arXiv subjects

Stig Helveg

Publications and source records attributed to Stig Helveg.

8 recordsLinked to original sources

arXiv2026

Role of self-coherence in single-electron phase contrast imaging

The extension of coherent lattice contrast into the energy loss region in high-resolution transmission electron microscopy (HRTEM) is described by a pulse-like electron-sample interaction in the energy/time uncertainty limit. It generates a wave packet by electron self-interference in any coherent-inelastic scattering event with energy loss. The width of this wave packet is characterized by a self-coherence length ls({\Delta}E) that is predictable because an intrinsic decoherence phase around one radian is set by the expectation value for phase fluctuations. In this case the visibility of interference contrast from a crystalline sample with lattice parameter a is limited by a Rayleigh-like transfer factor P(ls, a) in the self-coherently illuminated sample area. The model is verified by energy-filtered HRTEM images of hexagonal BN and identifies energy-loss-induced phase noise as a single-electron visibility limit distinct from resolution limitations caused by ensemble-coherence or counting-statistical noise.

cond-mat.mtrl-sci↗

arXiv2026

Contrastive Image-Metadata Pre-Training for Materials Transmission Electron Microscopy

The transmission electron microscope facilitates the highest-resolution imaging of any instrument ever created, and its limiting factor is no longer spatial resolution but dose efficiency. Low electron doses avoid sample damage but produce noisy images for which, unlike in classical computer vision, there is no ground truth. Autonomous materials experimentation poses a related problem, since closed-loop instruments need representations grounded in the microscope state at acquisition. Both demand representations grounded in how an image was acquired. We release 7,330 paired high-angle annular dark-field scanning-TEM (HAADF-STEM) images and their seven-dimensional acquisition metadata, and propose Contrastive Image-Metadata Pre-training (CIMP), a CLIP-style encoder that aligns the two modalities and reaches 84.4% Top-1 cross-modal retrieval on a held-out split. All seven parameters are individually recoverable from the frozen visual embedding through a linear probe, and we use the embedding to condition a metadata-conditioned style-transfer model that re-renders experimental images under different acquisition parameters. Virtually scaling dwell time and beam current of low-dose images turns this model into a physics-informed denoiser; in a blind user study, experimental microscopists prefer it over the current state-of-the-art denoiser for STEM imagery on 70.2% of trials.

cs.LG↗

arXiv2025

Visualizing phonon edge states on molybdenum disulphide

We employ Molecular Dynamics (MD) simulations to study atom vibrational amplitudes in carbon-supported Molybdenum Disulphide (MoS2) nanoparticles. Enhanced and correlated atom vibrational amplitudes are observed as the nanoparticle edges are approached from the bulk, consistent with recent experimental High-Resolution Transmission Electron Microscopy (HR-TEM) observations by Chen et al (Nature Communications 12, 5007 (2021). Analysis of phonon modes in finite systems explains the experimental observation by low-energy phonon modes confined at the nanoparticle edge, underscoring the need of full MD modeling for accurate HR-TEM image interpretation. Noticeably, we introduce a workflow for training Equivariant Neural Network-based machine learning potentials using limited Density Functional Theory (DFT) calculations. This approach effectively captures both covalent and van der Waals interactions, enabling accurate extrapolations of DFT calculations to larger systems with built-in error estimation.

cond-mat.mtrl-sci↗

arXiv2025

Open Gas-Cell Transmission Electron Microscopy at 50 pm Resolution

Transmission electron microscopy (TEM) has reached ~ 50 picometer resolution in a high vacuum, enabling single-atom sensitive imaging of nanomaterials. Extending this capability to gaseous environments would allow for similar visualizations of nanomaterial dynamics under chemically reactive conditions. Here, we examine a new TEM system that maintains 50 pm resolution at pressures up to 1 mbar, demonstrated using nanocrystalline Au immersed in N2. The system features an open gas-cell with a four-stage differential pumping system, a 5th order aberration corrector for broad-beam TEM, a monochromatized electron beam, an ultra-stable microscope platform, Nelsonian low electron dose-rate illumination, and direct electron detection. Young fringe experiments and exit wave phase imaging confirm the atomic resolution and indicate location-dependent vibrational blur at surface terminations. Thus, this platform advances in situ and operando TEM studies of gas-surface interactions in diverse fields, including catalysis, corrosion, and crystal growth.

