DeepMind's GNoME Unveils Structures of Two Million New Materials
Recently, Google DeepMind researchers have introduced a groundbreaking AI tool, GNoME, predicting structures of over 2 million materials, offering vast implications across multiple industries, including renewable energy, semiconductor design, and computing.
- GNoME elevates 'stable materials' knowledge tenfold, critical for applications like computer chips and batteries, with 381,000 predicted to be most stable from the 2.2M structures.
AI Mechanism of GNoME
- Graph Neural Network (GNN): GNoME, a graph neural network model, interprets input data as a graph, resembling atom connections, allowing predictions at atomic bond levels.
- Active Learning Strategy: Trained using active learning, GNoME expands its dataset and improves precision from 50% to ....
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