Zsuzsanna Koczor-Benda1,2, Philippe Roelli3, Christophe Galland4, Edina Rosta1,2. 1. Department of Physics and Astronomy, University College London, London, WC1E 6BT, United Kingdom. 2. Department of Chemistry, King's College London, London, SE1 1DB, United Kingdom. 3. Nano-Optics Group, CIC nanoGUNE BRTA, 20018 San Sebastián, Spain. 4. Institute of Physics, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.
Abstract
We present Molecular Vibration Explorer, a freely accessible online database and interactive tool for exploring vibrational spectra and tensorial light-vibration coupling strengths of a large collection of thiolated molecules. The "Gold" version of the database gathers the results from density functional theory calculations on 2800 commercially available thiol compounds linked to a gold atom, with the main motivation to screen the best molecules for THz and mid-infrared to visible upconversion. Additionally, the "Thiol" version of the database contains results for 1900 unbound thiolated compounds. They both provide access to a comprehensive set of computed spectroscopic parameters for all vibrational modes of all molecules in the database. The user can simultaneously investigate infrared absorption, Raman scattering, and vibrational sum- and difference-frequency generation cross sections. Molecules can be screened for various parameters in custom frequency ranges, such as a large Raman cross-section under a specific molecular orientation, or a large orientation-averaged sum-frequency generation (SFG) efficiency. The user can select polarization vectors for the electromagnetic fields, set the orientation of the molecule, and customize parameters for plotting the corresponding IR, Raman, and sum-frequency spectra. We illustrate the capabilities of this tool with selected applications in the field of surface-enhanced spectroscopy.
We present Molecular Vibration Explorer, a freely accessible online database and interactive tool for exploring vibrational spectra and tensorial light-vibration coupling strengths of a large collection of thiolated molecules. The "Gold" version of the database gathers the results from density functional theory calculations on 2800 commercially available thiol compounds linked to a gold atom, with the main motivation to screen the best molecules for THz and mid-infrared to visible upconversion. Additionally, the "Thiol" version of the database contains results for 1900 unbound thiolated compounds. They both provide access to a comprehensive set of computed spectroscopic parameters for all vibrational modes of all molecules in the database. The user can simultaneously investigate infrared absorption, Raman scattering, and vibrational sum- and difference-frequency generation cross sections. Molecules can be screened for various parameters in custom frequency ranges, such as a large Raman cross-section under a specific molecular orientation, or a large orientation-averaged sum-frequency generation (SFG) efficiency. The user can select polarization vectors for the electromagnetic fields, set the orientation of the molecule, and customize parameters for plotting the corresponding IR, Raman, and sum-frequency spectra. We illustrate the capabilities of this tool with selected applications in the field of surface-enhanced spectroscopy.
Infrared
(IR) absorption and Raman scattering spectroscopy constitute
the most informative nondestructive optical methods to obtain fingerprints
of molecular species. While both signals are intrinsically too weak
to allow detection of single molecules or molecular monolayers, surface-enhanced
IR and Raman spectroscopy (SEIRA and SERS, respectively) circumvent
this limitation by leveraging a combination of chemical and electromagnetic
(plasmonic) enhancement factors. The former describe the effects of
orbital modifications and charge transfer on IR and Raman activities
when a molecule binds to a metal (most often gold, silver, copper,
etc.). The latter results from the enhanced local fields provided
by localized surface plasmon resonances supported by metallic nanostructures.
Over the years, the power of SEIRA and SERS for molecular spectroscopy
has been firmly established, with applications extending beyond fundamental
research into biosensing and security.[1−3] IR absorption and Raman
scattering can also be leveraged together in a process called vibrational
sum-frequency generation,[4] which has proven
useful for time-resolved studies of vibrational properties and dynamics
of molecules at interfaces,[5−7] such as in the context of catalysis.
