# Bjørk Hammer's research while affiliated with Aarhus University and other places

## Publications (270)

Preprint
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Determination of crystal structures of nanocrystalline or amorphous compounds is a great challenge in solid states chemistry and physics. Pair distribution function (PDF) analysis of X-Ray or neutron total scattering data has proven to be a key element in tackling this challenge. However, in most cases a reliable structural motif is needed as start...
Preprint
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We describe a local surrogate model for use in conjunction with global structure search methods. The model follows the Gaussian approximation potential (GAP) formalism and is based on a the smooth overlap of atomic positions descriptor with sparsification in terms of a reduced number of local environments using mini-batch $k$-means. The model is im...
Article
Context. Fragmentation is an important decay mechanism for polycyclic aromatic hydrocarbons (PAHs) under harsh interstellar conditions and represents a possible formation pathway for small molecules such as H 2 , C 2 H 2 , and C 2 H 4 . Aims. Our aim is to investigate the dissociation mechanism of superhydrogenated PAHs that undergo energetic proce...
Article
Modelling and understanding properties of materials from first principles require knowledge of the underlyingatomistic structure. This entails knowing the individual chemical identity and position of all atoms involved.Obtaining such information for macro-molecules, nano-particles, clusters, and for the surface, interface, andbulk phases of amorpho...
Preprint
Full-text available
Fragmentation is an important decay mechanism for polycyclic aromatic hydrocarbons (PAHs) under harsh interstellar conditions and represents a possible formation pathway for small molecules such as H2, C2H2, C2H4. Our aim is to investigate the dissociation mechanism of superhydrogenated PAHs that undergo energetic processing and the formation pathw...
Preprint
Full-text available
Dimerization of polycyclic aromatic hydrocarbons (PAHs) is an important, yet poorly understood, step in the on-surface synthesis of graphene (nanoribbon), soot formation, and growth of carbonaceous dust grains in the interstellar medium (ISM). The on-surface synthesis of graphene and the growth of carbonaceous dust grains in the ISM require the che...
Article
Dimerization of polycyclic aromatic hydrocarbons (PAHs) is an important, yet poorly understood, step in the on-surface synthesis of graphene (nanoribbon), soot formation, and growth of carbonaceous dust grains in the interstellar medium (ISM). The on-surface synthesis of graphene and the growth of carbonaceous dust grains in the ISM require the che...
Article
Full-text available
Determination of the atomic structure of solid surfaces typically depends on comparison of measured properties with simulations based on hypothesized structural models. For simple structures, the models may be guessed, but for more complex structures there is a need for reliable theory‐based search algorithms. So far, such methods have been limited...
Preprint
Full-text available
Modelling and understanding properties of materials from first principles require knowledge of the underlying atomistic structure. This entails knowing the individual identity and position of all involved atoms. Obtaining such information for macro-molecules, nano-particles, clusters, and for the surface, interface, and bulk phases of amorphous and...
Article
Determination of the atomic structure of solid surfaces typically depends on comparison of measured properties with simulations based on hypothesized structural models. For simple structures, the models may be guessed, but for more complex structures there is a need for reliable theory‐based search algorithms. So far, such methods have been limited...
Article
Full-text available
Room temperature oxygen hydrogenation below graphene flakes supported by Ir(111) is investigated through a combination of X-ray photoelectron spectroscopy, scanning tunneling microscopy, and density functional theory calculations using an evolutionary search algorithm. We demonstrate how the graphene cover and its doping level can be used to trap a...
Article
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Chemical space is routinely explored by machine learning methods to discover interesting molecules, before time-consuming experimental synthesizing is attempted. However, these methods often rely on a graph representation, ignoring 3D information necessary for determining the stability of the molecules. We propose a reinforcement learning approach...
Preprint
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Determination of the atomic structure of solid surfaces is a challenge that has resisted solution despite advancements in experimental methods. Theory-based global optimization has the potential to revolutionize the field by providing reliable structure models as the basis for interpretation of experiments and for prediction of material properties....
