The following formula was used for quantifying the
H
2
O
2
production, with N being the collection efficiency of the
ring-disk-electrode:
H2O2%¼2IRing=N
IDisk þIRing=N100 (4)
2.4 Ex situ and in situ evaluation of Fe surface site density
(SD) and turnover frequency
CO cryo chemisorption measurements. CO pulse chemi-
sorption and temperature programmed desorption (TPD) were
performed in a Thermo Scientific TPD/R/O 110 instrument.
A weighed mass of 100 to 150 mg of catalyst was inserted
between two pieces of quartz wool at the bottom of the internal
quartz bulb. Before the measurement, the catalyst was pre-treated
to remove any species strongly adsorbed on the metal-based sites
on the surface, in particular O
2
. Pre-treatment of the catalyst
begins with cleaning of the lines with helium (20 cm
3
min
1
,
30 min) and a consecutive ramp heating from 30 to 600 1C
(10 1Cmin
1
, 15 min hold time at 600 1C)andfollowedby
cooling to room temperature. Pulse chemisorption at 80 1C
(dry ice and acetone) consisted of 10 min line flushing (helium,
20 cm
3
min
1
), followed by six consecutive CO pulses injected by
the automated sample loop (helium as a carrier gas,
20 cm
3
min
1
, loop volume was determined to be 0.341 mL) in
intervals of 25 min.
68,85
Prior to TPD analysis, three consecutive
CO pulses are performed to ensure the saturation of the active
centres with CO. Thereafter TPD (80 1Cto6001C, 10 1Cmin
1
,
hold time 10 min, He as carrier, 20 cm
3
min
1
) with a consecutive
cooling to 30 1C(201min
1
) were performed.
For the catalyst surface areas and masses employed in this
study, the CO cryo adsorption reached saturation after 3 pulses.
The difference in peak areas (DA), corresponding to the
adsorbed molar CO amount, can be calculated from the six
individual baseline-corrected integral pulse areas A
1,sample
to
A
6
,
sample
(formal physical unit of the integrated detector signal
is [mV s]) according to:
DA¼A4;sample þA5;sample þA6;sample
3X
3
k¼1
Ak;sample (5)
Using the injection of a known volume of CO gas, a calibration
constant c
f
E4.14 10
7
mmol per unit area was derived. The
calibration factor was henceforth used for the conversion
between integral peak areas and molar CO amounts. In particular,
the molar amount of adsorbed CO (N
CO,ad
), also referred to as the
molar CO uptake, is the product of c
f
and DA. The mass-based
molaramountofadsorbedCO,n
CO
, was then calculated by
dividing by the mass of the catalyst sample inserted in the quartz
tube of the chemisorption reactor, m
cat
, according to
N
CO,ad
[nmol] = c
f
DA10
6
(6)
nCO nmol mgcat1
¼NCO;ad
mcat
(7)
The mass-based site density with CO chemisorption (SD
mass
(CO))
was then calculated from n
CO
via Avogadro’s constant (N
A
)
according to
SD
mass
(CO) [sites g
cat1
]=n
CO
[nmol mg
cat1
]N
A
[site mol
1
]
10
6
(8)
BET surface area-based SD values, SD
BET
(CO), with units of
[site m
2
], were obtained by dividing SD
mass
(CO) by the mass-
specific surface area, A
BET
[m
2
g
cat1
].
The turnover frequency TOF(CO) was calculated from the
catalyst mass-based kinetic current, J
kin,mass
[A g
cat1
], and the
CO uptake-derived catalyst mass-based surface site density,
SD
mass
(CO),ortheadsorbedmolaruptakeofCO,n
CO
,accordingto
TOF electronsite1s1
¼Jkin;mass NA
SDmass F
¼Jkin;mass NA
NCO;ad mcat1NA106F
¼Jkin;mass
nCO F
(9)
J
kin,mass
was evaluated from the ratio between the mass-transport
corrected geometric current density, J
kin
[mA cm
2
]andthe
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geometric catalyst loading, L
geo
[mg
Cat
cm
2
]ateither0.80or
0.85 V
RHE
.
The same turnover frequency (TOF) resulted from the mass-
transport corrected, BET surface area-based kinetic current
density J
kin,BET
[mA m
cat2
] and the BET surface area-based
SD values, SD
BET
, according:
TOF electronsite1s1
¼Jkin;BET NA
SDBET F
¼Jkin;BET NAABET
NCO mcat1NA106F
¼Jkin;BET ABET
nCO F
(10)
Nitrite reduction stripping. Measurements were conducted
with a conventional RRDE (Pine Instruments, model
AFE6R1AU, with a mirror polished glassy carbon disk elec-
trode and rotator model AFMSRCE), where the catalyst is
deposited on the glassy carbon disk electrode. The catalyst
loadingwasfixedat0.2mgcm
2
and 0.5 M acetate buffer at
pH 5.2 was utilized as electrolyte. The detailed experimental
steps were performed according to our previously reported
steps including cleaning protocol, measurement protocol, and
poisoning protocol.
77,87
It is important to utilize a current
integrator (or analog linear scan generator) when performing
the stripping measurements as normal staircase voltammetry
will not correctly measure the charges associated with these
processes.
The number of stripped molecules was calculated via the
electrochemical nitrite reduction stripping charge on Fe(II)N
x
sites (Q
strip
), assuming that the adsorption and stripping
process follow these steps:
The above mechanism identifies five electrons with the
reduction of one adsorbed NO per site (n
strip
= 5). Then, the
areal site density, SD
BET
(NO
2
), that is the number of Fe-based
surface sites normalized to the catalyst surface area, was
calculated as following:
SDBET NO2
ðÞsite nm2
¼Qstrip NA
nstrip FABET mcat
(13)
where Q
strip
is the coulometric charge in units of Coulomb
associated with the NO stripping peak, n
strip
is the number of
electrons associated with the reduction of one nitrite ion, m
cat
is the mass of the catalyst, and A
BET
is the mass-specific surface
area. Likewise, mass-based Fe surface site density, SD
mass
(NO
2
),
that is, the number of active sites per catalyst mass, was
calculated as:
SDmass NO2
ðÞsite g1
¼Qstrip NA
nstrip Fmcat
(14)
Nitrite adsorption significantly decreases the ORR performance of
the catalyst, but does not entirely block ORR activity, leading to a
70–80% decrease in ORR activity over the relevant range of
potentials (0.8–0.9 V
RHE
). This suggests that there is a range of
sites responsible for the ORR activity, and that nitrite adsorption
poisons those sites responsible for the majority of ORR current.
Hence, in order to extract the turn over frequency at a given
potential e.g. 0.80 V
RHE
,weusethedifferenceinkineticmass
current (J
kin,mass
) at that potential between the unpoisoned and
poisoned state divided by the number of sites
TOF electron site1s1
¼
Junpoisoned
kin;mass Jpoisoned
kin;mass
NA
SDmass NO2
ðÞF(15)
TOF is determined at both 0.80 and 0.85 V
RHE
, utilizing the
poisoned and unpoisoned kinetic currents at those potentials.
