Pierrick Berruyer1, Moreno Lelli2, Matthew P Conley3, Daniel L Silverio3, Cory M Widdifield4, Georges Siddiqi3, David Gajan1, Anne Lesage1, Christophe Copéret3, Lyndon Emsley5. 1. Institut des Sciences Analytiques UMR 5280 (CNRS/Université Lyon 1/ENS Lyon), Université de Lyon , Centre de RMN à Très Hauts Champs, 69100 Villeurbanne, France. 2. Magnetic Resonance Center (CERM), University of Florence , 50019 Sesto Fiorentino (FI), Italy. 3. Department of Chemistry and Applied Biosciences, ETH Zurich , CH-8037 Zurich, Switzerland. 4. Department of Chemistry, Durham University , DH1 3LE Durham, United Kingdom. 5. Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL) , CH-1015 Lausanne, Switzerland.
Abstract
The spatial arrangement of atoms is directly linked to chemical function. A fundamental challenge in surface chemistry and catalysis relates to the determination of three-dimensional structures with atomic-level precision. Here we determine the three-dimensional structure of an organometallic complex on an amorphous silica surface using solid-state NMR measurements, enabled through a dynamic nuclear polarization surface enhanced NMR spectroscopy approach that induces a 200-fold increase in the NMR sensitivity for the surface species. The result, in combination with EXAFS, is a detailed structure for the surface complex determined with a precision of 0.7 Å. We observe a single well-defined conformation that is folded toward the surface in such a way as to include an interaction between the platinum metal center and the surface oxygen atoms.
The spatial arrangement of atoms is directly linked to chemical function. A fundamental challenge in surface chemistry and catalysis relates to the determination of three-dimensional structures with atomic-level precision. Here we determine the three-dimensional structure of an organometallic complex on an amorphous silica surface using solid-state NMR measurements, enabled through a dynamic nuclear polarization surface enhanced NMR spectroscopy approach that induces a 200-fold increase in the NMR sensitivity for the surface species. The result, in combination with EXAFS, is a detailed structure for the surface complex determined with a precision of 0.7 Å. We observe a single well-defined conformation that is folded toward the surface in such a way as to include an interaction between the platinum metal center and the surface oxygen atoms.
Three-dimensional determination
of molecules and molecular assemblies
from single crystals by diffraction methods has led to today’s
structure-based understanding of the field. However, if the system
under investigation is located on a surface, as in many functional
materials,[1−5] three-dimensional structure determination is largely an unsolved
problem.In fact, it is not even known whether molecular fragments
at surfaces
form well-defined structures or if they adopt disordered conformations.
For example, specific metal–surface interactions have been
proposed to be essential in stabilizing active site structures in
many heterogeneous catalysts,[6−9] but so far it has not been possible to obtain three-dimensional
structures to confirm such interactions. A range of probes (XPS, EXAFS,
STM, etc.) are used to characterize surfaces, but they require either
model surfaces under high vacuum or very ordered materials, or they
yield only partial descriptions. Nuclear magnetic resonance (NMR)
spectroscopy would be an attractive method for determination of surface-supported
structures if it were not that the detection limit of NMR under conventional
conditions is too low to allow for the study of species at surfaces
in many modern materials. This problem has in principle been solved
with the introduction of dynamic nuclear polarization (DNP) surface
enhanced NMR spectroscopy (SENS), which can increase the NMR signal
intensity at surfaces by an order of magnitude.[10−12] It has now
been applied to record one- and two-dimensional NMR spectra of many
systems.[13−23] Very recently, the introduction of highly efficient polarizing agents,[24−26] nonaqueous solvents,[27] and the optimization
of sample formulation allows enhancements on the order of 100 to be
achieved, which corresponds to a reduction in acquisition times by
a factor of 10 000.Establishing precise quantitative
internuclear distances using
solid-state NMR methods requires the accurate measurement of the signal
decay with respect to moderately long (tens of milliseconds) evolution
delays, and is therefore only reliable with high signal-to-noise ratios.
Here we determine the three-dimensional structure of an organometallic
complex supported on an amorphous silica surface. This is achieved
through the sensitivity gain provided by DNP SENS enabling the implementation
of a series of multidimensional NMR correlation experiments providing
structural restraints. The result, in combination with EXAFS, is a
detailed structure for the surface complex, determined with a precision
of 0.7 Å. We observe a single well-defined conformation. Furthermore,
the ligand is folded toward the surface in such a way as to include
interactions between the coordinated metal and the surface oxygen
atoms, thus also illustrating that the surface is not innocent in
such hybrid organosilica materials.
