arXiv subjects

Hannu-Pekka Komsa

Publications and source records attributed to Hannu-Pekka Komsa.

At least 19 recordsLinked to original sources

arXiv2026

Fine-tuning of universal machine-learning interatomic potentials for high-entropy alloys with application to 2D (Mo,Ta,Nb,W,V)S$_2$

High-entropy alloy (HEA) materials and their two-dimensional counterparts (2D-HEAs) have recently attracted attention due to their tunable properties and catalytic potential, yet their chemical complexity makes direct density functional theory (DFT) calculations computationally prohibitive. The complexity also makes training of machine-learning interatomic potentials (MLIPs) challenging, but this could possibly be overcome by employing universal MLIPs as starting point. In this work, we investigate the applicability of universal MLIP models for 2D transition metal dichalcogenide HEAs and develop effective fine-tuning strategies. Training structures are systematically generated and selected, and the performance of universal and fine-tuned models are benchmarked against DFT. We find that all universal MLIPs employed in this work yield unsatisfactory mixing energies without fine-tuning. Applied to the experimentally synthesized (Mo,Ta,Nb,W,V)S$_2$ system, fine-tuned models based on enumerated structures can achieve near-DFT accuracy in predicting mixing energies while enabling Monte-Carlo simulations and random structure sampling at scales inaccessible to DFT.

cond-mat.mtrl-sci↗

arXiv2026

Atomic-Scale Quantum Control of Single Spin Defects in a Two-Dimensional Semiconductor

Individual spin defects in solids are promising building blocks for quantum technologies, but their deterministic creation, individual addressability, and operation near surfaces remain major challenges. Two-dimensional materials provide an attractive alternative, as their single-layer thickness enables direct atomic-scale access to defect states. Here, we demonstrate single-spin control of solid-state defects in a two-dimensional semiconductor by a combination of scanning tunneling microscopy and electron spin resonance. We create and manipulate individual sulfur vacancies and carbon substitution defects in monolayer molybdenum disulfide and characterize their spin dynamics, including coherent control, at the single-defect level. Using atomic manipulation, we further engineer and probe spin-spin interactions between defect pairs. Our results demonstrate deterministic creation, addressability, coherent manipulation, and controlled coupling of individual spin defects within a single experimental platform. This establishes atomically engineered spin defects in two-dimensional semiconductors as a versatile class of controllable solid-state quantum systems and opens a route towards tailored quantum sensing experiments.

cond-mat.mes-hall↗

arXiv2026

Massive Discovery of Low-Dimensional Materials from Universal Computational Strategy

Low-dimensional materials have attractive properties that drive intense efforts for novel materials discovery. However, experiments are tedious for systematic discovery, and present computational methods are often tuned to two-dimensional (2D) materials, overlooking other low-dimensional materials. Here, we combined universal machine-learning interatomic potentials (UMLIPs) and an advanced, interatomic force constant (FC) -based dimensionality classification method to make a massive discovery of novel low-dimensional materials. We first benchmarked UMLIPs' first-principles-level accuracy in quantifying FCs and calculated phonons for 35,689 materials from the Materials Project database. We then used the FC-based method for dimensionality classification to discover 9139 low-dimensional materials, including 1838 0D clusters, 1760 1D chains, 3057 2D sheets/layers, and 2484 mixed-dimensionality materials, all of which conventional geometric descriptors have not recognized. By calculating the binding energies for the discovered 2D materials, we also identified 887 sheets that could be easily or potentially exfoliated from their parent bulk structures.

cond-mat.mtrl-sci↗

arXiv2025

Resistive switching behaviors in vertically aligned MoS$_2$ films with Cu, Ag, and Au electrodes

