Natural language embeddings of synthesis and testing conditions improve ML predictions of glass dissolution rates and enable generalization to out-of-distribution compositions with new elements.
For dissolution experiments, glass was dried at 60°C, hand-ground, and sieved to 50–125 μm, then ultrasonically cleaned in deionized water and acetone
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Natural Language Embeddings of Synthesis and Testing conditions Enhance Glass Dissolution Prediction
Natural language embeddings of synthesis and testing conditions improve ML predictions of glass dissolution rates and enable generalization to out-of-distribution compositions with new elements.