Moreover, recent proposals and experiments inspired by the field of
cavity optomechanics[8,9] have translated this technique
into a potential technology for frequency upconversion from the THz
and IR domain into the visible domain.[4,10] Another related
and emerging research field is that of vibrational polaritons,[11−13] which aims in particular at remotely controlling chemical properties
and reaction rates through strong coupling of vibrational modes with
electromagnetic vacuum fluctuations.Online tools such as IRCalc[14] provide
valuable insights into molecular vibrations, IR and Raman activity
at the empirical or semiempirical level, for mainly educational purposes.Here, we present an open source online platform called Molecular
Vibration Explorer (MVE).[15] This
platform is an interactive molecular library for the design of cutting
edge spectroscopic applications, allowing to explore vibrational spectra
and light-vibration coupling for integration in plasmonic antennas
and cavities. With a database of thousands of commercially available
compounds and easy-to-navigate online tools, our work paves the way
for fast and uncomplicated molecular design. Indeed, many groups developing
these experimental techniques lack hardware, software, time or workforce
to search for molecules with optimal properties for a specific goal,
including IR vibrational strong coupling, frequency upconversion,
Raman tag, and so on.Our database is based on accurate DFT
calculations of molecular
vibrational properties that are made openly accessible and is complemented
by comprehensive numerical tools for easy exploration, analysis and
selection of molecules. Among the main features available on our platform
are the following:For each
molecule, orientation-averaged and orientation-dependent
IR, Raman, and frequency conversion (SFG) spectra.Interactive sorting and screening of the entire database
over user-defined frequency ranges according to a chosen parameter,
such as IR or Raman cross-section.3D
interactive plots of molecules and their vibrational
modes, dynamically linked to the orientation-dependent values of IR
and Raman cross sections.Identification
of chemically similar molecules within
the database as well as from a list of known self-assembling molecules.In the following, we first describe the
theory and methodology
behind the toolbox (sections 2.1 and 2.2), before presenting its main functionalities
in section . We
conclude by discussing examples of potential applications in section .
Methods
Definitions
We calculate both orientation-averaged
(denoted by angle brackets) and orientation-specific intensities for
IR absorption, Raman scattering and frequency conversion (specifically,
SFG) processes. The IR absorption intensity (in [km mol–1] units) of vibrational mode m is defined aswhere IR the
field polarization vector of the IR beam, μ′ is the dipole derivative vector, and CA = 2.9254 × 103, assuming μ′ is given in atomic units [e-bohr·bohr–1·amu–1/2].The Raman
intensity (differential Raman cross-section) for Stokes bands is given
in [cm2·sr–1] unitswhere ν̅R and ν̅ are the wavenumbers
of the pump laser and
of the normal mode, respectively. The prefactor includes the effect
of thermal occupancy of the vibration at temperature T. The polarization vectors of the pump (in) and Raman scattered (out)
fields are given by R,in and R,out, and is the polarizability derivative
tensor.
If is given in [bohr4·amu–1] units and wavenumbers in [cm–1], the constant scaling factor is CR =
2.060 × 10–45.The SFG intensity is calculated
aswhere C = CACR. I measures the net increase in anti-Stokes
Raman intensity
due to IR pumping, hence the plus sign in the wavenumber dependent
factor and the omission of the Bose Einstein occupancy.Note
that when averaging over multiple orientations, the overlap
of the IR and Raman modes need to be considered for each orientation
individually, asNevertheless, analytic formulas
for calculating
the averages over all possible relative orientations of the molecule
and fields, considering all possible field polarization settings,
can be derived (cf. Supporting Information, section S1). For orientation-specific intensities, the angle brackets
in eqs –3 can be omitted.Apart from individual normal
mode intensities, the target properties A, R, and P defined below
can also be used for ranking the molecules of the database in a specific
frequency range.where M refers to
the set
of normal modes that have frequencies in the range defined by the
user. These properties are standardized as described in ref (16). A, R, and P can also be calculated using orientation-specific
intensities, this enables fast comparison of molecular performance
at different orientations.The vibrational spectra of each molecule
can be plotted as discrete
(stick) spectra or broadened spectra. In the latter case, a Lorentzian
broadening is applied to IR and Raman spectra, for which fwhmIR and fwhmR can be specified separately, and the
SFG spectrum inherits the line shape of the product of these two Lorentzians.
