Polymorphism mediated by electric fields: a first principles study on organic/inorganic interfaces.

Organic/inorganic interfaces are known to exhibit rich polymorphism, where different polymorphs often possess significantly different properties. Which polymorph forms during an experiment depends strongly on environmental parameters such as deposition temperature and partial pressure of the molecule to be adsorbed. To prepare desired polymorphs these parameters are varied. However, many polymorphs are difficult to access within the experimentally available temperature-pressure ranges. In this contribution, we investigate how electric fields can be used as an additional lever to make certain structures more readily accessible. On the example of tetracyanoethylene (TCNE) on Cu(111), we analyze how electric fields change the energy landscape of interface systems. TCNE on Cu(111) can form either lying or standing polymorphs, which exhibit significantly different work functions. We combine first-principles calculations with a machine-learning based structure search algorithm and ab initio thermodynamics to demonstrate that electric fields can be exploited to shift the temperature of the phase transition between standing and lying polymorphs by up to 100 K.

Autonomous Single-Molecule Manipulation Based on Reinforcement Learning.

Building nanostructures one-by-one requires precise control of single molecules over many manipulation steps. The ideal scenario for machine learning algorithms is complex, repetitive, and time-consuming. Here, we show a reinforcement learning algorithm that learns how to control a single dipolar molecule in the electric field of a scanning tunneling microscope. Using about 2250 iterations to train, the algorithm learned to manipulate the molecule toward specific positions on the surface. Simultaneously, it generates physical insights into the movement as well as orientation of the molecule, based on the position where the electric field is applied relative to the molecule. This reveals that molecular movement is strongly inhibited in some directions, and the torque is not symmetric around the dipole moment.

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 requires 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.

Note: Reproducibility of potential energy surfaces of organic/metal interfaces on the example of PTCDA on Ag(111).

We recently published a benchmark study of common local, semi-local, and non-local exchange correlation functionals in combination with various van der Waals (vdW) corrections, where we investigated the reproducibility of the potential energy surface of perylenetetracarboxylic dianhydride on Ag(111). This Note presents an additional benchmark of the recently developed non-local many body dispersion (MBD-NL) vdW correction, coupled with the Perdew-Burke-Ernzerhof (PBE) functional. We find that this computation method shows similar performance as the established approaches. Notably, it yields very similar results as PBE + MBD.

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.

Correlation between two- and three-dimensional crystallographic lattices for epitaxial analysis. II. Experimental results.

While the crystal structure of the polymorph phase can be studied in three dimensions conveniently by X-ray methods like grazing-incidence X-ray diffraction (GIXD), the first monolayer is only accessible by surface-sensitive methods that allow the determination of a two-dimensional lattice. Here, GIXD measurements with sample rotation are compared with distortion-corrected low-energy electron diffraction (LEED) experiments on conjugated molecules: 3,4;9,10-perylenetetracarboxylic dianhydride (PTCDA), 6,13-pentacenequinone (P2O), 1,2;8,9-dibenzopentacene (trans-DBPen) and dicyanovinyl-quaterthiophene (DCV4T-Et2) grown by physical vapor deposition on Ag(111) and Cu(111) single crystals. For these molecular crystals, which exhibit different crystallographic lattices and crystal orientations as well as epitaxial properties, the geometric parameters of the three-dimensional lattice are compared with the corresponding geometry of the first monolayer. A comparison of the monolayer lattice from LEED investigations with the multilayer lattices determined by rotated GIXD experiments reveals a correlation between the first monolayer and the epitaxial growth of three-dimensional crystals together with lattice distortions and re-alignment of molecules. The selected examples show three possible scenarios of crystal growth on top of an ordered monolayer: (i) growth of a single polymorph, (ii) growth of three different polymorphs; in both cases the first monolayer serves as template. In the third case (iii) strong lattice distortion and distinct molecular re-alignments from the monolayer to epitaxially grown crystals are observed. This is the second part of our work concerning the correlation between two- and three-dimensional crystallographic lattices for epitaxial analysis. In the first part, the theoretical basis has been derived which provides a mathematical relationship between the six lattice parameters of the three-dimensional case and the three parameters obtained for the two-dimensional surface unit cell, together with their orientation to the single-crystalline substrate. In this work, a combined experimental approach of GIXD and LEED is introduced which can be used to investigate the effect of the epitaxial monolayer on the structural properties of molecular crystals grown on top.

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 (as would be obtained from X-ray standing wave measurements), which are ideal properties to read out 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.

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 on 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.

Toward 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 preferred 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 transition 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 reorientation of the molecules, which is thermodynamically more favorable for high dosages, but still high enough to enable ordered growth through diffusion of molecules. On the basis of the temperature-dependent diffusion and reorientation rates, we propose a temperature range at which the reorientation can be successfully suppressed.

Can We Predict Interface Dipoles Based on Molecular Properties?

We apply high-throughput density functional theory 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: (1) hypothetical, free-standing self-assembled monolayers with a large intrinsic dipole moment and (2) 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 the literature. For the latter, highly accurate correlations are found, which are, however, clearly unphysical.

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 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.

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

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 and the organic components of a hybrid interface, the proper choice of the electronic structure method, of the algorithms to solve these methods, and of the parameters that enter these algorithms is highly non-trivial. In fact, computational choices that work well for one of the components often perform poorly for the other. As a consequence, default settings for one materials class are typically inadequate for the hybrid system, which makes calculations employing such settings inefficient and sometimes even prone to erroneous results. To address this issue, we discuss how to choose appropriate atomistic representations for the system under investigation, we highlight the role of the exchange-correlation functional and the van der Waals correction employed in the calculation and we provide tips and tricks how to efficiently converge the self-consistent field cycle and to obtain accurate geometries. We particularly focus on potentially unexpected pitfalls and the errors they incur. As a summary, we provide a list of best practice rules for interface simulations that should especially serve as a useful starting point for less experienced users and newcomers to the field.

Nonintuitive Surface Self-Assembly of Functionalized Molecules on Ag(111).

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 unexpected structures, as we showcase here on the example of a homologous series of quinones on Ag(111). Naively, 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. The nonintuitive interplay of similarly important interaction mechanisms will continue to be a challenging aspect for the design of functional interfaces. With a detailed examination of all driving forces, we are, however, still able to devise a design principle for self-assembly of functionalized molecules.

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 perylene-tetracarboxylic dianhydride 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 density functional theory 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 display significant quantitative differences. In particular, the lateral positions of adsorption geometries agree well with experiment, while adsorption heights, energies, and barriers show larger discrepancies.

Electrostatic Design of 3D Covalent Organic Networks.

An innovative strategy for electrostatically designing the electronic structure of 3D bulk materials is proposed to control charge carriers at the nanoscale. This is achieved by shifting the electronic levels of chemically identical semiconducting elements through the periodic arrangement of polar functional groups. For the example of covalent organic networks, by first-principles calculations, the resulting collective electrostatic effects are shown to allow a targeted manipulation of the electronic landscape such that spatially confined pathways for electrons and holes can be realized. Mimicking donor-acceptor bulk heterojunctions, the new materials hold high promise for photovoltaic applications. The distinct advantage over the conventional approach of splitting excitons through chemically distinct donor and acceptor units is that here the magnitude of the band offset can be continuously tuned by varying the dipole density. A particularly promising feature of the suggested strategy is its structural versatility, which also enables the realization of more complex quantum structures such as quantum-cascades and quantum-checkerboards.