ViPErLEED package I: Calculation of $I(V)$ curves and structural optimization

Abstract

Low-energy electron diffraction (LEED) is a widely used technique in surface-science. Yet, it is rarely used to its full potential. The quantitative information about the surface structure, contained in the modulation of the intensities of the diffracted beams as a function of incident electron energy, LEED I(V), is underutilized. To acquire these data, minor adjustments would be required in most experimental setups, but existing analysis software is cumbersome to use. ViPErLEED (Vienna package for Erlangen LEED) lowers these barriers, introducing a combined solution for data acquisition, extraction, and computational analysis. These parts are discussed in three separate publications. Here, the focus is on the computational part of ViPErLEED, which performs automated LEED-I(V) calculations and structural optimization. Minimal user input is required, and the functionality is significantly enhanced compared to existing solutions. Computation is performed by embedding the Erlangen tensor-LEED package (TensErLEED). ViPErLEED manages parallelization, monitors convergence, and processes input and output. This makes LEED I(V) more accessible to new users while minimizing the potential for errors and the manual labor. Added functionality includes structure-dependent defaults, automatic detection of bulk and surface symmetries and their relationship, automated symmetry-preserving search procedures, adjustments to the TensErLEED code to handle larger systems, as well as parallelization and optimization. Modern file formats are used as input and output, and there is a direct interface to the Atomic Simulation Environment (ASE) package. The software is implemented primarily in Python (version >=3.7) and provided as an open-source package (GNU GPLv3 or later). A structure determination of the $\alpha$-Fe2O3(1-102)-(1x1) surface is presented as an example for the application of the software.

References in corpus (10)

• SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
• Array Programming with NumPy
• A new LEED Instrument for Quantitative Spot Profile Analysis
• Subsurface Cation Vacancy Stabilization of the Magnetite (001) Surface
• Single Rh adatoms stabilized on α-Fe2O3(1-102) by co-adsorbed water
• Accelerating the prediction of inorganic surfaces with machine learning interatomic potentials
• Surface Reduction State Determines Stabilization and Incorporation of Rh on α-Fe2O3(1-102)
• New submonolayer copper telluride phase on Cu(111) -- ad-chain and trough formation
• ViPErLEED package II: Spot tracking, extraction and processing of I(V) curves
• Critical behavior of the dimerized Si(001) surface: Continuous order-disorder phase transition in the two-dimensional Ising universality class

Cited by in corpus (5)

• ViPErLEED package II: Spot tracking, extraction and processing of I(V) curves
• Low-energy electron microscopy as a tool for analysis of self-assembled molecular layers on surfaces
• Growth and crystallographic structure of TiTe${}_2$ on Au(111): From sub-monolayer structures to single- and multi-layer films
• An improved reliability factor for quantitative low-energy electron diffraction
• When Surface Dynamics Fakes Symmetry -- Oxygen on Rh(100) Revisited