Posted in | News | Nanomaterials

AI-Powered Method Revolutionizes Analysis of 2D Materials

The Science

Two-dimensional (2D) materials-materials just a few atoms thick-can have special properties due to quantum mechanics. What makes these materials special is often their defects. But there are a huge number of potential defects, and they aren't all useful. That makes it challenging for scientists studying these materials. To solve this challenge, researchers developed an automated method to analyze an important part of the 2D materials puzzle-how matter interacts with electromagnetic radiation. The method combines scanning tunneling microscopy (STM) with artificial intelligence (AI) and Molecular Foundry, a Department of Energy Office of Science user facility, developed a means of performing spatially dense, point spectroscopic measurements with an STM in combination with AI and ML. This approach provides faster and more accurate statistically averaged data that map and identify spectroscopic signatures of heterogeneous surfaces. Using tungsten disulfide (WS2) and gold (Au-111) surfaces as a benchmark, the team demonstrated how to perform measurements with reproducible resulting spectra and how to create statistically significant electronic structure characterization of the different intrinsic defects that can be found on samples of interest.


This research was supported in part by the Center for Novel Pathways to Quantum Coherence in Materials, an Energy Frontier Research Center funded by the Department of Energy (DOE) Office of Science, Basic Energy Sciences (BES). Work was performed at the Molecular Foundry, a DOE Office of Science user facility. Work was also funded through the Center for Advanced Mathematics for Energy Research Applications, which is jointly funded by the DOE Office of Science, Advanced Scientific Computing Research (ASCR) and BES programs. Other funding sources included the National Science Foundation, Division of Materials Research, and the Swiss National Science Foundation.

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