Optimizing Neural Networks for Chemical Reaction Prediction: Insights from Methylene Blue Reduction Reactions

Optimizing Neural Networks for Chemical Reaction Prediction: Insights from Methylene Blue Reduction Reactions

This paper offers a thorough investigation of hyperparameter tuning for neural network architectures using datasets encompassing various combinations of Methylene Blue (MB) Reduction by Ascorbic Acid (AA) reactions with different solvents and concentrations. The aim is to predict coefficients of dec...

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Bibliographic Details
Main Authors: Ivan Malashin, Vadim Tynchenko, Andrei Gantimurov, Vladimir Nelyub, Aleksei Borodulin
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:International Journal of Molecular Sciences
Subjects:
drug design
chemical reaction prediction
hyperparameter tuning
neural network architecture
methylene blue reduction
machine learning in chemistry
Online Access:https://www.mdpi.com/1422-0067/25/7/3860

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https://www.mdpi.com/1422-0067/25/7/3860

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