1. Methods 2
1.1. Experimental Details 2
1.2. Computational Details 5
2. Validation of the reactive force field 11
3. Ab-initio MD simulations 19
4. Electronic origin of the differences in catalytic activity between different metal
surfaces 21
5. Evolution of various bonds during reactive molecular dynamics on various metal
surfaces 24
6. Repeatability of the results of MoNX-Cu nanocomposite coating in PAO 10 28
7. Results of another optimized nanocomposite coating: VN-Cu 29
SUPPLEMENTARY REFERENCES 30
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1. Methods
1.1 Experimental Details
MoNx-Cu coated and uncoated AISI 52100 steel samples were used as test
coupons. After Ar ion etching to remove the surface contaminants, the MoNx-Cu
nanocomposite was deposited using individual Mo (99.95%) and Cu (99.99%) targets in
a dual magnetron sputtering system. To achieve ≈6 at. % Cu in the composite coating,
4,000 W (9 W/cm2) and 200 W (0.45 W/cm2) were applied on Mo and Cu targets,
respectively. The substrate temperature was kept constant at 270oC. The total working
pressure was fixed at 0.4 Pa in a mixture of Ar/N2 (130 sccm/55 sccm, respectively).
After the deposition, the crystallographic phase analysis was done by X-ray
diffraction using monochromatized Cu Kα radiation (Bruker D2 Phaser); the chemical
composition was obtained by X-ray photoelectron spectroscopy (Physical Electronics
PHI 5400) using monochromatic Mg Kα X-ray source. The hardness and elastic
modulus of the coating were studied by nano-indentation (Hysitron Triboindenter TI-
950) with a Berkovich diamond probe and loads in the range of 0.5 mN to 12 mN. A
high-resolution transmission electron microscope (JEOL 2100F) operated at 200 kV
was also used to analyze the chemical and structural nature of the composite films and
the boundary films formed on rubbing surfaces.
The friction and wear experiments were carried out with a ball-on-disk test rig
(Tribometer Nanovea) in which a stationary steel ball (9.5 mm in diameter) was pressed
against a rotating disk (50-mm diameter and 7-mm thick) under 20 N load, which
created 1.3 GPa peak Hertzian contact pressure. The ball-on-disk experiments were
performed with coated and uncoated test pairs in (neat) basestock PAO 10 oil (whose
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kinematic viscosity at 40 and 100oC was 66 and 10 mm2/s, respectively) and in fully
formulated 5W30 oil (ILSAC GF-5 multigrade engine oil whose kinematic viscosity at 40
and 100°C was 61 and 11 mm2/s). The sliding contact surfaces of the ball and disk
specimens had a nominal surface roughness of 0.02 µm RMS. Prior to tribological tests,
all samples were cleaned twice by acetone and isopropanol solvent in an ultrasonic
bath for 5 minutes and then dried in open air. The lubricated sliding tests were
performed at room temperature and in ambient air with ≈40% relative humidity. The fully
formulated 5W30 and the PAO 10 oils were applied to the sliding surface with a syringe
in the amount of 0.05 ml, which was sufficient to cover the whole rubbing surface. The
total sliding distance accumulated during the tests was 3,600 m. The friction force
generated between the sliding ball and flat surfaces was continuously monitored and
later converted to the friction coefficients for the entire test cycle. The wear volumes on
the ball and disk samples were assessed with the help of optical microscopy (Olympus
STM6) and optical 3D non-contact surface profilometry (Bruker Contour GT).
Rubbing surfaces were analyzed by confocal Raman microscopy (inVia Reflex,
Renishaw, Inc.) using appropriate light sources with a range of wavelength (325 nm and
633 nm) to determine the nature of the tribo-chemical films that formed on the rubbing
surfaces during sliding. The Raman instrument was calibrated using an internal silicon
reference, and the spectra were recorded in the range of 100-3,200 cm-1. Fe2O3 micro
powder (≥99%, Sigma Aldrich) and highly oriented pyrolytic graphite (Ted Pella, lacey
carbon) were used as references.
The tribological layer was scrapped off the MoNx-Cu tested ball by using a
tungsten tip in a focused ion beam instrument. The use of the electron beam and ion
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beam was kept minimal to prevent damage on the sample. The thin film was
subsequently transferred to an Ominiprobe TEM grid to perform the TEM and EELS
analyses. The sp2 fraction was calculated using the EELS spectra by a very well-known
procedure.1,2 The EELS spectra were calibrated using highly oriented pyrolytic graphite
HOPG (Ted Pella, lacey carbon). The sp2 fraction (x) in the tribological layer was
determined by comparing the ratio of the π* and σ* peaks intensity with that of HOPG
using the equation (S1):
(S1)
The repeatability of the friction and wear tests were confirmed by running multiple
tests on MoNx-Cu coated pairs under the same conditions (Fig. S8 shows the results
from one of these tests). We provide Fig. S9 to show that carbon-rich tribofilm can also
form on Cu-containing VN-based nanocomposite coating.
