Deep learning automation, utilizing SAM and CNN, detects MoS₂ defects in STM images with 95% accuracy. DFT simulations analyzed defect states, revealing mid-gap features. This advancement accelerates research in 2D materials and promotes defect engineering in materials science.
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The Materials Square platform in fact provides extensive web-based functionalities for computational chemistry/materials research and training/education purposes, as detailed also in the following PDF brochure:
MaterialsSquare-brochure(2024).pdf (5.0 MB)
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