en:
The requirement of generating predictions that exactly fulfill the fundamental symmetry of the corresponding physical quantities has profoundly shaped the development of machine-learning models for physical simulations.In many cases, models are built using constrained mathematical forms that ensure that symmetries are enforced exactly. However, unconstrained models that do not obey rotational symmetries are often found to have competitive performance, and to be able to \emph{learn} to a high level of accuracy an approximate equivariant behavior with a simple data augmentation strategy.In this paper, we introduce rigorous metrics to measure the symmetry content of the learned representations in such models, and assess the accuracy by which the outputs fulfill the equivariant condition.We apply these metrics to two unconstrained, transformer-based models operating on decorated point clouds (a graph neural network for atomistic simulations and a PointNet-style architecture for particle physics) to investigate how symmetry information is processed across architectural layers and is learned during training.Based on these insights, we establish a rigorous framework for diagnosing spectral failure modes in ML models. Enabled by this analysis, we demonstrate that one can achieve superior stability and accuracy by strategically injecting the minimum required inductive biases, preserving the high expressivity and scalability of unconstrained architectures while guaranteeing physical fidelity.

This record includes sofware and instructions on how to reproduce the main results of this manuscript.

en: How unconstrained machine-learning models learn physical symmetries

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

atomistic-simulations

display_name: atomistic-simulations

cscs

display_name: cscs

equivariance

display_name: equivariance

erc

display_name: erc

interatomic-potentials

display_name: interatomic-potentials

snsf

display_name: snsf


$oid: OBSOLETE

en:
The Density-Functional Toolkit (DFTK) is a recent plane-wave density-functional theory (DFT) code, written with a flexible architecture and in a high-level language to facilitate development of new methods and support fundamental mathematical research on DFT. DFTK has been instrumental in a good dozen of recent papers, and its core DFT routines are considered stable. So far a systematic precision benchmark against other codes and approaches had not yet been performed. In this work, we apply the verification protocol established by E. Bosoni et al. [Nat. Rev. Phys. 6, 45-58 (2024)] based on the AiiDA high-throughput engine, to validate the precision of DFTK against the existing all-electron and pseudopotential data. This record contains our results, as well as the scripts needed to reproduce them. Out of the 720 systems, DFTK achieves excellent agreement with the all-electron average (ε<0.06) on 223 systems and good-but-not-excellent agreement (0.06<=ε<0.2) on 371 systems. Comparing DFTK with ABINIT (ABINIT@PW|PseudoDojo-v0.5), the agreement is excellent on 697 systems and good-but-not-excellent on 14 systems; the agreement is bad (ε>=0.2) for Ne and I systems only, likely due to the corresponding pseudopotentials.

This agreement is made possible by a custom "v0.5.1-fix" of PseudoDojo:

The pseudopotential files are truncated at rcut=5.99 bohr.

The UPF files in PseudoDojo v0.5 for Bi, Pb, Po, Rn, Te, Tl were missing the third projector and had to be re-generated with a patched ONCVPSP.

The new pseudopotentials in PseudoDojo v0.5 do not have a recommended Ecut, so we used the recommended Ecut of PseudoDojo v0.4.1 + 20 Ha.

We acknowledge and thank Yihan Wu for the initial versions of aiida-dftk and the DFTK support in aiida-common-workflows.

en: Precision verification results data for DFTK@PW|PseudoDojo-v0.5.1-fix

materialscloud

approval_status: approved

en: Materials Cloud

de: Materials Cloud

fr: Materials Cloud

it: Materials Cloud

political_level: other

state: active

type: organization

psi

capacity: public

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

automation

display_name: automation

dft

display_name: dft

equation-of-state

display_name: equation-of-state

pseudopotentials

display_name: pseudopotentials

verification

display_name: verification


en: Chromium oxide (Cr2O3) is widely considered a p-type transparent conducting oxide despite ongoing debate regarding its intrinsic transport character. Here, we resolve this question by computing phonon-limited electron and hole mobilities using the Boltzmann transport equation. We find that electron mobility systematically exceeds hole mobility over a wide temperature range, demonstrating that Cr2O3 is intrinsically n-type. Analysis of scattering mechanisms reveals that scattering with phonons affect electrons and holes similarly, and that the mobility asymmetry originates from the electronic structure, namely the larger effective mass and multi-valley character of the valence band. These results indicate that the commonly observed p-type behavior is likely extrinsic. The intrinsic n-type character, combined with moderate hole mobility, enables ambipolar transport and revises the role of Cr2O3 in transparent electronics. Additionally, the alignment of electrical and magnetic easy axes reveals coupling between charge transport and antiferromagnetic order, opening opportunities for magnetoelectric and spintronic devices

en: Challenging the p-type paradigm: intrinsic n-type mobility in antiferromagnetic Cr2O3

carrier-mobility

display_name: carrier-mobility

magnetism

display_name: magnetism

transparent-conducting-oxides

display_name: transparent-conducting-oxides


en: We perform a first-principles high-throughput screening of the mechanical properties of phonon-mediated superconductors derived from the recent experimentally synthesized superconducting materials database PRX Energy \textbf{4}, 033012 (2025). We develop the aiida-mechanical workflow which combines first-principles calculations of elastic constants and generalized stacking fault energies, to assess the ductility of superconducting candidates. Starting from 250 materials identified with promising superconducting critical temperatures, we computed their elastic tensors to evaluate the bulk modulus, shear modulus, Pugh's ratio, and Pettifor's ratio. To further characterize their plastic deformation behavior, we calculated the stacking fault energy and surface energy for selected materials and slip directions, allowing the estimation of Rice's ratio and related ductility indicators. We find that several new materials simultaneously exhibit high Tc and ductility, including HfPd2Al, TiRuSb, and ZrNi2Ga. This dataset provides the complete computational provenance. Specifically, it contains the fully relaxed crystal structures, Quantum ESPRESSO calculations for all elastic tensor (finite-displacement and Born approximation methodologies) and stacking fault energy workflows, as well as k-point and supercell convergence tests. This work offers a quantitative mapping of mechanical performance across a wide range of superconductors and provides a valuable reference for finding new practical superconducting materials.

en: In search of novel ductile superconductors

ductility

display_name: ductility

elastic-tensor

display_name: elastic-tensor

generalized-stacking-fault-energy

display_name: generalized-stacking-fault-energy

pettifors-ratio

display_name: pettifors-ratio

pughs-ratio

display_name: pughs-ratio

rices-ratio

display_name: rices-ratio

superconductor

display_name: superconductor

surface-energy

display_name: surface-energy


en:
Semilocal density functionals such as the Perdew-Burke-Ernzerhof (PBE) functional notoriously underestimate experimental band gaps. Hybrid functionals address this “band gap problem” by admixing a fraction of Fock exchange to semilocal exchange. The optimal mixing parameter depends on the specific material and can be identified as the inverse dielectric constant (dielectric-dependent hybrid functional, DDH). Here, we show that dielectric constants obtained using the r²SCAN meta-GGA functional are significantly more accurate than dielectric constants obtained using the semilocal PBE functional. We propose the DD-r²SCANH functional, a dielectric-dependent hybrid functional based on r²SCAN. DD-r²SCANH can outperform the standard PBE-based DDH in terms of band gaps and other electronic structure properties. Particularly impressive improvements are obtained for narrow-gap semiconductors such as Ge and InAs, where PBE wrongly predicts a metallic phase, but r²SCAN opens a band gap.

Here, we provide VASP input files for DD-r²SCANH, and further we provide the crystal structures used for our band gap benchmark in POSCAR format.

en: Dielectric-dependent hybrid functional from meta-GGA

density-functional-theory

display_name: density-functional-theory

electronic-bands

display_name: electronic-bands

electronic-structure

display_name: electronic-structure


en: The implementation of ultrasoft pseudopotentials into time-dependent density-functional perturbation theory is detailed for both the Sternheimer approach and the Liouville-Lanczos (LL) method, and equations are presented in the scalar relativistic approximation for periodic solids with finite momentum transfer q. The LL method is applied to calculations of the electron energy loss (EEL) spectrum of face-centered cubic bulk Au both at vanishing and finite q. Our study reveals the richness of the physics underlying the various contributions to the density fluctuation in gold. In particular, our calculations suggest the existence in gold of two quasiseparate 5d and 6s electron gasses, each one oscillating with its own frequency at, respectively, 5.1 eV and 10.2 eV. We find that the contribution near 2.2 eV comes from 5d to 6s interband transitions modified by the intraband contribution to the real part of the dielectric function, which we call a mixed excitation.

en: Electron energy loss spectroscopy of bulk gold with ultrasoft pseudopotentials and the Liouville-Lanczos method

dft

display_name: dft

eels

display_name: eels

eu-max

display_name: eu-max

genci

display_name: genci

gold

display_name: gold

interband-transitions

display_name: interband-transitions

intraband-transitions

display_name: intraband-transitions

liouville-lanczos-method

display_name: liouville-lanczos-method

loss-function

display_name: loss-function

marvelosp

display_name: marvelosp

mixed-excitations

display_name: mixed-excitations

plasmons

display_name: plasmons

quantum-espresso

display_name: quantum-espresso

sternheimer-equations

display_name: sternheimer-equations

tddft

display_name: tddft


en: This repository contains the scripts that were used to run the calculations that present a new biasing technique, the Adaptive Topography of Landscape for Accelerated Sampling (ATLAS). The techinque is implemented in plumed-2.0 and the input file are included in the repository, as well as a few scripts to postprocess the calculations and reproduce the plots presented in the paper

en: Global free-energy landscapes as a smoothly joined collection of local maps

enhanced-sampling

display_name: enhanced-sampling

epfl

display_name: epfl

erc

display_name: erc

machine-learning

display_name: machine-learning

molecular-dynamics

display_name: molecular-dynamics

snsf

display_name: snsf


en: We develop a scheme for finite-size corrections of vertical transition energies and single-particle energy levels involving defect states with built-in ionic polarization in supercell calculations.The method accounts on an equal footing for the screening of the electrons and of the ionic polarization charge arising from the lattice distortions. We demonstrate the accuracy of our corrections for various defects in MgO and in water by comparing with the dilute limit achieved through the scaling of the system size. The general validity of our formulation is also confirmed through a sum rule that connects vertical transition energies with formation energies of structurally relaxed defects.