TOF-SIMS studies of the tribofilm were carried out using an imaging ToF-SIMS
(PHI TRIFT III) instrument which was proven to be very versatile in revealing the
chemical nature of very thin (a few Å to 1–2 nm) surface layers with high mass and
spatial resolutions, providing both chemical and distributional (laterally and in depth)
information for a wide variety of masses down to hydrogen. The raw data streams of the
sputter depth profiles of examined area contain a full mass spectrum of every pixel in
three dimensional space; hence, the TOF-SIMS images of these films can be re-
constructed from selected masses and/or depths to provide chemical information.
Prior to TOF-SIMS analyses, we solvent cleaned the tested MoNx-Cu-coated ball using
heptane in order to remove the remnants of PAO oil. For the generation of SIMS
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spectra and images, we used liquid Au cluster ions as the primary ion sources (primary
ions were produced using a 22 keV-pulsed Au+ analytical gun, and the beam current
was between 500 pA and 3 nA). Cesium ions were used for sputtering of the
contaminant layers from top surfaces and for depth profiling purposes. The sputtering
area was kept 3 times larger than the analyzed area to prevent any artificial edge
effects during data collection. The sputtering gun was operated at 2 kV and 1,500 pA
and the sputtering time was 60 s for each cycle. The mass range was from 1 to 800
amu, and the mass resolution m/Δm was better than 2,300 at mass 25.
1.2 Computational Details
Reactive molecular dynamics
We employed reactive molecular dynamics (RMD) to investigate the atomic scale
processes governing the metal catalyzed formation of carbon-based boundary films
from linear olefins under tribological conditions. All RMD simulations are performed
using the classical MD simulation package LAMMPS3 in a canonical ensemble (NVT)
with a time step of 0.25 fs. Our typical computational supercell consists of two metal
slabs held at a vertical distance of ~2 nm apart, which act as rubbing surfaces (Figure
S1); each of these blocks containing 2,560 atoms (~3.5 nm × 4.0 nm × 2.0 nm). Periodic
boundary conditions are employed in the plane of metal slab (i.e., along x- and y-
directions). The lubricating oil is modeled as a mixture of linear terminal alkene chains
(alpha olefins) of various chain lengths (each containing 3 – 20 carbon atoms) oriented
along arbitrary directions. These linear chains are placed at random locations in the
empty space between the two metal slabs such that the overall mixture of alpha olefins
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contains ~1100 C atoms. We ensured that the atomic scale pathways identified by our
RMD simulations are indeed robust and are independent of the values of chain lengths,
as well as their distribution employed to model the olefins; the kinetics of the processes,
however, becomes slower as the average chain length increases. To simulate the
friction between two metal slabs, we impart a constant sliding velocity of 0.1 m/s
(following our experiments) along the x-direction while keeping the top metal block fixed
in space. Using this initial configuration, the system is equilibrated at 1000 K; the
constant temperature conditions are maintained by employing the Nosé-Hoover
thermostat as implemented in LAMMPS.3
To accurately capture the tribochemical reactions that occur at the sliding metal-
olefin interfaces, we describe the atomic interactions using a general bond-order based
reactive force field (ReaxFF), which is known to describe formation and dissociation of
chemical bonds well.4-6 In the framework of ReaxFF, the total energy is composed of
several contributions arising from covalent interactions (e.g., bond stretching, angle
bending, dihedral torsion, and over-/under-coordination), as well as non-bonded
interactions (e.g., van der Waals, Coulomb). The short-range bonded interaction terms
are computed from instantaneous bond-orders for each atom pair. This bond order, in
turn, is strongly influenced by the local environment around the particular pair of atoms,
thus, accounting for multi-body effects.4-6 The non-bonded interactions, on the other
hand, are computed for each pair of atoms regardless of its connectivity. In addition, the
atomic charges are evaluated at each step using an electronegativity equalization
scheme.7 Such a general formalism enables ReaxFF to accurately capture covalent,
ionic, and metallic bonding, as well as transition states along a reaction pathway.4-6
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Consequently, ReaxFF has been used successfully for a wide range of material
systems, including metals, metal-oxides, ceramics, metal-organics, and hydrocarbons.