3. Results and discussion
3.1 Physico chemical and electrochemical characterisations
Nitrogen sorption and particle size measurements. We note
that these results were produced from a round robin test and so
represent an average across laboratories. N
2
physisorption was
performed to determine the surface area and pore volume of
the four selected catalysts (Fig. 1a, b and Table 1). All four
catalysts showed high surface area in the range from 463 to
840 m
2
g
1
and isotherms with well-defined hysteresis indi-
cating the presence of mesopores (not shown here). The CNRS
catalyst exhibits the highest BET surface area, for the most part
due to micropores, followed by the UNM catalyst, which
showed large pore volumes in the mesoporous range. Obtained
from a similar hard templating technique, the PAJ catalyst
(11)
(12)
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displayed a slightly larger mesoporous volume but slightly lower
microporous volume than UNM, and ranked in the middle in
terms of BET area. The ICL catalyst, on the other hand, showed a
balanced microporous/mesoporous pore volume and displayed
the lowest BET area.
X-ray photoelectron spectroscopy. The elemental composi-
tion and chemical state of the catalysts were analyzed by XPS,
including the narrow scan regions at the N 1s and Fe 2p core
levels (Fig. 1c, d and Fig. S1, ESI†). The Fe 2p XPS data
displayed lower signal/noise ratio, because the signal intensity
of Fe photoelectrons was close to the detection limit (not shown
here). This is typical for Fe–N–C catalysts, due to the low site
density of atomically dispersed Fe–N
x
moieties. XPS Fe 2p core
level analysis at higher resolution did give an estimation of the
Fe amount located at or a few nm below the surface. This level
of surface sensitivity allows us distinguishing Fe–N
x
moieties at
or within few nm from the surface from Fe species encapsu-
lated by thick layers of carbon (410 nm). The latter case is
usual for metallic Fe or iron carbide particles in Fe–N–C
materials, since they catalyze graphitization and reprecipitation
of carbon around them during pyrolysis. Fe particles sur-
rounded by a carbon layer 410 nm (longer than the path
through which the corresponding photo-electrons may travel
in carbon) are invisible by XPS. In contrast to the Fe 2p region,
the N 1s region gave more insights on the qualitative and
quantitative nitrogen content, allowing deconvolution the
spectra into the contributions of functional groups into sp,
sp
2
and sp
3
hybridized nitrogen atoms and N atoms involved in
the Fe–N
x
motifs. It should be noted that the multi-peak fitting
of the N 1s core level region and the assignment of specific
binding energies to functional groups remains a controversial
topic of intense research and fitting variability across
laboratories.
13,91–94
In particular, the assignment and reliable
quantification of N atoms involved in Fe–N
x
moieties remains
difficult, as it requires the knowledge of the exact coordination
of the sites present in the sample. For example, the number of
nitrogen atoms coordinating the Fe centers and the number of
carbon atoms in the second coordination sphere can influence
the N 1s binding energy.
13,91
In addition, the average binding
energy of N atoms coordinating Fe cations in Fe–N
x
moieties
overlaps that for amine nitrogens.
13
Due to these difficulties,
the Fe–N
x
component is often not distinguished from the other
nitrogen groups. Considering close binding energies calculated
by DFT for slightly different Fe–N
x
structures,
91
we decided to
limit ourselves to a conservative fitting procedure with one
single component for Fe–N
x
, to avoid data over-interpretation.
Fig. 1 Physicochemical analyses of the four benchmark Fe–N–C catalysts: (a) BET specific area; (b) micro- and mesoporous volumes; (c) relative
content of nitrogen species (% relative to total N) as detected in high-resolution N 1s XPS spectra, with assignments of nitrogen species of: Imine
397.8 eV, Pyridinic 398.8 eV, Nx–Fe 399.9 eV, Pyrrolic 400.7 eV, Graphitic 401.7 eV, N–O 402.7 eV; (d) absolute content of each nitrogen species in the
catalysts by division of relative content from XP S with the wt% content of nitrogen as determined by elemental analysis.
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Fig. S1b (ESI†) shows the high-resolution N 1s XPS spectra for
the four benchmark catalysts that were fitted with a total of 6
components with fixed positions (see in Fig. 1c and d), assigning
one binding energy only to the coordinative Fe–N
x
structure. The
lowest binding energy (BE) peak at 397.8 eV was assigned to imine
or cyanide groups while the peak at 398.8 eV was attributed to
pyridinic nitrogen and nitrogen-coordinated metal atoms in coor-
dinative states such as Fe–N
2
and Fe–N
3
. The peak at 399.9 eV in
the metal-free samples was assigned to amine groups, whereas in
the case of Fe-containing samples, it is considered to arise from
both nitrogen of the mesomeric Fe–N
4
configuration and amines.
The peaks at 400.7 eV, 401.7 eV and 402.7 eV correspond to pyrrolic,
graphitic and N–O nitrogen, respectively. The detailed quantitative
analysis is summarized in Fig. 1c, d and Table 1.
Mo
¨ssbauer spectroscopy.
57
Fe Mo
¨ssbauer spectroscopy was
carried out in order to obtain qualitative and quantitative
information on the different Fe species present in the bulk of
the benchmark catalysts. As displayed in Fig. 2, each catalyst
has a distinct Mo
¨ssbauer fingerprint. The ICL sample showed
exclusively the presence of the well-documented D1 and D2
quadrupole doublets,
7,31
indicating the main or sole presence
of atomically dispersed Fe–N
x
sites. From the comparison
between calculated and experimental values of quadrupole split-
ting (QS), the doublets D1 and D2 have recently been assigned by
us to, mainly, high-spin Fe(III)N
4
(withOHorO
2
adsorbed on iron)
and low- or medium-spin Fe(II)N
4
sites, respectively.
69
It is impor-
tant however to note that the Mo
¨ssbauer signature of high-spin
Fe(III)N
4
sites and nanosized ferric oxides is similar, the latter
leading to a sextet spectral component only at very low tempera-
ture (o60 K) and/or in the presence of an external magnetic
field.