en: Finite-size corrections of defect energy levels involving ionic polarization

defects

display_name: defects

density-functional-calculations

display_name: density-functional-calculations

dielectric-properties

display_name: dielectric-properties

electric-polarization

display_name: electric-polarization

first-principles-calculations

display_name: first-principles-calculations

optical-absorption-spectroscopy

display_name: optical-absorption-spectroscopy

polarons

display_name: polarons

vacancies

display_name: vacancies


en: A central goal of condensed matter physics is to understand the rich and diverse electronic and optical properties that emerge as wavelike electrons move through the periodically-arranged atoms in crystalline materials. However, more than 90 years after Bloch derived the functional forms of electronic waves in crystals (now known as Bloch wavefunctions) rapid scattering processes have so far prevented their direct experimental reconstruction. In high-order sideband generation (HSG), electrons and holes generated in semiconductors by a near-infrared (NIR) laser are accelerated to high kinetic energy by a strong terahertz field, and recollide to emit NIR sidebands before they are scattered. Here we reconstruct the Bloch wavefunctions of two types of holes in gallium arsenide wavelengths much longer than the spacing between atoms by experimentally measuring sideband polarizations and introducing an elegant theory that ties those polarizations to quantum interference between different recollision pathways. These Bloch wavefunctions are compactly visualized on the surface of a sphere. Because HSG can, in principle, be observed from any direct-gap semiconductor or insulator, we expect the method introduced in this Article can be used to reconstruct low-energy Bloch wavefunctions in a large class of bulk and nanostructured crystalline materials, and thus enable important new insights into the origin and engineering of electronic and optical properties of condensed matter. This record contains the data and analysis scripts used for these experiments.

en: Reconstruction of Bloch wavefunctions of holes in a semiconductor

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

bloch-wavefunctions

display_name: bloch-wavefunctions

condensed-matter-physics

display_name: condensed-matter-physics

experimental

display_name: experimental

gallium-arsenide

display_name: gallium-arsenide

luttinger-hamiltonian

display_name: luttinger-hamiltonian

non-equilibrium-physics

display_name: non-equilibrium-physics

nonlinear-optics

display_name: nonlinear-optics

terahertz

display_name: terahertz


en: Rechargeable lithium-ion batteries dominate the consumer electronics and electric vehicle markets. However, concerns on Li availability have prompted the development of alternative high energy density electrochemical energy storage systems. Rechargeable batteries based on a Ca metal anode can exhibit advantages in terms of energy density, safety and cost. The development of rechargeable Ca metal batteries requires the identification of suitable high specific energy cathode materials. This work focuses on Ca-bearing minerals because they represent stable and abundant compounds. Suitable minerals should contain a transition metal able of being reversibly reduced and oxidized, which points to several major classes of silicates and carbonates: olivine (CaFeSiO4; kirschsteinite), pyroxene (CaFe/MnSi2O6; hedenbergite and johannsenite, respectively), garnet (Ca3Fe/Cr2Si3O12; andradite and uvarovite, respectively), amphibole (Ca2Fe5Si8O22(OH)2; ferroactinolite) and double carbonates (CaMn(CO3)2; kutnahorite and CaFe(CO3)2; ankerite). This work discusses their electrode characteristics based on crystal chemistry analysis and density functional theory (DFT) calculations. The results indicate that upon Ca deintercalation, compounds such as pyroxene, garnet and double carbonate minerals could display high theoretical energy densities (ranging from 780 to 1500 Wh/kg) with moderate structural modifications. As a downside, DFT calculations indicate a hampered Ca mobility in their crystal structures. The overall analysis then disregards olivine, garnet, pyroxene, amphibole and double carbonates as structural types for future Ca-cathode materials design.

en: Analysis of minerals as electrode materials for Ca-based rechargeable batteries

materialscloud

en: Materials Cloud

batteries

display_name: batteries

electrode-materials

display_name: electrode-materials

geochemistry

display_name: geochemistry

minerals

display_name: minerals


en: We proposed an efficient high-throughput scheme for the discovery of new stable crystalline phases. Our approach was based on the transmutation of known compounds, through the substitution of atoms in the crystal structure with chemically similar ones. The concept of similarity is defined quantitatively using a measure of chemical replaceability, extracted by data mining experimental databases. In this way we build more than 250k possible crystal phases, with almost 20k that are on the convex hull of stability. This dataset contains the optimized structure and the energy of these 250k materials calculated with the PBE approximation, in a format that is convenient for data-mining or for machine-learning applications.

en: Finding new crystalline compounds using chemical similarity

envi

en: Environment

density-functional-theory

display_name: density-functional-theory

high-throughput

display_name: high-throughput

machine-learning

display_name: machine-learning


en: We extend the quasiparticle self-consistent approach beyond the GW approximation by using a range-separated vertex function. The developed approach yields band gaps, dielectric constants, and band positions with an accuracy similar to highest-level electronic-structure calculations without exceeding the cost of regular quasiparticle self-consistent GW. We introduce an exchange-correlation kernel that accounts for the vertex over the full spatial range. In the long range it complies with the Ward identity, while it is approximated through the adiabatic local density functional in the short range. In this approach, the renormalization factor is balanced and the higher-order diagrams are effectively taken into account.

en: Vertex function compliant with the Ward identity for quasiparticle self-consistent calculations beyond GW

electronic-bands

display_name: electronic-bands

electronic-structure

display_name: electronic-structure

gw

display_name: gw

ionization-potential

display_name: ionization-potential

many-body-perturbation-theory

display_name: many-body-perturbation-theory

vertex

display_name: vertex


en: The magnetic and electronic nature of the γ-Al2O3/SrTiO3 spinel/perovskite interface is explored by means of x-ray absorption spectroscopy. Polarized x-ray techniques combined with atomic multiplet calculations reveal localized magnetic moments assigned to Ti3+ at the interface with equivalent size for in- and out-of-plane magnetic field directions. Although magnetic fingerprints are revealed, the Ti3+ magnetism can be explained by a paramagnetic response at low temperature under applied magnetic fields. Modeling the x-ray linear dichroism results in a Delta0 ∼ 1.9 eV splitting between the t2g and eg states for the Ti4+ 3d0 orbitals. In addition these results indicate that the lowest energy states have the out-of-plane dxz/dyz symmetry. The isotropic magnetic moment behavior and the lowest energy dxz/dyz states are in contrast to the observations for the two-dimensional electron gas at the perovskite/perovskite interface of LaAlO3/SrTiO3 that exhibits an anisotropic magnetic dxy ground state.

en: Magnetic and electronic properties at the γ-Al2O3/SrTiO3 interface

experimental

display_name: experimental

magnetism

display_name: magnetism

two-dimensional-electron-gas

display_name: two-dimensional-electron-gas

x-ray-absorption-spectroscopy

display_name: x-ray-absorption-spectroscopy


en:
Set of inputs to perform the calculations reported in the paper.
The i-pi input enables to perform molecular dynamics / metadynamics / REMD / PIMD simulations, with adequate thermostats.
The DFTB and LAMMPS input respectively enable to calculate force and energies within the DFTB and Neural Network Forcefield frameworks.
The CP2K input files enable to calculate force and energies at PBE and PBE0 level. The latter is used as the reference to train the neural network correction on top of DFTB.

Brief description of the work: We present a generally-applicable computational framework for the efficient and accurate characterization of molecular structural patterns and acid properties in explicit solvent using H₂O₂ and CH₃SO₃H in phenol as an example. In order to address the challenges posed by the complexity of the problem, we resort to a set of data-driven methods and enhanced sampling algorithms. The synergistic application of these techniques makes the first-principle estimation of the chemical properties feasible without renouncing to the use of explicit solvation, involving extensive statistical sampling. Ensembles of neural network potentials are trained on a set of configurations carefully selected out of preliminary simulations performed at a low-cost density-functional tight-binding (DFTB) level. Energy and forces of these configurations are then recomputed at the hybrid density functional theory (DFT) level and used to train the neural networks. The stability of the NN model is enhanced by using DFTB energetics as a baseline, but the efficiency of the direct NN (i.e., baseline-free) is exploited via a multiple-time step integrator. The neural network potentials are combined with enhanced sampling techniques, such as replica exchange and metadynamics, and used to characterize the relevant protonated species and dominant non-covalent interactions in the mixture, also considering nuclear quantum effects.