Computational Methods
The creation
of the database is described in ref (16). Currently, compounds containing thiols ensuring
strong affinity to gold surfaces are explored based on machine learning-predicted
and randomly selected molecules. The “Thiol” database
consists of unbound thiolated compounds, while the “Gold”
database simulates the immediate effects of linkage to the surface
by substituting the thiol hydrogen to a gold atom. While the “Gold”
database was specifically created for surface-enchanced applications,
the “Thiol” database can be used for modeling gas/solution
experiments (see, e.g., SI, Figure S5),
which are usually performed as a quick first check when screening
new molecules. Our databases can be easily extended to include additional
readily available compounds from tens of millions of commercially
available molecules (from databases such as eMolecules, MolPort, or Sigma-Aldrich). DFT
calculations are performed to determine molecular geometries and vibrational
properties at the B3LYP+D3/def2-SVP level using the Gaussian program
package. This level of modeling was shown to be sufficiently accurate
for both the “Thiol” and “Gold” databases
when determining the relative intensities of a set of test compounds
and simulating the finer details of vibrational spectra, by comparison
to solution phase Raman and SERS experiments, respectively.[16] See also an example in SI, Figure S5. Binding to the metal surface has been studied for
a couple of molecules like thiophenol previously. These include modeling
of gold clusters[17] or slabs[18] and give valuable information on the details
of vibrational spectra. According to our investigations (ref (16), SI, Figure S5), the “Gold” database gives a sufficiently
good match with SERS experiments to be used in an exploratory manner
for surface-enhanced applications. Analytic formulas for the orientation
averages of intensities were derived using Mathematica and are given in SI, section S1. MVE can be accessed via the Materials Cloud platform. The web application is created using Voila and is based on interactive Jupyter notebooks. Screenshots of the
web application pages are also shown in SI, section S2. Molecular similarity scores are generated using RDKit.
NGLView is used for the 3D visualization of molecules.
Results and Discussion
Functionalities
Exploring the Databases
The “Gold”
and “Thiol” databases can be explored separately, or
alternatively, specific molecules can be checked simultaneously in
the two databases by using the search tool described in section . The database
page allows for ranking molecules within the database and selecting
them for further analysis. The user may choose the target
property (A,R, or P) and set a frequency range of interest. A global frequency
scaling factor can be applied to improve agreement between DFT calculated
and experimentally measured frequencies. The respective directions
of the field polarization vectors (IR, R,in, and R,out)
can be specified independently, among three possible orthogonal directions x, y, and z. Intensities
⟨IA⟩, ⟨IR⟩, and ⟨Ic⟩ have been precomputed
and stored for all possible combinations of field polarizations and
considering a random orientation of molecules. A temperature of 298.15
K and Raman laser wavelength of 785 nm were used for computing Raman
and conversion intensities. The distribution of the target property
across the entire database, for mode frequencies within the user-specified
range, is plotted as a histogram, and a table is generated below that
shows all molecules sorted according to decreasing value of the target.
Further properties of the molecules and their individual normal modes
can be explored by navigating the links displayed in the table, as
described below.
Molecular Properties
Upon clicking
on “Go to molecule page” next to a
particular molecule, the new page displays vibrational spectra and
other relevant molecular properties and enables a high level of customization.
In the tab labeled “Set molecule orientation” on the left, the molecular orientation can be modified at
will by specifying the rotational angles ϕ, θ, and ξ
with respect to the Cartesian coordinate system defined along the
possible polarization vectors. The resulting orientation is instantly
displayed on the 3D molecular viewer while the corresponding Raman,
IR, and SFG spectra are also updated. The spectra for the selected
orientation can be directly compared with those for the orientation
average by checking “Show full orientation average” in the “Set plotting parameters”
tab on the left. For Raman scattering and SFG the temperature and
laser wavelength can be set in the “Set experimental
parameters” tab, while the frequency range, scaling
factor, style of the spectrum (stick, broadened, stick+broadened)
and corresponding broadening parameters (fwhmIR, fwhmR) can all be tuned in the “Set plotting parameters” tab. Finally, field polarization directions can be specified
in the “Set field polarization” tab.In addition to optical properties, physical properties of the molecule
relevant to surface-enhanced spectroscopy are listed below the 3D
drawing. The length of the projection of the molecule along the z axis is referred to as “Layer height”. Indeed, it corresponds to the approximate thickness of
a molecular monolayer assuming binding through the thiol group onto
a flat gold surface spanning the x and y plane. Its geometrical projection on the flat gold surface is given
by “XY projection”. These properties
can be used for estimating how the enhancement factor of surface-enchanced
experiments is affected by the geometrical properties of the molecule,
as described in ref (16). Another feature that is especially useful for navigating the database
is the table of similar molecules that is displayed at the bottom
of the page. Molecules susceptible to form self-assembled monolayers
(SAMs) and similar to the chosen molecule are listed to help optimization
of surface-enhanced applications.