14
The minor presence of nanosized ferric oxides can there-
fore not be entirely excluded from room temperature Mo
¨ssbauer
Table 1 Overview of physicochemical and electrocatalytic properties of the four benchmarking PGM-free Fe–N–C electrocatalysts for the oxygen
reduction reaction (ORR)
Method Unit
Catalyst
CNRS ICL PAJ UNM
N
2
physisorption Surface area m
2
g
1
840 26 46313 593 28 763 13
Micropore volume cm
3
g
1
0.269 0.137 0.103 0.181
Mesopore volume cm
3
g
1
0.203 0.317 0.92 0.88
57
Fe Mo
¨ssbauer Absorption area D1 % 42 38 11 40
D2 % 27 62 38 49
a-Fe % 18 0 15 0
g-Fe % 10 0 36 11
Fe
3
C%3000
Isomer shift D1 mm s
1
0.34 0.36 0.37 0.36
D2 mm s
1
0.45 0.55 0.40 0.41
a-Fe mm s
1
0.00 — — —
g-Fe mm s
1
0.08 — 0.12 0.08
Fe
3
Cmms
1
0.185 — — —
Composition ICP-MS Fe wt% 2.50 1.0 0.6 0.8
Elemental analysis C wt% 76.39 76.57 84.45 84.49
H wt% 1.08 1.15 0.81 0.82
N wt% 3.04 4.59 2.71 4.13
S wt% 0.23 1.39 — —
XPS Surface composition C 1s at% 91.51 86.78 95.43 91.46
O 1s at% 5.98 9.99 2.01 4.91
N 1s at% 2.15 3.06 2.3 3.37
Fe 2p
3/2
at% 0.36 0.16 0.25 0.26
Fraction of N species Imine (397.8 eV) % 18.6 26.6 14.4 15.3
Pyridinic (398.8 eV) % 21.6 12.8 11.6 15.4
N
x
–Fe (399.9 eV) % 15.8 16.7 7.1 14.8
Pyrrolic (400.7 eV) % 25.9 31 39.4 29.1
Graphitic (401.7 eV) % 16.2 12.9 22.1 17.6
N–O (402.7 eV) % 1.9 — 5.4 7.8
Electrochemistry
via RRDE
Intital activity 0.2 mg cm
2
J
lim
(0.2 V
RHE
)mAcm
2
3.5 0.3 4.77 0.07 4.3 0.6 3.9 0.7
J
kin
(0.80 V
RHE
)mAcm
2
0.40 0.09 0.24 0.06 0.465 0.005 0.48 0.43
J
kin
(0.85 V
RHE
)mAcm
2
0.12 0.06 0.05 0.02 0.100 0.001 0.10 0.09
H
2
O
2
(0.2 V
RHE
)% 52866475
H
2
O
2
(0.7 V
RHE
)% 531497385
Activity after AST 0.2 mg cm
2
J
lim
(0.2 V
RHE
)mAcm
2
3.1 4.2 0.2 3.9 0.5 3.41 0.09
J
kin
(0.80 V
RHE
)mAcm
2
0.4 0.22 0.01 0.18 0.07 0.13 0.05
J
kin
(0.85 V
RHE
)mAcm
2
0.09 0.05 0.01 0.04 0.02 0.03 0.01
H
2
O
2
(0.2 V
RHE
)% 102867310
H
2
O
2
(0.7 V
RHE
)% 1432013 19 616
Note: the electrochemical data are cross-laboratory averaged values. Each catalyst was measured in at least two different laboratories with two to
three repetitions for each catalyst loading.
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spectroscopy measurements alone, but the TEM analysis shown
later supports the absence of Fe clusters in the ICL sample. The
UNM catalyst showed, in addition to D1 and D2, the minor
presence of a singlet with isomer shift near 0 mm s
1
, assigned
to non-magnetic g-Fe or to nanosized superparamagnetic a-Fe.
In addition to D1, D2 and the same singlet component, the CNRS
catalyst shows a small contributionofasextetcomponentthatis
unambiguously assigned to magnetic a-Fe. The PAJ catalyst dis-
plays a spectrum that differs considerably from the other spectra.
While it contains the same four spectral components (D1, D2, the
singlet and sextet assigned to g-Fe and a-Fe), the singlet compo-
nent is by far the majority species and, in addition, the relative
content of D1 is lower than that of D2, an unusual feature for
Fe–N–C catalysts. The Mo
¨ssbauer results and analysis are in
accordance with TEM characterization (Fig. S2 and S3, ESI†). No
dense particles related to metallic Fe are observed in the TEM
image of the ICL catalyst while large dark particles assigned
mainly to a-Fe are seen for the CNRS catalyst. Surprisingly, the
PAJ catalyst shows rather small dark particles, that we assign to
g-Fe nanoparticles from the Mo
¨ssbauer spectroscopy analysis.
Despite different overall shapes of the spectra, their fitting
with unconstrained parameters (isomer shift, quadrupole split-
ting, hyperfine field and linewidth) resulted in spectral compo-
nents with relatively common parameters among these four
catalysts. As can be seen in Table 1 and Table S1 (ESI†), the
isomer shift (IS) and quadrupole splitting (QS) of the doublet
D1 ranges only from 0.34–0.37 mm s
1
and 0.75–1.10 mm s
1
for the four catalysts, respectively. While some small differences
Fig. 2 Comparison of the room temperature
57
Fe Mo
¨ssbauer spectra of the four benchmarking catalysts: (a) CNRS, (b) ICL, (c) PAJ, and (d) UNM.
(e) Relative area for each spectral component relative to the total absorption area and (f) absolute wt% of each Fe species determined from the relative
area, the Lamb–Mo
¨ssbauer factor of each species and the total Fe bulk content as determined by ICP. In (a–d), the colour code identifies the individual
spectral components, while in (e and f), the colour code identifies the catalysts.
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in the exact Fe coordination of D1 probably exist in these
four catalysts, it nevertheless clearly makes sense to assign this
particular spectral component to a single generic type of Fe–N
x
moieties in the later discuss of the overall results. The doublet
D2 with the larger QS-value has also relatively narrow range
of IS and QS values across these four catalysts (Table 1 and
Table S1, ESI†). While the singlet component has an IS corres-
ponding either to nano-sized a-Fe or to non-magnetic g-Fe, a
low temperature Mo
¨ssbauer measurement of the PAJ catalyst
revealed that this singlet did not split into a sextet at 30 K,
which excludes the assignment to a nanosized superpara-
magnetic g-Fe phase (nanometric a-Fe particles usually become
magnetically ordered at 30 K). For the sextets, the isomer shift
and hyperfine field values derived from the fittings correspond
perfectly to those for the reference compounds a-Fe and Fe
3
C,
so that those assignments are completely unambiguous.
The advantage of Mo
¨ssbauer spectroscopy compared to X-ray
diffraction for an identification of those phases lies in its
sensitivity which allows for unambiguous detection of even
very small amounts of such phases, which would be impossible
with XRD.
Electrochemical measurements. The ORR activity and selec-
tivity of the four benchmark catalysts was measured in all four
laboratories with conventional Rotating Ring Disk Electrode
(RRDE) setups. Focus was placed on the initial ORR activity and
H
2
O
2
selectivity. The RRDE experiments were performed at
0.2 and 0.8 mg cm
2
geometric catalyst loading. Fig. 3a shows
as an example one particular set of polarization curves and
H
2
O
2
selectivity curves of the four catalysts measured for a
loading of 0.8 mg cm
2
in the potential range from 0.0 to
0.9 V
RHE
. It can be observed that the onset potential of oxygen
reduction follows the order ICL oUNM oPAJ oCNRS
whereas the opposite trend is observed for the diffusion-
limited current density at 0.2 V
RHE
. It should be noted that
the polarization curves and peroxide selectivity shown were
measured in the same laboratory while data reported in Table 1
are averaged from measurements at several laboratories and
for several layers of each catalyst. The benchmark catalysts
exhibited generally low H
2
O
2
production, except perhaps for
the UNM catalyst with 10–11% below 0.5 V
RHE
. After Koutecky´–
Levich analysis of each curve (see Methods), the initial mass-
based ORR activity of each catalyst was obtained, averaged
across all four-laboratory data. Table 1 reports the mean ORR
mass activity of each catalyst, at a potential of 0.80 or 0.85 V
RHE
and for catalyst loadings of either 0.2 or 0.8 mg cm
2
. Initial
mass-based activities are compared in Fig. 3b and Fig. S4
(ESI†). Due to the error margin, a comparison of the present
catalysts, with similar activities, is not easily achievable.
As observed in Fig. 3b, the PAJ catalyst exhibited the highest
mass activity at the catalyst loading of 0.8 mg cm
2
whereas the
ICL catalyst appears as the least active in such conditions.