en: Simulating solvation and acidity in complex mixtures with first-principles accuracy: the case of CH₃SO₃H and H₂O₂ in phenol

acid

display_name: acid

acid-homogeneous-catalysis

display_name: acid-homogeneous-catalysis

artificial-intelligence

display_name: artificial-intelligence

catalysis

display_name: catalysis

marvel

display_name: marvel

reaction

display_name: reaction

solution-chemistry

display_name: solution-chemistry


en: Two-dimensional (2D) layered materials offer a materials platform with potential applications from energy to information processing devices. Although some single- and few-layer forms of materials such as graphene and transition metal dichalcogenides have been realized and thoroughly studied, the space of arbitrarily layered assemblies is still mostly unexplored. The main goal of this work is to demonstrate precise control of layered materials' electronic properties through careful choice of the constituent layers, their stacking, and relative orientation. Physics-based and AI-driven approaches for the automated planning, execution, and analysis of electronic structure calculations are applied to layered assemblies based on prototype one-dimensional (1D) materials and realistic 2D materials. We find it is possible to routinely generate moiré band structures in 1D with desired electronic characteristics such as a band gap of any value within a large range, even with few layers and materials (here, four and six, respectively). We argue that this tunability extends to 2D materials by showing the essential physical ingredients are already evident in calculations of two-layer MoS2 and multi-layer graphene moiré assemblies.

en: Computational design of moiré assemblies aided by artificial intelligence

artificial-neural-networks

display_name: artificial-neural-networks

high-throughput-calculations

display_name: high-throughput-calculations

two-dimensional-materials

display_name: two-dimensional-materials


en:
The production of enantiopure materials and molecules is of uttermost relevance in research and industry in numerous contexts, ranging from non-linear optics to asymmetric synthesis. In the context of the latter, we have investigated dehalogenation, which is an essential reaction step for a broad class of chemical reactions. Specifically, dehalogenation of prochiral 5-bromo-7-methylbenz(a)anthracene (BMA) on prototypical, chiral, intermetallic PdGa{111} surfaces under ultrahigh vacuum conditions. Enantioselective halogen elimination is demonstrated by combining temperature-programmed x-ray photoelectron spectroscopy, scanning probe microscopy, and density functional theory. On the PdGa{111} surfaces, the difference in debromination temperatures for the two BMA surface enantiomers amounts up to unprecedented 46 K. The significant dependence of the dehalogenation temperature of the BMA surface enantiomers on the atomic termination of the PdGa{111} surfaces, implies that the ensemble effect is pronounced in this reaction step. These findings evidence enantiospecific control and hence promote intrinsically chiral crystals for asymmetric on-surface synthesis.
The record contains input files to reproduce the calculations discussed in the manuscript and the raw data of the experimental images discussed.

en: Asymmetric elimination reaction on chiral metal surfaces

ab-initio

display_name: ab-initio

enantioselectivity

display_name: enantioselectivity

scanning-probe-microscopy

display_name: scanning-probe-microscopy

snsf

display_name: snsf


en: Cif files of relaxed "derived" copper surfaces from Cu2O, Cu2S, Cu3N, and Cu3P using EMT and published in J Gauthier, JH Stenlid, F Abild-Pedersen, M Head-Gordon, AT Bell, ACS Energy Letters, "The role of roughening to enhance selectivity to C2+ products during CO2 electroreduction on copper" (2021). These structures were used to evaluate the effect of roughening on catalytic selectivity of copper in electrochemcial CO2 reduction into valuable products such as fuels and commodity chemicals.

en: Atomic structures of 100nm x 100nm large oxide-, nitride-, sulfide-, and phosphide-derived copper surfaces

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

atomic-coordinates

display_name: atomic-coordinates

copper

display_name: copper

surface-structure

display_name: surface-structure


en: The record contains data that support our recent findings in the fabrication of cumulene containing polymers. Cumulene compounds are notoriously difficult to prepare and study because their reactivity increases dramatically with the increasing number of consecutive double bonds. In this respect, the emerging field of on‐surface synthesis provides exceptional opportunities because it relies on reactions on clean metal substrates under well‐controlled ultrahigh‐vacuum conditions. In the work we report the on‐surface synthesis of a polymer linked by cumulene‐like bonds on a Au(111) surface via sequential thermally activated dehalogenative C−C coupling of a tribenzoazulene precursor equipped with two dibromomethylene groups. The structure and electronic properties of the resulting polymer with cumulene‐like pentagon–pentagon and heptagon–heptagon connections have been investigated by means of scanning probe microscopy and spectroscopy methods and X‐ray photoelectron spectroscopy, complemented by density functional theory calculations.

en: On‐surface synthesis of cumulene‐containing polymers via two‐step dehalogenative homocoupling of dibromomethylene-functionalized tribenzoazulene

materialscloud

en: Materials Cloud

cscs

display_name: cscs

cumulene

display_name: cumulene

dfg

display_name: dfg

erc

display_name: erc

on-surface-synthesis

display_name: on-surface-synthesis

polymers

display_name: polymers


en: We study the nature of excess electrons in CsPbBr3 and identify several single and double polaronic states. We emphasize the importance of proper inclusion of the self-interaction corrections for the stability of small electron polarons in this material. We demonstrate that spin–orbit coupling (SOC) has a significant impact on the energetics of the polaronic states. In particular, we find that SOC disfavors electron localization and leads to different polaronic geometries. Additionally, by carrying out thermodynamic integration, we show that small electron polarons are thermally stabilized in CsPbBr3. The small energy differences between the localized and delocalized electronic states could possibly reconcile the apparently conflicting properties of high charge-carrier mobilities and low recombinations rates.

en: Small electron polarons in CsPbBr3

envi

en: Environment

halide-perovskites

display_name: halide-perovskites

polarons

display_name: polarons


en: In this record we provide data to support our recent findings on the synthesis of porphyrin-capped graphene nanoribbons. On-surface synthesis has emerged as a powerful tool for the construction of large, planar, π-conjugated structures that are not accessible through standard solution chemistry. Among such solid-supported architectures, graphene nanoribbons (GNRs) hold a prime position for their implementation in nanoelectronics due to their manifold outstanding properties. Moreover, using appropriately designed molecular precursors, this approach allows the synthesis of functionalized GNRs, leading to nanostructured hybrids with superior physicochemical properties. Among the potential "partners" for GNRs, porphyrins (Pors) outstand due to their rich chemistry, robustness, and electronic richness, among others. However, the use of such π-conjugated macrocycles for the construction of GNR hybrids is challenging and examples are scarce. In a recent publication we report singly and doubly Por-capped GNR segments presenting a commensurate and triply-fused GNR–Por heterojunction. The study of the electronic properties of such hybrid structures by high-resolution scanning tunneling microscopy, scanning tunneling spectroscopy, and DFT calculations reveals a weak hybridization of the electronic states of the GNR segment and the Por moieties despite their high degree of conjugation.

en: On-surface synthesis of singly and doubly porphyrin-capped graphene nanoribbon segments

dft

display_name: dft

graphene-nanoribbons

display_name: graphene-nanoribbons

porphyrin

display_name: porphyrin

snf

display_name: snf


en: In this record we provide data supporting our recent results discussed in the fabrication of non-benzenoid nanographenes. Nanographenes (NGs) have gained increasing attention due to their immense potential as tailor-made organic materials for nanoelectronics and spintronics. They exhibit a rich spectrum of physicochemical properties that can be tuned by controlling the size or the edge structure or by introducing structural defects in the honeycomb lattice. In the published manuscript we report the design and on-surface synthesis of NGs containing several odd-membered polycycles induced by a thermal procedure on Au(111). Our scanning tunneling microscopy, noncontact atomic force microscopy, and scanning tunneling spectroscopy measurements, complemented by computational investigations, describe the formation of two nonbenzenoid NGs (2A,B) containing four embedded azulene units in the polycyclic framework, via on-surface oxidative ring-closure reactions. Interestingly, we observe surface-catalyzed skeletal ring rearrangement reactions in the NGs, which lead to the formation of additional heptagonal rings as well as pentalene and as-indacene units in 2A,B, respectively. 2A,B on Au(111) both exhibit narrow experimental frontier electronic gaps of 0.96 and 0.85 eV, respectively, and Fermi level pinning of their HOMOs together with considerable electron transfer to the substrate. Ab initio calculations estimate moderate open-shell biradical characters for the NGs in the gas phase.

en: On-surface synthesis of non-benzenoid nanographenes by oxidative ring-closure and ring-rearrangement reactions

ab-initio-simulations

display_name: ab-initio-simulations

dfg-nsfc

display_name: dfg-nsfc

nanographenes

display_name: nanographenes

open-shell

display_name: open-shell


en:
We present the JuCLS (Jülich core-level shifts) database which collects first principles calculations of core-level binding energies and core-level shifts (also known as chemical shifts). The calculations for this database were performed with the FLEUR program [1], a feature-full, freely available, open source FLAPW (full-potential linearized augmented planewave) code, based on density-functional theory. The FLAPW-method is a very accurate all-electron method which within density functional theory is universally applicable to all atoms of the periodic table. All calculations are run with AiiDA through workflows within the AiiDA-FLEUR package (version 0.12.3) [2]. Our database collects predicted core-level shifts, binding energies for X-ray photoelectron spectroscopy (XPS) and as a side product formation energies. Core-level shifts are calculated within the initial state approximation and binding energies are extracted from core-hole simulations. The JuCLS v1.0 contains initial state core-level shifts and formation energies on 4435 of the 5058 stable binary metals from the Materials project database (MP) and calculations on 1271 elemental crystals from the Inorganic Crystal Structure Database (ICSD). This corresponds currently to over 130 000 unique core-level shifts and over 15 000 unique main line core-level shifts. The JuCLS database allows for the construction of theoretical X-ray photoelectron spectra containing a possible mixture of these materials. Furthermore, it allows for a direct chemical characterization of materials.

