arXiv subjects

Andreas Jeindl

Publications and source records attributed to Andreas Jeindl.

15 recordsLinked to original sources

arXiv2025

Molecular Arrangements in the First Monolayer of Cu-Phthalocyanine on In$_2$O$_3$(111)

Well-ordered organic molecular layers on oxide surfaces are key for organic electronics. Using a combination of scanning tunneling microscopy (STM) and non-contact atomic force microscopy (nc-AFM) we probe the structures of copper phthalocyanine (CuPc) on In$_2$O$_3$, a model for a prototypical transparent conductive oxide (TCO). These scanning-probe images allow the direct determination of the adsorption site and distortions of the molecules, which are corroborated by DFT calculations. Isolated CuPc molecules adsorb in a flat, slightly tilted geometry in three symmetry-equivalent configurations on the stoichiometric In$_2$O$_3$(111) surface. Increasing the coverage leads to densely-packed 1D chains oriented along $\langle1\bar{1}0\rangle$ directions, which dissolve into a highly ordered (2$\times$2) superstructure upon increasing the CuPc density to 3/4 per surface unit cell. At a coverage of one CuPc per surface unit cell, a densely packed (1$\times$1) superstructure fully covers the surface. The molecules still assume the same site and orientation as before, but they partially overlap to accommodate the high packing density, leading to a bending of the molecules. These results are compared to the behavior of CoPc on In$_2$O$_3$(111). In summary, we demonstrate that a uniform first layer of metal-phthalocyanine molecules can be realized on the In$_2$O$_3$(111) surface when using the proper metal atom in the molecule.

cond-mat.mtrl-sci↗

arXiv2023

Adsorption configurations of Co-phthalocyanine on In2O3(111)

Indium oxide offers optical transparency paired with electric conductivity, a combination required in many optoelectronic applications. The most-stable In2O3(111) surface has a large unit cell (1.43 nm lattice constant). It contains a mixture of both bulk-like and undercoordinated O and In atoms and provides an ideal playground to explore the interaction of surfaces with organic molecules of similar size as the unit cell. Non-contact atomic force microscopy (nc-AFM), scanning tunneling microscopy (STM), and density functional theory (DFT) were used to study the adsorption of Co-phthalocyanine (CoPc) on In2O3(111). Isolated CoPc molecules adsorb at two adsorption sites in a 7:3 ratio. The Co atom sits either on top of a surface oxygen ('F configuration') or indium atom ('S configuration'). This subtle change in adsorption site induces bending of the molecules, which is reflected in their electronic structure. According to DFT the lowest unoccupied molecular orbital of the undistorted gas-phase CoPc remains mostly unaffected in the F configuration but is filled by one electron in S configuration. At coverages up to one CoPc molecule per substrate unit cell, a mixture of domains with molecules in F and S configuration are found. Molecules at F sites first condense into a F-(2x2) structure and finally rearrange into a F-(1x1) symmetry with partially overlapping molecules, while S-sited molecules only assume a S-(1x1) superstructure.

cond-mat.mtrl-sci↗

arXiv2022

Long-range dispersion-inclusive machine learning potentials for structure search and optimization of hybrid organic-inorganic interfaces

The computational prediction of the structure and stability of hybrid organic-inorganic interfaces provides important insights into the measurable properties of electronic thin film devices, coatings, and catalyst surfaces and plays an important role in their rational design. However, the rich diversity of molecular configurations and the important role of long-range interactions in such systems make it difficult to use machine learning (ML) potentials to facilitate structure exploration that otherwise require computationally expensive electronic structure calculations. We present an ML approach that enables fast, yet accurate, structure optimizations by combining two different types of deep neural networks trained on high-level electronic structure data. The first model is a short-ranged interatomic ML potential trained on local energies and forces, while the second is an ML model of effective atomic volumes derived from atoms-in-molecules partitioning. The latter can be used to connect short-range potentials to well-established density-dependent long-range dispersion correction methods. For two systems, specifically gold nanoclusters on diamond (110) surfaces and organic $π$-conjugated molecules on silver (111) surfaces, we train models on sparse structure relaxation data from density functional theory and show the ability of the models to deliver highly efficient structure optimizations and semi-quantitative energy predictions of adsorption structures.