The CNRS and UNM catalysts showed comparable values.
At 0.2 mg cm
2
, the mass activity differences are within the
experimental error and are hence harder to compare (Fig. S4a
and c, ESI†). An accelerated stress test (AST) was also performed
to evaluate the stability of the catalysts at 0.2 mg cm
2
in load-
cycling conditions (Fig. S5, ESI†and Table 1). The CNRS and ICL
catalysts exhibited better stability than the PAJ and UNM catalysts.
Fig. 3 (a) Disk geometric current density measured with linear scan voltammetry (LSV) in RRDE setup and % peroxide derived from RRDE data.
(b) Averaged mass-based activity at 0.8 V
RHE
. The measurements were performed in O
2
-saturated 0.5 M H
2
SO
4
(pH 0.3) at a scan rate of 5 mV s
1
with a
catalyst loading of 0.8 mg cm
2
and the rotating speed was set to 1600 rpm at 25 1C. The Pt ring was held at +1.5 V
RHE
.
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The high stability of the ICL catalyst (comprising only Fe–N
x
sites)
to such a load-cycling AST in N
2
-saturated acid electrolyte is in
agreement with the stability reported in similar conditions for two
Fe–N–C catalysts derived from ZIF-8 and comprising also only
atomically-dispersed Fe–N
x
sites.
95
Similarly, the poor stability of
the PAJ catalyst to such a load-cycling AST in N
2
-saturated acid
electrolyte is in line with the poor stability observed in similar
conditions for one Fe–N–C catalyst derived from ZIF-8 but
comprising only iron-carbide particles.
95
The ORR selectivity of the catalysts was then studied at a
loading of 0.2 and 0.8 mg cm
2
(Fig. S6, ESI†). The % H
2
O
2
during ORR is generally low on the four benchmark catalysts,
ranging from 2 to 8%, except for the ICL sample at low loading
and at high potential, reaching ca. 14% (Fig. S6c, ESI†). The
general trend of increased peroxide formation with decreased
catalyst loading is observed, in accordance with previous
reports on both PGM-free and PGM-based catalysts.
96–99
Low
catalyst loadings imply thin layers, which increases the prob-
ability of the formed peroxide molecule to escape the active
layer before it can re-adsorb on another active site. Thick layers,
in contrast, increase the probability of peroxide re-adsorption
on a same or a different active site during its diffusion from the
inner part of the active layer towards the bulk electrolyte.
100
If re-adsorption occurs, then the initially formed peroxide
molecule can be further reduced to water, or can decompose
into O
2
and water. In contrast to the impact of catalyst loading
on the selectivity, no trend is observed in the selectivity as
a function of the electrochemical potential, with similar %
peroxide at 0.2 and 0.7 V
RHE
(Fig. S6a, b and c, d, ESI,†
respectively), except for the ICL catalyst. The error bar on ICL
sample regarding selectivity is however large.
3.2 Comparison between Fe surface site densities (SD) derived
from ex situ CO cryo-adsorption and in situ reductive nitrite
stripping
3.2.1 Evaluation of SD values and their normalization by
the catalyst mass or BET area. Recent reports have shown that
SD values of Fe–N–C catalysts can be evaluated using either an
ex situ CO cryo chemisorption or an in situ electrochemical
nitrite (NO
2
) adsorption/reductive stripping technique.
68,77,85
The two methods operate in vastly different physical and
chemical environments. The CO technique is a non-electro-
chemical environment and employs low temperature gas
adsorption/thermal stripping of molecular CO on a solid, with
the powders pre-annealed at 600 1C in argon. The NO
2
technique is a ‘‘partial knock out technique’’ that blocks a
fraction of the active surface Fe sites by NO adsorption, resulting
immediately in lower ORR current densities. Subsequent reduc-
tive stripping and quantification of the number of the coordinated
NO molecules in the same electrochemical environment
enables the evaluation of a large fraction of the total accessible
number of Fe sites under electrochemical conditions. SD values
were evaluated using both techniques and reported after
normalization by either the catalyst mass, referred to as SD
mass
,
or by the BET surface area, referred to as SD
BET
(see Experi-
mental methods).
More specifically, the ex situ CO cryo chemisorption method
evaluated the SD value under the assumption that one
adsorbed CO molecule corresponds to one Fe(II)N
x
moiety at
the surface of the pre-annealed, oxygen-free catalyst. Experi-
mentally, the CO adsorption was found to be complete after
three consecutive CO pulses at the chosen molar CO amounts
per pulse. Consequently, the last three out of the total six CO
pulses could be used as zero-uptake reference peaks for the CO
uptake calculations (Fig. S7, ESI†). The experimentally derived
CO uptakes on the four catalysts and the associated SD values
are summarized in Table S2 (ESI†), while the temperature-
programmed CO desorption profiles and peak assignments
and interpretations are shown in Fig. S8 (ESI†). The in situ
reductive NO
2
adsorption in the form of adsorbed NO probe
molecules and their subsequent reductive stripping to ammonia
was performed at pH 5.2 using RDE measurements. Voltammetric
scans were recorded before and after reductive NO poisoning
from NO
2
as well as after reductive removal of NO to ammo-
nia, resulting in the full recovery of the NO-poisoned surface
Fe sites (Fig. S9–S12, ESI†). Reductive NO
2
/NO poisoning
resulted in a significantly decreased catalytic ORR current
density, while the catalytic ORR current density was almost
completely recovered after reductive stripping of NO to ammonia
(compare dashed blue and solid black curves in Fig. S9c–S12c,
ESI†). Assuming that one NO molecule poisons one Fe surface
site, the differential stripping current with and without NO
poisoning yields the in situ SD values, which are summarized in
Table S2 (ESI†).
Fig. 4a displays the first-ever direct comparison between
experimental SD
mass
values obtained on one hand from the
in situ nitrite reduction and on the other hand from the ex situ
CO cryo chemisorption technique. It is noteworthy that despite
the vastly different analysis methods, the experimental SD
mass
values ranged reproducibly on the same order of magnitude of
10
19
sites g
catalyst1
. At the same time, the detailed SD
mass
(CO)
values derived from gaseous CO cryo chemisorption were
systematically (2to 8) greater than the SD
mass
(NO
2
) values.
This is largely attributed to Fe surface sites located inside gas
accessible but electrochemically inaccessible pores that are
likely to be less accessible for reductive NO
2
adsorption and
reductive NO stripping. Hence, these sites are not probed by the
in situ reductive NO
2
technique. In comparison, gaseous
CO
(g)
has facile accessibility to Fe surface sites even inside
the micropore structure of the dry solid catalysts. This hypoth-
esis will be supported by numerous correlations below. The
experimental NO
2
and CO-based SD
mass
values can be
regarded as lower and upper bounds of the surface Fe site
density of each Fe–N–C catalyst, respectively. As such, the NO
2
and CO-based site density values, for the first time, yield ranges
of averaged reactivity descriptors, such as the intrinsic turn
over frequencies of surface Fe sites of the benchmark Fe–N–C
ORR catalysts.
