New Machine Learning Method Optimizes Production of Atom-Thin Filters

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Ultra-thin two-dimensional (2D) materials are only one atom thick. They can act as powerful filters at the tiniest scales, even approaching sub-atomic dimensions. In this work, scientists used machine learning to develop a scalable method to grow high-quality (almost defect-free), atom-thin layers of boron and nitrogen.

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