Figure S1. Schematic representation of a typical computational supercell
containing two metal slabs (brown) separated by a vertical distance of ~2 nm. The
space between the two slabs is filled with linear alkenes of varying chain lengths
ranging from 3--20 carbon atoms. To simulate tribological conditions, the bottom metal
slab is imparted a constant sliding velocity of 0.1 m/s, while keeping the atoms in top
slab fixed. The C atoms belonging to the alkenes are shown in gray and the H atoms
are depicted in blue (see magnified image).
In this study, we explored five different metals, namely, Cu, Ni, V, and Mo. The
ReaxFF parameters for metal-hydrocarbon interactions are taken from (a) Cu/C/H:
Ref.8, (b) Ni/C/H: Ref.9, and (c) V/C/H: Ref.10. Since ReaxFF parameters are not
available in the literature for Mo/C/H, we employed Modified Embedded Atom Method
Metal
Metal
Olefins
v = 0.1 m/s
~2 nm
~2 nm
~2 nm
x
y
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(MEAM) to describe Mo-Mo interactions (parameters from Ref.11), Adaptive
Intermolecular Reactive Empirical Bond Order (AIREBO) potential for C-C, C-H
interactions,12 while the Mo-C, and Mo-H interactions are modeled by Lennard-Jones
(LJ) interactions with parameters obtained from Lorentz-Berthelot mixing rules (Table
S1). The LJ contribution for a pair of atoms, held at a distance r apart is given by:
E = 4es
r
æ
èç
ö
ø÷
12
-s
r
æ
èç
ö
ø÷
6é
ëêê
ù
ûúú, (1)
where σ and ε are independent parameters that define the length and energy scales
respectively. For each of the five metals, we perform NVT-MD simulations at 1,000 K for
1 ns. Using these simulations, we identified that all these transition metals catalyze
dehydrogenation of the alkenes, and breakdown of the longer hydrocarbon chains into
smaller fragments. Note that the reaction pathways predicted by the RMD simulations
are independent of supercell size. Even large system sizes (~ 1 million atoms; ~100,000
C atoms) showed catalytic formation of graphitic carbon tribofilms via reaction pathways
identical to those revealed by smaller supercells. Subsequently, V shows extensive
carbide formation, Mo shows reduced propensity to form carbides particularly at 1,000
K, while Cu and Ni do not form any carbide.
To validate the findings of ReaxFF with another interatomic potential model, as
well as to facilitate long MD simulation times, we repeated the MD simulations for
Cu/olefins system using EAM to describe Cu-Cu interactions,13 AIREBO for C-C, C-H
hydrocarbon interactions12 and LJ (Eq. 1) to describe the cross interactions (i.e, Cu-C,
and Cu-H); LJ parameters are listed in Table S1. The AIREBO interatomic potential
model has been successfully employed to study interactions between graphene and
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sliding interfaces under tribological conditions in a recent work.14 The parameters for the
LJ interactions are listed in Table S1. We performed NVT-MD simulations for the Cu-
olefins system at 1,000 K for 2 ns. In a typical tribological experiment, the free hydrogen
formed via dehydrogenation of olefins, and breakdown of longer alkenes into shorter
ones can escape the system through a free surface or can get adsorbed into the bulk
metal slab. To emulate this loss of atomic/molecular hydrogen from the system following
dehydrogenation/chain scission, an efficient hydrogen removal scheme is necessary.
Experimentally, the carbon-hydrogen (C-H) and hydrogen-hydrogen (H-H) bond lengths
are reported to be 1.09 Å and 0.74 Å, respectively; these bond lengths are accurately
reproduced by the AIREBO potential.15 In our simulations, we identified the hydrogen
atoms to be removed (either as free atomic hydrogen or as H2 dimer) from the
simulation cell using distance criteria. Specifically, we monitored the distance between
carbon and hydrogen atoms every 1 ps (Note, we verified that an increased frequency
of monitoring distances does not impact the results significantly). If the separation
between a previously bonded C-H pair is ≥ 1.5 Å, then the C-H bond was assumed to
be broken and the respective H atom was removed from the simulation cell. This is
certainly reasonable since the bond cut-off distance in AIREBO potential is 1.5 Å.
Similarly, if two H atoms are ≤ 0.75 Å apart, we considered them to have formed a H2
dimer; we removed the dimer to simulate loss of hydrogen gas.
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Table S1. Lennard Jones parameters ε and σ (Eq. 1) for various atomic pair types
derived by Lorentz-Berthelot mixing rules. For mixing, the LJ parameters for the
individual species are taken from the references listed for each pair.