Experimental
Section
NMR Spectroscopy
DNP SENS experiments were performed
using a solid-state DNP-NMR spectrometer made by Bruker BioSpin. It
consists of a wide-bore 9.4 T magnet (ω1H/(2π)
= 400 MHz, ω29Si/(2π) = 79.5 MHz, ω13C/(2π) = 100.7 MHz, ω15N/(2π)
= 40.6 MHz) with a Bruker Avance III HD spectrometer console, and
equipped with a triple resonance 3.2 mm low-temperature CPMAS probe
used in the 1H–13C–15N or 1H–29Si–15N configurations
with the proper insert. DNP is achieved by irradiating the sample
with microwaves at a frequency of 263 GHz which transfers polarization
to the 1H nuclei via the cross-effect.[28,29] The microwaves are generated by a gyrotron and delivered to the
sample by a corrugated waveguide with ≈22 W of power reaching
the sample.[30] The microwave power was optimized
so as to obtain maximum enhancement for each sample. Sapphire rotors
(with zirconia caps) were used for optimal microwave penetration.
Rotors are sealed with a Teflon insert to prevent loss of solvent
during the measurements.The REDOR DNP SENS data were acquired
with a MAS spinning frequency of 8.0 kHz and sample temperature of
approximately 110 K. SPINAL64 1H heteronuclear decoupling
was used with 100 kHz 1H nutation frequencies.[31]Experimental details for 13C-{15N} REDOR
experiments on N1-labeled materials can be found Table S3. Tables S4 and S5 lay out experimental parameters for 29Si-{15N} REDOR experiments on A-N and B-N materials, respectively. Selected REDOR experiments
were performed 3 times to establish the reproducibility of 29Si-{15N} REDOR with a long dephasing time: twice with
the same packed rotors a few months apart (rotors were kept in a −20
°C freezer) and a third time with a freshly prepared sample.
Experimental details for 13C-{15N} REDOR and 29Si-{15N} REDOR on N2-labeled materials
are given in Table S6. Note that, for all
experiments, the polarization delay was set to 1.3 TB,
where TB is the 1HDNP build-up time measured
with a 1H saturation–recovery experiment.All experimental details for DNP SENS spectroscopy are provided
in the SI.
Extended X-ray Absorption
Fine Structure (EXAFS)
Measurements
were carried out at the Pt L3 edge at the SuperXAS beamline
at SLS (PSI, Villigen, Switzerland). The storage ring was operated
at 2.4 GeV in top-up mode with a ring current of around 400 mA. The
incident photon beam provided by a 2.9 T super bend magnet source
was selected by a Si (111) quick-EXAFS monochromator and the rejection
of higher harmonics and focusing were achieved by a rhodium-coated
collimating mirror at 2.8 mrad and a rhodium-coated torroidal mirror
at 2.8 mrad. The beam size on the sample was 100 × 100 μm2. During the measurements, the monochromator was rotating
with 10 Hz frequency in 2° angular range, and X-ray absorption
spectra were collected in transmission mode using ionization chambers
specially developed for quick data collection with 1 MHz frequency.[32] The beamline energy was calibrated with Pt reference
foil to the Pt L3-edge position at 11 564.0 eV.
To avoid contact with air all samples were sealed in a glovebox. Each
sample pellet (with optimized thickness for transmission detection)
was placed in two aluminized plastic bags (polyaniline (15 μm),
polyethylene (15 μm), Al (12 μm), polyethylene (75 μm)
from Gruber-Folien GmbH & Co. KG, Straubing, Germany) using an
impulse sealer inside a glovebox; one sealing layer was removed immediately
before the measurements.[33] Data were analyzed
by standard procedures using the Ifeffit program package.[34,35]
Computation for the Structure Determination Procedure
Calculations
were performed using MathWorks Matlab software (versions
R2014B or R2016A). The processed TopSpin NMR data were imported into
MatLab with the ReadBruker2D script developed by the National Magnetic
Resonance Facility at Madison (NMRFAM) of the University of Wisconsin—Madison,
published under the GNU General Public License v3. Deconvolution was
performed using the peakfit v2.0 MatLab script available on the MathWorks
File Exchange platform under BSD license.