Fig. 4a reveals that the CNRS catalyst showed the largest
SD
mass
value while the PAJ catalyst showed the smallest value,
both in the ex situ and in situ SD metric. The ICL and UNM
catalysts show intermediate SD
mass
values, with interchanged
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ranking according to which method is considered for the
SD
mass
measurement. The underlying reason for such differ-
ences between the two methods is probably related to the
difference between gas-phase accessibility (ex situ method)
and electrochemical accessibility (in situ method). It seems
reasonable to assume that the electrochemical surface will
closely match the gas-phase surface for Fe–N–C materials with
low BET surface area (low proportion of micropores) while the
gap between the two concepts of accessibility will increase for
materials of increasing BET areas (typically, with high micro-
pore area). To evaluate this, the BET-normalized real Fe surface
site density (SD
BET
(CO) and SD
BET
(NO
2
)) were calculated and
correlated to each other in Fig. 4b. Now, the ICL catalyst with its
relatively low surface area of B400 m
2
g
1
displays a large
SD
BET
(NO
2
) value, while the ICL, PAJ and UNM catalysts define
a linear trend between the SD
BET
(NO
2
) and SD
BET
(CO) values.
In other words, for these three catalysts, the nitrite probe
sampled an almost identical fraction of the total number of
Fe sites that are available to CO via the gas phase. The absolute
numbers of SD however significantly differ between the two
methods (discussed later). The CNRS catalyst falls out of the
trend defined by the three other catalysts in Fig. 4b. This can be
explained if the electrochemical utilization of the Fe-based sites
is significantly lower with the CNRS catalyst than with the three
others. This in turn is well supported by the significantly higher
ratio of micropore to mesopore volume of CNRS vs. other
samples (Fig. 1b). The horizontal offset between SD
BET
(CO) of
CNRS and the blue regression line is directly attributed to the
effect of CO-accessibility of all Fe surface sites in micropores
and NO
2
inaccessibility of some of the Fe surface sites that are
located deep inside micropores.
3.2.2 Correlating CO- and NO
2
-derived turnover frequen-
cies (TOF). To compare intrinsic ORR reactivities between the
catalysts, average catalytic turnover frequencies (TOFs) were
calculated and correlated using experimental uncorrected
SD
mass
(CO) values, SD
mass
(NO
2
) values and mass-based kinetic
current densities at different applied electrode potentials
(0.80 and 0.85 V
RHE
) (Fig. 5). This TOF values are here to be
seen as the average across all electrochemically active sites, and
do not depend on whether they are evaluated using mass-based
or BET-based SD and ORR activity values. Note that the
CO-based TOF calculations used the ORR current densities
from Fig. S4 (ESI†) and Table 1, while the NO
2
-based TOF
evaluations relied on the differential ORR current densities of
the poisoned and the non-poisoned state of the catalyst at
pH 5.2 (Fig. S9–S12, ESI†). Fig. 5 indicates a close positive
correlation between the evaluated TOFs of both methods at
both electrode potentials, with TOFs increasing in the order
CNRS oICL oUNM oPAJ.
TOF values derived from NO
2
stripping are 2to 10
higher than the CO-derived TOFs, which follows from the ratio
between SD
mass
(NO
2
) and SD
mass
(CO). The lower TOFs derived
from SD
mass
(CO) appear to originate in the overestimation of
the catalytically active Fe surface site density. A more realistic
average TOF values of each catalyst may lie in between the two
TOF values in Fig. 5.
Looking at the TOFs derived from each probe technique
separately, we note that the large TOFs of the PAJ catalysts
may be attributed to an improved oxygen accessibility of the
catalytically active Fe surface site under operating conditions.
Another reason for the high TOFs may be the favorable mole-
cular structure of some or all of the catalytically active Fe
surface sites of PAJ, which leads to lower kinetic reaction
barriers and hence faster catalytic turn over cycles. On the
other hand, the CNRS catalyst exhibited the lowest TOFs in RDE
testing due to its high proportion of micropores, expected to be
hardly accessible due to non-wetting.
3.2.3 Fe surface site density (SD)–turnover frequency (TOF)
reactivity maps. Eqn (1) defines the experimental ORR mass
activity of a catalyst as the product of the catalytic active site
density, SD, and its intrinsic TOF. With values for SD and TOF
at hand, SD–TOF reactivity maps can be generated to analyze
the catalytic ORR reactivity (Fig. 6 and 7 display data at 0.80
V
RHE
, while Fig. S13 and S14 at 0.85 V
RHE
, ESI†). In SD–TOF
Fig. 4 Comparison of ex situ and in situ Fe surface site density (SD) values of the four Fe–N–C catalysts obtained using CO-chemisorption and nitrite
electrochemical reductive stripping. (a) SD
mass
values measured in situ vs. SD
mass
values measured ex situ;(b)SD
BET
values measured in situ vs. SD
BET
values measured ex situ. The y=xlines are indicated as dashed lines. Data were derived from measurements in Fig. S7–S12 (ESI†) and Table 1.
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reactivity maps each catalyst entry falls on its hyperbolic iso-
mass activity or iso-BET surface area activity curve, depending
whether SD
mass
or SD
BET
values are used. We propose SD–TOF
reactivity maps as useful new comparative analysis tool
to analyze and understand the origin of ORR reactivity of
PGM-free electrocatalysts. Moreover, SD–TOF reactivity maps
allow a knowledge-based correlation between catalyst synthesis
parameters, such as temperature, time, precursor type, etc. and
the two most important intrinsic reactivity descriptors.
Variations in the mass or surface area-normalized kinetic
reactivity can now be understood in terms of variations in the
SD, or TOF, or both. Entire synthesis–reactivity pathways inside
SD–TOF maps may trace the influence of individual synthetic
parameter variations, and thus allow for a rational development
of improved catalysts toward pre-defined target performances,
as illustrated in Fig. 6.
Fig. 6a and b show the catalyst mass-based SD
mass
–TOF
reactivity maps derived from CO and NO
2
, respectively. Both
maps reveal a consistent trend in catalyst mass activity,
J
kin,mass
, at 0.80 V
RHE
in the order ICL oCNRS oUNM E
PAJ. Differences in J
kin,mass
are due to the difference in
measurement conditions, such as pH. Analysis of the SD–TOF
maps demonstrates that the PAJ and CNRS catalysts both
exhibited high and comparable J
kin,mass
, however, the origin
of their reactivity was quite different: While CNRS features
many Fe sites at the surface with low average TOF, that is low
intrinsic reactivity, PAJ offers fewer, yet intrinsically very active
surface sites. This may be explained by the presence of many Fe
surface sites in the micropores of CNRS, which failed to be
accessible, and hence effective under electrochemical conditions.
PAJ, on the other hand, appears to feature fewer Fe surface sites
largely in macropores, where they are accessible and able to
Fig. 6 Site density–ORR turnover frequency maps (SD–TOF ORR reactivity maps) obtained by plotting the Fe surface site density (SD) and the
corresponding TOF for each of the four catalysts with iso-mass activity hyperbolic curves at 0.80 V
RHE
: (a) SD–TOF reactivity map derived from
SD
mass
(CO) (pH 1, activity values from Table 1) and (b) SD–TOF reactivity map derived from and SD
mass
(NO
2
) (pH 5.2 Fig. S9–S12, ESI†). SD–TOF
reactivity maps allow for a rational deconvolution and analysis of ORR reactivity of PGM-free catalysts. They also aid in establishing fundamental
synthesis–reactivity relationships. Dashed arrows indicate examples of catalyst target performance superimposing the highest observed SD (CNRS) with
the highest observed TOF (PAJ).