[1] https://flapw.de and www.judft.de
[2] https://github.com/JuDFTteam/aiida-fleur

en: JuCLS database of core-level shifts from all-electron density functional theory simulations for chemical analysis of X-ray photoelectron spectra

ab-initio

display_name: ab-initio

aiida-fleur

display_name: aiida-fleur

binding-energies

display_name: binding-energies

chemical-shifts

display_name: chemical-shifts

core-level

display_name: core-level

core-level-shifts

display_name: core-level-shifts

density-functional-theory

display_name: density-functional-theory

esca

display_name: esca

flapw

display_name: flapw

fleur

display_name: fleur

jucls

display_name: jucls

max

display_name: max

x-ray-photoelectron-spectroscopy

display_name: x-ray-photoelectron-spectroscopy

xps

display_name: xps


en: The article presents a series of methods that boost the speed of Wannier interpolation by several orders of magnitude, as well as their implementation in the WannierBerri code. The present dataset contains input files, scripts, and the resulting data, which allow to reproduce the examples and figures published in the article. The current version of the code is also included.

en: High performance Wannier interpolation of Berry curvature and related quantities with WannierBerri code

anomalous-hall-effect

display_name: anomalous-hall-effect

berry-curvature

display_name: berry-curvature

erc

display_name: erc

snsf

display_name: snsf

wannier-functions

display_name: wannier-functions


en: In the present record we provide the data obtained in ARPES experiments and input/output files of Quantum ESPRESSO calculations used in the publication entitled as this record. The experimental data consist of the Fermi surface at kz=π/c, the experimental band dispersion along the MΓM, XΓX and XMX, spin-resolved ARPES spectra, and spin-resolved ARPES spectra of surface states. The theoretical data consist in the bulk and slab calculations to support the experimental data.

en: Hidden bulk and surface effects in the spin polarization of the nodal-line semimetal ZrSiTe

arpes

display_name: arpes

epfl

display_name: epfl

hidden-polarization

display_name: hidden-polarization

marvel

display_name: marvel

spin-texture

display_name: spin-texture


exploding-and-weeping-ceramics

en: The systematic tuning of the lattice parameters to achieve improved kinematic compatibility between phases is a broadly effective strategy for improving the reversibility, and lowering the hysteresis, of solid-solid phase transformations. Here, "kinematic compatibility" refers to the fitting together of the phases. We present an apparently paradoxical example in which tuning to near perfect compatibility in (Zr/Hf)O2-(YNb)O4 results in a high degree of irreversibility, as manifested in explosive or "weeping" behavior on cooling through the tetragonal-to-monoclinic phase transformation. In the case of weeping the polycrystal slowly and steadily falls apart at the grain boundaries. These effects occur without chemical change. Finally, tuning to satisfy a condition we term the equidistance condition results in reversible behavior with the lowest hysteresis in this system. We give evidence that all these observations are explained by a more careful analysis of compatibility of the polycrystal, accounting for sample shape. These results show that an extreme diversity of behaviors, from reversible to explosive, is possible in a chemically homogeneous system by manipulating conditions of compatibility in unexpected ways. They provide critical concepts underlying the current search for a shape memory oxide ceramic.

en: Exploding and weeping ceramics

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

title_for_slug: exploding-and-weeping-ceramics

ceramics

display_name: ceramics

cystallographic-compatibility

display_name: cystallographic-compatibility

shape-memory

display_name: shape-memory


en:
Spintronics applications for high-density non-volatile memories require simultaneous optimization of the perpendicular magnetic anisotropy (PMA) and current-induced magnetization switching. These properties determine, respectively, the thermal stability of a ferromagnetic memory cell and a low operation power consumption, which are mutually incompatible with the spin transfer torque as the driving force for the switching. Here, we demonstrate a strategy of alloy engineering to overcome this obstacle by using electrically induced orbital currents instead of spin currents. A non-equilibrium orbital density generated in paramagnetic γ-FeMn flows into CoPt coupled to the magnetization through spin-orbit interaction, ultimately creating an orbital torque. Controlling the atomic arrangement of Pt and Co by structural phase transition, we show that the propagation length of the transferred angular momentum can be modified concurrently with the PMA strength. We find a strong correlation to the phase transition-induced changes of d orbitals with mₗ = ±1 and mₗ = ±2 character. The close link of orbital hybridization to the dynamic orbital response and magnetic properties offers new possibilities to realize optimally designed orbitronics memory and logic applications.
This dataset contains the DFT calculations for the electronic structure of CoPt in L1₁ and A1 structures that are discussed the corresponding publication.

en: DFT calculations of the electronic structure of CoPt in L1₁ and A1 structures

materialscloud

en: Materials Cloud

density-functional-theory

display_name: density-functional-theory

orbital-torque

display_name: orbital-torque

orbitronics

display_name: orbitronics


en: The chemical versatility of carbon imparts manifold properties to organic compounds, where magnetism remains one of the most desirable but elusive. Polycyclic aromatic hydrocarbons, also referred to as nanographenes, show a critical dependence of electronic structure on the topologies of the edges and the π-electron network, which makes them model systems with which to engineer unconventional properties including magnetism. In 1972, Erich Clar envisioned a bow-tie-shaped nanographene, C38H18, where topological frustration in the π-electron network renders it impossible to assign a classical Kekulé structure without leaving unpaired electrons, driving the system into a magnetically non-trivial ground state. In this record we include data needed to support our recent work where we demonstrate the experimental realization and in-depth characterization of this emblematic nanographene, known as Clar's goblet. Scanning tunnelling microscopy and spin excitation spectroscopy of individual molecules on a gold surface reveal a robust antiferromagnetic order with an exchange-coupling strength of 23 meV, exceeding the Landauer limit of minimum energy dissipation at room temperature. Through atomic manipulation, we realize switching of magnetic ground states in molecules with quenched spins. Our results provide direct evidence of carbon magnetism in a hitherto unrealized class of nanographenes, and prove a long-predicted paradigm where topological frustration entails unconventional magnetism, with implications for room-temperature carbon-based spintronics.

en: Topological frustration induces unconventional magnetism in a nanographene

envi

en: Environment

ab-initio

display_name: ab-initio

clar-goblet

display_name: clar-goblet

kondo

display_name: kondo

nanographene

display_name: nanographene


en: The vast chemical space of metal and ligand combinations in Transition Metal Complexes (TMCs) gives rise to a rich variety of electronic excited states with local and non-local character such as intra-ligand (IL), metal-centered (MC), metal-to-ligand (MLCT) or ligand-to-metal charge-transfer (LMCT) states. Those features are equally found in Metal Organic Frameworks (MOFs), defined as modular materials built from metal-nodes connected through organic-ligands. Because of the electronic and structural complexity of MOFs, the computational description of their excited states is a formidable challenge for which two different approaches have been usually followed: the solid state and the molecular perspective. The first consists in analysing the frontier electronic bands and crystal orbitals of the electronic ground state (GS) in periodic boundary conditions, while the latter points to an accurate computation of the excited states in representative clusters at the molecular level. Herein, we apply both approaches to evaluate the optical absorption properties of three experimentally reported Ti(IV) mononuclear MOFs with in silico metal substitutions with Zn(II), Cd(II), Fe(II), Ru(II) and Zr(IV) ions, thus covering d10, d6 and d0 electronic configurations of 1st and 2nd row TMCs in MOFs. Our analysis captures the main electronic features attributed to these systems while we discuss the main advantages and drawbacks of both approximations.

en: Optical absorption properties of metal-organic frameworks: solid state versus molecular perspective

mof

display_name: mof

optical-absorption

display_name: optical-absorption


en:
One proposed mechanism of implant fouling is attributed to the nonspecific adsorption of non-collagenous bone matrix proteins (NCPs) onto a newly implanted interface. With the goal of capturing the fundamental mechanistic and thermodynamic forces that govern changes in these NCP recognition domains as a function of γ-carboxyglutamic acid (Gla) post-translational modification and surface chemistry, we probe the adsorption process of the most commonly occurring NCP, osteocalcin, onto a mineral and metal oxide surface. Here, we apply two enhanced sampling methods to independently probe the effects of post-translational modification and peptide structure on adsorption. First, well-tempered metadynamics was used to capture the binding of acetyl and N-methylamide capped glutamic acid and Gla single amino acids onto crystalline hydroxyapatite and titania model surfaces at physiological pH. Following this, parallel tempering metadynamics in the well-tempered ensemble (PTMetaD-WTE) was used to study adsorption of the α-1 domain of osteocalcin onto hydroxyapatite and titania. Simulations were performed for the α-1 domain of osteocalcin in both its fully decarboxylated (dOC) and fully carboxylated (OC) form. Our simulations find that increased charge density due to carboxylation results in increased interactions at the interface, and stronger adsorption of the single amino acids to both surfaces. Interestingly, the role of Gla in promoting compact and helical structure in the α-1 domain resulted in disparate binding modes at the two surfaces, which is attributed to differences in interfacial water behavior. Overall, this work provides a benchmark for understanding the mechanisms that drive adsorption of Gla-containing mineralizing proteins onto different surface chemistries.