Computational Modeling
under Density Functional Theory
All DFT modeling was performed
with the Amsterdam Density Functional
(ADF) software suite, version 2014.10.[36,37] The experimentally
determined structure of precatalyst A was anchored on
the realistic amorphous silica surface model suggested previously
by Ugliengo et al.[38] To roughly approximate
the degree of surface hydroxylation and the desired Si–Si distance
of ca. 4.5 Å, the surface model having 5.4 OH nm–2 was chosen (coordinates provided in SI). Due to the size of the fragments anchored on the silica surface
model, periodic codes were not chosen as it was seen that prohibitively
large unit cell volumes (ca. 9000 Å3) would be required
to ensure no overlap between these fragments in adjacent cells. As
such, a discrete silica model cluster was selected having a diameter
of roughly 10 Å, to which A was then anchored. All
dangling oxygen atoms were terminated with hydrogen atoms, leading
to the starting cluster pictured in Figure S12, with the coordinates being provided in the SI. While efforts were made to ensure that the geometry of
the individual components (A and TMS) matched with that
determined from the experimental NMR data, due to the nature of the
amorphous silica surface model, there was a small difference in the
relative orientation between A and the TMS fragment.In all cases, DFT calculations were performed at the generalized
gradient approximation (GGA) level of theory using the exchange-correlation
functional of Perdew, Burke, and Ernzerhof (PBE).[39,40] Dispersion effects were included by the three parameter correction
presented by Grimme and co-workers.[41] Relativistic
effects were included at the scalar level during all computations
under the zeroth-order regular approximation (ZORA).[42−44] Due to the large nature of the cluster, the geometry optimization
portion of the calculation used frozen core basis sets (except hydrogen)
which were triple-ζ in the valence region (“TZP”
according to the ADF naming scheme). This was specified by setting
the parameter “core” equal to “medium”
in the input file, which translates into the following: C (1s frozen),
O (1s frozen), N (1s frozen), Si (up to 2p frozen), Cl (up to 2p frozen).
Effects due to solvation by 1,1,2,2-tetrachloroethane were included
using the conductor-like screening model (COSMO)[45,46] by using the following string in the “Solvation” block
of the input file: “Solv Eps = 8.42 Rad = 3.15”. The
final optimized geometry is provided in Figure S13 (coordinates given in separate file of the SI), and a comparison between the final DFT-optimized
geometry with that determined experimentally is given in Figure S14.
Synthesis of the Materials
All the details regarding
materials synthesis are given in the SI.
Synthesis of the Polarizing Agent
TEKPol2 was provided
by Prof. Paul Tordo and Dr. Olivier Ouari (Aix-Marseille University)
and prepared according to the synthesis previously reported.[26]
Results and Discussion
The surface
Pt-complex B studied here (Figure ) was used as a representative
surface site. B belongs to a broad family of metal-based
hybrid catalytic materials where metal–surface interactions
are thought to be important for function.[6−9] The precursor A (Figure ) is an example of
a supported ligand, closely related to ionic liquid phases (SILP),
which is a class of systems attracting large current interest.[47,48]A was synthesized via a sol–gel method in the
presence of a structure directing agent[49] to obtain a random distribution of organic units within the hexagonal
arrangement of cylindrical pores in the material.[50] Post modification of A with (CD3)3SiCl (vide infra) and derivatization
of the imidazolium unit with Pt(II) yields B, see Supporting Information. Both materials have been
synthesized with 15N-labels at two different positions: A/B-N represents material A/B with 15N-labeling at N1, whereas A/B-N is A or B with 15N-labeling at site N2. The concentration of active
surface species is about 0.2 nm–2 for the materials
studied here.
Figure 1
Chemical structure and NMR signal assignments. Left: the
chemical
structure of material A together with the 13C and 29Si CPMAS DNP SENS spectra for A-N. Right: the same for material B. Symbol * denotes spinning side bands, and § denotes pentachloroethane
impurity found in commercial 1,1,2,2 tetra-chloroethane used as the
impregnating solvent (see Supporting Information Figure S7 for details). For the 29Si spectra, the
deconvolution of the SiQ4/SiQ4′ peaks
is shown, where the component Gaussian peaks are drawn with solid
green lines and the sum is drawn with a dashed red line.
