Correction: Chemically-informed active learning enables data-efficient multi-objective optimization of self-healing polyurethanes
Kang Liang, Xinke Qi, Xu Xiao, Li Wang, Jinglai Zhang
TL;DR
This paper corrects a prior study on optimizing self-healing polyurethanes using chemical insights and active learning.
Contribution
The correction addresses errors in the original paper on multi-objective optimization of self-healing polyurethanes.
Findings
The correction clarifies inaccuracies in the original study's methodology.
It ensures the reliability of data-efficient optimization approaches for self-healing materials.
Abstract
Correction for ‘Chemically-informed active learning enables data-efficient multi-objective optimization of self-healing polyurethanes’ by Kang Liang et al., Chem. Sci., 2026, https://doi.org/10.1039/D5SC07752D.
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Taxonomy
TopicsPolymer composites and self-healing · Machine Learning in Materials Science · Hydrogels: synthesis, properties, applications