Neuromorphic computing circuits can be realized using memristors based on low-dimensional materials enabling enhanced metal diffusion for resistive switching. Here, we investigate memristive properties of vertically aligned MoS$_2$ (VA-MoS$_2$) films with three different metal electrodes: Ag, Cu, and Au. Despite having the same active material, all three metals show distinct switching behavior, which are crucial for neuromorphic computing applications: Ag enables volatile switching, Cu demonstrates stable non-volatile switching with retention over 2500 s, and Au shows no memristive response. Cu devices show abrupt resistance changes, and significant increase of copper content upon biasing, indicative of stable non-volatile switching based on filament formation and rupture. About 85% of Ag and Cu devices exhibit reliable memristor behavior. Our findings provide valuable insights into the memristive switching mechanism in VA-MoS$_2$ and present a promising avenue for facile fabrication of neuromorphic circuits by employing a set of different metals on a single active material.

cond-mat.mes-hall↗

arXiv2025

Screening of material defects using universal machine-learning interatomic potentials

Finding new materials with previously unknown atomic structure or materials with optimal set of properties for a specific application greatly benefits from computational modeling. Recently, such screening has been dramatically accelerated by the invent of universal machine-learning interatomic potentials that offer first principles accuracy at orders of magnitude lower computational cost. Their application to the screening of defects with desired properties or to finding new stable compounds with high density of defects, however, has not been explored. Here, we show that the universal machine-learning interatomic potentials have reached sufficient accuracy to enable large-scale screening of defective materials. We carried out vacancy calculations for 86 259 materials in the Materials Project database and analyzed the formation energies in terms of oxidation numbers. We further demonstrate the application of these models for finding new materials at or below the convex hull of known materials and for simulated etching of low-dimensional materials.

cond-mat.mtrl-sci↗

arXiv2024

Raman spectra of amino acids and peptides from machine learning polarizabilities

Raman spectroscopy is an important tool in the study of vibrational properties and composition of molecules, peptides and even proteins. Raman spectra can be simulated based on the change of the electronic polarizability with vibrations, which can nowadays be efficiently obtained via machine learning models trained on first-principles data. However, the transferability of the models trained on small molecules to larger structures is unclear and direct training on large structures in prohibitively expensive. In this work, we first train two machine learning models to predict polarizabilities of all 20 amino acids. Both models are carefully benchmarked and compared to DFT calculations, with neural network method found to offer better transferability. By combining machine learning models with classical force field molecular dynamics, Raman spectra of all amino acids are also obtained and investigated, showing good agreement with experiments. The models are further extended to small peptides. We find that adding structures containing peptide bonds to the training set greatly improves predictions even for peptides not included in training sets.

physics.comp-ph↗

arXiv2024

Tip-induced creation and Jahn-Teller distortions of sulfur vacancies in single-layer MoS$_{2}$

We present an atomically precise technique to create sulfur vacancies and control their atomic configurations in single-layer MoS$_{2}$. It involves adsorbed Fe atoms and the tip of a scanning tunneling microscope, which enables single sulfur removal from the top sulfur layer at the initial position of Fe. Using scanning tunneling spectroscopy, we show that the STM tip can also induce two Jahn-Teller distorted states with reduced orbital symmetry in the sulfur vacancies. Density functional theory calculations rationalize our experimental results. Additionally, we provide evidence for molecule-like hybrid orbitals in artificially created sulfur vacancy dimers, which illustrates the potential of our technique for the development of extended defect lattices and tailored electronic band structures.

cond-mat.mtrl-sci↗

arXiv2023

Polarizability Models for Simulations of Finite Temperature Raman Spectra from Machine Learning Molecular Dynamics

Raman spectroscopy is a powerful and nondestructive method that is widely used to study the vibrational properties of solids or molecules. Simulations of finite-temperature Raman spectra rely on obtaining polarizabilities along molecular dynamics trajectories, which is computationally highly demanding if calculated from first principles. Machine learning force fields (MLFF) are becoming widely used for accelerating molecular dynamics simulations, but machine-learning models for polarizability are still rare. In this work, we present and compare three polarizability models for obtaining Raman spectra in conjunction with MLFF molecular dynamics trajectories: (i) model based on projection to primitive cell eigenmodes, (ii) bond polarizability model, and (iii) symmetry-adapted Gaussian process regression (SA-GPR) using smooth overlap of atomic positions. In particular, we investigate the accuracy of these models for different systems and how much training data is required. Models are first applied to boron arsenide, where the first- and second-order Raman spectra are studied as well as the effect of boron isotopes. With MoS$_2$ we study the applicability of the models for highly anisotropic systems and for simulating resonant Raman spectra. Finally, inorganic halide perovskites CsPbBr$_3$ and CsSnBr$_3$ are studied with a particular interest in simulating the spectra across phase transitions and the evolution of the central peak. All models can be used to efficiently predict polarizabilities and are applicable to large systems and long simulation times, and while all three models were found to perform similarly for BAs and MoS$_2$, only SA-GPR offers sufficient flexibility to accurately describe complex anharmonic materials like the perovskites.

