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Comentario sobre "Predicción avanzada de las propiedades de los materiales: utilizando modelos de aprendizaje
Maximilian Fleck1, Samir Darouich2,3, Marcelle B M Spera1
1Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569, Stuttgart, Germany.
Journal of cheminformatics
|August 28, 2025
Resumen
El aprendizaje automático basado en la física mejora la predicción de la viscosidad cuando los datos son escasos. La integración de descriptores de dinámica molecular, como el calor de la vaporización, mejora la precisión de los líquidos puros.
Área de la Ciencia:
- Química Física
- Ciencias de los materiales
- Química computacional
Sus antecedentes:
- El aprendizaje automático basado en datos (ML) se enfrenta a desafíos en la predicción de propiedades con datos limitados.
- La integración de modelos basados en la física con el aprendizaje automático puede mejorar el rendimiento predictivo.
- Masticar y demás. Utilizó descriptores de dinámica molecular (DM) en relaciones cuantitativas estructura-propiedad (QSPR) para predecir la viscosidad del líquido.
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