Targeted nano-energetic material exploration through active learning algorithm implementation

Targeted nano-energetic material exploration through active learning algorithm implementation

This paper presents an active learning-based method designed to guide experiments towards user-defined specific regions, termed ”regions of interest,” within vast and multi-dimensional thermite design spaces. Thermites composed of metallic reactant coupled to an inorganic oxidizer are non-explosive...

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Bibliographic Details
Main Authors: Leandro Carreira, Lea Pillemont, Yasser Sami, Nicolas Richard, Alain Esteve, Matthieu Jonckheere, Carole Rossi
Format: Article
Language:English
Published: KeAi Communications Co. Ltd. 2025-03-01
Series:Energetic Materials Frontiers
Subjects:
Active learning
Materials design
Thermite
Performance optimization
Gaussian process
Intelligent sampling
Online Access:http://www.sciencedirect.com/science/article/pii/S2666647224000629
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