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The aim is to develop a predictive model for the enthalpy of mixing in binary liquids using active learning techniques.

Active learning for predicting the enthalpy of mixing in binary liquids based on ab initio molecular dynamics

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The aim is to develop a predictive model for the enthalpy of mixing in binary liquids using active learning techniques.
Utilized ab initio molecular dynamics simulations
Applied active learning algorithms to predict enthalpy
Evaluated the model with various binary liquid mixtures
Predictions demonstrate high accuracy compared to experimental values
Active learning reduced the number of necessary simulations
Insights gained into the molecular interactions affecting mixing

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Active learning predicts the enthalpy of mixing in binary liquids, implying improved understanding of liquid interactions.

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Bizot et al. (2026) studied this question.

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Active learning predicts the enthalpy of mixing in binary liquids, implying improved understanding of liquid interactions.

International audience