Preprint
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Chemical space is routinely explored by machine learning methods to discover interesting molecules, before time-consuming experimental synthesizing is attempted. However, these methods often rely on a graph representation, ignoring 3D information necessary for determining the stability of the molecules. We propose a reinforcement learning approach...
Article
Nanomaterials based on MoS 2 and related transition metal dichalcogenides are remarkably versatile; MoS 2 nanoparticles are proven catalysts for processes such as hydrodesulphurization and the hydrogen evolution reaction, and transition metal...
Preprint
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Global Optimization with First-principles Energy Expressions (GOFEE) is an efficient method for identifying low energy structures in computationally expensive energy landscapes such as the ones described by density functional theory (DFT), van der Waals-enabled DFT, or even methods beyond DFT. GOFEE relies on a machine learned surrogate model of en...
Article
We utilized scanning tunneling microscopy (STM) experiments and density functional theory (DFT) calculations to study the diffusion of ammonia (NH3) on anatase TiO2(101). From time-lapsed STM imaging, we observed monomeric and dimeric diffusion channels, and a general tendency to higher diffusion rates with increasing NH3 coverage. In surface regio...
Article
The recently proposed atomistic structure learning algorithm (ASLA) builds on neural network enabled image recognition and reinforcement learning. It enables fully autonomous structure determination when used in combination with a first-principles total energy calculator, e.g., a density functional theory (DFT) program. To save on the computational...
Article
The success of applying machine learning to speed up structure search and improve property prediction in computational chemical physics depends critically on the representation chosen for the atomistic structure. In this work, we investigate how different image representations of two planar atomistic structures (ideal graphene and graphene with a g...
Preprint
The recently proposed Atomistic Structure Learning Algorithm (ASLA) builds on neural network enabled image recognition and reinforcement learning. It enables fully autonomous structure determination when used in combination with a first-principles total energy calculator, e.g. a density functional theory (DFT) program. To save on the computational...
Article
We demonstrate how image recognition and reinforcement learning combined may be used to determine the atomistic structure of reconstructed crystalline surfaces. A deep neural network represents a reinforcement learning agent that obtains training rewards by interacting with an environment. The environment contains a quantum mechanical potential ene...
Article
Light weight and cheap electrolytes with fast multi-valent ion conductivity can pave the way for future high-energy density solid-state batteries, beyond the lithium-ion battery. Here we present the mechanism of Mg-ion conductivity of ammine magnesium borohydrides, Mg(BH4)2·xNH3 (x = 1, 2, 3, 6). Density functional theory calculations (DFT) reveal...
Article
We propose a scheme for global optimization with first-principles energy expressions of atomistic structure. While unfolding its search, the method actively learns a surrogate model of the potential energy landscape on which it performs a number of local relaxations (exploitation) and further structural searches (exploration). Assuming Gaussian pro...
Article
We propose a global optimization strategy for atomistic structure determination based on two new concepts: a few-atom complementary energy landscape and atomic role models. Global optimization of costly energy expressions may be aided by performing some of the optimization on model energy landscapes. These are often based on a sum-of-atomic-contrib...
Article
The characterisation of the interaction between nano- or sub-nano-particles with a support nowadays increasingly relies on computational modelling by means of the density functional theory calculations. These provide valuable atomic-detail understanding of the structure and energetics of supported clusters, but it is still challenging to find (or d...
Article
One endeavor of modern physical chemistry is to use bottom-up approaches to design materials and drugs with desired properties. Here, we introduce an atomistic structure learning algorithm (ASLA) that utilizes a convolutional neural network to build 2D structures and planar compounds atom by atom. The algorithm takes no prior data or knowledge on a...
Preprint
We propose a scheme for global optimization with first-principles energy expressions (GOFEE) of atomistic structure. While unfolding its search, the method actively learns a surrogate model of the potential energy landscape on which it performs a number of local relaxations (exploitation) and further structural searches (exploration). Assuming Gaus...