This record contains files necessary to reproduce enhanced sampling well-tempered metadynamics (wtMTD) and parallel tempering metadynamics in the well-tempered ensemble (PT-MetaD-WTE) simulations in PLUMED using GROMACS 2018.3.

en: Impact of glutamate carboxylation in the adsorption of the alpha-1 domain of osteocalcin to hydroxyapatite and titania

biomimetics

display_name: biomimetics

biomineralization

display_name: biomineralization

metadynamics

display_name: metadynamics

molecular-dynamics

display_name: molecular-dynamics


en: Density-functional theory is widely used to predict the physical properties of materials. However, it usually fails for strongly correlated materials. A popular solution is to use the Hubbard corrections to treat strongly correlated electronic states. Unfortunately, the exact values of the Hubbard U and J parameters are initially unknown, and they can vary from one material to another. In this semi-empirical study, we explore the U and J parameter space of a group of iron-based compounds to simultaneously improve the prediction of physical properties (volume, magnetic moment, and bandgap). We used a Bayesian calibration assisted by Markov chain Monte Carlo sampling for three different exchange-correlation functionals (LDA, PBE, and PBEsol). We found that LDA requires the largest U correction. PBE has the smallest standard deviation and its U and J parameters are the most transferable to other iron-based compounds. Lastly, PBE predicts lattice parameters reasonably well without the Hubbard correction.

en: Exploring DFT+U parameter space with a Bayesian calibration assisted by Markov chain Monte Carlo sampling

bayesian-calibration

display_name: bayesian-calibration

dftu

display_name: dftu

markov-chain-monte-carlo

display_name: markov-chain-monte-carlo

mcmc

display_name: mcmc


en: High-strength metal alloys achieve their performance via careful control of the nucleation, growth, and kinetics of precipitation. Alloy mechanical properties are then controlled by atomic scale phenomena such as shearing of the precipitates by dislocations. Atomistic modeling to understand the operative mechanisms requires length and time scales far larger than those accessible by first-principles methods. Here, a family of Behler-Parinello neural-network potentials (NNPs) for the Al-Mg-Si system is developed to enable quantitative studies of Al-6xxx alloys. The NNP is trained on metallurgically-important quantities computed by first principles density functional theory (DFT) leading to high fidelity predictions of intermetallic compounds, elastic constants, dilute solid-solution energetics, precipitate/matrix interfaces, Al stacking fault energies, antisite defect energies, and other quantities. A preliminary examination of early-stage clustering kinetics and energetics in Al-6xxx is then made, showing the formation of low-energy Mg-Si structures and the trapping of vacancies in these clusters. The Generalized Stacking Fault Energy surfaces (GSFE) for the three prevalent β" precipitate compositions in peak-aged Al-6xxx are then computed with the NNP, and are validated by DFT computations at key points. The NNP thus shows significant transferability across structures, making it a powerful approach for chemically-accurate simulations of metallurgical phenomena in Al-Mg-Si alloys.

en: Machine learning for metallurgy: a neural network potential for Al-Mg-Si

aluminum

display_name: aluminum

machine-learning

display_name: machine-learning

metallurgy

display_name: metallurgy


en: In this record, we provide the data supporting our recent results on the synthesis of nitrogen-substituted undecacene analogs. Heteroatom substitution in acenes allows to tailor their remarkable electronic properties, expected to include spin-polarization and magnetism for larger members of the acene family. Here, we present a strategy for the on-surface synthesis of three undecacene analogs substituted with four nitrogen atoms on an Au(111) substrate, by employing specifically designed diethano-bridged precursors. A similarly designed precursor is used to synthesize the pristine undecacene molecule. In the publication where the results are discussed, the experimental features of scanning probe microscopy are compared with ab initio simulations, to demonstrate that the ground state of the synthesized tetraazaundecacene has considerable open-shell character on Au(111). Additionally, we demonstrate that electronegative nitrogen atoms induce a considerable shift in energy level alignment compared to the pristine undecacene, and that the introduction of hydro-aza groups causes local anti-aromaticity in the synthesized compounds. Our work provides access to the precise fabrication of nitrogen-substituted acene and its analogs, potential building-blocks of organic electronics and spintronics, and a rich playground to explore pi-electron correlation.

en: On-surface synthesis and characterization of nitrogen-substituted undecacenes

aromaticity

display_name: aromaticity

cscs

display_name: cscs

experimental

display_name: experimental

heteroacenes

display_name: heteroacenes

on-surface-synthesis

display_name: on-surface-synthesis

open-shell

display_name: open-shell

snsf

display_name: snsf


en: By combining metal nodes and organic linkers one can make millions of different metal-organic frameworks (MOFs). At present over 90,000 MOFs have been synthesized and there are databases with over 500,000 predicted structures. This raises the question of whether a new experimental or predicted structure adds new information. For MOF-chemists the chemical design space is a combination of pore geometry, metal nodes, organic linkers, and functional groups, but at present we do not have a formalism to quantify optimal coverage of chemical design space. In this work, we show how machine learning can be used to quantify similarities of MOFs. This quantification allows us to use techniques from ecology to analyse the chemical diversity of these materials in terms of diversity metrics. In particular, we show that this diversity analysis can identify biases in the databases, and how such bias can lead to incorrect conclusions. This formalism provides us with a simple and powerful practical guideline to see whether a set of new structures will have the potential for new insights, or constitute a relatively small variation of existing structures.

en: Understanding the diversity of the metal-organic framework ecosystem

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

chemical-space

display_name: chemical-space

diversity

display_name: diversity

metal-organic-frameworks

display_name: metal-organic-frameworks


en: In this record we provide data to support our recent findings for the fabrication of Unsaturated Carbon Nanostructures with Regularly Fused Pentagon–Heptagon Pairs. Multiple fused pentagon–heptagon pairs are frequently found as defects at the grain boundaries of the hexagonal graphene lattice and are suggested to have a fundamental influence on graphene-related materials. However, the construction of sp2-carbon skeletons with multiple regularly fused pentagon–heptagon pairs is challenging. In this work, we found that the pentagon–heptagon skeleton of azulene was rearranged during the thermal reaction of an azulene-incorporated organometallic polymer on Au(111). The resulting sp2-carbon frameworks were characterized by high-resolution scanning probe microscopy techniques and feature novel polycyclic architectures composed of multiple regularly fused pentagon–heptagon pairs. Moreover, the calculated analysis of its aromaticity revealed a peculiar polar electronic structure.

en: On-surface synthesis of unsaturated carbon nanostructures with regularly fused pentagon-heptagon pairs

materialscloud

en: Materials Cloud

carbon-nanostructures

display_name: carbon-nanostructures

open-shell-systems

display_name: open-shell-systems

polymers

display_name: polymers


en: The correlation between electronic and crystal structures of 1T -TiSe2 in the charge-density wave (CDW) state is studied by x-ray diffraction in order to clarify basic properties in the CDW state, transport properties, and chirality. Three families of reflections are used to probe atomic displacements and the orbital asymmetry in Se. Two distinct onset temperatures are found: TCDW and a lower T∗ indicative for an onset of Se out-of-plane atomic displacements. T∗ coincides with a DC resistivity maximum and the onset of the proposed gyrotropic (chiral) electronic structure. However, no indication for chirality is found. The relation between the atomic displacements and the transport properties is discussed in terms of Ti 3d and Se 4p states that only weakly couple to the CDW order.

en: Correlation between electronic and structural orders in 1T-TiSe2

envi

en: Environment

charge-density-wave

display_name: charge-density-wave

crystal-symmetry

display_name: crystal-symmetry

electrical-conductivity

display_name: electrical-conductivity

marvel

display_name: marvel

paul-scherrer-institute

display_name: paul-scherrer-institute

resonant-elastic-x-ray-scattering

display_name: resonant-elastic-x-ray-scattering

structural-order-parameter

display_name: structural-order-parameter

transition-metal-dichalcogenide

display_name: transition-metal-dichalcogenide

x-ray-diffraction

display_name: x-ray-diffraction


en: We investigate the effect of charge self-consistency (CSC) in density-functional theory plus dynamical mean-field theory calculations compared to simpler "one-shot" calculations for materials where interaction effects lead to a strong redistribution of electronic charges between different orbitals or between different sites. We focus on two systems close to a metal-insulator transition (MIT), for which the importance of CSC is currently not well understood. Specifically, we analyze the strain-related orbital polarization in the correlated metal CaVO3 and the spontaneous electronic charge disproportionation in the rare-earth nickelate LuNiO3. In both cases, we find that the CSC treatment reduces the charge redistribution compared to cheaper one-shot calculations. However, while the MIT in CaVO3 is only slightly shifted due to the reduced orbital polarization, the effect of the site polarization on the MIT in LuNiO3 is more subtle. Furthermore, we highlight the role of the double-counting correction in CSC calculations containing different inequivalent sites.

en: Effect of charge self-consistency in DFT+DMFT calculations for complex transition metal oxides

dftdmft

display_name: dftdmft

dynamical-mean-field-theory

display_name: dynamical-mean-field-theory

electronic-properties-and-materials

display_name: electronic-properties-and-materials

electronic-structure

display_name: electronic-structure


en: One of the main applications of atomistic computer simulations is the calculation of ligand binding free energies. The accuracy of these calculations depends on the force field quality and on the thoroughness of configuration sampling. Sampling is an obstacle in simulations due to the frequent appearance of kinetic bottlenecks in the free energy landscape. Very often this difficulty is circumvented by enhanced sampling techniques. Typically, these techniques depend on the introduction of appropriate collective variables that are meant to capture the system's degrees of freedom. In ligand binding, water has long been known to play a key role, but its complex behaviour has proven difficult to fully capture. In this paper we combine machine learning with physical intuition to build a non-local and highly efficient water-describing collective variable. We use it to study a set of of host-guest systems from the SAMPL5 challenge. We obtain highly accurate binding free energies and good agreement with experiments. The role of water during the binding process is then analysed in some detail.

