52 research outputs found
Giant edge state splitting at atomically precise zigzag edges
Zigzag edges of graphene nanostructures host localized electronic states that
are predicted to be spin-polarized. However, these edge states are highly
susceptible to edge roughness and interaction with a supporting substrate,
complicating the study of their intrinsic electronic and magnetic structure.
Here, we focus on atomically precise graphene nanoribbons whose two short
zigzag edges host exactly one localized electron each. Using the tip of a
scanning tunneling microscope, the graphene nanoribbons are transferred from
the metallic growth substrate onto insulating islands of NaCl in order to
decouple their electronic structure from the metal. The absence of charge
transfer and hybridization with the substrate is confirmed by scanning
tunneling spectroscopy (STS), which reveals a pair of occupied / unoccupied
edge states. Their large energy splitting of 1.9 eV is in accordance with ab
initio many-body perturbation theory calculations and reflects the dominant
role of electron-electron interactions in these localized states.Comment: 14 pages, 4 figure
Electronic Band Dispersion of Graphene Nanoribbons via Fourier-Transformed Scanning Tunneling Spectroscopy
Atomically precise armchair graphene nanoribbons of width (7-AGNRs) are
investigated by scanning tunneling spectroscopy (STS) on Au(111). The analysis
of energy-dependent standing wave patterns of finite length ribbons allows, by
Fourier transformation, the direct extraction of the dispersion relation of
frontier electronic states. Aided by density functional theory calculations, we
assign the states to the valence band, the conduction band and the next empty
band of 7-AGNRs, determine effective masses of , and , respectively, and a band gap of eV.Comment: 20 pages, 7 figure
Advantageous nearsightedness of many-body perturbation theory contrasted with Kohn-Sham density functional theory
For properties of interacting electron systems, Kohn-Sham (KS) theory is often favored over many-body perturbation theory (MBPT), owing to its low computational cost. However, the exact KS potential can be challenging to approximate, for example in the presence of localized subsystems where the exact potential is known to exhibit pathological features such as spatial steps. By modeling two electrons, each localized in a distinct potential well, we illustrate that the step feature has no counterpart in MBPTs (including Hartree-Fock and GW) or hybrid methods involving Fock exchange because the spatial nonlocality of the self-energy renders such pathological behavior unnecessary. We present a quantitative illustration of the orbital-dependent nature of the nonlocal potential, and a numerical demonstration of Kohn's concept of the nearsightedness for self-energies, when two distant subsystems are combined, in contrast to the KS potential. These properties emphasize the value of self-energy-based approximations in developing future approaches within KS-like theories
High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation
Quantum chemical calculations on atomistic systems have evolved into a
standard approach to study molecular matter. These calculations often involve a
significant amount of manual input and expertise although most of this effort
could be automated, which would alleviate the need for expertise in software
and hardware accessibility. Here, we present the AutoRXN workflow, an automated
workflow for exploratory high-throughput lectronic structure calculations of
molecular systems, in which (i) density functional theory methods are exploited
to deliver minimum and transition-state structures and corresponding energies
and properties, (ii) coupled cluster calculations are then launched for
optimized structures to provide more accurate energy and property estimates,
and (iii) multi-reference diagnostics are evaluated to back check the coupled
cluster results and subject hem to automated multi-configurational calculations
for potential multi-configurational cases. All calculations are carried out in
a cloud environment and support massive computational campaigns. Key features
of all omponents of the AutoRXN workflow are autonomy, stability, and minimum
operator interference. We highlight the AutoRXN workflow at the example of an
autonomous reaction mechanism exploration of the mode of action of a
homogeneous catalyst for the asymmetric reduction of ketones.Comment: 29 pages, 11 figure
OPTIMADE, an API for exchanging materials data
The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification
Materials Cloud, a platform for open computational science
Materials Cloud is a platform designed to enable open and seamless sharing of
resources for computational science, driven by applications in materials
modelling. It hosts 1) archival and dissemination services for raw and curated
data, together with their provenance graph, 2) modelling services and virtual
machines, 3) tools for data analytics, and pre-/post-processing, and 4)
educational materials. Data is citable and archived persistently, providing a
comprehensive embodiment of the FAIR principles that extends to computational
workflows. Materials Cloud leverages the AiiDA framework to record the
provenance of entire simulation pipelines (calculations performed, codes used,
data generated) in the form of graphs that allow to retrace and reproduce any
computed result. When an AiiDA database is shared on Materials Cloud, peers can
browse the interconnected record of simulations, download individual files or
the full database, and start their research from the results of the original
authors. The infrastructure is agnostic to the specific simulation codes used
and can support diverse applications in computational science that transcend
its initial materials domain.Comment: 19 pages, 8 figure
On-surface synthesis of graphene nanoribbons with zigzag edge topology
Graphene-based nanostructures exhibit a vast range of exciting electronic
properties that are absent in extended graphene. For example, quantum
confinement in carbon nanotubes and armchair graphene nanoribbons (AGNRs) leads
to the opening of substantial electronic band gaps that are directly linked to
their structural boundary conditions. Even more intriguing are nanostructures
with zigzag edges, which are expected to host spin-polarized electronic edge
states and can thus serve as key elements for graphene-based spintronics. The
most prominent example is zigzag graphene nanoribbons (ZGNRs) for which the
edge states are predicted to couple ferromagnetically along the edge and
antiferromagnetically between them. So far, a direct observation of the
spin-polarized edge states for specifically designed and controlled zigzag edge
topologies has not been achieved. This is mainly due to the limited precision
of current top-down approaches, which results in poorly defined edge
structures. Bottom-up fabrication approaches, on the other hand, were so far
only successfully applied to the growth of AGNRs and related structures. Here,
we describe the successful bottom-up synthesis of ZGNRs, which are fabricated
by the surface-assisted colligation and cyclodehydrogenation of specifically
designed precursor monomers including carbon groups that yield atomically
precise zigzag edges. Using scanning tunnelling spectroscopy we prove the
existence of edge-localized states with large energy splittings. We expect that
the availability of ZGNRs will finally allow the characterization of their
predicted spin-related properties such as spin confinement and filtering, and
ultimately add the spin degree of freedom to graphene-based circuitry.Comment: 15 pages, 4 figure
OPTIMADE, an API for exchanging materials data.
The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification
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