Properties
of Vibrational Modes
Upon clicking on “Check
normal modes”
next to a particular molecule, the user can explore all normal modes
of the selected molecule through 3D visualization. The dependence
of the IR, Raman, and conversion/SFG intensity of a specific normal
mode on molecular orientation is represented by a projection onto
the plane perpendicular to the axis of rotation. The direction of
the field polarization vectors of the IR and Raman (excitation and
scattered) beams can also be set on this page.
Searching the Database
MVE features
a SMILES-based search tool that operates with molecular similarity
scores. Potential hits and the most similar molecules are listed for
the “Thiol” and “Gold” databases, as well
as for the library of known SAMs. For molecules that are included
in both databases, the search tool provides a quick way to compare
properties of thiolated and gold-linked forms (see SI, section S3 for an example). This comparison can be used
for example to exploit the effects of surface linkage (chemical enhancement)
or conversely to select robust vibrational peaks, not affected by
a change in linkage.
Example Applications
Sum-frequency
generation (SFG) has proven to be a useful tool for a variety of investigations
in surface science.[5] The combined selection
rules of IR and Raman processes enable to optically study the symmetry
of crystalline structures,[19] to investigate
the bonding of molecules to metallic surfaces[20−22] and the orientation
of molecular layers on different substrates.[23,24] The experimental characterization of these molecules requires access
to the nonvanishing elements of the nonlinear polarizability tensor,
which can for certain molecules be addressed sequentially using different
polarization combinations. All these components can be extracted with
the help of our toolbox and can be used to reconstruct the IR, Raman,
and upconversion (SFG) spectra for all combinations of local electromagnetic
fields and orientation of the molecule. Figure illustrates different spectra obtained for
the NH2-BPhT molecule both for a specific orientation of
the molecule and for the orientation-averaged case. In this section
of the manuscript, the specific orientation will correspond to the
initial orientation of the “Gold” database’s
molecules in MVE: S–Au bond along the z-axis, while the polarization
of the three local electromagnetic fields (IR, Raman excitation, Raman
scattering), if not explicitly given in the text, will be chosen along z. This default configuration is expected to well approximate
most common situations in surface-enhanced studies.[25] One interesting feature for spectroscopy is that the more
constrained selection rules for SFG allow only a few vibrational modes
to feature sizable upconversion efficiency. This aspect can be leveraged
in experiments where the level of background arising from the substrates
or other molecules present in the vicinity might prevent detection
of the targeted molecules.
Figure 1
From top to bottom, numerical simulations of
IR absorption (red
line), Raman scattering (blue), and conversion (SFG, purple) spectra
of a NH2-BPhT molecule for a specific orientation. The
orientation averaged spectra is depicted with gray areas for each
spectrum. All local fields are chosen to be parallel to the z-axis.
From top to bottom, numerical simulations of
IR absorption (red
line), Raman scattering (blue), and conversion (SFG, purple) spectra
of a NH2-BPhT molecule for a specific orientation. The
orientation averaged spectra is depicted with gray areas for each
spectrum. All local fields are chosen to be parallel to the z-axis.In the situation where
the polarizations are defined by a plasmonic
nanostructure and a specific orientation of the molecule is expected,[4] the MVE toolbox permits to investigate the orientation
dependence of the IR absorption, Raman, and SFG signals. Figure illustrates, for
the case of cross-polarized local fields (IR field along y, Raman in/out fields along x), the changes in the
different processes’ magnitudes as a function of the molecule
orientation. As evidenced in the figure, even though the corresponding
absorption and Raman signatures look rather similar, the molecular
orientation dependence of SFG efficiency shows clearly distinct patterns
for different vibrational modes of NH2-BPhT. We note that
a cross-polarization configuration is not typical in doubly resonant
plasmonic cavities but could be achieved using specific antennas.[26] Thanks to the prediction of orientation dependence
the MVE toolbox may help to optically assess the orientation of self-assembled
monolayers within metallic structures[27] in a similar way as it could be determined in TERS experiments.[28,29] The MVE toolbox will also be useful in designing nanostructures
and molecular layers maximizing the conversion efficiency of the SFG
process for frequency conversion applications.[4,9]
Figure 2
From top
to bottom, numerical simulations of the dependence of
the IR absorption, Raman scattering, and SFG spectra on the orientation
of the molecule with respect to external local fields for the three
main upconversion-active modes of NH2-BPhT. In this figure,
local fields are chosen to be cross-polarized: IR field along y (gray arrow) and Raman in/out fields along x (red arrow).