Atom-pair ε (eV) σ (Å) References
Cu-C 3.433 × 10-4 2.838 12,16
Cu-H 2.495× 10-4 2.463 12,17
Mo-C 0.0536 3.070 12,18
Mo-H 0.0389 2.695 12,18
Ab-initio molecular dynamics simulations
To validate the atomic scale pathways predicted by our ReaxFF based MD
simulations, we employed ab-initio MD simulations (AIMD) within the generalized
gradient approximation (GGA) using the projector-augmented wave formalism as
implemented in the Vienna Ab-initio Simulation Package (VASP).19,20 The exchange
correlation is described by the Perdew-Burke-Ernzerhof (PBE) functional,21 and the
plane wave energy cut-off is set at 400 eV. The Brillouin zone is sampled at the -point
only. Using the AIMD simulations in the canonical ensemble (NVT), we monitor the
temporal evolution of 1-pentene (a representative olefin) molecule on three different
metal surfaces: Cu (111), Mo (001) and V (001) as well as MoN (100) and VN (100) at
various temperatures in range of 1,000 K-1,500 K for 10 ps using a timestep of 0.5 fs.
The surface slab supercells consisted of 5 atomic layers (100-200 atoms) with
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dimensions ~1.5 nm x 1.5 nm in the plane of each layer. Periodic boundary conditions
are employed along all directions; a vacuum of 2 nm was employed in the direction
normal to the surface to avoid spurious interactions across the periodic boundaries. The
pentene molecule is initially placed at a random location on the metal /nitride surface at
a vertical height of 0.2 nm. Constant temperature conditions are maintained using a
Nose thermostat as implemented in VASP.19,20
2. Validation of the reactive force field
To assess the suitability of ReaxFF for investigating tribochemical processes in
olefins, we first compared the ReaxFF predicted energies of an elaborate set of
configurations (~20,000) of various representative hydrocarbons, namely benzene,
butane, butadiene, cyclohexane, ethylene, icosene, octane, pentane, pyrene, and
propene; 2,000 distinct configurations for each of these hydrocarbons were sampled via
high temperature (1500 K) ReaxFF MD simulations. Indeed, such a data intensive
validation of the ReaxFF force field for the olefin system has not been reported before.
These configurations were used as input structures and single point energies of these
olefin configurations were determined at M06-2X/6-311++G(d,p) level of theory using
Gaussian 09. The minimum energy of these clusters was taken as ground states and
the relative QM single point energies were computed.
Figure S2 shows the comparison between the relative configurational energies
derived from ReaxFF with that obtained from quantum calculations. Figure S2 (a)
compares the ReaxFF predicted energies (relative to the most stable geometry for a
given hydrocarbon) for these confirmations with those obtained from density functional
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theory (DFT) calculations. To place these comparisons in perspective, we have also
shown the performance of AIREBO, an accomplished interatomic potential for
hydrocarbons in Figure S2 (b). Note the extensively large of configurations sampled (~
2,000 for each of the different olefin systems) from the MD trajectories. By employing
such a large cross-validation test set, we are ensuring that the test set amply samples
the energy landscape; this test set provides good representation of the diverse
configurations, which are expected to be encountered during elongation of C-C, and C-
H bonds, bending of C-C-C angles, and other hydrocarbon activation processes that
can occur under tribological conditions. We find that there is an excellent correlation
between the predictions of the force fields and the quantum calculations. The average
differences in the energy values predicted by force fields as compared to those
quantum calculations (mean absolute error; MAE) are ~0.04-0.05 kcal/mol for all the
cases, which suggests an excellent agreement. The MAE in the energy values
predicted by ReaxFF when compared to DFT values is 0.04 eV/atom with a standard
deviation of 0.03 eV/atom; AIREBO provides similar accuracy with error of 0.05 ± 0.04
eV/atom. It is important to note that since even DFT calculations are not expected to
reach chemical accuracy (0.04 eV/atom), both ReaxFF and AIREBO potentials are
performing essentially at the limit of DFT accuracies. Also, a comparison of the
energetic ordering of the solvated structures between the force field and the quantum
calculations shows excellent agreement. Given the remarkable accuracy of the force
field employed in this work, it is quite reasonable to expect that the lowest energy
configuration clusters chosen from a diverse set of MD configurations adequately
represent the most thermodynamically stable cluster structures upon which further
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quantum calculations can be performed. Furthermore, we have also performed ab initio
MD simulations of the hydrocarbon dissociation process (see Main text) and observe
that the elementary steps involved in the catalytic process such as dehydrogenation of
the hydrocarbon chains (C-H bond scission), and scission of the C-C backbone of the
chains are in remarkably good agreement with the predictions of the reactive force
fields. Collectively, our rigorous and extensive cross-validation of the ReaxFF by AIMD
simulations and M06-DFT calculations shows remarkably good agreement and provides
sufficient degree of confidence in the predictive power of the force fields for systems
involving olefins interactions with the different metals investigated in this study.