cond-mat.mtrl-sci↗

arXiv2022

The role of adatoms for the adsorption of F4TCNQ on Au(111)

Organic adlayers on inorganic substrates often contain adatoms, which can be incorporated within the adsorbed molecular species, forming two-dimensional metal-organic frameworks at the substrate surface. The interplay between native adatoms and adsorbed molecules significantly changes various adlayer properties such as the adsorption geometry, the bond strength between the substrate and the adsorbed species, or the work function at the interface. Here we use dispersion-corrected density functional theory to gain insight into the energetics that drive the incorporation of native adatoms within molecular adlayers based on the prototypical, experimentally well-characterized system of F4TCNQ on Au(111). We explain the adatom-induced modifications in the adsorption geometry and the adsorption energy based on the electronic structure and charge transfer at the interface. With this, we provide deeper insight into the general mechanisms causing the incorporation of adatoms within an adlayer made of a strong acceptor molecular species.

cond-mat.mtrl-sci↗

arXiv2021

From a bistable adsorbate to a switchable interface: tetrachloropyrazine on Pt(111)

Virtually all organic (opto)electronic devices rely on organic/inorganic interfaces with specific properties. These properties are, in turn, inextricably linked to the interface structure. Therefore, a change in structure can introduce a shift in function. If this change is reversible, it would allow constructing a switchable interface. We accomplish this with tetrachloropyrazine on Pt(111), which exhibits a double-well potential with a chemisorbed and a physisorbed minimum. These minima have significantly different adsorption geometries allowing the formation of switchable interface structures. Importantly, these structures facilitate different work function changes and coherent fractions (X-ray standing wave measurements), which are ideal properties to readout the interface state. We perform surface structure search using a modified version of the SAMPLE approach and account for thermodynamic conditions using ab-initio thermodynamics. This allows investigating millions of commensurate as well as higher-order commensurate interface structures. We identify three different classes of structures exhibiting different work function changes and coherent fractions. Using temperature and pressure as handles we demonstrate the possibility of reversible switching between those different classes, creating a dynamic interface for potential applications in organic electronics.

cond-mat.mtrl-sci↗

arXiv2021

Interfacial charge transfer influences thin-film polymorphism

The structure and chemical composition are the key parameters influencing the properties of organic thin films deposited on inorganic substrates. Such films often display structures that substantially differ from the bulk, and the substrate has a relevant influence on their polymorphism. In this work, we illuminate the role of the substrate by studying its influence for para-benzoquinone on two different substrates, Ag(111) and graphene. We employ a combination of first principles calculations and machine learning to identify the energetically most favorable structures on both substrates and study their electronic properties. Our results indicate that for the first layer, similar structures are favorable for both substrates. For the second layer we find two significantly different structures. Interestingly, graphene favors the one with less, while Ag favors the one with more electronic coupling. We explain this switch in stability as an effect of the different charge transfer on the two substrates.

cond-mat.mtrl-sci↗

arXiv2021

How much does surface polymorphism influence the work function of organic/metal interfaces?

Molecules adsorbing on metal surfaces form a variety of different surface polymorphs. How strongly this polymorphism affects interface properties is a priori unknown. In this work we investigate how strongly the surface polymorphism influences the interface work functions for various metal/organic interfaces. To evaluate the whole bandwidth of possible polymorphs, we perform full theoretical structure search, probing millions of polymorph candidates. All of these candidates might be observed in reality, either by kinetic trapping or by thermodynamic occupation. Employing first-principles calculations and machine learning we predict and analyze the work function changes for those millions of candidates for three physically distinct model systems: the weakly interacting naphthalene on Cu(111), the strongly interacting anthraquinone on Ag(111), and tetracyanoethylene, which undergoes a re-orientation from lying to standing polymorphs on the Cu(111) surface. These thorough investigations indicate that kinetic trapping of flat lying molecules can lead to work function differences of a few hundred meV. If the molecules also reorientate, this can increase to a change of several eV. We further show that the spread in work function decreases when working in thermodynamic equilibrium, but thermally occupied phases still lead to an intrinsic uncertainty at elevated temperatures.

cond-mat.mtrl-sci↗

arXiv2021

Can we predict interface dipoles based on molecular properties?