cond-mat.mes-hall↗

arXiv2023

Controlled defect production in monolayer MoS2 via electron irradiation at ultralow accelerating voltages

Control on spatial location and density of defects in 2D materials can be achieved using electron beam irradiation. Conversely, ultralow accelerating voltages (less than or equal to 5kV) are used to measure surface morphology, with no expected defect creation. We find clear signatures of defect creation in monolayer (ML) MoS2 at these voltages. Evolution of E' and A1' Raman modes with electron dose, and appearance of defect activated peaks indicate defect formation. To simulate Raman spectra of MoS2 at realistic defect distributions, while retaining density-functional theory accuracy, we combine machine-learning force fields for phonons and eigenmode projection approach for Raman tensors. Simulated spectra agree with experiments, with sulphur vacancies as suggested defects. We decouple defects, doping and carbonaceous contamination using control (hBN covered and encapsulated MoS2) samples. We observe cryogenic PL quenching and defect peaks, and find that carbonaceous contamination does not affect defect creation. These studies have applications in photonics and quantum emitters.

cond-mat.mes-hall↗

arXiv2022

Raman Spectra of Titanium Carbide MXene from Machine-Learning Force Field Molecular Dynamics

MXenes represent one of the largest class of 2D materials with promising applications in many fields and their properties tunable by the surface group composition. Raman spectroscopy is expected to yield rich information about the surface composition, but the interpretation of measured spectra has proven challenging. The interpretation is usually done via comparison to simulated spectra, but there are large discrepancies between the experimental and earlier simulated spectra. In this work, we develop a computational approach to simulate Raman spectra of complex materials that combines machine-learning force-field molecular dynamics and reconstruction of Raman tensors via projection to pristine system modes. The approach can account for the effects of finite temperature, mixed surfaces, and disorder. We apply our approach to simulate Raman spectra of titanium carbide MXene and show that all these effects must be included in order to properly reproduce the experimental spectra, in particular the broad features. We discuss the origin of the peaks and how they evolve with surface composition, which can then be used to interpret experimental results.

physics.comp-ph↗

arXiv2022

High-throughput computation of Raman spectra from first principles

Raman spectroscopy is a widely-used non-destructive material characterization method, which provides information about the vibrational modes of the material and therefore of its atomic structure and chemical composition. Interpretation of the spectra requires comparison to known references and to this end, experimental databases of spectra have been collected. Reference Raman spectra could also be simulated using atomistic first-principles methods but these are computationally demanding and thus the existing databases of computational Raman spectra are fairly small. In this work, we developed an optimized workflow to calculate the Raman spectra more efficiently compared to existing approaches. The workflow was benchmarked and validated by comparison to experiments and previous computational methods for select technologically relevant material systems. Using the workflow, we performed high-throughput calculations for a large set of materials (5099) belonging to many different material classes, and collected the results to a database. Finally, the contents of database are analyzed and the calculated spectra are shown to agree well with the experimental ones.