Figure S2. Comparison of cohesive energies of a wide range of structural
configurations (sampled via reactive MD simulations at 1500 K) for numerous
hydrocarbons, as predicted by (a) ReaxFF, and (b) AIREBO empirical potentials, with
those obtained from DFT calculations. For each hydrocarbon, the energies plotted are
relative to their most stable configuration.
Charge transfer events between metal surfaces and olefins play a crucial role in
activating the hydrocarbons, which underpins the response of olefins to tribiological
environment. Indeed, the reactive force field (ReaxFF) employed in this work [Ref. 8] to
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describe the interactions between Cu, C and H accounts for transfer of electronic
charge between atoms using electronegativity equalization method (EEM) [Ref. 7].
Using this method, the equilibrium charges on each atom are determined self-
consistently at each step during a molecular dynamics simulation; these charges are
strongly dependent on the local atomic arrangement. Owing to the environmental
dependent charges, the ReaxFF is able to accurately predict the bond formation and
bon breakage phenomena and thus is able to handle the reactive processes within the
framework of classical molecular dynamics. The EEM technique has been found to
accurately describe charge-transfer (i.e., redistribution of charges) in a wide range of
systems including metals, oxides, semiconductors, polymers and hydrocarbons.5,6,14,22-
24 An accurate description of the charge transfer is important for describing bond
energetics for any given system. More relevant to the current study, the ReaxFF
parameters employed in the current study accurately predict bond-dissociation, angle
distortions, and chemical reaction energies associated with Cu/hydrocarbon
complexes.8 For instance, ReaxFF predicts dissociation energies within < 0.5 eV/atom
of those obtained from quantum mechanical (QM) calculations, as shown in Table S2
[Ref.8]. These QM calculations were performed using the hybrid density functional
theory functional B3LYP, which is known to give accurate description of reaction profiles
for transition metal complexes with organic molecules.8,25
Table S2. Comparison of bond dissociation energies predicted by ReaxFF with
those obtained from QM calculations [Ref. 8]
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Reactant Products EQM
(eV/atom)
EReaxFF
(eV/atom)
CuCH3 Cu + CH3 2.35 2.18
Cu(CH3)2 CH3Cu+ CH3 1.14 1.31
Cu(CH3)3 (CH3)2Cu + CH3 1.22 0.71
CH3-Cu=CH2 CH3-Cu + CH2 1.94 1.56
Cu-C6H5 Cu + C6H5 0.11 0.11
More importantly, we note that the electron transfer (re-distribution of charges)
obtained from the electronegativity equalization method (EEM) influences the bonding
potential. This unique feature of ReaxFF makes it an appropriate interatomic potential
model to represent the dissociation and formation of bonds via electron transfer. In fact,
the distinguishing feature of ReaxFF compared to other “variable charge models”, which
also employ EEM, lies in its ability to capture chemical bond formation/breakage within
the framework of molecular dynamics simulations. For instance, upon combining EEM
with simplistic (non-bond order) functional forms such as Morse or Buckingham (termed
variable charge models, e.g., Ref. 26), the charge-redistribution affects only the
Coulombic terms; the absence of bond-order terms make them inherently incapable of
capturing breakage of an already existing bond or the formation of a new chemical bond
that occur via electron transfer. Such variable charge potential models can describe
structure, mechanics, energetics, and atomic charge variations (values between 0 and
atomic valency) under dynamical conditions. However, it cannot model reactive
processes such as oxidation. In essence, a variable charge model, which employs non-
bonded interactions combined with EEM, cannot describe any kind of chemical reaction.
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ReaxFF, on the other hand, is a powerful method precisely because of its ability
to identify bond order between every atom pair based on its local atomic environment,
i.e., all atoms within a sphere of a certain cut-off radius (typically 10 Å) around this pair.
This in conjunction with charge redistribution via EEM method allows it to treat complex
chemical reactions within the MD framework.5 For the sake of simplicity, the bond order
can be considered to be equivalent to the number of chemical bonds in the system. For
example, in ethene (H2C=CH2), the bond between two carbon atoms has a bond order
of 2 (1, 1 π bond), while C-H bonds have bond order of 1 (1 bond).
Figure S3 Dependence of the total bond order and its components as a function
of interatomic distance between two carbon atoms [Ref. 27].
In molecular orbital theory, the bond order BO is defined as half the difference
between the number of bonding electrons Nb, and anti-bonding electrons Nab, written as:
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BO =Nb - Nab
2.