We apply high-throughput DFT calculations and symbolic regression to hybrid inorganic/organic interfaces with the intent to extract physically meaningful correlations between the adsorption-induced work function modifications and the properties of the constituents. We separately investigate two cases: Hypothetical, free standing self-assembled monolayers with a large intrinsic dipole moment, and metal-organic interfaces with a large charge-transfer induced dipole. For the former we find - without notable prior assumptions - the Topping model, as expected from literature. For the latter, highly accurate correlations are found, which are, however, clearly unphysical.

cond-mat.mtrl-sci↗

arXiv2021

Towards targeted kinetic trapping of organic-inorganic interfaces: A computational case study

Properties of inorganic-organic interfaces, such as their interface dipole, strongly depend on the structural arrangements of the organic molecules. A prime example is tetracyanoethylene (TCNE) on Cu(111), which shows two different phases with significantly different work functions. However, the thermodynamically pre-ferred phase is not always the one that is best suited for a given application. Rather, it may be desirable to selectively grow a kinetically trapped structure. In this work, we employ density functional theory and transi-tion state theory to discuss under which conditions such a kinetic trapping might be possible for the model system of TCNE on Cu. Specifically, we want to trap the molecules in the first layer in a flat-lying orientation. This requires temperatures that are sufficiently low to suppress the re-orientation of the molecules, which is thermodynamically more favorable for high dosages, but still high enough to enable ordered growth through diffusion of molecules. Based on the temperature-dependent diffusion and re-orientation rates, we propose a temperature range at which the re-orientation can be successfully suppressed.

physics.comp-ph↗

arXiv2021

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

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 calculations. 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 \emph{sp}- and \emph{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 effectively leave the molecular frontier orbitals largely unperturbed, to be a promising lead for the design of organic-metal interfaces with a low charge injection barrier.

cond-mat.mes-hall↗

arXiv2021

Surface Self-Assembly of Functionalized Molecules on Ag(111): More Than Just Chemical Intuition

The fabrication of nanomaterials involves self-ordering processes of functional molecules on inorganic surfaces. To obtain specific molecular arrangements, a common strategy is to equip molecules with functional groups. However, focusing on the functional groups alone does not provide a comprehensive picture. Especially at interfaces, processes that govern self-ordering are complex and involve various physical and chemical effects, often leading to structures that defy chemical intuition, as we showcase here on the example of a homologous series of quinones on Ag(111). From chemical intuition one could expect that such quinones, which all bear the same functionalization, form similar motifs. In salient contrast, our joint theoretical and experimental study shows that profoundly different structures are formed. Using a machine-learning-based structure search algorithm, we find that this is due to a shift of the balance of three antagonizing driving forces: adsorbate-substrate interactions governing adsorption sites, adsorbate-adsorbate interactions favoring close packing, and steric hindrance inhibiting certain otherwise energetically beneficial molecular arrangements. The theoretical structures show excellent agreement with our experimental characterizations of the organic/inorganic interfaces, both for the unit cell sizes and the orientations of the molecules within. With a detailed examination of all driving forces, we are further able to devise a design principle for self-assembly of functionalized molecules. The non-intuitive interplay of similarly strong interaction mechanisms will continue to be a challenging aspect for the design of functional interfaces. Our agreement between theory and experiment combined with the new physical insights indicates that these methods have now reached the necessary accuracy to do so.

cond-mat.mes-hall↗

arXiv2020

Reproducibility of Potential Energy Surfaces of Organic/Metal Interfaces on the Example of PTCDA on Ag(111)

