arXiv subjects

Oliver T. Hofmann

Publications and source records attributed to Oliver T. Hofmann.

At least 19 recordsLinked to original sources

arXiv2026

Computational Determination of Optimal Growth Protocols for Metastable Polymorphs

The reliable growth of a desired target structure remains a central challenge for organic-inorganic interfaces. Specific interface structures can exhibit properties that are superior compared to those of other possible interface structures, but identifying growth conditions that selectively produce a given surface structure is difficult, particularly when the target structure is thermodynamically metastable. Here, we demonstrate how time-dependent temperature and pressure protocols can be optimized to promote the high-yield formation of a metastable surface polymorph. To this end, we combine kinetic Monte Carlo simulations with a parameterized nucleation-and-growth model and apply optimal control theory to predict growth recipes that maximize the yield of the desired target structure. Applying this approach to a prototypical model of an organic molecules adsorbed on a metal surface, we identify experimentally plausible protocols that guide the system through phase space while avoiding kinetic growth regimes in which formation of the thermodynamically stable structure is favored. Compared to a manually optimized three-step protocol, the optimized control trajectory increases the yield of the desired metastable phase from 73 % to 97 % for the same total protocol duration.

cond-mat.mtrl-sci↗

arXiv2026

Impact of the Lattice Constant on the Polymorphism of Organic/Inorganic Interfaces

The polymorphism of organic/metal interfaces influences many of their properties. As a result, a host of contemporary research focuses on analyzing the factors which are pertinent for modifying polymorphism. In this work, we elucidate how the lattice constant of the underlying lattice affects the energetic landscape of adsorbate monolayers for the model system of tetracyanoquinodimethane (TCNQ) on coinage metal surfaces with varying lattice constants. In particular, we focus on how the adsorbateadsorbate and the adsorbate-substrate interaction are affected when increasing the lattice constant and changing the surface chemistry. Based on these investigations, we show that the adsorbate-substrate interaction for some adsorption geometries can change significantly with the lattice constant. In addition, due to a transition from repulsive to attractive adsorbate-adsorbate interactions, polymorphs with tight packing become more favorable, if the lattice constant is increased, resulting in a lattice-constant-based phase transition.

cond-mat.mtrl-sci↗

arXiv2026

Roadmap on Advancements of the FHI-aims Software Package

Electronic-structure theory is the foundation of the description of materials including multiscale modeling of their properties and functions. Obviously, without sufficient accuracy at the base, reliable predictions are unlikely at any level that follows. The software package FHI-aims has proven to be a game changer for accurate free-energy calculations because of its scalability, numerical precision, and its efficient handling of density functional theory (DFT) with hybrid functionals and van der Waals interactions. It treats molecules, clusters, and extended systems (solids and liquids) on an equal footing. Besides DFT, FHI-aims also includes quantum-chemistry methods, descriptions for excited states and vibrations, and calculations of various types of transport. Recent advancements address the integration of FHI-aims into an increasing number of workflows and various artificial intelligence (AI) methods. This Roadmap describes the state-of-the-art of FHI-aims and advancements that are currently ongoing or planned.

cond-mat.mtrl-sci↗

arXiv2026

Emergent Rate Laws for Collective Lying-Standing Transitions

Lying-standing transitions in the first molecular monolayer at organic-inorganic interfaces strongly influence interface dipoles, energy-level alignment, and growth modes, yet their collective kinetics remain difficult to predict. Here, we establish a quantitative adsorbate-to-kinetics relationship using first-principles-based kinetic Monte Carlo simulations combined with a mean-field coarse-graining strategy. Focusing on tetracyanoethylene on Cu(111), we show that the collective transition rate cannot be inferred from any single elementary step but emerges from coupled microscopic processes, including reorientation, adsorption, and diffusion. A local two-step reorientation mechanism captures the diffusion-limited regime, while diffusion of lying molecules accelerates the transition in diffusion-enhanced regimes by suppressing back-reorientation via vacancy-molecule decoupling. This effect is described by a regime-dependent geometric factor accounting for deviations between single-molecule and collective rate constants. By varying molecular size and footprint ratio, we demonstrate that geometry is an intrinsic control parameter. While the collective rate scales approximately with molecular area, increasing the footprint ratio between lying and standing configurations yields order-of-magnitude accelerations due to enhanced vacancy creation and diffusion-assisted stabilization. Finally, we derive an analytical expression for the collective reorientation rate constant linking temperature- and pressure-dependent microscopic rate constants to geometric parameters. The formulation reproduces the simulations across kinetic regimes and provides transferable design principles for engineering lying-standing transition timescales at organic-inorganic interfaces.