Chemical structure and NMR signal assignments. Left: the
chemical
structure of material A together with the 13C and 29Si CPMAS DNP SENS spectra for A-N. Right: the same for material B. Symbol * denotes spinning side bands, and § denotes pentachloroethane
impurity found in commercial 1,1,2,2 tetra-chloroethane used as the
impregnating solvent (see Supporting Information Figure S7 for details). For the 29Si spectra, the
deconvolution of the SiQ4/SiQ4′ peaks
is shown, where the component Gaussian peaks are drawn with solid
green lines and the sum is drawn with a dashed red line.To obtain a signal-to-noise ratio that is as high
as possible and
thus precise quantitative information on the sample from solid-state
NMR, sample preparation for DNP must be done carefully. Sample formulation
was optimized to yield the highest sensitivity in DNP SENS experiments.
Samples were prepared by impregnating 15 mg of the powdered material
with 17 μL of a 16 mM solution of TEKPol2[26] in 1,1,2,2-tetrachloroethane (TCE),[27] and then packed into a 3.2 mm sapphire rotor sealed with
a Teflon insert and a zirconia cap. TEKPol2 is the best performing
polarizing agent reported to date in nonaqueous solvents at 9.4 T
and around 110 K.[26] DNP SENS enhancements
are linked to 1H spin–lattice relaxation times,
and surface passivating groups containing methyl moieties can lead
to rapid 1H spin–lattice relaxation and therefore
poor signal enhancements. The materials used here were thus passivated
with deuterated trimethysilyl group (TMS-d9) since deuteration yields long relaxation times and concomitant
high enhancements.[51] Finally, samples were
degassed to reduce relaxation due to dissolved O2.[52] With this protocol, the enhancement of the solvent
was εH = 213 for A and εH = 200 for B, which is the highest value obtained so
far for an impregnated materials sample, and which enables experiments
that were not possible before.Figure shows the
resulting 13C and 29SiDNP SENS cross-polarization
magic angle spinning (CPMAS) NMR spectra for A-N. The 13C NMR spectrum contains sufficiently
well-resolved signals to assign the three alkyl carbons, and the TMS
groups. Similarly, SiTMS and SiT3 can be easily
assigned in the 29Si NMR spectra. Discrimination between
SiQ4 and SiQ4′ signals is possible by
deconvolution of the broad Q-site peak and by assignment of the two
overlapping signals with a DNP SENS 29Si–29Si refocused two-dimensional INADEQUATE at natural isotopic abundance
(Figure S1).[53] The spectra of B (Figure ) are similar to those of A,
with an extra 13C signal at 173 ppm, which was assigned
to the C6 carbene signal using a 1H–15N–13C double CP DNP SENS experiment (Figure S7). Two-dimensional 1H–13C and 1H–29Si heteronuclear
correlation (HETCOR) experiments on A-N and B-N confirm the
assignment of the resolved resonances and provide access to the corresponding 1H chemical shifts (Figures S3–S6).Structural constraints were obtained from DNP SENS 13C-{15N} and 29Si-{15N} rotational
echo double resonance (REDOR) experiments[54,55] on the 15N-labeled samples. Modulation of the 13C and 29Si signal intensity as a function of the 15N recoupling time is characteristic of the distance between
isolated spin pairs. For each compound, 12 REDOR curves were measured.
Fits of the four C3–N and C2–N (i = 1 or 2) curves yielded distances in agreement with canonical
values for the covalent geometry (Figures S9 and S10). The remaining eight C1–N, SiTMS–N, SiQ4′–N, and SiT3–N (with i = 1 or 2) curves provided nontrivial structural information
used in the 3D structure determination.
Structure Determination
Procedure
The three-dimensional
structure of the organometallic complex was determined with a method
analogous to that routinely used for NMR protein structure determination,
where the covalent geometry is assumed and only the conformational
degrees of freedom are varied in order to find the best agreement
with the ensemble of experimental constraints. The whole surface-structure
determination process is outlined in Figure and detailed in the SI. For surface complexes, the number of conformational degrees
of freedom is often relatively limited, and we can envisage a systematic
search of all possible conformers. The conformational degrees of freedom
are the seven torsion angles (noted as α1, α2, α3, α4, α5, α6, and α7 in Figure ), and the distance between
the SiT3 and SiQ4′ atoms (dSiT3-SiQ4′). The rotation around α2 within the TMS group is set to an arbitrary value since a
low barrier to rotation is expected, and hence, a distribution of
conformers should be present (as for the methyl groups themselves).
Note that due to the nature of the silica surface, the distance dSiT3-SiQ4′ can only take discrete
values. The best fit structures determined in this way are shown in Figure , along with the
8 corresponding REDOR curves superimposed on the experimental data
for A (top) and B (bottom). To assess the
reliability of the structures, the reproducibility of the experimental
data was verified by performing the DNP SENS Si-{15N} REDOR
experiments for A-N and B-N in triplicate. All data were
consistent within error, and the ensemble of data was used for the
final structure determination.
