AI RESEARCH
SemiConLens: Visual Analytics for 2D Semiconductor Discovery
arXiv CS.LG
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ArXi:2605.04067v1 Announce Type: cross The past few years have witnessed vibrant efforts in discovering new two-dimensional (2D) semiconductor materials from both academia and the industry, due to their promising potential in resolving the severe performance deterioration of traditional semiconductors resulting from condensed silicon thickness. However, existing methods (e.g., Density Functional Theory (DFT) or machine-learning-based approaches) suffer from various challenges such as small datasets, and reliability and trustworthiness issues.