Molecular adsorption at organic/metal interfaces depends on a range of mechanisms: covalent bonds, charge transfer, Pauli repulsion and van der Waals (vdW) interactions shape the potential energy surface (PES), making it key to understanding organic/metal interfaces. Describing such interfaces with density functional theory requires carefully selecting the exchange correlation (XC) functional and vdW correction scheme. To explore the reproducibility of the PES with respect to the choice of method, we present a benchmark of common local, semi-local and non-local XC functionals in combination with various vdW corrections. We benchmark these methods using perylenetetracarboxylic dianhydride (PTCDA) on Ag(111), one of the most frequently studied organic/metal interfaces. For each method, we determine the PES using a Gaussian process regression algorithm, which requires only about 50 DFT calculations as input. This allows a detailed analysis of the PESs' features, such as the positions and energies of minima and saddle points. Comparing the results from different combinations of XC functionals and vdW corrections enables us to identify trends and differences between the approaches. PESs for different computation methods are in qualitative agreement, but also displaying significant quantitative differences. In particular, lateral positions of adsorption geometries agree well with experiment, while adsorption heights, energies and barriers show larger discrepancies.

physics.comp-ph↗

arXiv2019

SAMPLE: Surface structure search enabled by coarse graining and statistical learning

In this publication we introduce SAMPLE, a structure search approach for commensurate organic monolayers on inorganic substrates. Such monolayers often show rich polymorphism with diverse molecular arrangements in differently shaped unit cells. Determining the different commensurate polymorphs from first principles poses a major challenge due to the large number of possible molecular arrangements. To meet this challenge, SAMPLE employs coarse-grained modeling in combination with Bayesian linear regression to efficiently map the minima of the potential energy surface. In addition, it uses ab initio thermodynamics to generate phase diagrams. Using the example of naphthalene on Cu(111), we comprehensively explain the SAMPLE approach and demonstrate its capabilities by comparing the predicted with the experimentally observed polymorphs.

cond-mat.mtrl-sci↗

arXiv2019

Understanding the correlation between electronic coupling and energetic stability of molecular crystal polymorphs: The instructive case of quinacridone

A crucial factor determining charge transport in organic semiconductors is the electronic coupling between the molecular constituents, which is heavily influenced by the relative arrangement of the molecules. This renders quinacridone, with its multiple, structurally fundamentally different polymorphs and their diverse intermolecular interactions an ideal test case for analyzing the correlation between the electronic coupling in a specific configuration and the configuration's energetic stability. To provide an in-depth analysis of this correlation, starting from the $α$-polymorph of quinacridone, we also construct a coplanar model crystal. This allows us to systematically compare the displacement-dependence of the electronic coupling with that of the total energy. In this way, we identify the combination of Pauli repulsion and orbital rehybridization as the driving force steering the system towards a structure in which the electronic coupling is minimal (especially for the valence band and at small displacements). The general nature of these observations is supported by equivalent trends for an analogous pentacene model system. This underlines that the design of high-performance materials cannot rely on the "natural" assembly of the $π$-conjugated backbones of organic semiconductors into their most stable configurations. Rather, it must include the incorporation of functional groups that steer crystal packing towards more favorable structures, where aiming for short-axis displacements or realizing comparably large long-axis displacements appear as strategies worthwhile exploring.

cond-mat.mtrl-sci↗

arXiv2018

Leaving the Valley: Charting the Energy Landscape of Metal/Organic Interfaces via Machine Learning

The rich polymorphism exhibited by inorganic/organic interfaces is a major challenge for materials design. In this work we present a method to efficiently explore the potential energy surface and predict the formation energies of polymorphs and defects. This is achieved by training a machine learning model on a list of only 100 candidate structures that are evaluated via dispersion-corrected Density Functional Theory (DFT) calculations. We demonstrate the power of this approach for tetracyanoethylene on Ag(100) and explain the anisotropic ordering that is observed experimentally.

cond-mat.mtrl-sci↗