Fig. 5 Correlations between the catalyst turnover frequencies (TOFs) derived from SD
mass
(CO) and SD
mass
(NO
2
) values at (a) 0.80 V
RHE
and
(b) 0.85 V
RHE
.
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contribute to the experimental reactivity. UNM and ICL catalysts
fall in between the two extreme cases, with their quantitative
J
kin,mass
–SD–TOF patterns varying between Fig. 6a and b due to the
varying test conditions. From SD–TOF maps, catalyst development
targets can be derived: Increasing the SD of the PAJ catalyst
or, alternatively, introducing more sites of the PAJ type into
CNRS, that is, accessible sites in macropores or sites that closely
resemble the PAJ molecular structure, should be a rational
strategy to arrive at the target points of 6.6 and 17 A g
1
in the
respective maps of Fig. 6. Another interesting point to note is that
catalystswithhighTOFvalues,suchasPAJ,fallintoregionsofthe
map where the iso-activity J
kin,mass
curves are located more
densely. Provided an absolute increase in SD
mass
, catalysts such
as PAJ would gain a much larger increase in J
kin,mass
than catalysts
located at a more centered position of the same iso-activity curve.
In other words, synthetic strategies to increase SD
mass
will have
more impact on catalyst located on the right of the map than on
catalysts located on the left.
A similar analysis was performed in the corresponding
SD
BET
–TOF maps (Fig. 7a for SD
BET
(CO)–TOF and Fig. 7b
SD
BET
(NO
2
)–TOF) that both revealed a general trend in areal
catalytic activity in the order CNRS oICL oUNM oPAJ. The
data points represented as squares in Fig. 7a indicate that
CNRS and PAJ remained at the extremes, in the sense that
CNRS exhibited, on average, the most Fe surface sites per
catalyst surface area, while fewer Fe site per catalyst surface
area of PAJ featured the highest average TOF and resulted in the
highest ORR reactivity. The relatively low BET surface area of
ICL reversed the site density trends of ICL and UNM in Fig. 7a.
The areal ORR activity of ICL now trails that of UNM only
slightly. In the SD
BET
(NO
2
)–TOF map of Fig. 7b, CNRS and ICL
now exhibit similar areal site densities, while ICL featured a
50% higher ORR activity, which gives testament to its effective
catalytic Fe sites at the surface. Fig. 7a also includes CO-based
areal site density data SD
BET,corr
(round symbols) that corrects
for Fe surface sites that are inaccessible at ambient conditions
and thus quantitatively matched the NO
2
-derived SD
BET
values
for non-microporous catalysts. While all trends were preserved,
the data points increased their spread along the TOF scale, which
now more closely match those of the NO
2
derived map in Fig. 7b.
3.2.4 Identifying the molecular and chemical state and
physical location of Fe surface sites. In order to learn more
about the molecular identity, chemical state and physical
location of Fe surface sites in the four Fe–N–C catalysts,
we analyzed a large number of correlations between various
molecular, compositional, morphological characteristics and
the Fe surface site densities (SD
mass
,SD
BET
) and their corres-
ponding TOF values (Fig. 8, 9 and Fig. S15–S20, ESI†). More
specifically, we analyzed relations between site densities and
pore structure (micropore, mesopore and total pore volume) in
Fig. 8, Fig. S15a, b, and S16 (ESI†), nitrogen species (pyridinic-N
and pyrrolic-N) in Fig. S15c, d, and S17 (ESI†), Fe bulk content
in Fig. 8, and TOF in Fig. S18 and S19, ESI.†Emphasis is placed
on correlations between Fe surface site densities and the
abundance of
57
Fe Mo
¨ssbauer spectroscopy-derived Fe–N
x
sites
(high spin D1 site and medium or low spin D2 site) in Fig. 9,
Fig. S16, and S19 (ESI†).
Fe surface site density and physico-chemical surface properties.
Fe surface site densities, SD
mass
, displayed close correlations
(r
2
= 80–95%) with micropore volume (Fig. 8a, Fig. S15a and b,
ESI†). The greater the micropore volume (PAJ to CNRS), the
higher was the SD
mass
value for both the CO and NO
2
probe
techniques. However, the difference in the SD
mass
value
between the CO and NO
2
probe techniques increased with
increasing micropore volume. In other words, the ratio of
inaccessible Fe sites inside the micropores increased with
the micropore volume (Fig. 8a). As expected, the number of
inaccessible pore sites was largest for the ZIF-derived highly
micro porous CNRS catalyst.
Generally, gaseous CO uptake-based SD
mass
(CO) values appear
to correlate closer with pore-related catalyst characteristics
Fig. 7 Areal site density, SD
BET
–ORR turnover frequency (TOF) reactivity maps with each of the four catalysts plotted on its hyperbolic iso-areal activity
curve at 0.80 V
RHE
: (a) SD
BET
(CO)–TOF reactivity map (square symbols) and SD
BET,corr
(CO)–TOF reactivity map (round symbols) derived from CO
cryo chemisorption (pH 1, activity values from Table 1) and (b) SD
BET
(NO
2
)–TOF reactivity map derived from reductive NO
2
stripping (pH 5.2
Fig. S9–S12, ESI†).
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(Fig. 8a and Fig. S15, ESI†), which is plausible given the
generally better accessibility of pores to gaseous CO molecules.
To support this conclusion further, we present the correlations
of BET-based areal Fe surface site densities, SD
BET
, with surface
nitrogen species (Fig. S17, ESI†): while their resulting r
2
values
are somewhat lower than those of the SD
mass
correlations,
CO-based SD
BET
values again correlate much better with
physico-chemical surface properties. For correlations between
SD values and bulk properties, in contrast, this finding does no
longer hold, as will be shown further below.
Plots of SD
BET
values against bulk Fe wt% content (Fig. 8b)
show that overall Fe content followed the trend in SD
BET
(CO)
for all four catalysts closely. The SD
BET
(NO
2
) data, however,
scale well only for PAJ, UNM, and ICL – the catalysts with
limited microporosity – while the significantly larger bulk
Fe content (B2.5) of CNRS appears offset from the other
catalysts. It can be concluded that all the additional Fe bulk
content of CNRS appears ineffective in raising the Fe surface
site density sampled by the NO
2
probe.
The correlation between pore structure and the weight
content of the
57
Fe D1 doublet (Fig. 8c) suggested that the
high-spin Fe D1 sites are preferentially formed and hence
located in micropores and less so in mesopores. That conclu-
sion is also supported by the combined correlation between
SD
mass
(CO), D1 wt% content and micropore volume illustrated
in the 3D plot in Fig. S16 (ESI†).
Finally, the relations between pyrrolic N and Fe–N
x
species
and the TOF values, derived from CO and NO
2
, is shown in
Fig. S18 (ESI†). Consistent with eqn (1), the observed relations
are strictly inverse to those found between the pyridinic- and
pyrrolic N species and the SD
BET
values (Fig. S17, ESI†): PAJ and
CNRS with the highest and lowest average TOF values showed
the fewest and largest number of Fe–N
x
sites near the surface,
fully in line with the trends with pyridinic nitrogen species.