cond-mat.mtrl-sci↗

arXiv2025

Defect complexes in CrSBr revealed through electron microscopy and deep learning

Atomic defects underpin the properties of van der Waals materials, and their understanding is essential for advancing quantum and energy technologies. Scanning transmission electron microscopy is a powerful tool for defect identification in atomically thin materials, and extending it to multilayer and beam-sensitive materials would accelerate their exploration. Here we establish a comprehensive defect library in a bilayer of the magnetic quasi-1D semiconductor CrSBr by combining atomic-resolution imaging, deep learning, and ab-initio calculations. We apply a custom-developed machine learning work flow to detect, classify and average point vacancy defects. This classification enables us to uncover several distinct Cr interstitial defect complexes, combined Cr and Br vacancy defect complexes and lines of vacancy defects that extend over many unit cells. We show that their occurrence is in agreement with our computed structures and binding energy densities, reflecting the intriguing layer interlocked crystal structure of CrSBr. Our ab-initio calculations show that the interstitial defect complexes give rise to highly localized electronic states. These states are of particular interest due to the reduced electronic dimensionality and magnetic properties of CrSBr and are furthermore predicted to be optically active. Our results broaden the scope of defect studies in challenging materials and reveal new defect types in bilayer CrSBr that can be extrapolated to the bulk and to over 20 materials belonging to the same FeOCl structural family.

cond-mat.mtrl-sci↗

arXiv2024

Single electron self-coherence and its wave/particle duality in the electron microscope

Intensities in high-resolution phase-contrast images from electron microscopes build up discretely in time by detecting single electrons. A wave description of pulse-like coherent-inelastic interaction of an electron with matter is detailed and verified. In perspective, the interaction time of any matter wave compares with the lifetime of a virtual particle of any elemental interaction, suggesting the present concept of coherent-inelastic interactions of matter waves might be generalizable.

cond-mat.mtrl-sci↗

arXiv2022

Direct evidence of a continuous transition between waves and particles

The correlation between particle and wave descriptions of electron-matter interactions is analyzed by measuring the delocalization of an evanescent field using electron microscopy. Its spatial extension coincides with the energy-dependent, self-coherence length of propagating wave packets that obey the time-dependent Schrödinger equation and undergo a Goos-Hänchen shift. In the Heisenberg limit they are created by self-interferences during coherent-inelastic Coulomb interactions with a decoherence phase Δϕ = 0.5 rad and shrink to particle-like dimensions for energy losses of more than 1000 eV.

quant-ph↗

arXiv2022

Reconstructing the exit wave in high-resolution transmission electron microscopy using machine learning

Reconstruction of the exit wave function is an important route to interpreting high-resolution transmission electron microscopy (HRTEM) images. Here we demonstrate that convolutional neural networks can be used to reconstruct the exit wave from a short focal series of HRTEM images, with a fidelity comparable to conventional exit wave reconstruction. We use a fully convolutional neural network based on the U-Net architecture, and demonstrate that we can train it on simulated exit waves and simulated HRTEM images of graphene-supported molybdenum disulphide (an industrial desulfurization catalyst). We then apply the trained network to analyse experimentally obtained images from similar samples, and obtain exit waves that clearly show the atomically resolved structure of both the MoS$_2$ nanoparticles and the graphene support. We also show that it is possible to successfully train the neural networks to reconstruct exit waves for 3400 different two-dimensional materials taken from the Computational 2D Materials Database of known and proposed two-dimensional materials.

cond-mat.mtrl-sci↗