Linus Pauling (Ref. 28) demonstrated that the partial bond-order contributions
BOij
a
(a value between 0 and 1) arising from a bond type (i.e, , π, or ππ bonds) for a
given atomic pair i-j can be described as a continuous function of the instantaneous
distance between atoms i and j (rij) Such a function results in a partial contribution of 1
for rij values within a specific distance (i.e, equilibrium i-j bond length) As rij increases,
BOij
a
decreases smoothly before eventually vanishing at large distances. In the
framework of ReaxFF, the total bond order for an atomic pair i-j is defined as the sum of
partial contributions from , π, and ππ bonds, written as:
BOij = exp aij
a rij
r0
a
æ
èç
ö
ø÷
bijaé
ë
êê
ù
û
úú
a
å Dij
a, a Î {s ,p,pp},
whereDij
a
is a correction term that accounts for over-coordination and under-
coordination effects, while aij
a
and bij
a
are specific (empirical) bond parameters. The total
bond order BOij can take values between 0 (no bond) and 3 (1, 1 π, and 1 ππ bond).
As shown by Fig. R2, this total bond-order becomes 3 below equilibrium bond length,
while vanishing at large inter-atomic distances.. The different ranges of , π, and ππ
partial contributions guarantee a large flexibility in the set-up of reactive force fields.
Note that the bond-order can be uniquely determined for all pairs of atoms from the
inter-atomic distance rij. In addition, multi-body effects are accounted via a rigorous
bond-order correction scheme, such that the bond order between a given pair i-j is also
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influenced by all the atomic pairs within a prescribed cut-off (typically sphere of 10 Å
radius) around it.
Briefly, in ReaxFF, all connectivity dependent (bonded) interactions, including the
bond, valence, and torsion angles are strong functions of bond order; these bond orders
are updated at every MD timestep. Although this makes ReaxFF computationally more
intensive compared to other empirical potentials, the bond-order dependence of all
bonded interactions makes it capable of capturing bond dissociation/formation during a
typical MD run. At each step MD step, the redistribution of atomic charges is derived via
EEM scheme; the electron transfer described by EEM impacts the atomic coordination,
and interatomic distances, and thereby, affects the bond orders and eventually bonding
interactions. This unified bond order formalism coupled with the geometry dependent
charge calculation scheme (EEM) accounts for polarization effects, and ensures that
catalytic reactions, wherein, electron transfer influences the electron occupation of the
bonding, and anti-bonding orbitals are adequately captured. In the literature, ReaxFF
has been successfully used to model several reactive processes, including transition
metal catalyzed growth of carbon nanotubes,29,30 catalytic oxidation of hydrocarbons,6,31
thermal decomposition of polymers,24 reduction of graphene oxide,32 superlubricity
enabled by graphene nanoscrolls,14 and aqueous protonation across graphene.33
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3. Ab-initio MD simulations
In addition to ensuring that the energetic predictions of ReaxFF are on par with
DFT calculations, we also validated the ReaxFF predicted atomic scale pathways via ab
initio molecular dynamics (AIMD) simulations [Fig. S3]. To accomplish this, we
monitored the temporal evolution of a 1-pentene (a representative olefin) molecule on
three different metal surfaces: Cu (111), Mo (001) and V (001) at various temperatures
(1,000-1,500 K) over 10 ps. As shown in Fig. S3 (a-c), on the Cu (111) surface, the
pentene molecule undergoes dehydrogenation (C-H dissociation), and scission of C-C
bonds identical to ReaxFF predictions; we note that these events are independent of
temperature within the simulated range. For Mo (001), significant de-hydrogenation of
pentene is observed. However, despite the existence of stable Mo-carbides, no carbide
formation is observed; in fact, the C-C bonds remain intact [Fig. S3 (d-f)]. This is
possibly due to lack of necessary thermal energy required to surmount reaction barriers
at the temperatures considered here. More importantly, this is in excellent agreement
with our reactive MD simulations, which show C-H bond dissociation without any C-C
scissions resulting in largely linear chains of longer hydrocarbons rather than a graphitic
structure. In the case of V (001), identical to our ReaxFF MD predictions, AIMD shows
violent de-hydrogenation, C-C bond breaking, followed by formation of V-C bonds [Fig.
S3 (g-i)].
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Figure S3. Snapshots at selected times during AIMD simulations of 1-pentene on
(a-c) Cu (111), (d-f) Mo (001), and (g-i) V (001) surfaces at 1,000 K. In all the panels,
top views of the metal surfaces are shown; the atoms are represented as spheres,
colored by their type: C (black), H (blue), Cu (brown), Mo (red), and V (cyan). Videos of
the various ab-initio trajectories are provided in the supporting information.