physics.comp-ph↗

arXiv2022

Screening 0D materials for 2D nanoelectronics applications

As nanoelectronic devices based on two-dimensional (2D) materials are moving towards maturity, optimization of the properties of the active 2D material must be accompanied by equal attention to optimizing the properties of and the interfaces to the other materials around it, such as electrodes, gate dielectrics, and the substrate. While these are usually either 2D or 3D materials, recently K. Liu et al. [Nat. Electron. 4, 906 (2021)] reported on the use of zero-dimensional (0D) material, consisting of vdW-bonded Sb$_2$O$_3$ clusters, as a highly promising insulating substrate and gate dielectric. Here, we report on computational screening study to find promising 0D materials for use in nanoelectronics applications, in conjunction with 2D materials in particular. By combining a database and literature searches, we found 16 materials belonging to 6 structural prototypes with high melting points and high band gaps, and a range of static dielectric constants. We carried out additional first-principles calculations to evaluate selected technologically relevant material properties, and confirmed that all these materials are van der Waals-bonded, thus allowing for facile separation of 0D clusters from the 3D host and also weakly perturbing the electronic properties of the 2D material after deposition.

cond-mat.mtrl-sci↗

arXiv2021

Metal-insulator transition in monolayer MoS$_2$ via contactless chemical doping

Much effort has been made to modify the properties of transition metal dichalcogenide layers via their environment as a route to new functionalization. However, it remains a challenge to induce large electronic changes without chemically altering the layer or compromising its two-dimensionality. Here, a non-invasive technique is used to shift the chemical potential of monolayer MoS$_2$ through p- and n-type doping of graphene (Gr), which remains a well-decoupled 2D substrate. With the intercalation of oxygen (O) under Gr, a nearly rigid Fermi level shift of 0.45 eV in MoS$_2$ is demonstrated, whereas the intercalation of europium (Eu) induces a metal-insulator transition in MoS$_2$, accompanied by a giant band gap reduction of 0.67 eV. Additionally, the effect of the substrate charge on 1D states within MoS$_2$ mirror-twin boundaries (MTBs) is explored. It is found that the 1D nature of the MTB states is not compromised, even when MoS$_2$ is made metallic. Furthermore, with the periodicity of the 1D states dependent on substrate-induced charging and depletion, the boundaries serve as chemical potential sensors functional up to room temperature.

cond-mat.mtrl-sci↗

arXiv2021

Fermiology of two-dimensional titanium carbide and nitride MXenes

MXenes are a family two-dimensional transition metal carbide and nitride materials, which often exhibit very good metallic conductivity and are thus of great interest for applications in, e.g., flexible electronics, electrocatalysis, and electromagnetic interference shielding. However, surprisingly little is known about the fermiology of MXenes, i.e, the shape and size of their Fermi-surfaces, and its effect on the material properties. One reason for this may be that MXene surfaces are almost always covered by a mixture of functional groups, and studying Fermi-surfaces of disordered systems is cumbersome. Here, we study fermiology of four common Ti-based MXenes as a function of the surface functional group composition. We first calculate the effective band structures of systems with explicit mixed surfaces and observe gradual evolution in the filling of the Ti-d band and resulting shift of Fermi-level. We then demonstrate that these band structures can be closely approximated by using pseudohydrogenated surfaces, and also compare favorably to the experimental angle-resolved photoemission spectroscopy results. By modifying the pseudohydrogen charge we then proceed to plot Fermi-surfaces for all systems and extract their properties, such as the Fermi-surface area and average Fermi-velocity. These are in turn used to evaluate the electrical conductivity with the relaxation time fitted to experimentally measured conductivities.

cond-mat.mtrl-sci↗

arXiv2020

First principles study of stability of MXenes under electron beam

Interactions of two-dimensional MXene sheets and electron beam of (scanning) transmission electron microscope are studied via first-principles calculations. We simulated the knock-on displacement threshold for Ti$_3$C$_2$ MXene sheet via ab initio molecular dynamics simulations and for five other MXenes (Ti$_2$C, Ti$_2$N, Nb$_2$C, Mo$_2$TiC$_2$, and Ti$_3$CN) approximately from defect formation energies. We evaluated sputtering cross section and sputtering rates, and based on those the evolution of the surface composition. We find that at the exit surface and for "low" TEM energies H and F sputter at equal rates, but at "high" TEM energies the F is sputtered most strongly. In the enter surface, H sputtering dominates. The results were found to be largely similar for all studied MXenes, and although the displacement thresholds varied between the different metal atoms the thresholds were always too high to lead to significant sputtering of the metal atoms. We simulated electron microscope images at the successive stages of sputtering, and found that while it is likely difficult to identify surface groups based on the spot intensities, the local contraction of lattice around O groups should be observable. We also studied MXenes encapsulated with graphene and found them to provide efficient protection from the knock-on damage for all surface group atoms except H.

