Cover Image

PySlice: Routine Vibrational Electron Energy Loss Spectroscopy Prediction with Universal Interatomic Potentials

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Walker, Harrison A., Pfeifer, Thomas W., Zeiger, Paul M., Hachtel, Jordan A., Pantelides, Sokrates T., Hoglund, Eric R.
Format:	Preprint
Published:	2026
Subjects:	Materials Science Computational Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Phonon selection and interference in momentum-resolved electron energy loss spectroscopy
by: Pfeifer, Thomas W., et al.
Published: (2025)

Nonequivalent Atomic Vibrations at Interfaces in a Polar Superlattice (Adv. Mater. 33/2024)
by: Eric R. Hoglund, et al.
Published: (2024)

Topology-Driven Vibrations in a Chiral Polar Vortex Lattice
by: Hoglund, Eric R., et al.
Published: (2025)

Perspective on Atomic-Resolution Vibrational Electron Energy-Loss Spectroscopy
by: Haas, Benedikt, et al.
Published: (2024)

Hydrogen bonding in water under extreme confinement
by: Xu, Xintong, et al.
Published: (2024)

Using Electron Energy-Loss Spectroscopy to Measure Nanoscale Electronic and Vibrational Dynamics in a TEM
by: Kim, Ye-Jin, et al.
Published: (2023)

Comparative analysis of plasmon modes in layered Lindhard metals and strange metals
by: de Vries, Niels, et al.
Published: (2025)

Theory of Momentum-Resolved Electron Energy-Loss Spectra of Coupled Phonon and Magnon Excitations
by: Castellanos-Reyes, José Ángel, et al.
Published: (2025)

Engineering strong magnetoelectricity using a hexagonal 2D material on electron-doped hexagonal LuFeO$_3$
by: Swamynadhan, M. J., et al.
Published: (2024)

Engineering Collinear Magnetization in Hexagonal LuFeO3 and Magnetoelectric Control of Skyrmions in Hexagonal 2D Epilayers
by: M. J. Swamynadhan, et al.
Published: (2024)

Superradiant Electron Energy Loss Spectroscopy
by: Ruimy, Ron, et al.
Published: (2022)

Mesoscale Magnetostructural Phase Separation in Fe‐deficient Fe 5 GeTe 2
by: Haoyang Ni, et al.
Published: (2025)

Interface Excitation Effect in Reflection Electron Energy Loss Spectroscopy
by: A. Simon, et al.
Published: (2025)

Adaptive Loss Weighting for Machine Learning Interatomic Potentials
by: Ocampo, Daniel, et al.
Published: (2024)

Bruce Nathan Ames, 1928–2024: A meaningful scientific life
by: Errol Zeiger
Published: (2024)

Benchmarking Universal Machine Learning Interatomic Potentials for Elastic Property Prediction
by: Gao, Pengfei, et al.
Published: (2025)

Universal Machine Learning Interatomic Potentials are Ready for Phonons
by: Loew, Antoine, et al.
Published: (2024)

Electron Energy Loss Spectroscopy of 2D Materials in a Scanning Electron Microscope
by: Simonaitis, John W., et al.
Published: (2024)

Benchmarking Universal Interatomic Potentials on Zeolite Structures
by: Ito, Shusuke, et al.
Published: (2025)

Importance of Electronic Entropy for Machine Learning Interatomic Potentials
by: Petersen, Martin Hoffmann, et al.
Published: (2026)

Electron Energy Loss Spectroscopy of oriented targets and magnetic transitions
by: Iatrakis, Ioannis, et al.
Published: (2026)

Quantum Simulation of Electron Energy Loss Spectroscopy for Battery Materials
by: Kunitsa, Alexander, et al.
Published: (2025)

Programmable Beam Control for Electron Energy-Loss Spectroscopy and Ptychography
by: Palos, Mariana, et al.
Published: (2025)

Energy & Force Regression on DFT Trajectories is Not Enough for Universal Machine Learning Interatomic Potentials
by: Miret, Santiago, et al.
Published: (2025)

Ruddlesden-Popper chalcogenides push the limit of mechanical stiffness and glass-like thermal conductivity in single crystals
by: Hoque, Md Shafkat Bin, et al.
Published: (2023)

Nanoscale and Element-Specific Lattice Temperature Measurements using Core-Loss Electron Energy-Loss Spectroscopy
by: Palmer, Levi D., et al.
Published: (2024)

Efficient and Accurate Machine Learning Interatomic Potential for Graphene: Capturing Stress-Strain and Vibrational Properties
by: Hawthorne, Felipe, et al.
Published: (2025)

Machine Learning a Universal Harmonic Interatomic Potential for Predicting Phonons in Crystalline Solids
by: Lee, Huiju, et al.
Published: (2024)

Axion Mie Theory of Electron Energy Loss Spectroscopy in Topological Insulators
by: Schultz, Johannes, et al.
Published: (2020)

Revealing Information from Weak Signal in Electron Energy-Loss Spectroscopy with a Deep Denoiser
by: Wang, Yifan, et al.
Published: (2025)

From Evaluation to Design: Using Potential Energy Surface Smoothness Metrics to Guide Machine Learning Interatomic Potential Architectures
by: Liu, Ryan, et al.
Published: (2026)

Structural characterization of VC0.88 using transmission Extended Electron Energy Loss Fine Structure Spectroscopy
by: A. Duarte Moller
Published: (2003)

Energy Underprediction from Symmetry in Machine-Learning Interatomic Potentials
by: Nong, Wei, et al.
Published: (2025)

Probing the Electronic Structure of Prussian Blue and Analog Films by Photoemission and Electron Energy Loss Spectroscopies
by: Jessica B. Martins, et al.
Published: (2024)

Benchmarking Universal Machine Learning Interatomic Potentials on Elemental Systems
by: Tahmasbi, Hossein, et al.
Published: (2025)

Comparing the Latent Features of Universal Machine‐Learning Interatomic Potentials
by: Sofiia Chorna, et al.
Published: (2026)

Hierarchical Crystal Structure Prediction of Zeolitic Imidazolate Frameworks Using DFT and Machine-Learned Interatomic Potentials
by: Xu, Yizhi, et al.
Published: (2026)

Reexamining the strange metal charge response with transmission inelastic electron scattering
by: de Vries, Niels, et al.
Published: (2026)

DFT Accuracy on Crystal Structure Prediction with Machine Learning Interatomic Potentials
by: Midgley, Laurence I., et al.
Published: (2026)

Structure and mechanical properties of monolayer amorphous carbon and boron nitride
by: Zhang, Xi, et al.
Published: (2023)