The excellent agreement between the atomic scale dynamic events predicted our
reactive MD simulations, with those obtained from AIMD further ascertains the validity of
our employed empirical potential in describing reaction pathways over ns timescales
and nanometer length scales under tribological conditions. We note that such length
0 ps 5 ps 10 ps
d e f
a b c
0 ps 1 ps 10 ps
0 ps 0.5 ps 10 ps
g h i
Figure 5. Snapshots at selected times during AIMD simulations of
1-pentene on (a-c) Cu (111), (d-f) Mo (001), and (g-i) V (001)
surfaces at 1000 K.
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and timescales, necessary to study the tribo-chemical formation of graphitic structures
from olefins in operando, are not tractable via AIMD simulations.
4. Electronic origin of the differences in catalytic activity between different metal
surfaces
To investigate the effect of electronic structure on the different catalytic activity of these
metal surfaces, we turn to DFT calculations. For the sake of simplicity, we choose
ethene as a representative olefin for this task. First, we identified the most probable
adsorption geometry of ethene on Cu (111), Mo(001), and V(001) surfaces respectively,
via AIMD simulations. Using these initial configurations, we allowed the atoms to relax
to minimum energy state via conjugate-gradient minimization within the framework of
DFT and generalized gradient approximation (GGA), and Perdew-Burke-Ernzerhof
exchange correlation functional.19-21 We found that ethene merely physisorbs onto
Cu(111) surface as indicated by a low adsorption energy Ea of -0.34 eV, while it strongly
binds to Mo(001) [Ea = -2 eV] and V(001) [Ea = -1.5 eV].
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Figure S4. Projected electronic density of states for the sp2 and pz orbitals of the
two C atoms in ethene for (a) isolated molecule, and when adsorbed on (b) Cu, (c)
Mo, and (d) V, In panels (b-d) the partial density of states belonging to the d-orbitals of
the transition metals in the top surface layer are also shown.
To understand the changes in the electronic structure of ethene molecule when
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adsorbed onto the various metal surfaces, we plot the density of states projected onto
the C atoms of ethene, as well as the metal atoms in the top layer of the surface closest
to the adsorbed ethene molecule [Fig. S4]. In an isolated ethene molecule, as expected,
the projected density of electronic states (PDOS) of sp2 (i.e, s, px and py) orbitals as well
as pz are filled, as shown in Fig. S4(a). Upon adsorption on Cu (111) surface, the
projected density of states on the C atoms, and surface Cu atoms follow the well-known
Dewar–Chatt–Duncanson bonding mechanism for adsorption of organic molecules on
metals.34 Essentially, the occupied pz (π) orbitals of ethene donate electrons to Cu d-
orbitals, which manifests itself as a strong mixing between the bonding pz states (below
Fermi level) with the Cu d orbitals in the PDOS plot [Fig. S4(b)]. These d-orbitals, in
turn, move the donated electrons into the unoccupied π* states of ethene, as indicated
by emergence of a broad peak in pz states beyond Fermi level [Fig. S4(b)]. In addition,
the bonding sp2 states are far below the Fermi level, and do not mix with the Cu d
states. This is also consistent with the charge transfer analysis [Fig. S5(a)], which
shows a weak charge density transferred from Cu surface to ethene. On the other hand,
the d-orbitals of both Mo and V exhibit strong hybridization with the sp2 and pz states of
ethene, at energy states (5-6 eV) below the Fermi level [Fig. S4(b,c)]. Furthermore, only
slight mixing of C pz and d-states of Mo and V is observed beyond the Fermi level
indicating weak anti-bonding states. This results in strong binding between the surface
Mo/V atoms with the carbon atoms of ethene, which is further evidenced by extensive
charge transfer between ethene and metal surface [Fig. S5(b,c)]. Such a strong binding
results in formation of carbide phases, which precludes the formation of the solid
lubricating films.
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Figure S5. Cross-sectional view of the electronic charge transfer between the
adsorbed ethene molecule and four different substrates , namely (a) Cu, (b) Mo,
and (c) V as obtained from DFT calculations. The plane shown in panels (a-d) is normal
to the surface of the substrate, and contains the two carbon atoms of the ethene
molecule. The transferred charge densities are shown in e-/bohr3.
5. Evolution of various bonds during reactive molecular dynamics on various
metal surfaces
We plotted the temporal evolution of the number of C-H, C-C, metal-C, metal-H, and
H-H bonds for Cu, Mo and V surfaces as shown in Fig S6. On Cu (111), the olefins lose
~85% of their H atoms in ~ 0.7 ns which diffuse to the bulk of the Cu slab as atomic H or
leave the system as H2 molecule. No Cu-C bonds form, while there is ~40% increase in
the number of C-C bonds [Fig. S6(a-d)]. The dehydrogenation occurs over faster
timescales on Mo and V surfaces, as compared to Cu [Fig. S6(e-l)]. However, Mo (001)
results in lower C-H bond dissociations as compared to Cu (only ~50% H atoms are
removed from the olefins) within ~0.2 ns, beyond which the system essentially reaches
equilibrium [Fig. S6(e-h)]. Similar to our AIMD simulations, our reactive MD simulations
also do not predict any Mo carbide formation [Fig. S6(g)]. V (001) shows violent
Cu (111) a b
-0.01
0.01
0
c V (001) Mo (001)
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dehydrogenation – the olefins lose nearly all their H atoms within ~ 5 ps. In addition,
contrary to Cu and Mo, on V (001), the number of C-C bonds drops drastically to ~50%
of its initial value within ~5 ps [Fig. S6(i-l)]. Fig. S6(k) clearly shows that nearly all the C-
atoms get bonded to V, indicating extensive carbide formation.