en: The role of water in host-guest interaction

enhanced-sampling

display_name: enhanced-sampling

erc

display_name: erc

host-guest

display_name: host-guest

ligand-binding

display_name: ligand-binding

molecular-dynamics

display_name: molecular-dynamics

neural-network

display_name: neural-network

snsf

display_name: snsf

water

display_name: water


en: In this record we provide data supporitng our recent results discussed in the characterization of the fabrication process of graphene nanoribbons. The prototypical surface reaction of 10,10′-dibromo-9,9′-bianthryl (DBBA) toward the seven-atom-wide armchair graphene nanoribbon (7-AGNR) on the Au(111) surface has been investigated by means of vibrational spectroscopy, thermal desorption spectroscopy, and density functional theory. Specifically, a direct correlation between annealing temperature and the formation of various intermediate species is derived. By comparison of IR spectra with results from DFT calculations, an identification of reaction intermediates has been achieved, allowing for a precise mapping of individual reaction steps. Thereby, we identify a prior unknown partially dehalogenated and strongly tilted DBBA* monoradical species (DBBA-1Br) after mild annealing (380–450 K). This inclined adsorption geometry stabilizes the second Br atom, preventing full dehalogenation. According to our calculations, dimerization of DBBA-1Br reverses this inclination and provides an efficient way to enable abstraction of the second Br atom and initiate polyanthracene chain formation by means of DBBA* addition. As a competitive process to dimerization, a small number of the DBBA* monoradicals recombine with previously released bromine atoms, leading to associative DBBA desorption. In the course of thermal processing, hydrogen release signals planarization of the twisted anthracene units of DBBA by means of cyclodehydrogenation and formation of the final 7-AGNR. Based on the results of this work, an in-depth understanding of the on-surface synthesis of 7-AGNR on Au(111), starting with a DBBA molecular precursor, has been attained.

en: Reaction pathway towards 7-atom-wide armchair graphene nanoribbon formation and identification of intermediate species on Au(111)

cscs

display_name: cscs

dfg

display_name: dfg

graphene-nanoribbons

display_name: graphene-nanoribbons

ir-spectroscopy

display_name: ir-spectroscopy

on-surface-synthesis

display_name: on-surface-synthesis


en: This work presents extensive first-principles (Car-Parrinello) molecular dynamics simulations of the solid-state electrolyte Li10GeP2O12 (LGPO) in a tetragonal phase -not synthesized so far- that is isostructural to the highly Li-ion conductive tetragonal phase of the sulfide analogue Li10GeP2S12 (LGPS). We provide comparative simulations of the experimentally known orthorhombic phase of LGPO (that we call here LISICON, from the family of superionic conductors to which LGPO belongs) and of the two experimentally known phases of LGPS, quasi-orthorhombic (called thio-LISICON) and tetragonal. We extract diffusion coefficients from fixed-cell simulations in the canonical ensemble and we study dynamical stability from variable-cell simulations in the isobaric-isothermal ensemble. The main outcome of this work is that, according to these simulations, although tetragonal LGPO is less stable than its orthorhombic allotrope, it exhibits a much higher conductivity, comparable to that presently estimated for both phases of LGPS. These results indicate that hypothetical tetragonal LGPO, if synthesized, could make a very attractive Li-ion conductor.

en: High Li-ion conductivity in tetragonal LGPO: a comparative first-principles study against known LISICON and LGPS phases

big-map

display_name: big-map

dynamical-stability

display_name: dynamical-stability

first-principles-molecular-dynamics

display_name: first-principles-molecular-dynamics

ionic-conductivity

display_name: ionic-conductivity

ionic-transport

display_name: ionic-transport

lgpo

display_name: lgpo

lgps

display_name: lgps

lisicon

display_name: lisicon

solid-state-electrolytes

display_name: solid-state-electrolytes


en:
Results of an ab initio structure search on the H+C+N+O quaternary space at 500GPa.

The solar system's outer planets, and many of their moons, are dominated by matter from the H–C–N–O chemical space, based on solar system abundances of hydrogen and the planetary ices H2O, CH4 , and NH3 . In the planetary interiors, these ices will experience extreme pressure conditions, around 5 Mbar at the Neptune mantle–core boundary, and it is expected that they undergo phase transitions, decompose, and form entirely new compounds. While temperature will dictate the formation of compounds, ground- state density functional theory allows us to probe the chemical effects resulting from pressure alone. These structural developments in turn determine the planets' interior structures, thermal evolution, and magnetic field generation, among others. Despite its importance, the H–C–N–O system has not been surveyed systematically to explore which compounds emerge at high-pressure conditions, and what governs their stability. Here, we report on and analyze an unbiased crystal structure search among H–C–N–O compounds between 1 and 5 Mbar. We demonstrate that simple chemical rules drive stability in this composition space, which explains why the simplest possible quaternary mixture HCNO—isoelectronic to diamond—emerges as a stable compound and discuss dominant decomposition products of planetary ice mixtures.

en: Rules of formation of H–C–N–O compounds at high pressure and the fates of planetary ices

ab-initio-random-structure-searching

display_name: ab-initio-random-structure-searching

h-c-n-o-chemistry

display_name: h-c-n-o-chemistry

high-pressure

display_name: high-pressure

planetary-ices

display_name: planetary-ices


en: A simultaneously accurate and computationally efficient parametrization of the energy and atomic forces of molecules and materials is a long-standing goal in the natural sciences. In pursuit of this goal, neural message passing has lead to a paradigm shift by describing many-body correlations of atoms through iteratively passing messages along an atomistic graph. This propagation of information, however, makes parallel computation difficult and limits the length scales that can be studied. Strictly local descriptor-based methods, on the other hand, can scale to large systems but do not currently match the high accuracy observed with message passing approaches. This work introduces Allegro, a strictly local equivariant deep learning interatomic potential that simultaneously exhibits excellent accuracy and scalability of parallel computation. Allegro learns many-body functions of atomic coordinates using a series of tensor products of learned equivariant representations, but without relying on message passing. Allegro obtains improvements over state-of-the-art methods on the QM9 and revised MD-17 data sets. A single tensor product layer is shown to outperform existing deep message passing neural networks and transformers on the QM9 benchmark. Furthermore, Allegro displays remarkable generalization to out-of-distribution data. Molecular dynamics simulations based on Allegro recover structural and kinetic properties of an amorphous phosphate electrolyte in excellent agreement with first principles calculations. Finally, we demonstrate the parallel scaling of Allegro with a dynamics simulation of 100 million atoms.

en: Learning local equivariant representations for large-scale atomistic dynamics

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

density-functional-theory

display_name: density-functional-theory

machine-learning

display_name: machine-learning

molecular-dynamics

display_name: molecular-dynamics


en: We present a first-principles investigation of the structural, electronic, and magnetic properties of pyrolusite (β-MnO2) using conventional and extended Hubbard-corrected density-functional theory (DFT+U and DFT+U+V). The onsite U and intersite V Hubbard parameters are computed using linear-response theory in the framework of density-functional perturbation theory. We show that while the inclusion of the onsite U is crucial to describe the localized nature of the Mn(3d) states, the intersite V is key to capture accurately the strong hybridization between neighboring Mn(3d) and O(2p) states. In this framework, we stabilize the simplified collinear antiferromagnetic (AFM) ordering (suggested by the Goodenough-Kanamori rule) that is commonly used as an approximation to the experimentally-observed noncollinear screw-type spiral magnetic ordering. A detailed investigation of the ferromagnetic and of other three collinear AFM spin configurations is also presented. The findings from Hubbard-corrected DFT are discussed using two kinds of Hubbard manifolds -- nonorthogonalized and orthogonalized atomic orbitals -- showing that special attention must be given to the choice of the Hubbard projectors, with orthogonalized manifolds providing more accurate results than nonorthogonalized ones within DFT+U+V. This work paves the way for future studies of complex transition-metal compounds containing strongly localized electrons in the presence of pronounced covalent interactions.

en: Importance of intersite Hubbard interactions in β-MnO2: A first-principles DFT+U+V study

materialscloud

en: Materials Cloud

band-gap

display_name: band-gap

crystal-structure

display_name: crystal-structure

cscs

display_name: cscs

density-of-states

display_name: density-of-states

dftu

display_name: dftu

dftuv

display_name: dftuv

goodenough-kanamori-rule

display_name: goodenough-kanamori-rule

hubbard-parameters

display_name: hubbard-parameters

hubbard-projectors

display_name: hubbard-projectors

magnetic-moment

display_name: magnetic-moment

marvelosp

display_name: marvelosp

nonorthogonalized-atomic-orbitals

display_name: nonorthogonalized-atomic-orbitals

orthogonalized-atomic-orbitals

display_name: orthogonalized-atomic-orbitals

self-interactions

display_name: self-interactions

snsf

display_name: snsf

spin-configuration

display_name: spin-configuration


en: We present a symmetry-based exhaustive approach to explore the structural and compositional richness of two-dimensional materials. We use a combinatorial engine' that constructs potential compounds by occupying all possible Wyckoff positions for a certain space group with  combinations of chemical elements. These combinations are restricted by imposing charge neutrality and the Pauling test for electronegativities. The structures are then pre-optimized with a specially crafted universal neural-network force-field, before a final step of geometry optimization using density-functional theory is performed. In this way we unveil an unprecedented variety of two-dimensional materials, covering the whole periodic table in more than 30 different stoichiometries of form AnBm or AnBmCk. Among the found structures we find examples that can be built by decorating nearly all Platonic and Archimedean tesselations as well as their dual Laves or Catalan tilings. We also obtain a rich, and unexpected, polymorphism for some specific compounds. We further accelerate the exploration of the chemical space of two-dimensional materials by employing machine-learning-accelerated prototype search, based on the structural types discovered in the exhaustive search. In total, we obtain around 6500 compounds, not present in previous available databases of 2D materials, with an energy of less than 250 meV/atom above the convex hull of thermodynamic stability.