physics.comp-ph↗

arXiv2025

Metastable Monolayer Formation through a Connector Structure

The intentional growth of metastable surface structures of organic molecules adsorbed on inorganic substrates is a challenging task. It is usually unclear which kinetic mechanism leads to the metastable surface polymorph after a deposition experiment. In this work we investigate a growth procedure that allows to intentionally grow a defined metastable surface structure starting from thermodynamic equilibrium. This procedure is applicable to organic-inorganic interface systems that exhibit a thermodynamically stable connector structure that can be exploited to grow the metastable target structure. With specific temperature and pressure changes in the system a significant yield of the target polymorph can be achieved. We demonstrate this procedure on a simplified microscopic interface system of rectangular molecules adsorbing on a square lattice substrate with kinetic Monte Carlo growth simulations.

cond-mat.mtrl-sci↗

arXiv2024

MAM-STM: A software for autonomous control of single moieties towards specific surface positions

In this publication we introduce MAM-STM, a software to autonomously manipulate arbitrary moieties towards specific positions on a metal surface utilizing the tip of a scanning tunneling microscope (STM). Finding the optimal manipulation parameters for a specific moiety is challenging and time consuming, even for human experts. MAM-STM combines autonomous data acquisition with a sophisticated Q-learning implementation to determine the optimal bias voltage, the z-approach distance, and the tip position relative to the moiety. This then allows to arrange single molecules and atoms at will. In this work, we provide a tutorial based on a simulated response to offer a comprehensive explanation on how to use and customize MAM-STM. Additionally, we assess the performance of the machine learning algorithm by benchmarking it within a simulated stochastic environment.

physics.app-ph↗

arXiv2023

The impact of static distortion waves on superlubricity

Friction is a major source of energy loss in mechanical devices. This energy loss may be minimized by creating interfaces with extremely reduced friction, i.e. superlubricity. Conventional wisdom holds that incommensurate interface structures facilitate superlubricity. Accurately describing friction necessitates precise modeling of the interface structure. This, in turn, requires the use of accurate first-principles electronic structure methods, especially when studying organic/metal interfaces, which are highly relevant due to their tunability and propensity to form incommensurate structures. However, the system size required to calculate incommensurate structures renders such calculations intractable. As a result, studies of incommensurate interfaces have been limited to very simple model systems or strongly simplified methodology. We overcome this limitation by developing a machine-learned interatomic potential that is able to determine energies and forces for structures containing thousands to tens of thousands of atoms with an accuracy comparable to conventional first principles methods but at a fraction of the cost. Using this approach, we quantify the breakdown of superlubricity in incommensurate structures due to the formation of static distortion waves. Moreover, we extract design principles to engineer incommensurate interface systems where the formation of static distortion waves is suppressed, which facilitates low friction coefficients.

cond-mat.mtrl-sci↗

arXiv2023

Kinetic trapping of charge-transfer molecules at metal interfaces

Despite the common expectation that conjugated organic molecules on metals tend to adsorb in a flat-lying wetting layer, several recent studies have found strong indications for coverage-dependent transitions to upright-standing phases, which exhibit notably different physical properties. In this work, we argue that from an energetic perspective, thermodynamically stable upright-standing phases may be more common than hitherto thought. However, for kinetic reasons this phase may often not be observed experimentally. Indeed, using first principles kinetic Monte Carlo simulations, we find that the structure with lower molecular density is (almost) always formed first, reminiscent of Ostwalds rule of stages. The phase transitions to the thermodynamically stable upright-standing phase are likely to be kinetically hindered under conditions typically used in surface science (gas phase adsorption at low flux). This provides a possible explanation why they are commonly not observed. Investigating both the role of the growth conditions and the energetics of the interface, we find that the time for the phase transition is determined mostly by the deposition rate and, thus, mostly independent of the nature of 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↗

arXiv2022

Numerical Quality Control for DFT-based Materials Databases

Electronic-structure theory is a strong pillar of materials science. Many different computer codes that employ different approaches are used by the community to solve various scientific problems. Still, the precision of different packages has only recently been scrutinized thoroughly, focusing on a specific task, namely selecting a popular density functional, and using unusually high, extremely precise numerical settings for investigating 71 monoatomic crystals. Little is known, however, about method- and code-specific uncertainties that arise under numerical settings that are commonly used in practice. We shed light on this issue by investigating the deviations in total and relative energies as a function of computational parameters. Using typical settings for basis sets and k-grids, we compare results for 71 elemental and 63 binary solids obtained by three different electronic-structure codes that employ fundamentally different strategies. On the basis of the observed trends, we propose a simple, analytical model for the estimation of the errors associated with the basis-set incompleteness. We cross-validate this model using ternary systems obtained from the NOMAD Repository and discuss how our approach enables the comparison of the heterogeneous data present in computational materials databases.

physics.comp-ph↗

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↗