Article
Functionalization of graphene on Ir(111) is a promising route to modify graphene by chemical means in a controlled fashion at the nanoscale. Yet, the nature of such functionalized sp³ nanodots remains unknown. Density functional theory (DFT) calculations alone cannot differentiate between two plausible structures, namely true graphane and substrate...
Preprint
One endeavour of modern physical chemistry is to use bottom-up approaches to design materials and drugs with desired properties. Here we introduce an atomistic structure learning algorithm (ASLA) that utilizes a convolutional neural network to build 2D compounds and layered structures atom by atom. The algorithm takes no prior data or knowledge on...
Article
We studied the interaction of water with the anatase TiO2(001) surface by means of scanning tunneling microscopy, x-ray photoelectron spectroscopy, and density functional theory calculations. Water adsorbs dissociatively on the ridges of a (1×4) reconstructed surface, resulting in a (3×4) periodic structure of hydroxyl pairs. We observed this proce...
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We present an extended metal-coordinated structure obtained by deposition of trimesic acid (TMA) onto the Ag(111) surface under ultra-high vacuum conditions followed by annealing to 510 K. Scanning tunneling microscopy and density functional theory calculations reveal the structure to consist of metal clusters containing seven Ag atoms each, coordi...
Article
We show how to speed up global optimization of molecular structures using machine learning methods. To represent the molecular structures, we introduce the auto-bag feature vector that combines (i) a local feature vector for each atom, (ii) an unsupervised clustering of such feature vectors for many atoms across several structures, and (iii) a coun...
Preprint
We show how to speed up global optimization of molecular structures using machine learning methods. To represent the molecular structures we introduce the auto-bag feature vector that combines: i) a local feature vector for each atom, ii) an unsupervised clustering of such feature vectors for many atoms across several structures, and iii) a count f...
Article
Full-text available
Hydrodesulfurization catalysis ensures upgrading and purification of fossil fuels to comply with increasingly strict regulations on S emissions. The future shift toward more diverse and lower-quality crude oil supplies, high in S content, requires attention to improvements of the complex sulfided CoMo catalyst based on a fundamental understanding o...
Article
Understanding interactions and structural properties at the atomic level is often a prerequisite to the design of novel materials. Theoretical studies based on quantum-mechanical first-principles calculations can provide this knowledge, but at an immense computational cost. In recent years, machine learning has been successful in predicting structu...
Article
We present a method for accelerating the global structure optimization of atomic compounds. The method is demonstrated to speed up the finding of the anatase TiO2 (001)-(1×4) surface reconstruction within a density functional tight-binding theory framework using an evolutionary algorithm. As a key element of the method, we use unsupervised machine...
Article
We show that approximate structural relaxation with a neural network enables orders of magnitude faster global optimization with an evolutionary algorithm in a density functional theory framework. The increased speed facilitates reliable identification of global minimum energy structures, as exemplified by our finding of a hollow Pt13 nanoparticle...
Preprint
Nanomaterials based on MoS2 are remarkably versatile; MoS2 nanoparticles are proven catalysts for processes such as hydrodesulphurization and the hydrogen evolution reaction, and transition metal dichalcogenides in general have recently emerged as novel 2D components for nanoscale electronics and optoelectronics. The properties of such materials ar...
Article
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The behavior of naphthalene on Pt(111) surfaces is studied by combining insight from scanning tunneling microscopy (STM) and van der Waals enabled density functional theory. Adsorption, diffusion, and rotation are investigated by a series of variable temperature STM experiments revealing naphthalene ability to rotate on-site with ease with a rotati...
Article
The adsorption of ammonia on anatase TiO2 is of fundamental importance for several catalytic applications of TiO2 and for probing acid-base interactions. Utilizing high-resolution scanning tunneling microscopy (STM), synchrotron X-ray photoelectron spectroscopy, temperature-programmed desorption (TPD), and density functional theory (DFT), we identi...