Figure 2
Three-dimensional structure determination.
Possible 3D structures
for the system were generated in silico, as visualized
here with a simple “ball and stick” model, by rotating
atoms around the 4 axes (α1, α3,
α4, and α5) in 15° steps for
each of the four selected SiT3–SiQ4′ distances. Analytical REDOR curves were then calculated for each
structure and compared to the ensemble of experimental REDOR curves
to determine (i) the single 3D structure in best agreement with the
experimental data, and (ii) the distribution of conformers that agree
with the data to within the estimated experimental error.
Figure 3
Three-dimensional structures of materials A and B. The experimental DNP SENS REDOR data are shown
on the left
for A (above) and for the Pt-complex B (below)
with black dots for the 8 different spin pairs which generate nontrivial
constraints. The solid red and green lines are the calculated REDOR
curves for the structures in best agreement with the experimental
data. The internuclear distances for each spin pair in the structure
in best agreement with the experimental data are reported for each
curve. The corresponding best fit structures are shown on the right,
and coordinates are given in the SI. The
dashed lines shown on the structures correspond to the REDOR constraints
used for structure determination.
Three-dimensional structure determination.
Possible 3D structures
for the system were generated in silico, as visualized
here with a simple “ball and stick” model, by rotating
atoms around the 4 axes (α1, α3,
α4, and α5) in 15° steps for
each of the four selected SiT3–SiQ4′ distances. Analytical REDOR curves were then calculated for each
structure and compared to the ensemble of experimental REDOR curves
to determine (i) the single 3D structure in best agreement with the
experimental data, and (ii) the distribution of conformers that agree
with the data to within the estimated experimental error.Three-dimensional structures of materials A and B. The experimental DNP SENS REDOR data are shown
on the left
for A (above) and for the Pt-complex B (below)
with black dots for the 8 different spin pairs which generate nontrivial
constraints. The solid red and green lines are the calculated REDOR
curves for the structures in best agreement with the experimental
data. The internuclear distances for each spin pair in the structure
in best agreement with the experimental data are reported for each
curve. The corresponding best fit structures are shown on the right,
and coordinates are given in the SI. The
dashed lines shown on the structures correspond to the REDOR constraints
used for structure determination.Since we do not have any experimental NMR constraints on
the torsion
angle around the N1–C3 axis (α6), this orientation was determined using the Pt–O distance
obtained from EXAFS analysis of B which, depending on
the model used, suggests a Pt–O distance of approximately 2.68
Å (Figure S16 and Table S8 of the SI are providing details of the EXAFS data
analysis). The structure therefore strongly suggests the presence
of stabilizing noncovalent interactions between Pt and the oxygen
atom of the trimethylsiloxy group. The analysis of the EXAFS data
also provided the Pt–C and Pt–Cl distances which are
consistent with values obtained from the CSD. The same α6 value was used for A for display purposes.
Structure Verification with a DFT Computational Approach
A density functional theory (DFT) geometry optimization, starting
from the experimentally determined structure of A, finds
the experimentally determined structure is largely retained (Figure S14 compares the experimentally determined
structure and the DFT optimized one), increasing confidence in the
result, with an RMSD between the experimentally determined and the
DFT optimized structure of only 0.69 Å (i.e., within our stated
uncertainty). Furthermore, a calculation of the NMR chemical shift
was performed. The agreement between the calculated and experimental
chemical shifts is reasonable.
Definition of an Ensemble
of Conformation within Experimental
Error
Cross-validation was used to estimate the uncertainty
on the final structure. Figure shows the ensemble of structures for material B that are within the uncertainty of the measurements. Note that no
structures were found for B which are compatible with
the shortest dSiT3-SiQ4′ distance of 3.17 Å. For each of the values of dSiT3-SiQ4′, the structures remain otherwise
qualitatively very similar; i.e., the key features of the structures
do not actually change much with variations in dSiT3-SiQ4′, and so the choice of the silica surface
model does not appear to be critically important in determining the
structure. As shown in Figure , the distribution of possible structures is small. The RMSD
(including the non-H atoms in the tether and the two nitrogen atoms)
among of the ensemble is 0.62 Å for dSiT3-SiQ4′ = 4.50 Å, 0.71 Å for dSiT3-SiQ4′ = 5.59, and 0.70 Å for dSiT3-SiQ4′ = 5.83 Å, indicating that the structures are well-constrained
by the data.