Figure S6. Evolution of chemical bonds during a typical reactive molecular
dynamics simulation under tribological conditions for olefins on (a-d) Cu (111), (e-
h) Mo (001), and (i-l) V(001) surfaces. The number of C-C (a,e,i; red), C-H (b,f,j; blue),
and metal (M)-C (d,h,l) bonds are normalized by the number of C atoms, while the M-H
and H-H bonds are normalized by the number of H atoms initially present in the system
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We have investigated the effect of different crystallographic orientations of Cu,
Mo, and V on the atomic scale dynamics that occur under tribological conditions. We
found that the atomic scale events, i.e., dehydrogenation, C-C bond scission, and
carbide formation (on V) occur irrespective of the crystallographic orientation of the
surface. Also, we found that the formation (or lack of it) of DLC-like structures on a
metal surface is primarily controlled by the propensity of the metal substrate to form
carbide, and does not strongly depend on the crystallographic orientation of the surface.
On the other hand, the kinetics associated with the different atomic scale events (i.e,
dehydrogenation, C-C scission, and carbide formation) are, indeed, related to the
surface orientation.
Fig. S7(a-d) shows the evolution of the number of C-C, C-H, M-C, M-H and H-H
bonds during typical reactive MD simulations of olefins on three high symmetry Cu
surfaces (i.e., 111, 100 and 110) under tribological conditions. We find that there is a
direct correlation between the stability of a surface, and the rate (and extent) of
dehydrogenation. Owing to its face-centered cubic symmetry, the stability of surfaces
decreases as 111 > 100 > 110; as shown by Fig. S7 (b,d) the extent as well as the rate
of dehydrogenation is highest for 110 (the least stable surface). However, as shown by
Fig. S7(a), the formation of C-C bonds follow similar rate irrespective of the orientation.
Moreover, there is no carbide formation for Cu surface of any orientation. Figs. S7(e-g)
illustrate the configuration of the olefins after 1 ns of tribo-chemical activity via reactive
MD simulation; all the surface orientations result in the formation of DLC-like structure.
Nevertheless, a systematic study of the effect of surface orientation on reaction kinetics
is a subject worth pursuing further.
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Figure S7. Effect of crystallographic orientation of the surface on the tribo-
chemical formation DLC-like carbon from olefins during reactive MD simulations.
The evolution of (a) C-C, (b) C-H, (c) Cu-C, and (d) Cu-H + H-H bonds during a typical
MD run are shown on Cu (111) [red], Cu (100) [blue] and Cu (110)[green] surfaces.
The number of C-C, C-H and Cu-C bonds are normalized by the number of C atoms,
while the Cu-H and H-H bonds are normalized by the number of H atoms initially
present in the system. We have also provided MD snapshots at 1 ns for each of the
high symmetry surfaces (e) Cu (111), (f) Cu (100), and (g) Cu (110).
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6. Repeatability of the results of MoNx-Cu nanocomposite coating tested in PAO
10
Fig. S8. Experiment showing very close repeatability of the friction results from
MoNx-Cu coating in PAO 10. MoNx-Cu nanocomposite coating was tested twice to see
the reproducibility of the results in terms of friction, wear and carbon-rich tribofilm
formation; the results shows that the tribological behavior of the coating is fairly
reproducible.
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7. Comparison of MoNx-Cu and VN-Cu coatings
Figure S9. Comparison of MoNx-Cu with another catalytically active
nanocomposite coating (VN-Cu) developed at Argonne National Laboratory. VN-
Cu nanocomposite coating was deposited in a similar manner to that of MoNx-Cu, the
results show similar tribological behavior in terms of wear and friction (except for the
initially unsteady frictional behavior of VN-Cu). The generation of the amorphous carbon
protective tribofilm can be observed in the Raman spectra (633 nm laser) of both the
VN-Cu and MoN-Cu coated balls; the presence of G and D bands shows that the nature
of the tribofilms is the same, i.e., primarily based on amorphous carbon.
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