From top
to bottom, numerical simulations of the dependence of
the IR absorption, Raman scattering, and SFG spectra on the orientation
of the molecule with respect to external local fields for the three
main upconversion-active modes of NH2-BPhT. In this figure,
local fields are chosen to be cross-polarized: IR field along y (gray arrow) and Raman in/out fields along x (red arrow).
Molecule Optimization
or Fingerprinting
Another opportunity offered by the MVE
database is to scrutinize
molecules similar to a reference molecule already controlled experimentally.
As demonstrated in Figure , a simple change in one termination of the BPhT molecule
can lead to significant changes in the respective magnitude of the
different SFG active modes. The toolbox therefore provides a way to
optimize upconversion efficiency by carefully designing the molecule
and could also be used reversely in order to experimentally differentiate
the upconverted signals from very similar molecules, changing only
by one termination.[30]
Figure 3
Averaged (gray area)
and orientation specific (purple line) conversion
spectra of BPhT (a), NH2-BPhT (b), Br-BPhT (c), and F-BPhT
(d).
Averaged (gray area)
and orientation specific (purple line) conversion
spectra of BPhT (a), NH2-BPhT (b), Br-BPhT (c), and F-BPhT
(d).
SERS
and Advanced IR Detection
One direct application of the MVE
database consists in exploring
possible molecules for improved SERS signals in applications such
as SERS tags[31,32] or fundamental studies of molecular
optomechanics.[8,33] As evidenced in Figure , there are numerous commercially
available molecules compatible with gold functionalization that would
reach levels of Raman activity comparable or higher than standard
compounds used in SERS experiments like BPhT. Additionally, filtering
the database on the region of interest for low-light IR detectors
at room temperature[9] (20–50 THz),
we can identify molecular vibrations with SFG coefficients orders
of magnitude larger than the molecule (BPhT) used in the recent surface-enhanced
upconversion experiments.[4,10]
Figure 4
Distribution of SFG coefficients
and Raman activities for all vibrational
modes of the “Gold” database lying in the 20–50
THz spectral range, identified in ref (9), for its interest in IR detector applications.
We highlight BPhT with a gray circle, the only molecule ever used
to date in a continuous wave SFG experiment.[4] Two other molecules with significantly higher calculated SFG efficiencies
are highlighted in yellow and green. Full names of the molecules are
given in SI, section S4.
Distribution of SFG coefficients
and Raman activities for all vibrational
modes of the “Gold” database lying in the 20–50
THz spectral range, identified in ref (9), for its interest in IR detector applications.
We highlight BPhT with a gray circle, the only molecule ever used
to date in a continuous wave SFG experiment.[4] Two other molecules with significantly higher calculated SFG efficiencies
are highlighted in yellow and green. Full names of the molecules are
given in SI, section S4.
IR Vibrational Strong Coupling
The MVE database also opens new routes to explore the regime of vibrational
strong coupling (VSC)[12] in systems containing
one or few molecules only. Recent studies of the coupling between
molecular vibrations and surface phonon–polaritons modes of
hBN have achieved this regime.[13] The narrow
range accessible with these phonon–polaritons modes (1400–1550
cm–1) requires very specific molecules to achieve
sufficiently strong coupling. MVE enables to quickly identify molecules (Figure ) with IR cross sections that are promising
for strong coupling applications. In addition, the database allows
to identify vibrational modes that would not only reach the IR vibrational
strong coupling regime but would simultaneously enable substantial
conversion of the generated phonons to the visible via molecular optomechanical
upconversion. The molecule used in ref (13) is illustrated on the same figure to highlight
the number of other molecular vibrations that would achieve similar
or better IR intensities while enabling more suitable or controlled
deposition, smaller footprint or higher compatibility with molecular
SFG experiments. The same approach could also be instrumental in the
design of the interaction between other surface modes like graphene
plasmons and vibrations.[36,37]
Figure 5
Distribution of SFG coefficients
and Raman activities for all vibrational
modes of the “Gold” database lying in the 1400–1550
cm–1 range that match surface phonon-polariton (SPhP)
modes of hexagonal boron nitride (hBN). We highlight with a gray circle
the molecule (CBP) experimentally used to achieve vibrational strong
coupling with an SPhP mode of hBN.[13] Two
other molecules with significantly higher calculated IR absorption
cross sections and SFG efficiencies are highlighted in yellow and
green. Full names of the molecules are given in SI, section S4.