Figure 4
Ensemble of conformers for the Pt-complex B. There
are 14 structures of B with dSiT3-SiQ4′ = 4.50 Å, 25 with dSiT3-SiQ4′ = 5.59 Å, and 23 with dSiT3-SiQ4′ = 5.83 Å shown. The RMSD among the ensemble is 0.62 Å
for dSiT3-SiQ4′ = 4.50 Å,
0.71 Å for dSiT3-SiQ4′ = 5.59 Å, and 0.70 Å for dSiT3-SiQ4′ = 5.83 Å. The structures are superimposed by aligning SiT3, SiQ4′, and O.
Ensemble of conformers for the Pt-complex B. There
are 14 structures of B with dSiT3-SiQ4′ = 4.50 Å, 25 with dSiT3-SiQ4′ = 5.59 Å, and 23 with dSiT3-SiQ4′ = 5.83 Å shown. The RMSD among the ensemble is 0.62 Å
for dSiT3-SiQ4′ = 4.50 Å,
0.71 Å for dSiT3-SiQ4′ = 5.59 Å, and 0.70 Å for dSiT3-SiQ4′ = 5.83 Å. The structures are superimposed by aligning SiT3, SiQ4′, and O.In these structures we observe first that the complex adopts
a
single well-defined conformation on the surface, and that the flexible
tether allows the organic moieties to fold toward the silica surface,
suggesting stabilizing interactions between the silica surface and
the aromatic groups. The N1 and N2 distances
to the surface (defined as the plane perpendicular to the plane spanned
by the SiT3–C1 vector) are 3.64 and 3.82
Å in B (whereas the van der Waals radius would be
1.50 Å and the distances in a fully extended conformation perpendicular
to the surface would be 4.16 and 6.16 Å).Importantly,
our results do allow for the possibility of a distribution
of structures, and yet, interestingly, as seen in Figure , for all the different values
of dSiT3-SiQ4′, the conformation
of the organic fragment in B determined experimentally
is well-defined and very similar: folded toward the surface, with
a structure such that the C–Pt–O interaction is roughly
constant.The structure ensemble has also been investigated
for material A and the ensemble of conformers provided
in Figure S34. We also found that the organic
fragment in A is well-defined.
Conclusion
In summary, using dynamic nuclear polarization surface enhanced
multidimensional NMR methods, we have been able to obtain multiple
structural constraints that allow us, in combination with EXAFS, to
directly determine the three-dimensional structure of a surface species
with an average RMSD in the positions of the ligand of 0.71 Å.
The result shows a single well-defined structure, which is not significantly
disordered. Additionally, the ligand conformation is determined to
be folded toward the silica surface, with interactions between the
coordinated metal and surface oxygen sites, thus illustrating that
the surface is not innocent in such hybrid organosilica materials.
This information corroborates several previously published results,[6,7,50]which suggested that metal–surface
interactions existed and are important to stabilize active species
in immobilized catalysts. The approach developed here demonstrates
quantitatively the existence of such interactions on an immobilized
Pt–NHC surface species used as a prototypical surface site.
Surface-structure determination is expected to guide the future design
of immobilized catalysts, by directly exploiting interactions with
the support.
Authors: Anne Lesage; Moreno Lelli; David Gajan; Marc A Caporini; Veronika Vitzthum; Pascal Miéville; Johan Alauzun; Arthur Roussey; Chloé Thieuleux; Ahmad Mehdi; Geoffrey Bodenhausen; Christophe Copéret; Lyndon Emsley Journal: J Am Chem Soc Date: 2010-11-10 Impact factor: 15.419
Authors: Thorsten Maly; Galia T Debelouchina; Vikram S Bajaj; Kan-Nian Hu; Chan-Gyu Joo; Melody L Mak-Jurkauskas; Jagadishwar R Sirigiri; Patrick C A van der Wel; Judith Herzfeld; Richard J Temkin; Robert G Griffin Journal: J Chem Phys Date: 2008-02-07 Impact factor: 3.488
Authors: Sachin R Chaudhari; Dorothea Wisser; Arthur C Pinon; Pierrick Berruyer; David Gajan; Paul Tordo; Olivier Ouari; Christian Reiter; Frank Engelke; Christophe Copéret; Moreno Lelli; Anne Lesage; Lyndon Emsley Journal: J Am Chem Soc Date: 2017-07-27 Impact factor: 15.419