UNM and ICL TOF values fit well into the N %–TOF trend lines
in Fig. S18 (ESI†), following concomitantly the trends in SD
BET
,
but not that of microporosity (Fig. 8a and c). Again, pyrrolic
nitrogen atoms appear most abundant in PAJ with the largest
TOF, but this does by no means imply that these Fe sites are
constituted by coordinating pyrrolic N atoms. It rather
indicates that the rather low pyridinic N content is still suffi-
cient to constitute the N centers that coordinate Fe centers.
Fe surface site density and molecular Fe bulk moieties. We now
turn to an analysis of the relation between the catalyst mass-
and BET-normalized Fe surface site densities, SD
mass
and
SD
BET
, and the mass-normalized bulk abundance of the two
main types of Fe–N
x
moieties that are distinguished by
57
Fe
Mo
¨ssbauer spectroscopy, referred to as ‘‘D1’’ and ‘‘D2’’ (Fig. 9).
D1 and D2 differ due to the oxidation and electronic spin
states of iron in Fe–N
x
moieties, which in turn can be
triggered by different local structures or different accessibility
to O
2
.
7,15,69
Both types of Fe sites have been repeatedly
suspected to act as catalytically active sites, or at least as
precursor sites, where oxygen adsorption and reduction occurs.
The twelve correlations split into pairs of two, in particular
those involving SD
mass
values(Fig.9a–c),SD
BET
values (Fig. 9d–f)
correlated with bulk ratios of D1 (a and d), D2 (b and e), and
D1 + D2 (c and f).
Looking at Fig. 9a, c, d and f, SD
mass
(NO
2
) follows D1 and
D1 + D2 much better than SD
mass
(CO), which is plausible
considering that D1 and D2 are porosity- and surface area-
independent, mass-normalized bulk metrics, while SD
mass
(CO)
values, unlike SD
mass
(NO
2
) values, take micro porous
morphology into account. Conversely, it is the surface area-
corrected SD
BET
(CO), unlike SD
BET
(NO
2
), that correlate very
well with the abundance of D1 and D1 + D2 Fe sites. We conclude
from the data that both SD probing methods appear sensitive for
D1 type Fe sites, and D1 sites appear to exist both in meso- and
micro-pores. Based on the trends in SD
mass
(NO
2
), the NO
2
probetechniquesamplesFesurface sites predominantly in
mesopores, and likely also at the entry of micropores, but not
deep inside micropores. This is supported by the data pattern in
SD
BET
(NO
2
) of Fig. 9d where the microporous CNRS catalyst is
offset at much larger abundance of D1 at essentially constant
values of the areal density SD
BET
(NO
2
). Some recent researches
Fig. 8 Correlations between the CO cryo adsorption-based Fe surface site density SD
mass
(CO) and NO
2
stripping-based Fe surface site density
SD
mass
(NO
2
) and (a) the micropore volume, (b) the bulk Fe content, (c) correlation between pore volume with the weight ratio of the molecular D1
doublet obtained from
57
Fe Mo
¨ssbauer spectroscopy.
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demonstratedthatthepresenceofFeorFe
3
C was beneficial for
boosting the catalytic activity of Fe–N
x
moieties through tuning
the charge density of central iron atom in Fe–N
x
moieties.
101
The
existenceofFeand/orFe
3
C might contribute to the high ORR
activity for the investigated catalysts. Only the ICL catalyst has a
sole presence of atomically dispersed Fe–N
x
sites from Mo
¨ssbauer
spectroscopy results.
Note that the two most active catalysts (UNM, PAJ) possess
the fewest D1 Fe sites in the bulk and, accordingly, display the
lowest Fe site density in three of four metrics, with SD
mass
(CO)
of ICL being the only exception, likely due to its low surface
area and low micro pore volume. This gives testament to the
high intrinsic reactivity of their type of sites.
All catalysts except CNRS exhibit significantly larger bulk
abundances of the molecular medium-spin D2 Fe site com-
pared to those of D1 (PAJ 4, UNM 1.5, ICL 2). ICL and
CNRS, the two less active catalysts, display comparable large
abundance of D2 (0.6–0.7 wt%). Only the areal density values of
SD
BET
(NO
2
), that is, the metric, the magnitude of which is
least sensitive to porosity, correlate well with the bulk abun-
dance of D2 (Fig. 9e). All others trace D2 content poorly. While
both SD probing methods appear clearly sensitive to D2 Fe
Fig. 9 Correlations between Fe surface site densities, SD
mass
and SD
BET
, and the bulk weight abundance of the two principle molecular Fe sites, D1 and
D2, derived from
57
Fe Mo
¨ssbauer spectroscopy doublets. (a–c) SD
mass
(CO), SD
mass
(NO
2
), and (d–f) SD
BET
(CO) and SD
BET
(NO
2
) plotted against the
weight ratio of the molecular D1 site (a and d), the weight ratio of the molecular D2 site (b and e), the sum D1 + D2 (c and f).
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surface sites, the data also suggest that D2 Fe sites may be
predominantly present in mesopores, and less so in micropores.
Correlations with the combined abundances (D1 + D2) generally
deteriorated compared to those with D1 alone, underlining the
importantroleofD1typeFesitesintheORRprocess.
For completeness, we also analyzed the correlations of the
CO- and NO
2
-derived TOF values at 0.80 V
RHE
(Fig. 5) with D1,
D2, and D1 + D2 as shown in Fig. S19 (ESI†). Average TOF values
dropped with increasing weight content of bulk Fe sites,
suggesting a decreasing mean efficacy of the Fe sites with
increasing Fe site abundance. CNRS catalysts are offset at very
low TOF values. In agreement with our conclusions above, this
suggests that Fe sites in micropores (CNRS) appear highly
ineffective catalytic sites, which, in turn, highlights the bene-
ficial effect of meso- and possibly macro-pores as the physical
location of effective Fe surface sites in PGM free Fe–N–C
catalysts.
3.2.5 Catalyst Fe site utilization. Only a portion of all D1
and D2 Fe–N
x
sites of any catalyst is actually located at the
catalyst (pore) surface, and can, in principle, act as catalytically
active sites under ORR conditions. It would be quite useful
to know the ratio of all Fe sites that are located at the
catalyst surface and are potentially catalytic active sites. This
ratio can be referred to as ‘‘site utilization factor’’ and can be
used as a guiding metric in the design of improved Fe–N–C
catalysts. Synthesis efforts should evolve toward utilization
factor of unity, in which case all Fe sites could act as catalytic
active sites.
The SD
mass
(CO) and SD
mass
(NO
2
) metric probe and quan-
tify the number of D1 and D2 Fe–N
x
sites on the surface under
ex situ and in situ conditions, respectively. SD
mass
(CO) and
SD
mass
(NO
2
) data in Fig. 10a (cf. Fig. 4) recall that under
in situ NO
2
conditions (presence of electrolyte and applied
potential) the number of accessible, and hence potentially
catalytic active Fe surface sites is smaller than the ex situ Fe
surface site density suggests (see earlier discussion). This is
why from SD
mass
(CO) and SD
mass
(NO
2
) values a less and more
stringent site utilization factor will ensue.
