First-principles calculations of hybrid inorganic–organic interfaces: from state-of-the-art to best practice

Hofmann, Oliver; Zojer, Egbert; Hörmann, Lukas; Jeindl, Andreas; Maurer, Reinhard J.

doi:10.1039/d0cp06605b

Cited by 45 publications

(74 citation statements)

References 350 publications

(525 reference statements)

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“…We note in passing that the computational method we employ here (PBE + TS surf ) has a tendency to induce molecular bending upon adsorption, 70 thus overestimating the molecular dipole, while underestimating the adsorption distance. 71 − 73 As a consequence, the effect of Pauli pushback is overestimated. The latter describes the effect that the electron density spilling out from the surface is pushed back by the π conjugated electron system of the molecular adsorbate layer.…”

Section: Resultsmentioning

confidence: 99%

Electronic Properties of Tetraazaperopyrene Derivatives on Au(111): Energy-Level Alignment and Interfacial Band Formation

et al. 2021

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N-heteropolycyclic aromatic compounds are promising organic electron-transporting semiconductors for applications in field-effect transistors. Here, we investigated the electronic properties of 1,3,8,10-tetraazaperopyrene derivatives adsorbed on Au(111) using a complementary experimental approach, namely, scanning tunneling spectroscopy and two-photon photoemission combined with state-of-the-art density functional theory. We find signatures of weak physisorption of the molecular layers, such as the absence of charge transfer, a nearly unperturbed surface state, and an intact herringbone reconstruction underneath the molecular layer. Interestingly, molecular states in the energy region of the sp- and d-bands of the Au(111) substrate exhibit hole-like dispersive character. We ascribe this band character to hybridization with the delocalized states of the substrate. We suggest that such bands, which leave the molecular frontier orbitals largely unperturbed, are a promising lead for the design of organic–metal interfaces with a low charge injection barrier.

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Section: Resultsmentioning

confidence: 99%

Electronic Properties of Tetraazaperopyrene Derivatives on Au(111): Energy-Level Alignment and Interfacial Band Formation

et al. 2021

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“…It is generally known that some properties are particularly sensitive to finite size effects of the model slab in surface calculations. [65] Surface energies and surface electronic states are often discussed as an example of this. [63] Calculations of copper slabs with 30 layers or more are not unheard of.…”

Section: Convergence Of Electronic Friction Tensor and Vibrational Li...mentioning

confidence: 99%

Ab initio calculation of electron-phonon linewidths and molecular dynamics with electronic friction at metal surfaces with numeric atom-centered orbitals

Box¹,

Stark²,

Maurer³

2021

Preprint

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Molecular motion at metallic surfaces is affected by nonadiabatic effects and electron-phonon coupling. The ensuing energy dissipation and dynamical steering effects are not captured by classical molecular dynamics simulations, but can be described with the molecular dynamics with electronic friction method and linear response calculations based on density functional theory. Herein, we present an implementation of electron-phonon response based on an all-electron numeric atomic orbital description in the electronic structure code FHI-aims. After providing details of the underlying approximations and numerical considerations, we present significant scalability and performance improvements of the new code compared to a previous implementation [Phys. Rev. B 94, 115432 (2016)]. We compare convergence behaviour and results of our simulations for exemplary systems such as CO on Cu(100), H 2 adsorption on Cu(111), and CO on Ru(0001) against existing plane wave implementations. We find that our all-electron calculations exhibit faster and more monotonic convergence behaviour than conventional plane-wave-based electron-phonon calculations. Our findings suggest that many electron-phonon linewidth calculations in literature may be underconverged. Finally, we showcase the capabilities of the new code by studying the contribution of interband and intraband excitations to vibrational linewidth broadening of aperiodic motion in previously unfeasibly large periodic surface models.

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“…This is exacerbated by the challenge of interpreting macroscopically averaged photoemission data for complex molecules. [8][9][10][11] First-principles simulation of photoemission signatures have the potential to dramatically accelerate high throughput screening of organic materials, but the high computational cost associated with accurate many-body excited-state calculations limits their applicability to small molecular systems. 12,13 Machine learning (ML) methods have the ability to overcome the gap between experiment and theory for spectroscopic characterization by reducing the computational effort of spectroscopic simulations without sacricing prediction accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…This is exacerbated by the challenge of interpreting macroscopically averaged photoemission data for complex molecules. 8–11 …”

Section: Introductionmentioning

confidence: 99%

Physically inspired deep learning of molecular excitations and photoemission spectra

Westermayr

Maurer

2021

Chem. Sci.

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First-principles calculations of hybrid inorganic–organic interfaces: from state-of-the-art to best practice

Abstract: The computational characterization of inorganic-organic hybrid interfaces is arguably one of the technically most challenging applications of density functional theory. Due to the fundamentally different electronic properties of the inorganic...

Cited by 45 publications

References 350 publications

Electronic Properties of Tetraazaperopyrene Derivatives on Au(111): Energy-Level Alignment and Interfacial Band Formation

Electronic Properties of Tetraazaperopyrene Derivatives on Au(111): Energy-Level Alignment and Interfacial Band Formation

Ab initio calculation of electron-phonon linewidths and molecular dynamics with electronic friction at metal surfaces with numeric atom-centered orbitals

Physically inspired deep learning of molecular excitations and photoemission spectra

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