en: Symmetry-based computational search for novel binary and ternary 2D materials

envi

en: Environment

crystal-graph-neural-networks

display_name: crystal-graph-neural-networks

density-functional-theory

display_name: density-functional-theory

high-throughput

display_name: high-throughput

machine-learning

display_name: machine-learning


en: Defect chemistry, strain, and structural, magnetic and electronic degrees of freedom constitute a rich space for the design of functional properties in transition metal oxides. Here, we show that it is possible to engineer polarity and ferroelectricity in non-polar perovskite oxides via polar defect pairs formed by anion vacancies coupled to substitutional cations. We use a self-consistent site-dependent DFT+U approach that accounts for local structural and chemical changes upon defect creation and which is crucial to reconcile predictions with the available experimental data. Our results for Fe-doped oxygen-deficient SrMnO3 show that substitutional Fe and oxygen vacancies can promote polarity due to an o -center displacement of the defect charge resulting in a net electric dipole moment, which polarizes the lattice in the defect neighborhood. The formation of these defects and the resulting polarization can be tuned by epitaxial strain, resulting in enhanced polarization also for strain values lower than the ones necessary to induce a polar phase transition in undoped SrMnO3. For high enough defect concentrations, these defect dipoles couple in a parallel fashion, thus enabling defect- and strain-based engineering of ferroelectricity in SrMnO3.

en: Interplay between polarization, strain and defect-pairs in Fe-doped  SrMnO3-δ

cscs

display_name: cscs

defect-pair

display_name: defect-pair

doping

display_name: doping

ferroelectricity

display_name: ferroelectricity

point-defect

display_name: point-defect

polarization

display_name: polarization

self-consistent-dftu

display_name: self-consistent-dftu

strain

display_name: strain

thin-film

display_name: thin-film


en: Organic photodetectors have promising applications in low-cost imaging, health monitoring and near infrared sensing. Recent research on organic photodetectors based on donor-acceptor systems has resulted in narrow-band, flexible and biocompatible devices, of which the best reach external photovoltaic quantum efficiencies approaching 100%. However, the high noise spectral density of these devices limits their specific detectivity to around 10^13 Jones in the visible and several orders of magnitude lower in the near-infrared, severely reducing performance. Here, we show that the shot noise, proportional to the dark current, dominates the noise spectral density, demanding a comprehensive understanding of the dark current. We demonstrate that, in addition to the intrinsic saturation current generated via charge-transfer states, dark current contains a major contribution from trap-assisted generated charges and decreases systematically with decreasing concentration of traps. By modeling the dark current of several donor-acceptor systems, we reveal the interplay between traps and charge-transfer states as source of dark current and show that traps dominate the generation processes, thus being the main limiting factor of organic photodetectors detectivity.

en: Reverse dark current in organic photodetectors and the major role of traps as source of noise

dark-current

display_name: dark-current

detectivity

display_name: detectivity

organic-photodetectors

display_name: organic-photodetectors

traps

display_name: traps


en: Graph neural networks have enjoyed great success in the prediction of material properties for both molecules and crystals. These networks typically use the atomic positions (usually expanded in a Gaussian basis) and the atomic species as input. Unfortunately, this information is in general not available when predicting new materials, for which the precise geometrical information is unknown. In this work, we circumvent this problem by predicting the thermodynamic stability of crystal structures without using the knowledge of the precise bond distances. We replace this information with embeddings of graph distances, allowing our networks to be used directly in high-throughput studies based on both composition and crystal structure prototype. Using these embeddings, we combine the newest developments in graph neural networks and apply them to the prediction of the distances to the convex hull. To train these networks, we curate a dataset of over 2 million density-functional calculations of crystals with consistent calculation parameters from various sources. The new dataset allows for the creation of a high quality convex hull and a large scale transfer learning approach. We apply the resulting model to the high-throughput search of 15 million tetragonal perovskites of composition ABCD2. As a result, we identify several thousand potentially stable compounds and demonstrate that transfer learning from the newly curated dataset reduces the required training data by 50%.

en: Crystal-graph attention networks for the prediction of stable materials

pbe

display_name: pbe


en: The paper reports on a theoretical description of work function of TiN, which is one of the most used materials for the realization of electrodes and gates in CMOS devices. Indeed, although the work function is a fundamental quantity in quantum mechanics and also in device physics, as it allows the understanding of band alignment at heterostructures and gap states formation at the metal/semiconductor interface, the role of defects and contaminants is rarely taken into account. Here, by using first principles simulations, we present an extensive study of the work function dependence on nitrogen vacancies and surface oxidation for different TiN surface orientations. The results complement and explain a number of existent experimental data, and provide a useful tool to tailoring transport properties of TiN electrodes in device simulations.

en: Controlling the TiN electrode work function at the atomistic level: a first principles investigation

defects

display_name: defects

dft

display_name: dft

electrodes

display_name: electrodes

gates

display_name: gates

intersect

display_name: intersect

oxidation

display_name: oxidation

titanium-nitride

display_name: titanium-nitride


en: The formation of large polarons has been proposed as reason for the high defect tolerance, low mobility, low charge carrier trapping and low nonradiative recombination rates of lead halide perovskites. Recently, direct evidence for large-polaron formation has been reported from a 50% effective mass enhancement in angle-resolved photoemission of CsPbBr₃ over theory for the orthorhombic structure. We present in-depth band dispersion measurements of CsPbBr₃ and GW calculations which lead to almost identical effective masses at the valence band maximum of 0.203+/-0.016 m₀ in experiment and 0.217 m₀ in orthorhombic theory. We argue that the effective mass can be explained solely on the basis of electron-electron correlation and large polaron formation cannot be concluded from photoemission data.

en: Is there a polaron signature in angle-resolved photoemission of CsPbBr₃?

large-polaron

display_name: large-polaron


en: We introduce HP, an implementation of density-functional perturbation theory, designed to compute Hubbard parameters (on-site U and inter-site V) in the framework of DFT+U and DFT+U+V. The code does not require the use of computationally expensive supercells of the traditional linear-response approach; instead, unit cells are used with monochromatic perturbations that significantly reduce the computational cost of determining Hubbard parameters. HP is an open-source software distributed under the terms of the GPL as a component of Quantum ESPRESSO. As with other components, HP is optimized to run on a variety of different platforms, from laptops to massively parallel architectures, using native mathematical libraries (LAPACK and FFTW) and a hierarchy of custom parallelization layers built on top of MPI. The effectiveness of the code is showcased by computing Hubbard parameters self-consistently for the phospho-olivine LixMn0.5Fe0.5PO4 (x=0, 0.5, 1) and by highlighting the accuracy of predictions of the geometry and Li intercalation voltages.

en: HP - A code for the calculation of Hubbard parameters using density-functional perturbation theory

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

cscs

display_name: cscs

density-functional-perturbation-theory

display_name: density-functional-perturbation-theory

hubbard-parameters

display_name: hubbard-parameters

linear-response-theory

display_name: linear-response-theory

marvelosp

display_name: marvelosp

open-science

display_name: open-science

open-source-software

display_name: open-source-software

quantum-espresso

display_name: quantum-espresso

self-interaction-corrections

display_name: self-interaction-corrections

transition-metal-compounds

display_name: transition-metal-compounds


en: Formation of base pairs between the nucleotides of a ribonucleic acid (RNA) sequence gives rise to a complex and often highly branched RNA structure. While numerous studies have demonstrated the functional importance of the high degree of RNA branching—for instance, for its spatial compactness or interaction with other biological macromolecules—RNA branching topology remains largely unexplored. Here, we use the theory of randomly branching polymers to explore the scaling properties of RNAs by mapping their secondary structures onto planar tree graphs. Focusing on random RNA sequences of varying lengths, we determine the two scaling exponents related to their topology of branching. Our results indicate that ensembles of RNA secondary structures are characterized by annealed random branching and scale similarly to self-avoiding trees in three dimensions. We further show that the obtained scaling exponents are robust upon changes in nucleotide composition, tree topology, and folding energy parameters. Finally, in order to apply the theory of branching polymers to biological RNAs, whose length cannot be arbitrarily varied, we demonstrate how both scaling exponents can be obtained from distributions of the related topological quantities of individual RNA molecules with fixed length. In this way, we establish a framework to study the branching properties of RNA and compare them to other known classes of branched polymers. By understanding the scaling properties of RNA related to its branching structure, we aim to improve our understanding of the underlying principles and open up the possibility to design RNA sequences with desired topological properties.

en: Scaling properties of RNA as a randomly branching polymer

materialscloud

en: Materials Cloud

polymer-physics

display_name: polymer-physics

rna

display_name: rna

scaling

display_name: scaling

statistical-mechanics

display_name: statistical-mechanics


en: In a unified regenerative fuel cell (URFC) or reversible fuel cell the oxygen bifunctional catalyst must switch reversibly between the oxygen reduction reaction (ORR), fuel cell mode, and the oxygen evolution reaction (OER), electrolyzer mode. However, it is often unclear what effect alternating between ORR and OER has on the electrochemical behavior and physiochemical properties of the catalyst. Herein, operando X-ray absorption spectroscopy (XAS) is utilized to monitor the continuous and dynamic evolution of the Co, Mn, and Fe oxidation states of perovskite catalysts Ba0.5Sr0.5Co0.8Fe0.2O3-δ (BSCF) and La0.4Sr0.6MnO3-δ (LSM), while the potential is oscillated between reducing and oxidizing potentials with cyclic voltammetry. The results reveal the importance of investigating bifunctional catalysts by alternating between fuel cell and electrolyzer operation and highlight the limitations and challenges of bifunctional catalysts. It is shown that the requirements for ORR and OER performance are divergent and that the oxidative potentials of OER are detrimental to ORR activity. These findings are used to give guidelines for future bifunctional catalyst design. Additionally, it is demonstrated how sunlight can be used to reactivate the ORR activity of LSM after rigorous cycling.