Distribution of SFG coefficients
and Raman activities for all vibrational
modes of the “Gold” database lying in the 1400–1550
cm–1 range that match surface phonon-polariton (SPhP)
modes of hexagonal boron nitride (hBN). We highlight with a gray circle
the molecule (CBP) experimentally used to achieve vibrational strong
coupling with an SPhP mode of hBN.[13] Two
other molecules with significantly higher calculated IR absorption
cross sections and SFG efficiencies are highlighted in yellow and
green. Full names of the molecules are given in SI, section S4.
Molecule
Detection
One prospective
technological application of the database is related to the subwavelength
dimension of the newly demonstrated SFG devices.[4] In advanced designs, constituted of different subwavelength–frequency
upconverters, simultaneous detection at different frequencies would
be possible, akin to metapixel imaging systems realized with dielectric
nanostructures.[34] Such IR recognition devices
could be valuable for the detection of toxic substances. For example,
the VX nerve agent has different characteristic IR absorption lines[35] that could well be targeted by SFG nanodevices. Figure shows different
molecules extracted from the database that could efficiently detect
variations of IR absorption at the 490, 1067, and 1232 cm–1 characteristic lines of the VX nerve agent.
Figure 6
(a) Schematics of the
proposed detection scheme for substance identification.
From top to bottom, broadband infrared light is passing through the
substance to be identified,[34] after which
it is analyzed thanks to an upconversion layer containing molecules
with SFG active modes at matched frequencies, so that spectroscopy
is eventually performed using visible light detectors. (b) Example
of SFG active molecules identified in the database with vibrational
frequencies matching the main characteristic IR absorption lines of
the VX nerve agent. The top spectrum corresponds to the numerically
calculated absorption spectrum of the VX nerve agent (adapted from
ref (35)). Then, from
top to bottom, the conversion spectra correspond to the spectra extracted
from the MVE database for the compounds V, VI, and VII. Full name
of the molecules are given in SI, section S4.
(a) Schematics of the
proposed detection scheme for substance identification.
From top to bottom, broadband infrared light is passing through the
substance to be identified,[34] after which
it is analyzed thanks to an upconversion layer containing molecules
with SFG active modes at matched frequencies, so that spectroscopy
is eventually performed using visible light detectors. (b) Example
of SFG active molecules identified in the database with vibrational
frequencies matching the main characteristic IR absorption lines of
the VX nerve agent. The top spectrum corresponds to the numerically
calculated absorption spectrum of the VX nerve agent (adapted from
ref (35)). Then, from
top to bottom, the conversion spectra correspond to the spectra extracted
from the MVE database for the compounds V, VI, and VII. Full name
of the molecules are given in SI, section S4.
Conclusions
In conclusion, we presented the Molecular
Vibrational Explorer (hosted on the Materials Cloud open platform) that allows interactive access to a large database
of vibrational and spectroscopic properties for thousands of molecules.
The database targets surface-enhanced applications such as SERS, SEIRA,
and vibration-assisted frequency upconversion; it can also be expanded
in the future with more molecules. We illustrated the use of the Molecular
Vibrational Explorer in the optimization of molecules for a number
of applications including SERS tags, vibrational strong coupling,
and frequency upconversion for substance detection. We believe that
the Molecular Vibrational Explorer will foster progress and productivity
in a broad range of research fields related to molecular spectroscopy,
nano-optics, and surface science.
Authors: Daniel Rodrigo; Odeta Limaj; Davide Janner; Dordaneh Etezadi; F Javier García de Abajo; Valerio Pruneri; Hatice Altug Journal: Science Date: 2015-07-10 Impact factor: 47.728
Authors: Itai Epstein; David Alcaraz; Zhiqin Huang; Varun-Varma Pusapati; Jean-Paul Hugonin; Avinash Kumar; Xander M Deputy; Tymofiy Khodkov; Tatiana G Rappoport; Jin-Yong Hong; Nuno M R Peres; Jing Kong; David R Smith; Frank H L Koppens Journal: Science Date: 2020-06-12 Impact factor: 47.728