To derive experimental site utilization factors, we note
that Mo
¨ssbauer spectroscopy yields experimental quantitative
estimates of the combined abundance (in weight%) of D1 and
D2 Fe sites in bulk and surface of the catalysts, Fe
D1+D2
. From
Fe
D1+D2
the maximum possible mass-based Fe surface site
density (SD
max,D1+D2
) can be calculated as:
SD
max,D1+D2
[site g
cat1
]=Fe
D1+D2
[wt%]/100/M
Fe
N
A
where M
Fe
is the molar mass of iron, and N
A
is Avogadro’s
constant. Trends in SD
max,D1+D2
values for the four catalysts are
illustrated in Fig. 10a with PAJ (B2.2 10
19
sites g
1
)oUNM
(7.2 10
19
sites g
1
)oICL (11 10
19
sites g
1
)oCNRS
(16 10
19
sites g
1
).
Normalizing SD
mass
(CO) and SD
mass
(NO
2
) with SD
max,D1+D2
yields CO and NO
2
-related site utilization factors, F, (Fig. 10b)
according to:
F
D1+D2
(CO) = SD
mass
(CO)/SD
max,D1+D2
F
D1+D2
(NO
2
)=SD
mass
(NO
2
)/SD
max,D1+D2
While the magnitude of F
D1+D2
(NO
2
) is significantly smaller
(o10%), both types of site utilization factors exhibit the
identical trend according: ICL oCNRS oUNM oPAJ. This
is why the variations in utilization factors remained much
smaller for the NO
2
-related data set. F
D1+D2
(NO
2
) represents
the more stringent metric for guiding synthetic efforts. While
F
D1+D2
(CO) of PAJ suggests that almost 80% of all Fe–N
x
sites
are located at the surface, its F
D1+D2
(NO
2
) value demonstrates
that just about 10% of Fe–N
x
sites are electrochemically acces-
sible. Both metric call for improved morphological and mole-
cular catalyst designs that would deliberately place Fe–N
x
sites
in electrochemically accessible locations, such as meso pores.
Once F
D1+D2
values reach unity, further synthetic efforts to
raise SD must remain ineffective and can give way to efforts to
improve the (average) TOF values of (individual) Fe sites, in
order to arrive at more active Fe–N–C ORR catalysts.
Fig. 10 (a) Quantitative comparison of the maximum surface site density of D1 and D2 Fe sites (SD
max,D1+D2
) and the Fe surface site densities, SD
mass
(CO)
and SD
mass
(NO
2
) of the four benchmark Fe–N–C catalysts; (b) Fe site utilization factors, F
D1+D2
(CO) and F
D1+D2
(NO
2
) of the four benchmark Fe–N–C
catalysts.
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4. Conclusion
This cross-laboratory study compared and contrasted the
physico-chemical properties and catalytic performance of four
PGM-free Fe/N-doped carbon catalysts, Fe–N–C that efficiently
catalyze the electrochemical reduction of molecular oxygen to
water. The four selected catalysts, named PAJ, CNRS, UNM, and
ICL were considered as state-of-art benchmark catalysts. What
sets this study apart from previous similar studies, however, is
the previously unachieved depth in the analysis of the origin of
the catalytic reactivities. This was made possible by means of a
deconvolution of catalytic performance metrics, such as the
electrocatalytic mass activity (MA) and the surface area-based
specific activity in terms of mass-normalized (SD
mass
) and BET
surface area-normalized (SD
BET
) Fe surface site density (SD) and
intrinsic catalytic turnover frequencies (TOF). This is the
first time that Fe surface site densities and TOF values were
evaluated and compared side-by-side for the same set of
Fe–N–C catalysts using in situ nitrite reduction and ex situ CO
cryo adsorption.
Initial ex situ characterization established the order of
increasing kinetic mass-based ORR activity at 0.80 V
RHE
to
ICL oCNRS oUNM oPAJ. Electrochemical NO
2
adsorp-
tion/stripping measured a proportion of the surface Fe sites,
electrochemically underutilizing the number of surface Fe sites
potentially available, as disclosed by CO measurements. If we
were able to access all the CO-accessible sites in an electro-
chemical environment, we could potentially boost the ORR
activity by a factor of 2–4.
Key conclusions include the first direct correlation of
previously elusive SD values derived from CO and NO
2
prob-
ing. Both techniques yield SD
mass
and SD
BET
estimates of the
order of 10
19
sites per gram catalyst and 10
16
sites per m
2
catalyst area, respectively. SD(CO) values were of larger magni-
tude due to the ready CO accessibility of Fe sites in the catalyst
pore structure. TPD data further rationalized a deconvolution
of SD
BET
(CO) data, which revealed a remarkable quantitative
agreement between SD
BET,corr
(CO) and SD
BET
(NO
2
) values.
SD–TOF reactivity maps were introduced as a data tool to
analyze the origin of ORR reactivity of PGM-free Fe–N–C
catalysts and aid in the design of more active ORR catalysts.
These maps showed that PAJ exhibited the lowest Fe site
density, which was offset by catalytically highly active site,
which is why PAJ exhibited the highest mass-based ORR
activity. CNRS, on the other hand, owing to its micropore
structure featured the largest Fe SD at the lowest average
TOF. The SD–TOF maps therefore suggested synthetic efforts
to raise the SD of PAJ in order to achieve further improved ORR
catalysts.
Correlations between Fe SD and (ex situ) physico-chemical
surface and bulk properties of the catalysts led to the conclu-
sions that (i) pyridinic nitrogen species are prevalent building
blocks for Fe–N
x
surface sites, (ii) high spin Fe sites (D1) are
present in macro and micro pores, and (iii) medium spin Fe
sites (D2) are present preferentially in mesopores and less so in
micropores.
Finally, a Fe site utilization factor was introduced and
evaluated for each catalyst from both the experimental
CO- and NO
2
based SD values. Site utilization factors derived
from both SD techniques were fully consistent in their trends
across the four catalysts. For PAJ, they suggested that roughly
80% of all available bulk Fe sites (D1 + D2) are located at the
surface, while 10% remained available under operating ORR
conditions. ICL, on the other hand, displayed 20% sites at the
surface under ex situ conditions, and around 8% under opera-
ting conditions. Site utilization factors may be used as guide-
lines where synthetic optimization of catalyst morphologies is
needed and when SD improvements are no longer necessary or
effective.
In summary, this study represents a significant step forward
in our analysis and understanding of the reactivity of PGM-free
ORR catalysts. The proposed experimental methodologies and
analytical data tools can easily be applied to new Fe–N–C ORR
catalysts or even to metal–N–C single site catalysts for electro-
catalytic processes other than the ORR. We expect that this
work will help transform M–N–C catalysis research from the
realm of empirical trial-and-error into a future, progressively
more knowledge-based process.
Conflicts of interest
There are no conflicts to declare.
Acknowledgements
The research leading to the present results has received funding
from the Fuel Cells and Hydrogen 2 Joint Undertaking under
grant agreement no. 779366. This Joint Undertaking receives
support from the European Union’s Horizon 2020 research and
innovation program, Hydrogen Europe and Hydrogen Europe
research.P.S.acknowledgespartialfinancialsupportbythe
German Federal Ministry of Education and Research under the
German-Israeli battery program via the grant ‘‘Korrzellkat’’ with
FKZ 03XP0251.
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