en: Time-resolved oxidation state changes are key to elucidating the bifunctionality of perovskite catalysts for oxygen evolution and reduction

envi

en: Environment

alkaline

display_name: alkaline

experimental

display_name: experimental

oer

display_name: oer

orr

display_name: orr

snsf

display_name: snsf


en: Accurate computational predictions of band gaps are of practical importance to the modeling and development of semiconductor technologies, such as (opto)electronic devices and photoelectrochemical cells. Among available electronic-structure methods, density-functional theory (DFT) with the Hubbard U correction (DFT+U) applied to band edge states is a computationally tractable approach to improve the accuracy of band gap predictions beyond that of DFT calculations based on (semi)local functionals. At variance with DFT approximations, which are not intended to describe optical band gaps and other excited-state properties, DFT+U can be interpreted as an approximate spectral-potential method when U is determined by imposing the piecewise linearity of the total energy with respect to electronic occupations in the Hubbard manifold (thus removing self-interaction errors in this subspace), thereby providing a (heuristic) justification for using DFT+U to predict band gaps. However, it is still frequent in the literature to determine the Hubbard U parameters semiempirically by tuning their values to reproduce experimental band gaps, which ultimately alters the description of other total-energy characteristics. Here, we present an extensive assessment of DFT+U band gaps computed using self-consistent ab initio U parameters obtained from density-functional perturbation theory to impose the aforementioned piecewise linearity of the total energy. The study is carried out on 20 compounds containing transition-metal or p-block (group III-IV) elements, including oxides, nitrides, sulfides, oxynitrides, and oxysulfides. By comparing DFT+U results obtained using nonorthogonalized and orthogonalized atomic orbitals as Hubbard projectors, we find that the predicted band gaps are extremely sensitive to the type of projector functions and that the orthogonalized projectors give the most accurate band gaps, in satisfactory agreement with experimental data. This work demonstrates that DFT+U may serve as a useful method for high-throughput workflows that require reliable band gap predictions at moderate computational cost.

en: Extensive benchmarking of DFT+U calculations for predicting band gaps

band-gap

display_name: band-gap

dftu

display_name: dftu

hubbard-correction

display_name: hubbard-correction

lowdin-orthogonalization

display_name: lowdin-orthogonalization

self-interaction

display_name: self-interaction


en: The dataset contains the result of 48 Nudged Elastic Band calculations of Li(2-x)VO2F diffusion barriers in the format of Atomic Simulation Environment (ASE) trajectories. The NEB was performed with VASP, using projector augmented-wave (PAW) method to describe electron-ion interaction. The disordered rock salt cells were created using a 3 x 4 x 4 supercell containing 96 atoms (in case of no vacancies). PBE is used as XC functional while a rotationally invariant Hubbard U correction was applied to the d orbital of V with a U value of 3.25 eV. See more details in the paper.

en: On-the-fly assessment of diffusion barriers of disordered transition metal oxyfluorides using local descriptors

big-map

display_name: big-map

fet-open

display_name: fet-open

lirichfcc

display_name: lirichfcc

lithium-diffusion

display_name: lithium-diffusion

machine-learning

display_name: machine-learning

nudged-elastic-band

display_name: nudged-elastic-band


en:
Strong correlations within a symmetry-unbroken ground-state wavefunction can show up in approximate density functional theory as symmetry-broken spin-densities or total densities, which are sometimes observable. They can arise from soft modes of fluctuations (sometimes collective excitations) such as spin-density or charge-density waves at non-zero wavevector. In this sense, an approximate density functional for exchange and correlation that breaks symmetry can be more revealing (albeit less accurate) than an exact functional that does not. The examples discussed here include the stretched H2 molecule, antiferromagnetic solids, and the static charge-density wave/Wigner crystal phase of a low-density jellium. Time-dependent density functional theory is used to show quantitatively that the static charge density wave is a soft plasmon. More precisely, the frequency of a related density fluctuation drops to zero, as found from the frequency moments of the spectral function, calculated from a recent constraint-based wavevector- and frequency-dependent jellium exchange-correlation kernel.

This record contains all raw data used in this project. The second version contains better-converged data for the frequency moments. The parameters used to generate this data are included in a text file. The third version includes third moment sum rule data that is more stable (a typo in the spline interpolation was rectified, see the Gitlab commit record for more detailed information), as well as expanded correlation energy per electron data. The MCP07 analytic continuation to imaginary frequencies is also more correctly treated in this new data set.

en: Interpretations of ground-state symmetry breaking and strong correlation in wavefunction and density functional theories

density-functional-theory

display_name: density-functional-theory

exchange-correlation-kernel

display_name: exchange-correlation-kernel

jellium

display_name: jellium


en: This record contains the experimental results of the first ultrafast spectroscopic investigation of the electronic properties of SmB6, proposed to realize a Kondo topological insulator.  We employ a multi-temperature model to extract the electron-phonon coupling constant in the range 0.13-0.04, within the assumption of a strong coupling to the optical phonon modes in the range 10-19 meV.

en: SmB6 electron-phonon coupling constant from time- and angle-resolved photoelectron spectroscopy

electron-phonon-coupling

display_name: electron-phonon-coupling

electronic-bands

display_name: electronic-bands

experimental

display_name: experimental

kondo-system

display_name: kondo-system


en: This record contains data to support the findings discussed in our recent work on the synthesis and characterization of super-nonazethrene. Beginning with the early work of Clar et al. in 1955, zethrenes and their laterally-extended homologues, super-zethrenes, have been intensively studied in the solution phase, and are widely investigated as optical and charge transport materials. Super-zethrenes are also considered to exhibit an open-shell ground state. Zethrenes may thus serve as model compounds to investigate nanoscale π-magnetism. However, their synthesis is extremely challenging due to their high reactivity. In the work we report here a combined in-solution and on-surface synthesis of the hitherto largest zethrene homologue – super-nonazethrene – on Au(111). Using single-molecule scanning tunneling microscopy and spectroscopy, we show that super-nonazethrene exhibits an open-shell singlet ground state featuring a large spin polarization-driven electronic gap of 1 eV. We obtain real-space maps of the frontier molecular orbitals, and find that they correspond to singly occupied molecular orbitals. In consistence with the emergence of an open-shell ground state, high-resolution tunneling spectroscopy reveals inelastic singlet-triplet spin excitations in super-nonazethrene, characterized by a strong intramolecular magnetic exchange coupling of 51 meV. Further insights are gained by mean-field and many-body perturbation theory calculations. Given the paucity of zethrene chemistry on surfaces, our results therefore provide unprecedented access to large open-shell zethrene compounds amenable to scanning probe measurements, with potential application in molecular spintronics.

en: On-surface synthesis and characterization of super-nonazethrene

ab-initio-simulations

display_name: ab-initio-simulations

erc

display_name: erc

graphene-flagship

display_name: graphene-flagship

nanographene

display_name: nanographene

scanning-tunneling-microscopy

display_name: scanning-tunneling-microscopy

zethrenes

display_name: zethrenes


en: Doping has been widely used to control the charge carrier concentration in organic semiconductors. However, in conjugated polymers, n-doping is often limited by the tradeoff between doping efficiency and charge carrier mobilities, since dopants are often randomly distributed within polymers, leading to significant structural and energetic disorder. Here, we screen a large number of polymer building block combinations and explore the possibility of designing n-type conjugated polymers with good tolerance to dopant-induced disorder. We show that a carefully designed conjugated polymer with a single dominant planar backbone conformation, high torsional barrier at each dihedral angle, and zigzag backbone curvature is highly dopable and can tolerate dopant-induced disorder. With these features, the newly designed diketopyrrolopyrrole (DPP)-based polymer can be efficiently n-doped and exhibit high n-type electrical conductivities over 120 S cm−1, much higher than the reference polymers with similar chemical structures. This work provides a new polymer design concept for highly dopable and highly conductive polymeric semiconductors.

en: Approaching disorder-tolerant semiconducting polymers

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

disorder-tolerant

display_name: disorder-tolerant

n-doping

display_name: n-doping

semiconducting-polymers

display_name: semiconducting-polymers


en: C2N is an ordered two-dimensional carbon nitride with a high density (1.7 × 10^14 cm−2) of 3.1 Å-sized nanopores, making it promising for high-flux gas sieving for energy-efficient He and H2 purification. Herein, we discuss the accurate calculation of potential energy surfaces for He, H2, N2, and CO2 across C2N nanopores, to characterize the gas-sieving potential of C2N. We compare the potential energy surface derived from density-functional theory calculations using five commonly used van der Waals (vdW) approximations. While all five functionals point that the C2N nanopore yields He/N2 and H2/N2 selectivities over 1000, adsorption energies and energy barriers vary remarkably depending on the approximation chosen. To make progress, we compare the calculations against the results from the adiabatic connection fluctuation dissipation theory, with random-phase approximation, known to be accurate in capturing vdW interactions. The comparison indicates that the interaction energy is less accurate with vdW density functional theory. On the other hand, more empirical corrections work reasonably well, a finding that we also confirm for another carbon nitride lattice, poly(triazine imide). Overall, we recommend these for screening carbon nitride materials for gas separation, but also comparing functionals with higher-order approaches when dealing with different materials.

en: Gas transport across carbon nitride nanopores: a comparison of van der Waals functionals against the random-phase approximation

materialscloud

en: Materials Cloud

carbon-nitrides

display_name: carbon-nitrides

cscs

display_name: cscs

epfl

display_name: epfl

marvel

display_name: marvel

nanoscale-transport

display_name: nanoscale-transport

random-phase-approximation

display_name: random-phase-approximation

snsf

display_name: snsf

van-der-waals-approximations

display_name: van-der-waals-approximations