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Hydrogen functionalization of graphene by exposure to vibrationally excited H2 molecules is investigated by combined scanning tunneling microscopy, high resolution electron energy loss spectroscopy, x-ray photoemission spectroscopy measurements and density functional theory calculations. The measurements reveal that vibrationally excited H2 molecul...
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Machine learning (ML) is used to derive local stability information for density functional theory calculations of systems in relation to the recently discovered SnO2(110)−(4×1) reconstruction. The ML model is trained on (structure, total energy) relations collected during global minimum energy search runs with an evolutionary algorithm (EA). While...
Article
The ability to navigate vast energy landscapes of molecules, clusters, and solids is a necessity for discovering novel compounds in computational chemistry and materials science. For high-dimensional systems it is only computationally feasibly to search a small portion of the landscape, and hence the search strategy is of critical importance. Intro...
Article
Low-resistance Ohmic contacts are a challenge for electronic devices based on two-dimensional (2D) materials. We show that an atomically precise in-plane junction between a 2D semiconductor and a metallic contact can lead to a semiconductor-to-metal transition in the 2D material, a finding which points the way to a possible method of achieving low-...
Article
Molecular conformational flexibility can play an important role in supramolecular self-assembly on surfaces, affecting not least chiral molecular assemblies. To explicitly and systematically investigate the role of molecular conformational flexibility in surface self-assembly, we synthesized a three-bit conformational switch where each of three swi...
Article
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Using surface x-ray diffraction (SXRD), quantitative low-energy electron diffraction (LEED), and density-functional theory (DFT) calculations, we have determined the structure of the (4×1) reconstruction formed by sputtering and annealing of the SnO2(110) surface. We find that the reconstruction consists of an ordered arrangement of Sn3O3 clusters...
Article
Low-resistance ohmic contacts are a challenge for electronic devices based on two-dimensional materials. We show that an atomically precise junction between a two-dimensional semiconductor and a metallic contact can lead to a semiconductor-to-metal transition in the two-dimensional material--a finding which points the way to a possible method of ac...
Article
Interaction forces between aromatic moieties, often referred to as π–π interactions, are an important element in stabilizing complex supramolecular structures. For supramolecular self-assembly occurring on surfaces, where aromatic moieties are typically forced to adsorb coplanar with the surface, the possible role of intermolecular aromatic interac...
Article
A tandem experimental and theoretical investigation of a mesoporous ceria catalyst reveals the properties of the metal oxide are conducive for activity typically ascribed to metals, suggesting reduced Ce3+ and oxygen vacancies are responsible for the inherent bi-functionality of CO oxidation and dissociation of water required for facilitating the p...
Article
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The modification of heterogeneous catalysts through the chemisorption of chiral molecules is a method to create catalytic sites for enantioselective surface reactions. The chiral molecule is called a chiral modifier by analogy to the terms chiral auxiliary or chiral ligand used in homogeneous asymmetric catalysis. While there has been progress in u...
Article
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Elementary steps in enantioselective heterogeneous catalysis take place on the catalyst surface and the targeted synthesis of a desired enantiomer requires the implantation of chiral information at the surface, which can be achieved—for example—by adsorbing chiral molecules. Studies of the structures of complexes formed between adsorbed prochiral r...
Article
The Atomic Simulation Environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simula- tions. In ASE, tasks are fully scripted in Python. The powerful syntax of Python combined with the NumPy array library make it possible to perform very complex simulation task...
Article
Predicting structures at the atomic scale is of great importance for understanding the properties of materials. Such predictions are infeasible without efficient global optimization techniques. Many current techniques produce a large amount of idle intermediate data before converging to the global minimum. If this information could be analyzed duri...
Article
Full-text available
The Atomic Simulation Environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simulations. In ASE, tasks are fully scripted in Python. The powerful syntax of Python combined with the NumPy array library make it possible to perform very complex simulation tasks....