cond-mat.mtrl-sci↗

arXiv2020

Photoluminescence Lineshapes for Color Centers in Silicon Carbide from Density Functional Theory Calculations

Silicon carbide with optically and magnetically active point defects offers unique opportunities for quantum technology applications. Since interaction with these defects commonly happens through optical excitation and de-excitation, a complete understanding of their light-matter interaction in general and optical signatures, in particular, is crucial. Here, we employ quantum mechanical density functional theory calculations to investigate the photoluminescence lineshapes of selected, experimentally observed color centers (including single vacancies, double vacancies, and vacancy impurity pairs) in 4H-SiC. The analysis of zero-phonon lines as well as Huang-Rhys and Debye-Waller factors are accompanied by a detailed study of the underlying lattice vibrations. We show that the defect lineshapes are governed by strong coupling to bulk phonons at lower energies and localized vibrational modes at higher energies. Generally, good agreement to the available experimental data is obtained, and thus we expect our theoretical work to be beneficial for the identification of defect signatures in the photoluminescence spectra and thereby advance the research in quantum photonics and quantum information processing.

cond-mat.mtrl-sci↗

arXiv2020

Band Bending and Valence Band Quantization at Line Defects in MoS$_2$

The variation of the electronic structure normal to 1D defects in quasi-freestanding MoS$_2$, grown by molecular beam epitaxy, is investigated through high resolution scanning tunneling spectroscopy at $5$K. Strong upwards bending of valence and conduction bands towards the line defects is found for the 4|4E mirror twin boundary and island edges, but not for the 4|4P mirror twin boundary. Quantized energy levels in the valence band are observed wherever upwards band bending takes place. Focusing on the common 4|4E mirror twin boundary, density functional theory calculations give an estimate of its charging, which agrees well with electrostatic modeling. We show that the line charge can also be assessed from the filling of the boundary-localized electronic band, whereby we provide a measurement of the theoretically predicted quantized polarization charge at MoS$_2$ mirror twin boundaries. These calculations elucidate the origin of band bending and charging at these 1D defects in MoS$_2$. The 4|4E mirror twin boundary not only impairs charge transport of electrons and holes due to band bending, but holes are additionally subject to a potential barrier, which is inferred from the independence of the quantized energy landscape on either side of the boundary.

cond-mat.mes-hall↗

arXiv2020

Niobium doping induced mirror twin boundaries in MBE grown WSe2 monolayers

Mirror twin boundary (MTB) brings unique 1D physics and properties into two-dimensional transition metal dichalcogenides (TMDCs), but they were rarely observed in non-Mo-based TMDCs. Herein, by post-growth Nb doping, high density 4|4E-W and 4|4P-Se MTBs were introduced into molecular beam epitaxy (MBE) grown WSe2 monolayers. Of them, 4|4E-W MTB with a novel structure was discovered experimentally for the first time, while 4|4P-Se MTBs present a random permutations of W and Nb, forming a 1D alloy system. Comparison between the doped and non-doped WSe2 confirmed that Nb dopants are essential for MTB formation. Furthermore, quantitative statistics reveal the areal density of MTBs is directly proportional to the concentration of Nb dopants. To unravel the injection pathway of Nb dopants, first-principles calculations about a set of formation energies for excess Nb atoms with different configurations were conducted, based on which a model explaining the origin of MTBs introduced by excess metal was built. We conclude that the formation of MTBs is mainly driven by the collective evolution of excess Nb atoms introduced into the lattice of host WSe2 crystal and subsequent displacement of metal atoms (W or Nb). This study provides a novel way to tailor the MTBs in 2D TMDC materials via proper metal doping and presents a new opportunities for exploring the intriguing properties.

cond-mat.mtrl-sci↗