Computational scanning tunneling microscope image database

Kamal Choudhary,Sergei V Kalinin,Charles Camp,Rama Vasudevan,Maxim Ziatdinov,Kevin F Garrity,Francesca Tavazza

doi:10.1038/s41597-021-00824-y

Abstract

We introduce the systematic database of scanning tunneling microscope (STM) images obtained using density functional theory (DFT) for two-dimensional (2D) materials, calculated using the Tersoff-Hamann method. It currently contains data for 716 exfoliable 2D materials. Examples of the five possible Bravais lattice types for 2D materials and their Fourier-transforms are discussed. All the computational STM images generated in this work are made available on the JARVIS-STM website (https://jarvis.nist.gov/jarvisstm). We find excellent qualitative agreement between the computational and experimental STM images for selected materials. As a first example application of this database, we train a convolution neural network model to identify the Bravais lattice from the STM images. We believe the model can aid high-throughput experimental data analysis. These computational STM images can directly aid the identification of phases, analyzing defects and lattice-distortions in experimental STM images, as well as be incorporated in the autonomous experiment workflows.

Highlights

Background & SummarySince the invention of the scanning tunneling microscope (STM)[1], this technique has become an essential tool for characterizing material surfaces and adsorbates
As density functional theory (DFT)-STM images are constructed using defect-free materials, they provide standard reference images (SRI) that are useful to aid in identifying phases[11,12], analyzing defects[13,14] and quantifying lattice-distortions[15] in experimental STM images
A DFT-STM database is essential to provide a direct link between atomic positions and images, which can aid experimental analysis

Summary

Introduction

Background & SummarySince the invention of the scanning tunneling microscope (STM)[1], this technique has become an essential tool for characterizing material surfaces and adsorbates. A DFT-STM database is essential to provide a direct link between atomic positions and images, which can aid experimental analysis. The orbital-projected electronic density of states available in our database can help explain which atoms and orbitals contribute to an experimental STM image.

Results

Conclusion