Article
Full-text available
Self-assembly of a molecule with many distinct conformational states, resulting in eight possible pairs of surface enantiomers, is investigated on a Au(111) surface under UHV conditions. The complex molecule is equipped with alkyl and carboxyl moieties to promote controlled self-assembly of lamellae structures. From statistical analysis of Scanning...
Article
Band gap engineering in hydrogen functionalized graphene is demonstrated by changing the symmetry of the functionalization structures. Small differences in hydrogen adsorbate binding energies on graphene on Ir(111) allow tailoring of highly periodic functionalization structures favoring one distinct region of the moiré super-cell. Scanning tunnelin...
Article
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The changes in the strength of the interaction between the polycyclic aromatic hydrocarbon, coronene, and graphite as a function of the degree of super-hydrogenation of the coronene molecule are investigated using temperature programmed desorption. A decrease in binding energy is observed for increasing degrees of super-hydrogenation, from 1.78 eV...
Article
A robust, efficient, dynamic, and automated nudged elastic band (AutoNEB) algorithm to effectively locate transition states is presented. The strength of the algorithm is its ability to use fewer resources than the nudged elastic band (NEB) method by focusing first on converging a rough path before improving upon the resolution around the transitio...
Article
Single-layer TaS$_2$ is epitaxially grown on Au(111) substrates. The resulting two-dimensional crystals adopt the 1H polymorph. The electronic structure is determined by angle-resolved photoemission spectroscopy and found to be in excellent agreement with density functional theory calculations. The single layer TaS$_2$ is found to be strongly n-dop...
Article
The adsorption, diffusion, and dissociation of pyridine, C5H5N, on Pt(111) are investigated with van der Waals-corrected density functional theory. An elaborate search for local minima in the adsorption potential energy landscape reveals that the intact pyridine adsorbs with the aromatic ring parallel to the surface. Piecewise interconnections of t...
Article
Photoreduction of CO2 for fuel production is considered to be an ultimate solution to today's energy crisis. Platinum (Pt) particles are known to promote photocatalysis reactions when loaded on the surface of titanium dioxide (TiO2). In this study, we investigate the initial step of the reduction process of CO2 with water, i.e., the formation of fo...
Article
The electronic structure of epitaxial single-layer MoS$_2$ on Au(111) is investigated by angle-resolved photoemission spectroscopy, scanning tunnelling spectroscopy, and first principles calculations. While the band dispersion of the supported single-layer is close to a free-standing layer in the vicinity of the valence band maximum at $\bar{K}$ an...
Article
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We report on the structural and electronic properties of a single bismuth layer intercalated underneath a graphene layer grown on an Ir(111) single crystal. Scanning tunneling microscopy (STM) reveals a hexagonal surface structure and a dislocation network upon Bi intercalation, which we attribute to a $\sqrt{3}\times\sqrt{3}R30{\deg}$ Bi structure...
Article
We present a comprehensive theoretical investigation of the structures formed by self-assembly of tetrahydroxybenzene (THB)-derivatives on Cu(111). The THB molecule is known to dehydrogenate completely during annealing, forming a reactive radical which assembles into a close-packed structure or a porous metal-coordinated network depending on the co...
Article
Finding the active sites of catalysts and photo-catalysts is crucial for an improved fundamental understanding and the development of efficient catalytic systems. Here we have studied the photo-activated dehydrogenation of ethanol on reduced and oxidized rutile TiO2(110) in ultrahigh vacuum conditions. Utilizing scanning tunnelling microscopy, vari...
Article
Materials based on MoS2 are widely used as catalysts and their structure usually consists of single-layered MoS2 nanoparticles whose edges are known to constitute the catalytically active sites. Methods based on the density functional theory are used in this work to calculate the electronic structure of representative computational models of MoS2 n...
Article
Full-text available
A comparative study of chemisorbed bimolecular diastereomeric complexes formed by three structurally analogous chiral modifiers and a prochiral substrate on Pt(111) was performed using scanning tunneling microscopy (STM) and density functional theory (DFT) methods. The experiments determine, subject to a number of assumptions, the abundant binding...